(1) Background: Depressional wetlands are highly vulnerable to changes in temperature and rainfall, affecting littoral vegetation, thus HydroGeoMorphic (HGM) wetland types. This study aimed to assess the utility of Sentinel-2A vegetation indices in enhancing delineation and sub-classify depressional HGM types. (2) Methods: We sampled 84 pairs of four vegetation indices from 10x10m plots along 14 belt transects in eight depressional wetlands in Mpumalanga, South Africa. We evaluated vegetation index differences between and within wetlands, focusing on lit-toral gradients. (3) Results: Significant differences (Bonferroni p

The evaluation of Eco-Environmental Quality (EEQ) is important to maintain the quality of ecology and is crucial for the protection of the environment and promote sustainable development. In the past 30 years, Rupandehi district has gone into rapid urbanization and population growth due to the migration of people causing drastic changes in Land use. This study takes Rupandehi district as a study area and analyses the land use change dynamics and its impact on the ecological environment from 1993 to 2023. The study utilizes the cloud computing capability of Google Earth Engine (GEE) to extract multiple indices using Landsat remote sensing data. We also applied the Thresholding approach to various spectral indices to extract land use information in GEE. The Remote Sensing Ecological Indices (RSEI) was constructed using Principal Component Analysis (PCA) to monitor the ecological quality and the effect of Land Use Land Cover (LULC) change on the quality of ecology was analysed. The result shows that the overall ecological quality of the Rupandehi district is good ranging from 0.59 in 1993 to 0.67 in 2023 with a significant impact of land use change. The eco-environmental quality of the study area is deteriorating because of a sharp increase in built-up areas and deforestation as well as the loss of agricultural land. Meanwhile, the spatial and temporal distribution of land use change collides with the change in the ecological quality of the study area. This study provides an accurate and rapid assessment of ecological quality and monitors the impact of land use change on it providing a scientific basis for researchers, government, and others to preserve the ecology and promote sustainable and eco-friendly development.

The application of distributed fiber optic strain and temperature measurement can be utilized to address a multitude of measurement tasks across a diverse range of fields, particularly in the context of structural health monitoring in the domains of building construction, civil engineering, and special foundation engineering. However, a comprehensive understanding of the influences on the measurement method and the sensors is essential to prevent misinterpretations or measurement deviations. In this context, this study investigated the effects of moisture exposure, including various salt solutions and a high pH value, on a distributed strain measurement using Rayleigh backscattering. Three fiber optic sensors with different coating materials and one uncoated fiber were exposed to five different solutions for 24 hours. The study revealed significant discrepancies in deformation between the three coating types depending on the surrounding solution. Furthermore, in contrast to the prevailing literature, which predominantly describes swelling effects, a negative deformation was observed in a magnesium chloride solution. The findings of this study indicate that corresponding effects can impact the precision of measurement, potentially leading to misinterpretations. Conversely, these effects could be used to conduct large-scale monitoring of chemical components using distributed fiber optic sensing.

Droplet-based microfluidics has revolutionized numerous fields such as biomedical research, pharmaceuticals, drug discovery, food engineering, flow chemistry, and cosmetics. This paper presents a comprehensive study focusing on the detection and characterization of droplets with volumes in the nanoliter range. Leveraging the precise control of minute liquid volumes, we introduced a novel spectroscopic On-Chip microsensor equipped with integrated microfluidic channels for droplet generation, characterization, and sensing, simultaneously. The microsensor, designed with Interdigitated-Ring-Shaped Electrodes (IRSE) and seamlessly integrated with microfluidic channels, offers enhanced capacitance and impedance signal amplitudes, reproducibility, and reliability in droplet analysis. We were able to make analyses of droplets length in the range 1.0-6.0 mm, velocity 0.66-2.51 mm/s, droplet volume 1.07nL-113.46nL. Experimental results demonstrated that the microsensor's has a great performance in terms of droplet size, velocity, and length, with a significant signal amplitude of capacitance and impedance, and real-time detection capabilities, thereby highlighting its potential for facilitating microcapsule reactions and enabling on-site real-time detection for chemical and biosensor analyses on-chip.

Given the context of global climate change, a worldwide increase in land surface temperature (LST) is anticipated, leading to the exacerbation and broadening of its impacts. This could jeopardize the environmental conditions in countries with a predominantly hot and harsh climate, such as Bahrain, one of the Cooperation Countries (GCC) nations. Conversely, Bahrain is currently experiencing significant population growth, leading to a surge in demand for land to accommodate the construction of additional residential developments. This circumstance allows investigation of the potential impact of land use and land cover alterations on the variation in Land Surface Temperature (LST). In order to accomplish this objective, a residential development project was executed within the timeframe spanning from 2013 to 2023. Four sets of Landsat 8 OLI/TIRS remote sensing datasets were selected, with each set corresponding to one of the four climate seasons. Each set consisted of two images: one capturing the study area before the commencement of the development process and the other depicting the study area after the completion of the development. The study area was analyzed by extracting the land surface temperature (LST), normalized difference vegetation index (NDVI), and normalized difference built-up index (NDBI) on various dates. Subsequently, correlation and regression analysis were employed to examine the interrelationships among these three variables. The findings demonstrated a notable rise in the mean land surface temperature throughout the spring and autumn seasons following the conclusion of land development activities. The findings indicate a positive and robust association between LST and NDBI across all seasons. Moreover, this relationship strengthened following the completion of development activities in the area. Conversely, there was a negative correlation between LST and NDVI prior to the region's development, which transformed into a positive relationship post-development. These results provide empirical support for the notion that small-scale residential developments contribute to a notable increase in LST, primarily driven by the expansion of impervious surfaces in built-up areas. The findings can potentially contribute to the formulation of localized adaptation strategies for small-scale residential development projects.

The increasing rate of adoption of innovative technological achievements along with the penetration of the Next Generation Internet (NGI) technologies and Artificial Intelligence (AI) in the water sector, are leading to a shift to a Water-Smart Society. New challenges have emerged in terms of data interoperability, sharing, and trustworthiness due to the rapidly increasing volume of heterogeneous data generated by multiple technologies. Hence, there is a need for efficient harmonisation and smart modeling of the data to foster advanced AI analytical processes which will lead to efficient water data management. The main objective of this work is to propose two Smart Data Models focusing on the modeling of the Satellite Imaginary data and the Flood Risk Assessment processes. The utilisation of those models reinforces the fusion and homogenisation of diverse information and data facilitating the adoption of AI technologies for flood mapping and monitoring. Furthermore, a holistic framework has been developed and evaluated via qualitative and quantitative performance indicators revealing the efficacy of the proposed models concerning the usage of the models in real cases. The framework is based on the well-known and compatible technologies on NGSI-LD standards which are customised and applicable easily to support the water data management processes effectively.

Optical “fingerprints” are widely used in chemometrics-assited recognition of samples of different nature. An emerging trend in this area is the transition from obtaining "static" spectral data to reactions occurring over time. The indicator reactions are usually carried out in aqueous solutions; in this study we have developed the reactions that occur in an organic solvent, which makes it possible to recognize fat-soluble samples. In this capacity, we used 5W40, 10W40 and 5W30 motor oils of 4 manufacturers, totally 6 samples. The procedure involved mixing of the dye, sample, and reagents (HNO3, HCl, or t-butyl hydroperoxide) in ethanolic solution in a 96-well plate and measuring absorbance or near-IR fluorescence intensity every several minutes during 20–55 min. The obtained photographic images were processed by linear discriminant analysis (LDA) and k-nearest neighbors algorithm (kNN). The discrimination accuracy was evaluated by using the validation procedure. Reaction of oxidation of a dye with nitric acid allowed to recognize all 6 samples with 100% accuracy by LDA. Merging data of 4 reactions that did not provide complete discrimination ensured an accuracy of 93% by kNN technique. The developed indicator systems have good prospects for the discrimination of other fat-soluble samples. Overall, the results confirm the viability of the kinetic-based discrimination strategy.

Forests, integral to human civilization, hold immense value and play a vital role in maintaining ecological harmony. Despite India's goal of extensive forest coverage, significant progress is still needed. Uncontrolled forest fires pose a severe threat, particularly in Uttarakhand's Pauri Garhwal district. To address this challenge, a comprehensive study examined surface and subsurface hydrological factors influencing the forest fire occurrences, such as elevation, aspect, slope, vegetation, proximity to human settlements, proximity to waterbodies, Active faults and lineament density. A total of 15 such factors were integrated with advanced techniques of remote sensing and GIS and coupled with historical fire data to create a precise forest fire risk map using the support vector machine algorithm. Forest fire risk map was classified into 5 distinct risk zones, Very High Risk (47.38 Km2), High Risk (275.98 km2, Moderate Risk (985.49 km2), Low Risk (1741.17 km2) and Very Low Risk (2374.11 km2) aiding in proactive fire management. By embracing this innovative tool, decision-makers can protect forests, preserve biodiversity, and ensure a sustainable future for generations to come.

Computer vision models of salient object detection attempt to mimic the ability of the human visual system to select relevant objects in images. To this end, the development of deep neural networks on high-end computers has recently made it possible to achieve high performance. However, it remains a challenge to develop deep neural network models of the same performance for devices with much more limited resources. In this work, we propose a new approach for a lightweight salient object detection neural network model, inspired by the cone and spatial opponent processes of the primary visual cortex (V1), that inextricably link color and shape in human color perception. Our proposed model, namely CoSOV1net, is trained from scratch, without using backbones from image classification or other tasks. Experiments, on the most widely used and challenging datasets for salient object detection, show that CoSOV1Net achieves competitive performance (i.e. Fβ=0.931 on the ECSSD dataset) with state-of-the-art salient object detection models, while having low number of parameters (1.14M), low FLOPS (1.4G) and high FPS (211.2) on GPU (nvidia Geforce RTX 3090 TI) compared to the state-of-the-art in the salient object detection or lightweight salient object detection task. Thus, CoSOV1net turns out to be a lightweight salient object detection that can be adapted to mobile environments and resource-constrained devices.

Since 2007, at the Electron Science Research Institute (ESRI) nano-fabrication laboratories, Edith Cowan University, Australia, we have devoted research efforts to the synthesis and characterization of bismuth-containing ferrite-garnet-type thin-film magneto-optic (MO) materials of different compositions. We report on the development and properties of highly bismuth-substituted iron-garnet thin films prepared by using radio frequency (RF) magnetron sputtering. We study the process parameters associated with the RF magnetron sputter deposition technique and investigate the results of optimizing process parameters and implementing several special techniques including the fabrication of co-sputtered nanocomposite films, all-garnet multilayer structures, applying oxygen plasma treatment on amorphous garnet layers just after the deposition process, and designing modifications of the annealing crystallization process and regimes for achieving the best MO properties. We demonstrated significant improvement in MO properties of Bi-containing ferrite-type garnet thin-film materials, including record-high MO figures of merit and improved conventional and un-conventional hysteresis loops of Faraday rotation. The attractive optical, magnetic, and magneto-optic properties obtained in highly bismuth-substituted iron garnet thin-film materials of multiple composition types are relevant in the context of manufacturing next-generation ultra-fast optoelectronic devices, such as light intensity switches and modulators, high-speed flat panel displays, and high-sensitivity sensors.

The analysis of the human movement patterns based on the mobile network data makes it possible to examine a very large population cost-effectively, and led to several discoveries about human dynamics. However, the application of this data source is still not common practice. The goal of this study was to analyze the commuting tendencies of the Budapest Metropolitan Area using mobile network data and propose an automatized alternative to the current, questionnaire-based method. Commuting is predominantly analyzed by the census, but that is performed only once in a decade in Hungary. To analyze commuting, the home and the work locations of the subscribers are determined based on their appearances during and outside the working hours. The home locations were compared to census data at a settlement level. Then, the settlement and district level commuting tendencies were identified and compared to the findings of census-based sociological studies. It has been found that commuting analysis based on mobile network data strongly correlates with the census-based findings, even though home and work locations have been estimated by statistical methods. All the examined aspects, including commuting from sectors of the agglomeration to the districts of Budapest and demographic distribution of the commuters, show that mobile network data can be an automatized, fast, cost-effective, and relatively accurate way of commuting analysis, that could provide a powerful tool to the sociologists interested in commuting.

The 2020 Elucidating the role of clouds-circulation coupling in climate - Ocean-Atmosphere (EUREC4A-OA) and Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) campaigns sought to improve the knowledge of the interaction between clouds, convection and circulation and their function in our changing climate. The campaign consisted of numerous research technologies, some of which are relatively novel to the scientific community. In this study we used a saildrone uncrewed surface vehicle to validate satellite and modelled sea surface salinity (SSS) products in the Western Tropical Atlantic. These products include the Soil Moisture Active Passive (SMAP) Jet Propulsion Laboratory (JPL), SMAP Remote Sensing Systems (RSS), and Hybrid Coordinate Ocean Model (HYCOM). In addition to the validation, we investigated a fresh tongue south east of Barbados. The saildrones accurately depicted the salinity conditions and all satellite and modelled products performed well in areas that lacked small-scale salinity variability. However, SMAP RSS 70 km outperformed its counterparts in areas with small submesoscale irregularities while RSS 40 km was better at identifying small irregularities in salinity such as a fresh tongue. These results will allow researchers to make informed decisions regarding the most ideal product for their application and aid in the improvement of mesoscale and submesoscale SSS products, which can lead to the refinement of numerical weather prediction (NWP) and climate models.

Deep learning classification is the state-of-the-art of machine learning approach. Earlier work proves that the deep convolutional neural network has successfully and brilliantly in different applications such as images or video data. Recognizing and clarifying the remote sensing aspect of the earth's surface and exploit land cover and land use (LCLU). First, this article summarized the remote sensing emerging application and challenges for deep learning methods. Second, we propose four approaches to learn efficient and effective CNNs to transfer image representation on the ImageNet dataset to recognize LCLU datasets. We use VGG16, Inception-ResNet-V2, Inception-V3, and DenseNet201 models to extract features from the EACC dataset. We use pre-trained CNNs on ImageNet to extract features. For feature selection we proposed principal component analysis (PCA) to improve accuracy and speed up the model. We train our model by multi-layer perceptron (MLP) as a classifier. Lastly, we apply the multi-granularity encoding ensemble model. We achieve an overall accuracy of 92.3% for the nine-class classification problem. This work will help remote sensing scientists understand deep learning tools and apply them in large-scale remote sensing challenges

Silicon-based photonic integrated circuit (PIC) is a research focus in producing high-density photonics. One of the potential applications of silicon PIC is the sensing and measurement system. In this work, we use the one-dimensional photonic crystal (1D-PhC) cavity design which and utilize it at the PIC level design. The 1D PhC design used as the compact model has the same characteristics as experimentally demonstrated in previous works. The compact model is made from the S-parameter extraction of the 1D-PhC device which is done by using Lumerical FDTD software. The PIC design integrates the 1D-PhC device as a sensing component with a PN-phase shifter (PN-PS) to function as a refractive index (RI) sensor calibration or tuning circuit. A custom design of PN-PS device is used by simulating and extracting the bias voltage-effective index (bias-Neff) data by using Lumerical DEVICE and MODE into the circuit simulator. The circuit-level simulation is done by using Lumerical Interconnect software. Finally, we show the GDSII layout design of the 1D-PhC based photonic sensor calibration circuit with an analysis of generic silicon PIC design rules. The designed PIC is applicable for the bio-sensing applications and photonic SOC component. This work also shows the promise of PIC design approach for further PIC development.

(1) Background: Sensing of critical events or flow signatures in nature often presents itself as a coupled interaction between a fluid and arrays of slender flexible beams, such a wind-hairs or whiskers. It is hypothesized that important information is gained in highly noisy environments by the inter-correlation within the array. (2) Methods: The present study uses a model sea lion head with artificial whiskers in the form of slender beams (optical fibres), which are subjected to a mean flow with overlaid turbulent structures generated in the wake of a cylinder. Motion tracking of the array of fibres is used to analyse the correlation of the bending deformations of pairs of fibres. (3) Results: Cross-correlation of the bending signal from tandem pairs of whiskers proves that the detection of vortices and their passage along the animals head is possible even in noisy environments. The underlying pattern, during passage of a vortex core, is a jerk-like response of the whiskers, which can be found at later arrival-times in similar form in the downstream whisker's response. (4) Conclusion: Coherent vortical structures can be detected from cross-correlation of pairs of cantilever-beam like sensors even in highly turbulent flows. Such vortices carry important information within the environment, e.g. the underlying convection velocity. More importantly in nature, these vortices are characteristic elementary signals left by prey and predators. The present work can help to further develop flow, or critical event, sensory systems which can overcome high noise levels due to the proposed correlation principle.

The evaluation of geometric defects is necessary in order to maintain the integrity of structures over time. These assessments are designed to detect damages of structures and ideally help inspectors to estimate the remaining life of structures. Current methodologies for monitoring structural systems, while providing useful information about the current state of a structure, are limited in the monitoring of defects over time and in linking them to predictive simulation. This paper presents a new approach to the predictive modeling of geometric defects. A combination of segmented from point clouds are parametrized using the convex hull algorithm to extract features from detected defects, and a stochastic dynamic model is then adapted to these features to model the evolution of the hull over time. Describing a defect in terms of its parameterized hull enables consistent temporal tracking for predictive purposes, while implicitly reducing data dimensionality and complexity as well. In this study, 2D point clouds analogous to information derived from point clouds were first generated over simulated life-cycles. The evolutions of point cloud hull parameterizations were modeled as stochastic dynamical processes via autoregressive integrated moving average (ARIMA) and vectorized autoregression (VAR) and compared against ground truth. The results indicate that this convex hull approach provides consistent and accurate representations of defect evolution across a range of defect topologies and is reasonably robust to noisy measurements, however assumptions regarding the underlying dynamical process play a significant the role in predictive accuracy. The results were then validated on experimental data from fatigue testing with high accuracy. Longer term, the results of this work will support finite element model updating for predictive analysis of structural capacity.

This article analyzes some available bike mobile applications for smartphones as an alternative to bike computers (Cycle Computers or speedometer or speed sensors). We have records of a large number of MTB (Mountain Bike) datasets, 219 datasets were recorded on 4 different routes. These applications create maps and profiles from geographic data. Inputs can be in GPS data (tracks and waypoints), driving routes, street addresses, or simple coordinates. Most applications estimate fields such as speed, heading, slope, distance, VMG (velocity made good) and pace (cadence). However, it is necessary to calculate the relationship between cadence and power in pedaling so that cyclists know the appropriate moment to apply power to their legs to improve the torque. This paper shows tables, comparative graphs, and performance evaluation of biking routes in four different cycling mobile applications.

All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i) use only the relative radiance data in the image along with published data, and several new assumptions, (ii) in order to specify and operate the simplified radiative transfer equation (RTE), (iii) for the purpose of retrieving both the satellite derived bathymetry (SDB) and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need (i) for formal atmospheric correction, (ii) nor for conversion of relative radiance into calibrated reflectance , (iii) nor for existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM). This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a “near-nadir” view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.

Present worldwide difficulties in healthcare and the environment have motivated the investigation and research of novel materials in an effort to find novel techniques to address the current chal-lenges and requirements. In particular, the use of nanomaterials has demonstrated a significant promise in the fight against bacterial infections and the problem of antibiotic resistance. Metal na-noparticles and carbon-based nanomaterials in particular have been highlighted for their excep-tional abilities to inhibit many types of bacteria and pathogens. In order for these materials to be as effective as possible, synthetic techniques are crucial. Therefore, in this review article, we high-light some recent developments in the design and synthesis of various nanomaterials, including metal nanoparticles (e.g., Ag, Zn, or Cu), metal hybrid nanomaterials, and the synthesis of mul-ti-metallic hybrid nanostructured materials. Following that, examples of these materials’ applica-tions in antimicrobial performance targeted at eradicating multi-drug resistant bacteria, material protection such as microbiologically influenced corrosion (MIC), or additives in construction ma-terials have been described.

The present article describes the synthesis of an isonicotinate-derived meso-arylporphyrin, that has been fully characterized by spectroscopic methods (including fluorescence spectroscopy), as well as by elemental analysis and by HR-MS. The structure of a n-hexane monosolvate has been determined by single crystal X-ray diffraction analysis. The radical scavenging activity of this new porphyrin against the 2,2-diphenyl-1-picrylhydrazyl (DDPH) radical has been measured. Its antifungal activity against three yeast strains (C. albicans ATCC 90028, C. glabrata ATCC 64677 and C. tropicalis ATCC 64677) has been tested, using the disk diffusion and the microdilution methods. Whereas the measured antioxidant activity was low, the porphyrin showed moderate but encouraging antifungal activity. Finally, a study of its effect on the germination of lentil seeds revealed interesting allelopathic properties.

Background. Transferrin receptor 1 (TfR1), glucose transporter 1 (GLUT1), and CD98hc are candidates for targeted therapy at the blood-brain barrier (BBB). Our objective was to challenge the expression of TfR1, GLUT1, and CD98hc in brain capillaries by the histone deacetylase inhibitor (HDACi) valproic acid (VPA). Methods. Primary mouse brain capillary endothelial cells (BCECs) and brain capillaries isolated from mice injected intraperitoneally with VPA were examined using RT-qPCR and ELISA. Targeting to the BBB was performed by injecting monoclonal anti-TfR1 (Ri7217)-conjugated gold nanoparticles measured using ICP-MS. Results. In BCECs co-cultured with glial cells, Tfrc mRNA expression was significantly higher after 6 h VPA returning to baseline after 24 h. In vivo Glut1 mRNA expression was significantly higher in males, but not females', receiving VPA, whereas Cd98hc mRNA expression was unaffected by VPA. TfR1 increased significantly in vivo after VPA, whereas GLUT1 and CD98hc were unchanged. Uptake of anti-TfR1-conjugated nanoparticles was unaltered by VPA in spite upregulated TfR expression. Conclusions. VPA upregulates TfR1 in brain endothelium in vivo and in vitro. VPA does not increase GLUT1 and CD98hc proteins. The increase in TfR1 does not result in higher anti-TfR1 antibody targetability, suggesting targeting sufficiently occurs with available transferrin receptors without further contribution from accessory VPA-induced TfR1.

Nitraria tangutorum Bobrov is a berry shrub with white flowers and red fruits, which grows in the deserts in the Tibetan Plateau, Mongolia, and western China. Its fruit N. tangutorum fruit (NTF) contains various bioactive compounds, with anti-fatigue, anti-inflammatory, and neuroprotective functions. However, the high saccharide content of NTF makes it unsuitable for diabetic patients. In this study, we fermented NTF to obtain N. tangutorum fermented juice (NTJ), and N. tangutorum fermented residue (NTR), which are suitable for diabetics to consume. We characterized the bioactive compounds in NTF, NTR, and NTJ, and found that fermentation increased the diversity of bioactive compounds, and greatly reduced sucrose, glucose, and fructose content while generating trehalose, which has the potential to manage blood glucose levels. Further, NTJ displays anti-diabetic potential due to various compounds anti-diabetic properties. This study provides a basis for further clinical research on NTJ's anti-diabetic function in humans.

The subject of the conducted study was focused on the development of new type of technical blends reinforced with natural fillers. The study was divided into two parts, where in the firsts stage of the research unmodified POM was reinforced with different types of natural fillers: cellulose, wood flour and husk particles. In order to select the type of filler intended for further modification, the mechanical characteristics was assessed. The 20% wood flour (WF) filler system was selected as the reinforcement. The second stage of research involved the use of combination of polyoxymethylene POM and poly(lactic acid) PLA. POM/PLA blend (ratio 50/50 %) were modified with elastomeric compound (EBA) and chain extender as reactive compatibilized (CE). The microscopic analysis revealed that for POM/PLA system the filler-matrix interface is characterized by better wettability, which might suggest higher adhesion. The mechanical performance revealed that for POM/PLA-based composites the properties were very close to the results for POM-WF composites; however, there is still large difference in thermal resistance in favor of POM-based materials. The increase in thermomechanical properties for POM/PLA composites occurs after heat treatment. The increasing crystallinity of the PLA phase allows for an significant increase of the head deflection temperature (HDT), even above 125 °C.

The temperature effect plays an important role for an accurate determination of the polar free energy, polar thermodynamic parameters, and enthalpic and entropic Lewis’s acid base properties of oxides, polymers and composites polymers/oxides. The adsorption of polymers on other solid surfaces is crucial in many industrial applications, coatings, paints, catalysis, colloids and adhesion processes. (1) Background: Inverse gas chromatography at infinite was used for the physico-chemical characterization of solid substrates by determining the thermodynamic parameters of adsorption of model organic solvents on solid surfaces such as polymers, metallic oxides, carbon fibers, pharmaceutical or 3D/4D printing substrates. (2) Methods: A new method based on the London dispersion equation was applied with a new parameter associating the deformation po-larizability and the harmonic mean of the ionization energies of solvent. More accurate values of the dispersive and polar interaction energies of the various organic solvents adsorbed on PMMA in bulk phase and PMMA/silica at different recovery fractions were obtained as well as the Lewis acid-base parameters and the transition temperatures of the different composites. (3) Results: This new methodology gave very interesting results on the behavior of PMMA adsorbed on silica. An important effect of the temperature and the recovery fraction on the various physicochemical and thermodynamic properties was highlighted. The variations of all interaction parameters showed the presence of three transition temperatures for the different PMMA adsorbed on silica with the various coverage rates with a shift of these temperatures for a recovery fraction of 31% (4) Con-clusions: An important variation of the polar enthalpy and entropy of adsorption, the Lewis ac-id-base parameters and the intermolecular separation distance as a function of the temperature and the recovery fraction of PMMA on silica.

In order for the body to function properly, it needs not only food, but also nutrients and non-nutritive bioactive compounds that have an immunomodulating effect. This applies not only to healthy people, but especially to people with accompanying chronic diseases, including type 2 diabetes. Unfortunately, the current food industry and the use of highly processed food promote nutritional deficiencies. Many studies confirm their occurrence in patients with type 2 diabetes. The article presents the influence of selected nutrients on the functioning of the immune system, which ensures homeostasis of the body, with particular emphasis on type 2 diabetes. The role of macroelements, microelements, vitamins and selected substances, such as omega-3 acids, coenzyme Q10 and alpha-lipoic acid. The minimum scope of tests that should be performed in patients to directly or indirectly determine the degree of malnutrition in this group of patients is presented.

The effects of simulated acid rain (SAR) on the photosynthetic performance of subtropical coniferous species have not been thoroughly investigated. In this study, we treated two coniferous species, Pinus massoniana (PM) and Cunninghamia lanceolata (CL), with SAR and then analyzed photosynthetic activities via the simultaneous measurement of prompt fluorescence(PF), delayed fluorescence(DF), and modulated reflection at 820 nm(MR820). Following the low-pH SAR treatment, the I–P phase of the OJIP curves of PM and CL decreased significantly and then the K-band and L-band were detectable. The delayed fluorescence for both PM and CL decreased as the pH of the SAR solution decreased, with a more significant decrease in the I1 peak than in the I2 peak. According to the MR820 curve, the exposure to SAR stress inhibited the rapid decrease and slow increase in the MR820 transients of PM and CL. The gradients of the decreasing and increasing phases were lower for CL than for PM at pH 2.5. In addition, SAR decreased the light energy captured per unit area (ABS/CSm) and the quantum yield of electron transfer per unit area (ETO/CSm), but it increased the accumulation of QA−, thereby decreasing primary photochemical efficiency (TRO/CSm, φPO). These changes in photosystem II (PSII) resulted in a decrease in the maximum quantum yield of PSII (Fv/Fm) and the performance index (PIABS). Moreover, PSII was protected from thylakoid membrane photodamages through the increase in heat dissipation per unit area (DIO/CSm) in response to SAR. The increase in δRO as the pH of the SAR solution decreased was observed for PM, but not for CL. Considered together, the study findings suggest that SAR treatments can decrease chlorophyll contents and damage the OEC in PM and CL, which obstructs the transfer of electrons on the donor and acceptor sides of PSII. However, PM is better able to withstand SAR stress than CL, likely because of the activation of a protective mechanism (reflected by the change in δRO). Therefore, in coniferous forest areas severely affected by acid rain, CL may need to be protected more than PM.

The study delved into the impact of two extrusion processing parameters—screw speed (SS at 400, 600, 800 RPM) and material moisture content in the extruder barrel (M at 12, 15, 18%) at constant feed rate (50 kg/h)—on reducing the content of alternariol (AOH), alternariol monomethyl ether (AME), tenuazonic acid (TeA), and tentoxin (TEN) in whole-grain red sorghum flour. Ultra-performance liquid chromatography coupled with a triple-quadrupole mass spectrometer (UPLC-MS/MS) was used for determination of Alternaria toxin levels. The extruder die temperature ranged between 136 and 177 °C, the pressure at the die was from 0.16 to 6.23 MPa, the specific mechanical energy ranged from 83.5 to 152.3 kWh/t, the torque ranged between 88 to 162.8 Nm, while the mean retention time of material in the barrel was between 5.6 and 13 s. Optimal parameters for reducing the concentration of all Alternaria toxins with the satisfactory quality of sorghum snacks were: SS=400 RPM, M= 12%, with a reduction of 61.4, 76.4, 12.1 and 50.8% for AOH, AME, TeA and TEN, respectively.

Transitions from seed to seedling represent a critical developmental step in the life cycle of higher plants, dramatically affecting plant ontogenesis and stress tolerance. The release from dormancy to acquiring the germination ability is defined by a balance of phytohormones, with a substantial contribution of abscisic acid (ABA), which inhibits germination. We studied the embryonic axes of Pisum sativum L. before and after radicle protrusion. Our previous work compared RNA sequencing-based transcriptomics in the embryonic axes isolated before and after radicle protrusion. The current study aims to analyze ABA-dependent gene regulation during the transition of embryonic axes from germination to post-germination stage. First, we determined the levels of abscisates (ABA, phaseic acid, dihydrophaseic acid, and neo-phaseic acid) using the ultra-high-performance liquid chromatography-tandem mass spectrometry. Second, we made a detailed annotation of ABA-associated genes using RNA sequencing-based transcriptome profiling. Finally, we analyzed the DNA methylation pattern in the promoters of the PsABI3, PsABI4, and PsABI5 genes. We showed that changes in the abscisate profile are characterized by the accumulation of ABA catabolites, and the ABA-related gene profile is accompanied by the upregulation of genes controlling the seedling development and the downregulation of genes controlling the water deprivation. The expression of ABI3, ABI4 and ABI5, which encode the crucial transcription factors during late maturation, was downregulated by more than 20-fold, and their promoters exhibited a high level of methylation already at the late germination stage. Thus, although ABA remains important, other regulators seems to be involved in the transition from seed to seedling.

Plants are exposed to a variety of abiotic and biotic stresses leading to increased formation of reactive oxygen species (ROS) in plant cells. ROS are capable of oxidizing proteins, pigments, lipids, nucleic acids, and other cell molecules, disrupting their functional activity. During the process of evolution, numerous antioxidant systems were formed in plants, including antioxidant enzymes and low-molecular-weight non-enzymatic antioxidants. Antioxidant systems perform neutralization of ROS and therefore prevent oxidative damage of cell components. In the present review, we focus on the biosynthesis of non-enzymatic antioxidants in higher plant cells such as ascorbic acid (vitamin C), glutathione, flavonoids, isoprenoids, including carotenoids, tocopherol (vitamin E), ubiquinone and plastoquinone. Their functioning and their reactivity with respect to individual ROS are described. The review is also devoted to the modern genetic engineering methods, which are widely used to change the quantitative and qualitative content of the non-enzymatic antioxidants in cultivated plants. These methods allow to obtain various plant lines with given properties in a rather short time. The most successful approaches for plant transgenesis and plant genome editing for the enhancement of the biosynthesis and the content of these antioxidants are discussed.

Basic features of seed dormancy are illustrated. The seed overall regulatory network governs seed metabolism and development, and it is coordinated by plant hormones. A functional model focused on abscisic acid (ABA), the foremost plant hormone in dormancy, is used as a framework to critically discuss the literature. Gibberellins (GAs) have a main role in germination, and the ABA – GAs balance is a typical feature of the seed state: ABA dominates during dormancy and GAs prevail through germination. Thus, the literature converges toward envisaging the development switch between dormancy and germination as represented by the ABA/GAs ratio. The ABA – GAs antagonism is based on mutual inhibition, a feature of the regulatory network architecture that characterizes development trajectories based on a regulatory circuit with a bistable switch. Properties of such kind of regulatory architecture are introduced step by step, and it is shown that seed development – towards either dormancy or germination – is more properly represented by a tristable regulatory circuit, whose intermediate metastable states ultimately take one or the other development trajectory. Although the ABA/GAs ratio can conveniently represent the state of the seed overall regulatory network along the seed development trajectory, specific (unknown) dormancy factors are required to determine the development trajectory. The development landscape is shown to provide a well-suited representation of seed states travelling along developmental trajectories, particularly when the states are envisioned as regulatory circuits. Looking at seed dormancy in terms of regulatory circuits and development landscapes offers a valuable perspective to improve our understanding of this biological phenomenon.

Ribotoxin-like proteins (RL-Ps) are specific ribonucleases found in mushrooms that are able to cleave a single phosphodiester bond located in the Sarcin-Ricin Loop (SRL) of the large rRNA. The cleaved SRL interacts differently with some ribosomal proteins (P-stalk). This action blocks protein synthesis because the damaged ribosomes are unable to interact with elongation factors. Here, the amino acid sequence of eryngitin 3 and 4, RL-Ps isolated from Pleurotus eryngii fruiting bodies, was determined to: i) obtain structural information on this specific ribonuclease family from edible mushrooms; and ii) explore the structural determinants which justify their different biological and antipathogenic activities. Indeed, eryngitin 3 (exhibited higher toxicity with respect to eryngitin 4 against tumoral cell lines and model fungi. Structurally, eryngitin 3 and 4 consist of 132 amino acids, most of them identical and exhibit a single free cysteinyl residue. The amino acidic differences between the two toxins are: i) an additional phenylalanyl residue at the N-terminus of eryngitin 3, not retrieved in eryngitin 4; and ii) an additional arginyl residue at C-terminus of eryngitin 4, not retrieved in eryngitin 3. The 3D-models of eryngitins show slight differences at the N- and C-terminal regions. In particular, the positive electrostatic surface at C-terminal of eryngitin 4 is due to the additional arginyl residue not retrieved in eryngitin 3. This additional positive charge could interfere with the binding to the SRL (substrate) or with some ribosomal proteins (P-stalk structure), during substrate recognition.

The root extracts of Symphytum officinale (comfrey) are commonly used in traditional medicine to treat muscle, joint, skin and bone disorders. However, little information is available on the biomedical functions of comfrey leaves. In this study, sequencing results of Internal Transcribed Spacer and trnL-trnF genes showed that plants purchased from the local market were comfrey and named as S. officinale WL (WL). The optimal extraction conditions of WL leave with the highest extract yield and contents of total phenols and flavonoids by microwave-assisted extraction were identified. The antioxidative and anti-inflammatory activities and possible molecular mechanism(s) of the WL leaf extract (WLE) were evaluated. Furthermore, the major component of WLE was identified as rosmarinic acid by HPLC. Results showed that the optimal extract condition was obtained with 750W microwave power, 50℃, 75% methanol, the solid-to-solvent ratio of 1:10, and 15 minutes. Results of all DPPH, ABTS and superoxide radical scavenging activities, reducing power, ferrous ion chelating activity, and ferric reducing antioxidant power showed high antioxidative capacities of WLE. Furthermore, WLE showed obvious DNA protecting activity. WLE attenuated lipopolysaccharides-stimulated inflammation by suppressing iNOS, COX-2, IL-1β, IL-6, and TNF-α expressions in RAW264.7 macrophages. These attenuations involved in inactivations of lipopolysaccharides-induced NF-κB and MAPK signaling pathways.

There is an increasing interest in biomarkers of nitric oxide dysregulation and oxidative stress to guide management and identify new therapeutic targets in patients with chronic obstructive pulmonary disease (COPD). We conducted a systematic review and meta-analysis of the association between circulating metabolites within the arginine (arginine, citrulline, ornithine, asymmetric, ADMA, and symmetric, SDMA dimethylarginine), transsulfuration (methionine, homocysteine, and cysteine) and folic acid (folic acid, vitamin B6, and vitamin B12) metabolic pathways and COPD. We searched electronic databases from inception to 30 June 2023 and assessed the risk of bias and the certainty of evidence. In 21 eligible studies, compared to healthy controls, patients with stable COPD had significantly lower methionine (standardized mean difference, SMD=-0.50, 95% CI -0.95 to -0.05, p=0.029) and folic acid (SMD=-0.37, 95% CI -0.65 to -0.09, p=0.009), and higher homocysteine (SMD=0.78, 95% CI 0.48 to 1.07, p˂0.001) and cysteine concentrations (SMD=0.34, 95% CI 0.02 to 0.66, p=0.038). Additionally, COPD was associated with significantly higher ADMA (SMD=1.27, 95% CI 0.08 to 2.46, p=0.037), SDMA (SMD=3.94, 95% CI 0.79 to 7.08, p=0.014), and ornithine concentrations (SMD=0.67, 95% CI 0.13 to 1.22, p=0.015). In subgroup analysis, the SMD of homocysteine was significantly associated with the biological matrix assessed and the forced expiratory volume in the first second to forced vital capacity ratio, but not with age, study location, or analytical method used. Our study suggests the presence of significant alterations in metabolites within the arginine, transsulfuration, and folic acid pathways which can be useful for assessing nitric oxide dysregulation and oxidative stress and identifying novel treatment targets in COPD. (PROSPERO registration number: CRD42023448036)

This study propounds a sustainable alternative to petroleum-based polyurethane (PU) foams aiming to curtail this nonrenewable resource's continued and uncontrolled use. Coconut fatty acid distillate (CFAD) and crude glycerol (CG), both wastes from vegetable oil processes, were utilized for bio-based polyol production for rigid PU foam application. The raw materials were subjected to catalyzed glycerolysis with alkaline-alcohol neutralization and bleaching. The resulting polyol possessed properties suitable for rigid foam application with an average OH number of 215 mg KOH/g, acid number of 7.2983 mg KOH/g, and Gardner color value of 18. The polyol was used to prepare rigid PU foam, and its properties were determined using FTIR, TGA/DTA, and UTM. Additionally, the cell foam morphology was investigated by scanning electron microscope (SEM) in which most of its structure revealed an open-celled network and quantified at 92.71% open cell content using pycnometric testing. The PU foam thermal and mechanical analysis results showed an average compressive strength of 70.59 kPa, thermal conductivity of 46.50 mWm-1K-1, and density of 32.79 kgm-3. These properties showed its applicability as thermal insulating foam, thus, demonstrating the potential use of CFAD and CG in commercial polyol and PU foam production.

In globe artichoke both the edible portion and the waste biomass are recognized as valuable sources of bioactive compounds. For this study, heads with 30 cm-long floral stems, including 2-3 leaves, were harvested from five genotypes which included two traditional vegetatively-propagated varietal types (‘Brindisino,’ and ‘Violetto di Foggia,’) and three "seed"-propagated hybrids (‘Tempo,’ ‘Opal,’ and ‘Madrigal’). The study aimed to determine the total and individual polyphenolic concentrations (measured spectrophotometrically and by HPLC) and antioxidant activity (AA) in different artichoke parts, namely the "hearts" (H), head waste (HW), stem waste (SW), and leaf waste (LW). ‘Brindisino’ SW exhibited the highest accumulation of luteolin (26,317 mg kg−1 F.W.), while ‘Tempo’ H displayed the highest cynarin content (190 mg kg−1 F.W.). ‘Tempo’ HW and H showed the highest levels of apigenin (640 mg kg−1 F.W.), and the greatest source of chlorogenic acid was found in the HW of ‘Opal’ and the H of ‘Brindisino’ (4,300 mg kg−1 F.W.). The hybrids generally exhibited lower total polyphenolic concentrations than the traditional genotypes, particularly evident in the LW. The SW demonstrated the highest concentration of total polyphenols (18,000 mg kg−1 F.W.), followed by the edible H and non-edible HW (12,000 mg kg−1 F.W.), while the LW exhibited the lowest concentration (2,000 mg kg−1 F.W.). Interestingly, the AA did not precisely align with the total polyphenolic concentration, showing slight variations between the examined parts and genotypes.

Trans fatty acids (TFA) are a concern for public health due to their negative impact on cardiovascular health. This study aimed to assess the levels of TFA and other fatty acids in popular edible oils and fried foods commonly consumed in Tanzania. A total of 57 samples from 38 brands of edible oils and 20 samples of fried street foods and fast foods were collected in Dar es Salaam, Tanzania. Capillary gas chromatography was used to determine TFA levels, while nutritional labeling and other fatty acid classes were also evaluated. Among the analyzed edible oils, 21% exceeded the recommended TFA levels, primarily found in popular brands of margarine, industrially refined sunflower oils, animal butter, and peanut butter. Only two food items surpassed the 2% TFA limit, but a majority of the foods had high levels of saturated fatty acids and a fatty acid profile similar to palm oil. Additionally, only 22% of the edible oils provided TFA content information. These findings indicate the persistence of TFA levels beyond recommended limits and inadequate TFA nutritional labeling in Tanzanian food products. Urgent interventions are necessary to reduce TFA levels and improve nutritional labeling practices to safeguard public health.

This paper presents the development of a cheap and rapid electrochemical sensor for ascorbic acid detection. In particular, the graphite ink working electrode of screen-printed cells was covered by a film of elecrosynthesized molecularly imprinted polypyrrole (e-MIP); differential pulse voltammetry (DPV) was the selected method for the analyte detection. The ascorbic acid molecules were suc-cessfully entrapped in the polypyrrole film, creating the recognition sites. The best results were obtained after polypyrrole overoxidation and performing the measurements in phosphate buffer solution 0.05 M/KCl 0.1M at pH 7.5. The comparison with the bare and the not imprinted polypyrrole-modified electrodes showed the highest selectivity and reproducibility of the e-MIP-based sensor. The developed method was applied to assess ascorbic acid in farmaceutical products obtaining values not significantly different from the declared content.

Acetic acid bacteria (AAB) form a bacterial film on the surface of alcoholic solutions and ferment ethanol to acetic acid while also producing bioactive compounds. To discover functional AAB for industrial use, we isolated and selected strains from farm-produced vinegars using a CaCO3-containing medium. The seven strains belonged to Acetobacter cerevisiae and A. pasteurianus. Physiological properties were determined, including ethanol tolerance at up to 12% (v/v). Acidification at a growth temperature of 40 ℃ was seen for GHA 7, GYA 23, JGB 21-17, and GHA 20 strains, which may be useful in vinegar production where thermotolerant AAB are required. The seven AAB isolates had strong antibacterial activity against Staphylococcus aureus. Antioxidant activity was 2- and 4-fold higher, respectively, for A cerevisiae and A. pasteurianus than for the control, 1% acetic acid. We also observed 91.3% inhibition of angiotensin-converting enzyme activity for the KSO 5 strain, higher than that for the positive control, 0.1% captopril (76.9%). All strains showed complete inhibition of α-glucosidase, except JGB 21-17 and GHA 7 with 98.3% inhibition. Our work suggests usefulness of the strains selected as seed strains for highly efficient production of functional vinegar and illustrates identification of useful functional characteristics on a scientific basis.

Vitamin C status is known to be associated with several demographic and lifestyle factors. These include gender, age, ethnicity, pregnancy/lactation, body weight, smoking status and dietary habits. In the present study, our aim was to interrogate the National Health and Nutrition Examination Survey (NHANES) 2017-2018 datasets to assess the impact of these factors on vitamin C dose-concentration relationships to establish if there are higher requirements for vitamin C in certain subpopulations and the possible extent of these additional requirements. The relevant data were extracted from the NHANES 2017-2018 datasets, the final cohort of which comprised 2828 non-supplementing adult males and females (aged 18 – 80+ years) with both vitamin C serum concentrations and dietary intake data available. The data was subsequently stratified by gender, age tertiles (≤36, 37-58, ≥59 years), ethnicity (non-Hispanic white, non-Hispanic black, and total Hispanic), socioeconomic tertiles (poverty income ratios: >3.0, 1.36 – 3.0, ≤1.35), weight tertiles (≤72, 72-91, ≥91 kg), BMI tertiles (≤26, 26-32, ≥32 kg/m2) and smoking status. Sigmoidal (four parameter logistic) curves with asymmetrical 95% confidence intervals were fitted to the dose-concentration data. We found that males required vitamin C intakes ~1.2-fold higher than females to reach ‘adequate’ serum concentrations of 50 µmol/L. Males had both higher body weight and a higher prevalence of smoking than females. Smokers required vitamin C intakes ~2.0-fold higher than non-smokers to reach adequate vitamin C concentrations. Relative to adults in the lighter weight tertile, adults in the heaver weight tertile required ~2.0-fold higher dietary intakes of vitamin C to reach adequate serum concentrations. We did not observe any impact of ethnicity or socioeconomic status on the vitamin C dose-concentration relationship, and although no significant difference between younger and older adults was observed at vitamin C intakes > 75 mg/day, at intakes < 75 mg/day, older adults had an attenuated serum response to vitamin C intake. In conclusion, certain demographic and lifestyle factors, specifically gender, smoking and body weight, have a significant impact on vitamin C requirements. Overall, the data indicate that the general population must consume ~110 mg/day of vitamin C to attain adequate serum concentrations, smokers require ~165 mg/day relative to non-smokers, and heavier people (100+ kg) require ~155 mg/day to reach the same vitamin C concentrations. These findings have important implications for global vitamin C dietary recommendations.

SiO2-SO3H, with a surface area of 115 m2/g, pore volume of 0.38 cm3g-1 and 1.32 mmol H+/g, was used as a 20% w/w catalyst for the preparation of methyl salicylate (Wintergreen oil or MS) from acetylsalicylic acid (ASA). A 94% conversion was achieved in a microwave reactor during 40.0 minutes at 120 oC in MeOH. The resulting crude product was purified by flash chromatography. The catalyst could be re-used three times.

The plant graft healing process is an intricate development influenced by numerous endogenous and environmental factors. This process involves the histological changes, physiological and biochemical reactions, signal transduction, and hormone exchanges in the grafting junction. Studies have shown that applying exogenous plant growth regulators can effectively promote the graft healing process and improve the quality of grafted plantlets. However, the physiological and molecular mechanism of graft healing formation remains unclear. In our present study, transcriptome changes in the melon and cucurbita genomes were analyzed between control and NAA treatment, and we provided the first view of complex networks to regulate graft healing under exogenous NAA application. The results showed that the exogenous NAA application could accelerate the graft healing process of oriental melon scion grafted onto squash rootstock through histological observation, increase the SOD, POD, PAL, and PPO activities during graft union development and enhance the contents of IAA, GA3, and ZR except for the IL stage. The DEGs were identified in the plant hormone signal-transduction, phenylpropanoid biosynthesis, and phenylalanine metabolism through transcriptome analysis of CK vs. NAA at the IL, CA, and VB stage by KEGG pathway enrichment analysis. Moreover, the exogenous NAA application significantly promoted the expression of genes involved in the hormone signal-transduction pathway, ROS scavenging system, and vascular bundle formation.

Attempts to find and quantify the supposed low entropy of organisms and its preservation are revised. Absolute entropy of the mixed components of non-living biomass (around -1.6 x 103 J K-1 L-1) is the reference to which other entropy decreases would be ascribed to life. Compartmentation of metabolites and departure from the equilibrium of metabolic reactions account for 1 and 40-50 J K-1 L-1, respectively, decreases of entropy and, though small, are distinctive features of living tissues. DNA and proteins do not supply significant decreases of thermodynamic entropy, but their low informational entropy is relevant for life and its evolution. No other living feature contributes significantly to the low entropy associated to life. The photosynthetic conversion of radiant energy to biomass energy accounts for the most of entropy (2.8 x 105 J K-1 carbon kg-1) produced by living beings. The comparative very low entropy produced in other processes (around 4.8 x102 J K-1 L-1 day-1 in human body) must be rapidly exported outside as heat to preserve the low entropy decreases due to compartmentation and non-equilibrium metabolism. Enzymes and genes are described whose control minimize the rate of production of entropy and could explain selective pressures in biological evolution and the rapid proliferation of cancer cells.

Recent research has identified the gut-brain axis as a key mechanistic pathway and potential therapeutic target in depression. In this paper, the potential role of gut hormones as potential treatments or predictors of response in depression is examined, with specific reference to the peptide hormone motilin. This possibility is explored through two methods: (a) a conceptual review of the possible links between motilin and depression, including evidence from animal and human research as well as clinical trials, and (b) an analysis of the relationship between a functional polymorphism (rs2281820) of the motilin (MLN) gene and cross-national variations in the prevalence of depression. It was observed that (a) there are several plausible mechanisms, including interactions with diet, monoamine, and neuroendocrine pathways, to suggest that motilin may be relevant to the pathophysiology and treatment of depression, and (b) there was a significant correlation between rs2281820 allele frequencies and the prevalence of depression after correcting for multiple confounding factors. These results suggest that further evaluation of the utility of motilin and related gut peptides as markers of antidepressant response is required, and that these molecular pathways represent potential future mechanisms for antidepressant drug development.

Study of fungal antibiotics in their competitive interactions with arthropods may lead to development novel biorational insecticides. Extracts of Alternaria tenuissima MFP253011 obtained by various methods showed a wide range of biological activity, including entomotoxic properties. Analysis of their composition and bioactivity allowed to reveal several known mycotoxins and unidentified compounds that may be involved in entomotoxic activity of the extracts. Among them, tenuazonic acid (TeA), which was the major component of the A. tenuissima extracts, was found the most likely to have larvicidal activity against Galleria mellonella. In the intrahaemocoel injection bioassay, TeA was toxic to G. mellonella and of Zophobas morio with LT50 6 and 2 days, respectively, at the level of 50 µg/larva. Administered orally, TeA inhibited growth of G. mellonella larvae and caused mortality of Acheta domesticus imagines (LT50 7 days) at a concentration of 250 µg/g of feed. TeA showed weak contact-intestinal activity against the two phytophages, Tetranychus urticae and Schizaphis graminum, causing the 12 and 40% of mortality at a concentration of 1 mg/mL. TeA was cytotoxic to Sf9 cell line (IC50 25 µg/mL). Thus, model insect G. mellonella and cell line Sf9 could be used for a further toxicological characterization of TeA.

Endothelial cells form a powerful interface between tissues and immune cells. In fact, one of the underappreciated roles of endothelial cells is to orchestrate immune attention to specific sites. Tumor endothelial cells have a unique ability to dampen the immune responses and thereby maintain an immunosuppressive microenvironment. Recent approaches to trigger immune responses in cancers have focused on activating nucleic acid sensors such as cGAS/STING in combination with immunotherapies. In this review, we present a case for targeting nucleic acid sensing pathways within the tumor vasculature to invigorate tumor immune responses. We introduce two specific nucleic acid sensors, the DNA sensor TREX1 and the RNA sensor RIG-I and discuss their functional roles in the vasculature. Finally, we present perspectives on how these nucleic acid sensors in the tumor endothelium can be targeted in an antiangiogenic and immune activation context. We believe understanding the role of nucleic acid sensing in the tumor vasculature can enhance our ability to design more effective therapies targeting the tumor microenvironment.

Mitochondrial dysfunctions, e.g. abnormal handling of mitochondrial DNA in TFAM mutants or in altered mitophagy, activate innate immunity. Recent reports also showed that deletion of mitochondrial matrix peptidase ClpP in mice transcriptionally upregulates inflammatory factors. Here, we studied ClpP-null mouse brain at two ages and embryonal fibroblasts, to identify which signaling pathways are responsible, employing mass spectrometry, immunoblots, and reverse transcriptase polymerase chain reaction. Anomalies in the mitochondrial unfolded protein responses pathway were prominent for the co-chaperone DNAJA3, and for its known interactor STAT1. Their mitochondrial dysregulation affected also their extra-mitochondrial abundance, as possible innate immune modulators. Increased expression was observed not only for the transcription factors Stat1/2, but also for two interferon-stimulated genes (Ifi44, Gbp3). Inflammatory responses were strongest for RLR pattern recognition receptors (Ddx58, Ifih1, Oasl2, Trim25) and several cytosolic nucleic acid sensors (Ifit1, Ifit3, Oas1b, Ifi204, Mnda). They can be explained by the accumulation of mitoribosomes and mitochondrial nucleoids in ClpP-null cells, which may act as damage-associated molecular patterns. The consistent dysregulation of these factors from early age might influence also human Perrault syndrome, where ClpP loss-of-function leads to early infertility and deafness, with subsequent widespread neurodegeneration.

The aim of this work was the study and evaluation of winery by-products in the framework of circular bioeconomy. Grape seeds and grape skins from Greek traditional Ionian Islands varieties were analyzed in an attempt to provide the appropriate basis for model development of their sustainable exploitation at a local or regional level. The wastes collected directly from the wineries immediately after the vinification process and analyzed by chromatographic and spectroscopic techniques. Also, annual production and yields were estimated. Grape seed oil quality was evaluated based on fatty acid methyl esters (FAMEs) composition. Grape skins phenolic fraction was extracted by an eco-friendly, non-toxic water-glycerol solvent system and were detected qualitatively. Also, total phenolic content (TPC) and antioxidant activity were measured. Based on estimated yields, our results demonstrate that winery by-products have the potential to promote the cyclical bioeconomy in a modern economic growth model that will reduce waste, and environmental costs as they can be reused as whole material in foods, dietary supplements, cosmetic ingredients, food colorants and preservatives.

Gut microbiota and its metabolites like short chain fatty acids (SCFAs) are linked with pathology of Alzheimer’s disease (AD)- a debilitating public health problem in older adults. However, strategies to beneficially modulate gut microbiota and its sensing signaling pathways remain largely unknown. Here, we screened, validated and established the agonists of free fatty acid receptor 2 (FFAR2) signaling, which senses beneficial signals from SCFAs produced by microbiota in the gut. We demonstrated that inhibition of FFAR2 signaling increases amyloid-beta (Aβ) stimulated neuronal toxicity. Thus, we screened FFAR2 agonists, using in-silico library of more than 144,000 natural compounds, and 15 compounds were selected based on binding with FFAR2 agonist sites. Further, cell culture toxicity and FFAR2 stimulatory experiments demonstrated that Fenchol (a natural compound commonly present in basil) was potent FFAR2 agonist in neuronal cells. Interestingly, we also demonstrated that Fenchol protects Aβ-stimulated neurodegeneration in FFAR2 dependent manner. In addition, Fenchol reduced AD like phenotypes such as Aβ-accumulation and, learning and memory behaviors in Caenorhabditis (C.) elegans. Fenchol increased Aβ-clearance by increasing proteasome/lysosome activity and reduced senescence in neuronal cells. These results demonstrated that the inhibition of FFAR2 signaling promotes Aβ-induced neurodegeneration, while activating it by Fenchol as a natural agonist reverse it by promoting Aβ-clearance and reducing cellular senescence; thus stimulation of FFAR2 signaling can be a therapeutic approach to prevent/ treat AD.

This study aimed to assess the response of 3D printed PLA scaffolds biomimetically coated with apatite on human primary osteoblast spheroids and evaluate the biological response to its association with Bone Morphogenetic Protein 2 (rhBMP-2) in rat calvaria. PLA scaffolds were produced via 3D printing, soaked in simulated body fluid (SBF) solution, and characterized by physical-chemical, morphological, and mechanical properties. The in vitro biological response was assessed with human primary osteoblast (HOb) spheroids. The in vivo analysis was conducted through the implantation of 3D printed PLA scaffolds either alone, covered by apatite (PLA-CaP) or PLA-CaP loaded with rhBMP-2 (PLA-CaP+rhBMP-2) on critical-sized defects (8 mm) of rat calvaria. Increased cell adhesion and in vitro release of growth factors (PDGF, bFGF, VEGF) was observed for PLA-CaP scaffolds when pre-treated with FBS. PLA-CaP+BMP2 presented higher values of newly formed bone (NFB) than other groups at all experimental periods (p<0.05), attaining 44.85% of NFB after 6 months. These findings indicate that functionalization of PLA scaffolds with biomimetic apatite can improve its biological properties in the presence of complex biological media. Its association with BMP2 may enhance bone repair, suggesting this strategy as a promising candidate for bone tissue engineering.

Optical rotatory dispersion (ORD) is a beautiful analytical technique for the study of chiral molecules and polymers. In this study, ORD was applied successfully to follow the degree of polycondensation of l-(+)-lactic acid toward the formation of poly(lactic acid) oligomers (PLAO) and high molecular weight poly(l-lactic acid) (PLLA) in a simple esterification reaction equipment. PLLA is a biodegradable polymer obtainable from renewable raw materials. The racemization of the intrinsically isotactic PLLA through thermal treatment can be easily followed through the use of ORD spectroscopy. Organic or molecular electronics is a hot topic dealing with the combination of π-conjugated organic compounds and polymers with specific properties (e.g. chirality) which can be exploited to construct optoelectronic devices such as organic light-emitting diodes (OLEDs), organic photovoltaic (OPV) high efficiency cells, switchable chirality devices, organic field-effect transistors (OFETs), and so on. ORD spectroscopy was applied to study either the gigantic optical rotation of PLLA films as well as to detect successfully the excitonic coupling occurring in thin solid PLLA green film loaded with a combination of two dyes: SY96 (a pyrazolone dye) and PB16 (the metal-free phthalocyanine pigment). The latter compound PLLA loaded with SY96 and PB16 shows a really gigantic optical activity in addition to typical ORD signal due to exciton coupling and may be considered as a simple and easily accessible model composite of a chiral polymer matrix combined with π-conjugated dyes for molecular electronics studies.

The development of a highly specific drug delivery system (DDS) for anti-cancer therapeutics is an area of intense research focus. Chemical engineering of a “smart” DDS to specifically target tumor cells has gained interest, designed for safer, more efficient, and effective use of chemotherapeutics for the treatment of cancer. However, the selective targeting and choosing the critical cancer surface biomarker are essential for targeted treatments to work. The folic acid receptor alpha (FRalpha) has gained popularity as a potential target in triple-negative breast cancer (TNBC). We have previously reported on a functionalized folic acid (FA)-conjugated amphiphilic alternating copolymer poly(styrene-alt-maleic anhydride) (FA-DABA-SMA) via a biodegradable linker 2,4-diaminobutyric acid (DABA) that has the essential features for efficient “smart” DDS. This biocompatible DDS self-assembles in a pH-dependent manner, providing stimuli-responsive, active targeting, extended-release of hydrophobic chemotherapeutic agents, and can effectively penetrate the inner core of 3-dimensional cancer spheroid models. The empty FA-DABA-SMA decreased spheroid volume, revealing a previously unknown mechanism of action. Upon further investigation, a size- and shape-dependent interaction FA-DABA-SMA with FR reduced the expression of p53, the product of the highly mutated TP53 gene, and additional oncogenic c-Myc and STAT3 proteins. Here, we investigated how this copolymer influences FR behavior and disrupting the receptor’s functions. Results indicate that FA-DABA-SMA increases FR expression levels in breast MDA MB-231 cancer cells and disrupting FR signaling by the reduction in HES1 and NOTCH1 protein expression levels. Also, FA-DABA-SMA induces apoptosis and further causes a change in the morphology of the MDA MB-231 cells, as well as significantly reduces their ability to migrate in a Scratch wound assay. Collectively, these findings provide a novel insight into the functionalized FA-DABA-SMA copolymer. The 350 kDa and 20 kDa copolymers actively target FRα to initialize internationalization. However, only the large size and sheet-shaped 350 kDa copolymers disrupt FRα signaling. The significance of these novel findings reveals the intracellular activity of the copolymer that is critically dependent on the size and structural shape. This report offers novel therapeutic insight into a dual mechanism of FA-DABA-SMA copolymer for its therapeutic potential for the treatment of cancer.

Almond (Prunus dulcis (Mill.) D.A.Webb) is one of the largest nut crops in the world. Recently, phenolic compounds, mostly stored in almond skin, have been associated with much of the health-promoting behavior associated with their intake. The almond skin enriched fraction obtained from cold-pressed oil residues of the endemic Moroccan Beldi ecotypes is particularly rich in chlorogenic acid. In this study, both almond skin extract (AE) and chlorogenic acid (CHL) supplements, similar to traditional positive control resveratrol, significantly increased the replicative life-span of yeast compared to the untreated group. Our results showed that AE and CHL significantly reduced the production of reactive oxygen and nitrogen species (ROS/RNS), most likely due to their ability to maintain mitochondrial function during aging, as indicated by the maintenance of normal mitochondrial membrane potential in treated groups. This may be associated with the observed activation of the anti-oxidative stress response in treated yeast, which results in activation at both gene expression and enzymatic activity levels for SOD2 and SIR2, the latter being an upstream inducer of SOD2 expression. Interestingly, the differential gene expression induction of mitochondrial SOD2 gene at the expense of the cytosolic SOD1 gene confirms the key role of mitochondrial function in this regulation. Furthermore, AE and CHL have contributed to the survival of yeast under UV-C-induced oxidative stress, by reducing the development of ROS / RNS, resulting in a significant reduction in cellular oxidative damage as evidenced by decreased membrane lipid peroxidation, protein carbonyl content and 8-oxo-guanine formation in DNA. Together, these results demonstrate the interest of AE and CHL as new regulators in the replicative life-span and control of the oxidative stress response of yeast.

Pneumonia is a severe lower respiratory tract infection that is a common complication and a major cause of mortality of the vitamin C-deficiency disease scurvy. This suggests an important link between vitamin C status and lower respiratory tract infections. Due to the paucity of information on the vitamin C status of patients with pneumonia, we assessed the vitamin C status of 50 patients with community-acquired pneumonia and compared these with 50 healthy community controls. The pneumonia cohort comprised 44 patients recruited through the Acute Medical Assessment Unit (AMAU) and 6 patients recruited through the intensive care unit (ICU); mean age 68 ± 17 years, 54% male. Clinical, microbiological and haematological parameters were recorded. Blood samples were tested for vitamin C status using HPLC with electrochemical detection and protein carbonyl concentrations, a marker of oxidative stress, using ELISA. Patients with pneumonia had depleted vitamin C status compared with healthy controls (23 ± 14 µmol/L vs 56 ± 24 µmol/L, P <0.001). The more severe patients in the ICU had significantly lower vitamin C status than those recruited through AMAU (11 ± 3 µmol/L vs 24 ± 14 µmol/L, P = 0.02). The total pneumonia cohort comprised 62% with hypovitaminosis C and 22% with deficiency, compared with only 8% hypovitaminosis C and no cases of deficiency in the healthy controls. The pneumonia cohort also exhibited significantly elevated protein carbonyl concentrations compared with the healthy controls (P < 0.001), indicating enhanced oxidative stress in the patients. We were able to collect subsequent samples form 28% of the cohort (mean 2.7 ± 1.7 days; range 1-7 days). These showed no significant differences in vitamin C status or protein carbonyl concentrations compared with baseline values (P = 0.6). Overall, the depleted vitamin C status and elevated oxidative stress observed in the patients with pneumonia indicates an enhanced requirement for the vitamin during their illness. Due to the important roles that vitamin C plays in the immune system, low vitamin C status is possibly both a cause and a consequence of the disease. Therefore, these patients would likely benefit from additional vitamin C supplementation to restore their blood and tissue levels to optimal. This may decrease oxidative stress and aid in their recovery.

Succinic semialdehyde dehydrogenase deficiency (SSADH-D) is a genetic disorder that results from the aberrant metabolism of the neurotransmitter γ-amino butyric acid (GABA). The disease is caused by the impaired activity of the mitochondrial enzyme succinic semialdehyde dehydrogenase. SSADH-D manifests as varying degree of mental retardation, autism, ataxia and epileptic seizures, but the clinical picture is highly heterogeneous. So far, there is no approved therapy for this disease. In this review, we briefly summarize the molecular genetics of SSADH-D, the past and ongoing clinical trials and the emerging features of the molecular pathogenesis, including redox imbalance and mitochondrial dysfunction. The main aim of this review is to discuss the potential use of further therapy approaches that have so far not been tested in SSADH-D, such as pharmacological chaperones, read-through drugs and gene therapy. Special attention will also be paid to elucidating the role of patient advocacy organizations in facilitating research and in the communication between the researchers and the patients.

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting variety of hydrophobic ligands including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth and this can be attributed to its estrogen-binding ability. Despite AFP has long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP-ligand interaction remain obscure. In our study we constructed homology-based 3D model of human AFP (HAFP) with the purpose to perform docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol) and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on ligand docked scoring function, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity sites were located in (i) a tunnel formed within HAFP subdomains IB and IIA and (ii) opposite side of the molecule in a groove originating from cavity formed between domains I and III, while (iii) the third low-affinity site was found at the bottom of the cavity. 100 ns MD simulation allowed studying their geometries and showed that HAFP-estrogen interactions occur due to van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP-antiestrogen binding. MM/GBSA rescoring method estimated binding free energies (ΔG_bind) and showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP-ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues along two disulfide bonds, Cys224-Cys270 and Cys269-Cys277 have key roles in both HAFP-estrogen and HAFP-antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein-ligand interactions and anti-cancer therapy strategies based on ER-binding ligands.

There are numerous approaches to model an influence of manufacturing parameters on the dissolution and disintegration of solid dosage forms. A modern approach for modelling and simulating complex and heterogeneous systems such as pharmaceutical tablets focuses on computationally-intensive finite-element or discreet element methods. Industrial challenges such as Process Analytical Technology (PAT) and Quality by Design are stimulating computer-based technologies to design, control and improve the quality of pharmaceutical compacts and their performance. In this study the disintegration and dissolution model based on the numerical solutions of the Noyes-Whitney equation and cellular automata supported disintegration model are proposed and evaluated. The results from in vitro release studies of the mefenamic acid formulations were compared to the calculated release patterns from the tablet structures obtained from microtomography experiments and the purely algorithmically created virtual tablets.

The blue sepal color of hydrangea is due to a metal complex anthocyanin composed of 3-O-glucosyldelphinidin (1) and an aluminum ion with the co-pigments 5-O-caffeoylquinic acid (2) and/or 5-O-p-coumaroylquinic acid (3). The three components, namely, anthocyanin, Al³⁺ and 5-O-acylquinic acids, are essential for blue color development, but the complex is unstable and only exists in aqueous solution. Furthermore, the complex did not give analyzable NMR spectra or crystals. Therefore, many trials to determine the detailed chemical structure of the hydrangea-blue complex have failed to date. Instead, via experiments mixing 1, Al³⁺ and 2 or 3 in a buffered solution at pH 4.0, we obtained the same blue solution derived from the sepals. However, the ratio was not stoichiometric but fluctuated. To determine the composition of the complex, we tried direct observation of the molecular ion of the complex using electrospray-ionization mass spectrometry. In a very low-concentration buffer solution (2.0 mM) at pH 4.0, we reproduced the hydrangea-blue color by mixing 1, 2 and Al³⁺ in ratios of 1:1:1, 1:2:1 and 1:3:1. All solution gave the same molecular ion peak at m/z = 843, indicating that the blue solution has a ratio of 1:1:1 for the complex. By using 3, the observed mass number was m/z = 827 and the ratio of 1, 3 and Al³⁺ was also 1:1:1. A mixture of 1, 3-O-caffeoylquinic acid (4) and Al³⁺ did not give any blue color but instead was purple, and the intensity of the molecular ion peak at m/z = 843 was very low. These results strongly indicate that the hydrangea blue-complex is composed of a ratio of 1:1:1 for 1, Al³⁺ and 2 or 3.

Abstract: Measures to counteract AMD generation need to start at the mineral surface, inhibiting mineral-oxidizing, acidophilic microbes. Laboratory and long-term field tests with pyrite-containing mining wastes, where Carbonaceous Phosphate Mining Waste (CPMW) was added, resulted in low acidity, and near neutral drainage. The effect was reproducible, nd confirmed by several independent research groups. This was shown to involve an organic coating, likely a biofilm. The biofilm formation was confirmed when CPMW was added to lignite coal waste with an initial pH of 1. Forty five days after the addition, the coal waste was dominated by heterotrophic microorganisms in biofilms. A review of the scientific literature supports that CPMW has physical and chemical characteristics which are capable of inducing a strong inhibitory effect on sulphide oxidation by forming an organic coating over the mineral surface. CPMW characteristics appear to provide the cornerstone of a new technology for the reduction of sulphide oxidation in mine wastes. An hypothesis for testing this technology is presented which could result in an economical and sustainable approach to mine waste and water management.

Establishment of diagnostic methods with low detection limits plays a critical role in the maintenance of early diagnosis, prevention of serious neurological complications, and control of the spread of ZIKA. In this study, we established the micro-droplet digital polymerase chain reaction (ddPCR) and real-time fluorescent quantification PCR (qPCR) protocols for the detection of Zika virus based on the NS5 gene. For the Zika standard plasmid, the standard curve of R² was 0.999, and the amplification efficiency was 92.203%, as determined by qPCR. Both ddPCR and qPCR were positive for cell culture of Zika nucleic acid.The minimum detection limit of ddPCR is 1–2 times lower than qPCR. Moreover, all tests of Dengue virus (1–4 serotypes) were negative in cell culture. Overall, these results suggested than ddPCR may have a lower limit of detection than qPCR.

Ataxin-2 (ATXN2) acts during stress-responses, modulating mRNA translation and nutrient metabolism. Atxn2 knockout mice exhibit progressive obesity, dyslipidemia and insulin resistance. Conversely, the progressive ATXN2 gain-of-function due to polyGlutamine (polyQ) expansions leads to a dominantly inherited neurodegenerative process named spinocerebellar ataxia type 2 (SCA2), with early adipose tissue loss and late muscle atrophy. We tried to understand lipid dysregulation in a SCA2 patient brain and in an authentic mouse model. Thin layer chromatography of a patient cerebellum was compared to the lipid metabolome of Atxn2-CAG100-KnockIn (KIN) mouse spinocerebellar tissue. The human pathology caused deficits of sulfatide, galactosylceramide, cholesterol, C22/24-sphingomyelin and gangliosides GM1a/GD1b, despite quite normal levels of C18-sphingomyelin. Cerebellum and spinal cord from the KIN mouse showed a consistent decrease of various ceramides, with a significant elevation of sphingosine in the more severely affected spinal cord. Deficiency of C24/26-sphingomyelins contrasted with excess C18/20-sphingomyelin. Spinocerebellar expression profiling revealed consistent reductions of CERS protein isoforms, of Sptlc2 and Smpd3, but upregulation of Cers2 mRNA, as prominent anomalies in the ceramide-sphingosine metabolism. Reduction of Asah2 mRNA correlated to deficient S1P levels. In addition, downregulations for the elongase Elovl1, Elovl4, Elovl5 mRNAs and ELOVL4 protein explain the deficit of very-long-chain sphingomyelin. Reduced ASMase protein levels correlated to the accumulation of long-chain sphingomyelin. Overall, a deficit of myelin lipids was prominent in SCA2 nervous tissue at prefinal stage, not compensated by transcriptional adaptation of several metabolic enzymes. Myelination is controlled by mTORC1 signals, so our human and murine observations are in agreement with the known role of ATXN2 yeast, nematode and mouse orthologs as mTORC1 inhibitors and autophagy promoters.

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

We present multi-sensor measurements from satellites, unmanned aerial vehicle, marine radar, thermal profilers and repeated conductivity-temperature-depth casts made in the Kara Gates strait connecting the Barents and the Kara Seas during spring tide in August 2021. Analysis of the field data during an 18-hour period from four stations evidence that a complex sill in the Kara Gates is the site of regular production of intense large-amplitude nonlinear internal waves. Satellite data show a presence of a relatively warm northeastward surface current from the Barents Sea toward the Kara Sea attaining 0.8-0.9 m/s. Triangle-shaped measurements of three thermal profilers revealed pronounced vertical thermocline oscillations up to 40 m associated with propagation of short-period nonlinear internal waves of depression generated by stratified flow passing a system of shallow sills in the strait. The most intense waves were recorded during the ebb tide slackening and reversal when the background flow was predominantly supercritical. Observed internal waves had wavelength of ~100 m and travelled northeastward with phase speeds of 0.8-0.9 m/s. The total internal wave energy per unit crest length for the largest waves was estimated to be equal to 1.0-1.8 MJ/m.

Specific climate adaptation and resilience measures can be efficiently designed and implemented at the regional and local level. Climate and environmental databases are of critical importance to achieving sustainability goals (SDGs) and for the efficient planning and implementation of suitable mitigation measures: Available databases can serve municipalities as a vital starting points to determine requirements, prioritize resources and allocate investments under consideration of commonly tight budget restrictions. High-quality geo, climate and environmental data are now available – data from remote sensing, i.e. Copernicus services will be of crucial importance. Forward-looking approaches exist to using such data to derive forecasts for urban planning process optimization for municipal administrations. On municipal level, however, the existing data have so far only been used to a limited extent, since there are no practical tools for urban planning that can be used to merge and meaningfully combine remote sensing data with local data and to further process and apply in municipal planning processes. Therefore, our project CoKLIMAx aims at the development of new digital products, advanced urban services and procedures, such as the development of practice-oriented technical tools that acquire various remote sensing and in-situ data sets for validation and further processing.

There is great importance and need of improving existing carbon materials fabrication methods. As such, this work proposes to discuss, interrogate, and propose viable hydrothermal, solvothermal, and other advanced carbon materials synthetic methods. The advanced carbon materials to be interrogated will include the synthesis of carbon dots, carbon nanotubes, nitrogen/titania-doped carbons, graphene quantum dots, and their nanocomposites with solid/polymeric/metal oxide supports. This will be done with special mind to microwave-assisted solvothermal and hydrothermal synthesis due to their favourable properties such as rapidity, low cost, and green/environmentally-friendliness. Thus, these methods are important during the current and future synthesis and modification of advanced carbon materials for application in energy, gas separation, sensing, and water treatment. Simultaneously, the work will pay special cognizance to methods reducing the fabrication costs and environmental impact while enhancing the properties as a direct result of the synthesis methods. As a direct result, the expectation is to impart a significant contribution to the scientific body of work regarding the improvement of the said fabrication methods.

An accurate radiative transfer model (RTM) is essential for the retrieval of soil moisture (SM) from microwave remote sensing data, such as the passive microwave measurements from the Soil Moisture Active Passive (SMAP) mission. This mission delivers soil moisture products based upon L-band brightness temperature data, via retrieval algorithms for surface and root-zone soil moisture, the latter is retrieved using data assimilation and model support. We found that the RTM based on the tau-omega (?-ω) model, can suffer from significant errors over croplands (in average between -9.4K and + 12.0K for Single Channel Algorithm SCA; -8K and + 9.7K for Dual-Channel Algorithm DCA) if the vegetation scattering albedo (omega) is treated as a constant and the temporal variations are not accounted. In order to reduce this uncertainty, we propose a time-varying parameterization of omega for the widely established zeroth order radiative transfer ?-ω model. The main assumption is that omega can be expressed by a functional relationship between vegetation optical depth (tau) and the Green Vegetation Fraction (GVF). The validation was performed from 14 May to 13 December 2015 over 61 Climate Reference Network sites (SCRN) classified as croplands. The application of the proposed time-varying vegetation scattering albedo results in a consistent improvement for the unbiased root mean square error of 16% for SCA and 15% for DCA. The reduction for positive and negative biases was 45% and 5% for SCA and 26% and 12% for DCA, respectively. This indicates that vegetation dynamics on croplands are better represented by a time-dynamic single scattering albedo.

Wetlands are one of the crucial natural resources. They provide invaluable biodiversity resources, aid in water quality improvement, support ground water recharge, help in moderating climate change and support flood control. Environment is in the other hand, where we live and something, we are very familiar with our day to day life. Geographic Information Systems (GIS), Remote Sensing and Global Positioning System (GPS) were a useful tool for wetland and environmental change analysis and to improve on the classification accuracy. This study investigates population and environmental change of Jarmet wetland and its surrounding area change analysis over the period of 1972 to 2015. The purpose of this study was to show land use/ land cover change of Jarmet wetland and its surrounding environment over years as a response to population growth. For this purpose, multi-temporal satellite imageries (Landsat MSS 1972, TM1986, ETM+ 2000, 2005 and 2015 and SRTM 2000) were obtained and used for LULC change analysis, elevation analysis and change detection analysis. ERDAS Imagine 2015, ARC GIS 10.5.1, Global Mapper11, ENVI 5.0 and DNR Garmin softwares were used to process the image data and accuracy assessment analysis. The result of LULC showed that there is spatial reduction in wetland, forest, Shrubland and grassland in the period of 43 years (1972-2015) by -1,722.8 ha, -296.2 ha, -1,718.7 ha and -661.9 ha respectively, due to increase in the farmland and plantation area as a response to overpopulation, lack of environmental policy implementation and irresponsible for natural resource degradation. The accuracy assessment of LULC change are done for recent satellite image showed the overall accuracy of 84.06% with Kappa index 75.19% this means this classification is accurately classified and handle greater than 75% of error. Finally, this study suggests that create strictly natural resource conservation law, stopping illegal expansion of farmland, educating society about the value of natural resource especially wetland and create a source of income for society rather than farming.

Land surface albedo determines the splitting of downwelling solar radiation into components which are either reflected back to the atmosphere or absorbed by the surface. Land surface albedo is an important variable for the climate community and therefore was defined by the Global Climate Observing System (GCOS) as an Essential Climate Variable (ECV). Within the scope of the Satellite Application Facility for Land Surface Analysis (LSA SAF) of EUMETSAT, a near-real time (NRT) daily albedo product was developed in the last decade from observations provided by the SEVIRI instrument on board the geostationary satellites of the Meteosat Second Generation (MSG) series. In this study we present a new collection of albedo satellite products based on the same satellite data. The MSG Ten-day ALbedo (MTAL) product incorporates MSG observations over 31 days with a frequency of NRT production of 10 days. The MTAL collection is more dedicated to climate analysis studies compared to the daily albedo that was initially designed for the weather prediction community. For this reason, a homogeneous reprocessing of MTAL was done in 2018 to generate a Climate Data Record (CDR). The resulting product is called MTAL-R and has been made available to the community in addition to the NRT version of the MTAL product which has been available for several years. The retrieval algorithm behind the MTAL products comprises three distinct modules: one for atmospheric correction, one for daily inversion of a semi-empirical model of the bidirectional reflectance distribution function, and one for monthly composition that also determines surface albedo values. In this study the MTAL-R CDR is compared to ground surface measurements and concomitant albedo products collected by sensors on-board polar-orbiting satellites (SPOT-VGT and MODIS). We show that MTAL-R meets the quality requirements if MODIS or SPOT-VGT are considered as reference. This work leads to 14 years of production of geostationary land surface albedo products with a guaranteed continuity in the LSA SAF for the future years with the forthcoming third generation of European geostationary satellites.

Fogo volcano erupted in 2014-15 producing an extensive lava flow field in the summit caldera that destroyed two villages, Portela and Bangaeira. The eruption started with powerful explosive activity, lava fountains, and a substantial ash column accompanying the opening of an eruptive fissure. Lava flows spreading from the base of the eruptive fissure produced three arterial lava flows. By a week after the start of the eruption, a master lava tube had already developed within the eruptive fissure and along the arterial flow. In this paper, we analyze the emplacement processes on the basis of observations carried out directly on the lava flow field, remote sensing measurements carried out with a thermal camera, SO₂ fluxes, and satellite images, in order to unravel the key factors leading to the development of lava tubes. These were responsible for the rapid expansion of lava for the ~7.9 km length of the flow field, as well as the destruction of the Portela and Bangaeira villages. The key factors leading to the development of tubes were the low topography and the steady magma supply rate along the arterial lava flow. Comparing time-averaged effusion rates (TADR) obtained from satellite and Supply Rate (SR) derived from SO₂ flux data, we estimate the amount and timing of the lava flow field endogenous growth, with the aim of developing a tool that could be used for hazard assessment and risk mitigation at this and other volcanoes.

The performance in terms of minimal Bayes’ error probability for detection of a high-dimensional random tensor is a fundamental under-studied difficult problem. In this work, we consider two Signal to Noise Ratio (SNR)-based detection problems of interest. Under the alternative hypothesis, i.e., for a non-zero SNR, the observed signals are either a noisy rank-R tensor admitting a Q-order Canonical Polyadic Decomposition (CPD) with large factors of size Nq  R, i.e, for 1  q  Q, where R, Nq ! ¥ with R1/q/Nq converge towards a finite constant or a noisy tensor admitting TucKer Decomposition (TKD) of multilinear (M1, . . . ,MQ)-rank with large factors of size Nq  Mq, i.e, for 1  q  Q, where Nq,Mq ! ¥ with Mq/Nq converge towards a finite constant. The detection of the random entries (coefficients) of the core tensor in the CPD/TKD is hard to study since the exact derivation of the error probability is mathematically intractable. To circumvent this technical difficulty, the Chernoff Upper Bound (CUB) for larger SNR and the Fisher information at low SNR are derived and studied, based on information geometry theory. The tightest CUB is reached for the value minimizing the error exponent, denoted by s?. In general, due to the asymmetry of the s-divergence, the Bhattacharyya Upper Bound (BUB) (that is, the Chernoff Information calculated at s? = 1/2) can not solve this problem effectively. As a consequence, we rely on a costly numerical optimization strategy to find s?. However, thanks to powerful random matrix theory tools, a simple analytical expression of s? is provided with respect to the Signal to Noise Ratio (SNR) in the two schemes considered. A main conclusion of this work is that the BUB is the tightest bound at low SNRs. This property is, however, no longer true for higher SNRs.

When extract building from high resolution remote sensing image with meter/sub-meter accuracy, the shade of trees and interference of roads are the main factors of reducing the extraction accuracy. Proposed a Bayesian Convolutional Neural Networks(BCNET) model base on standard fully convolutional networks(FCN) to solve these problems. First take building with no shade or artificial removal of shade as Sample-A, woodland as Sample-B, road as Sample-C. Set up 3 sample libraries. Learn these sample libraries respectively, get their own set of feature vector; Mixture Gauss model these feature vector set, evaluate the conditional probability density function of mixture of noise object and roofs; Improve the standard FCN from the 2 aspect:(1) Introduce atrous convolution. (2) Take conditional probability density function as the activation function of the last convolution. Carry out experiment using unmanned aerial vehicle(UVA) image, the results show that BCNET model can effectively eliminate the influence of trees and roads, the building extraction accuracy can reach 97%.

Cereal wastes such as rice bran and cereal dust are valuable yet underutilised by-products of grain processing. This study aimed to bio-convert these wastes into bacterial cellulose (BC), an emerging sustainable and renewable biomaterial, via an inexpensive solid-state fermentation (SSF) pre-treatment using three mould isolates. Medium substitution by directly using untreated rice bran or cereal dust did not significantly increase the yield of bacterial cellulose produced by a novel Novacetimonas sp. isolate (NCBI accession number PP421219) compared to the standard Hestrin-Schramm (HS) medium. In contrast, rice bran fermented with Rhizopus oligosporus yielded the highest bacterial cellulose (1.55 ± 0.6 g/L dry weight) compared to the untreated control (0.45 ± 0.1 g/L dry weight), demonstrating up to 22 % increase in yield. Using the SSF process, the media production costs were reduced by up to 90% compared to standard HS medium. Physicochemical characterisation using SEM, EDS, FTIR, XPS, XRD, and TGA were performed to gain insights into the internal structure, morphology, and chemical bonding of different produced BC, which revealed comparable biopolymer properties between BC produced in standard and waste-based media. Hence, our findings demonstrate the effectiveness of fungal SSF for transforming abundant cereal waste into BC, providing a circular economy solution to reduce waste and convert them into by-products to enhance the sustainability of the cereal industry.

This study comprehensively evaluates the DNA/RNA Defend Pro (DRDP) sample collection buffer designed to inactivate and stabilize patient samples. The primary objectives encompassed assessing DRDP's efficacy in ensuring sample stability, facilitating extraction-free polymerase chain reaction (PCR), and ensuring compatibility with rapid antigen testing.Ninety-five diagnostic nasopharyngeal swab samples tested for influenza A/B, RSV A/B, and/or SARS-CoV-2 were diluted 1/10 with DRDP and anonymized. Stability testing involved incubating 31 positive samples at 4 °C, 20 °C, and 37 °C for 7 days, with regular extraction-free nucleic acid amplification testing (NAAT).Results demonstrated that DRDP guaranteed viral RNA stability at all temperatures for influenza, SARS-CoV-2 and RSV showing stability up to 7 days at 4 °C. DRDP-diluted samples exhibited robust compatibility with direct PCR, as 72 out of 88 samples positive for cobas Liat also tested positive for direct PCR. Non-concordant results could be explained by the 200-fold lower input in the extraction-free NAAT.Compared to NAAT, rapid antigen testing demonstrated lower sensitivity, as expected, while maintaining perfect specificity. Clear cutoffs between positive and negative rapid antigen testing results were observed in both cobas Liat and direct PCR analyses, validating DRDP's compatibility with these techniques. In conclusion, DRDP is an effective stabilizing medium compatible with direct PCR and rapid antigen testing and shows great potential for optimizing diagnostic processes, particularly in resource-limited or time-sensitive scenarios.

The manufacturing method influences the properties of the produced components. This work investigates the influence of manufacturing methods such as fused filament fabrication (3D printing) and injection molding on water absorption, mechanical and thermal properties of the specimens produced from neat biobased poly(lactic acid) (PLA) polymer and poly(lactic acid)/wood composites. Acrylonitrile butadiene styrene (ABS) acts as the reference material due to its low water absorption and good functional properties. The printing layer thickness is one of the factors that affects the properties of a 3D printed specimen. The investigation includes two different layer thicknesses (0.2 mm and 0.3 mm) while maintaining uniform overall thickness of the specimens across two manufacturing methods. 3D printed specimens absorb significantly higher amounts of water than the injection molded specimens, and the increase in the layer thickness of the 3D printed specimens contributes to further increased water absorption. However, the swelling due to water absorption in 3D printed specimens decreases on increased layer thickness. Tensile, flexural and impact properties of all the specimens decrease after water absorption while the properties improve on decreasing the layer thickness. Higher porosity on increasing the layer thickness is the predominant factor. The results from dynamic mechanical analysis and microscopy validate the outcomes.

In an era of increasing interest in the potential health benefits of medicinal foods, the need to assess their safety and potential toxicity remains a critical concern. While these natural remedies have garnered substantial attention for their therapeutic potential, a comprehensive understanding of their effects on living organisms is essential. We examined 316 herbal extracts to determine their potential nematocidal attributes in Caenorhabditis elegans. Approximately 16% of these extracts exhibited the capacity to induce diminished survival rates and larval arrest, establishing a correlation between larval arrest and overall worm viability. Certain extracts led to an unexpected increase in male nematodes, accompanied by a discernible reduction in DAPI-stained bivalent structures and perturbed meiotic advancement, thereby disrupting the conventional developmental processes. Notably, Onobrychis cornuta and Veratrum lobelianum extracts activated a DNA damage checkpoint response via the ATM/ATR and CHK-1 pathways; hindering germline development. Our LC‒MS analysis revealed jervine in V. lobelianum and nine antitumor compounds in O. cornuta. Interestingly, linoleic acid replicated phenotypes induced by O. cornuta exposure, including an increased level of pCHK-1 foci, apoptosis, and the MAPK pathway. We observed that mutants in the MAPK pathway suppressed the reduction in worm survival, emphasizing its role in survivability, meiotic progression, and DNA damage checkpoint-mediated apoptosis. This study reveals complex interactions between herbal extracts and C. elegans processes, shedding light on potential antitumor effects and mechanisms. The findings provide insights into the complex landscape of herbal medicine's impact on a model organism, offering implications for broader applications.

The approval of sucrose fatty acid esters (SFAEs) as food additives/preservatives has triggered enormous interest in discovering new applications for these materials. Accordingly, many researchers reported that SFAEs consist of various sugar moieties, and hydrophobic side chains are highly active against certain fungal species. The combination of chain length and site of acylation is crucial in endowing the SFAE with high antimicrobial potency against Aspergillus species. Following several important studies, we herein present the synthesis and an assessment of the effects of acylation site and chain length (i.e., C-6 vs. C-2, C-3, C-4, and long-chain vs. short-chain) on the antimicrobial activity of mannopyranoside fatty acid esters. In vitro tests revealed that the fatty acid chain length in mannopyranoside esters significantly affects the antifungal activity where C12 chains are more potent against Aspergillus species. In terms of acylation site, mannopyranoside esters with a C8 chain substituted at the C-6 position are more active in antifungal inhibition. Molecular docking also revealed that these mannopyranoside esters had comparatively better stable binding energy, and hence better inhibition, with the fungal enzymes lanosterol 14-alpha-demethylase (3LD6), urate oxidase (1R51), and glucoamylase (1KUL) than the standard antifungal drug fluconazole. Additionally, the thermodynamic, orbital, drug-likeness, and safety profiles of these mannopyranoside esters were calculated and discussed, along with the structure-activity relationships (SAR). This study thus highlights the importance of the acylation site and lipid-like fatty acid chain length that govern the antimicrobial activity of mannopyranoside-based SFAE.

Vitamin C is an essential enzyme cofactor and antioxidant with pleiotropic roles in human physiology. Circulating vitamin C concentrations are lower in people with diabetes mellitus suggesting a higher dietary requirement for the vitamin. We interrogated the NHANES 2017/2018 and EPIC-Norfolk datasets to compare vitamin C requirements between those with and without diabetes mellitus using dose-concentration relationships fitted with sigmoidal (four parameter logistic) curves. The NHANES cohort (n=2828 non-supplementing adults) comprised 488 (17%) participants with diabetes (self-reported or HbA1c ≥6.5%). The participants with diabetes had a lower vitamin C status (median [IQR]) than those without (38 [17, 52] µmol/L vs 44 [25, 61] µmol/L, p&lt;0.0001), despite comparable dietary intakes between the two groups (51 [26, 93] mg/d vs 53 [24, 104] mg/d, p=0.5). Dose-concentration relationships indicated that the group without diabetes reached adequate vitamin C concentrations (50 µmol/L) with an intake of 81 (72, 93) mg/d, whilst the those with diabetes required an intake of 166 (126, NA) mg/d. In the EPIC-Norfolk cohort, comprising 20692 non-supplementing adults, 475 (2.3%) had self-reported diabetes at baseline. The EPIC cohort had lower a BMI than the NHANES cohort (26 [24, 28] kg/m2 vs 29 [25, 34] kg/m2, respectively). Correspondingly, the EPIC participants without diabetes required a lower vitamin C intake of 64 (63, 65) mg/d while those with diabetes required 129 (104, NA) mg/d to reach adequate circulating vitamin C status. C-reactive protein concentrations were strongly correlated with body weight and BMI and provided a surrogate biomarker for vitamin C requirements. In conclusion, people with diabetes have 1.4- to 1.6-fold higher requirements for vitamin C than those without diabetes. This corresponds to additional daily vitamin C intake requirements of ~30-40 mg for people with diabetes.

The diagnosis and management of cow's milk allergy (CMA) is a topic of debate and controversy. We aimed to compare the opinions of expert groups from the Middle East (n=14) and the European Society of Pediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) (n=13). These Expert groups voted on statements developed by the ESPGHAN group and published in a recent position paper. The voting outcome was compared. Overall, there was consensus amongst both groups of experts. Most experts agreed that symptoms of crying, irritability and colic, as single manifestations, do not suggest CMA. They agreed that amino-acid-based formula (AAF) should be reserved for severe cases (e.g. malnutrition and anaphylaxis) and that there is insufficient evidence to recommend a step-down approach. There was no consensus on the statement that a cow’s milk-based extensively hydrolysed formula (eHF) should be the first choice as a diagnostic elimination diet in mild/moderate cases. Although the statements regarding the role of hydrolysed rice formula as a diagnostic and therapeutic elimination diet were accepted, 3/27 disagreed. The votes regarding soy formula highlight the differences in opinion in the role of soy protein in CMA dietary treatment. Generally, soy-based formula is seldom available in the Middle East region. All ESPGHAN experts agreed that there was no added value of probiotics, prebiotics, and synbiotics to the efficacy of elimination diets, whereas 3/14 of the Middle East group thought there was sufficient evidence. Therefore, there is not a consensus on the optimal diagnostic and therapeutic elimination diet for CMA, but the first-choice elimination diet and the stepwise management approach reveal some differences.

The enteric nervous system is affected by inflammatory bowel diseases (IBD). Gut microbiota ferment dietary fibers and produce short-chain fatty acids, such as Butyrate, which bind to G protein-coupled receptors, such as GPR41, and contribute to maintaining intestinal health. This work aimed to study the GPR41 in myenteric neurons and analyze the effect of Butyrate in mice submitted to experimental ulcerative colitis. The 2, 4, 6 trinitrobenzene sulfonic acid (TNBS) was injected intrarectally in C57BL/6 mice (Colitis). Sham group received ethanol (vehicle). One group was treated with 100mg/kg of Sodium Butyrate (Butyrate), and the other groups received saline. Animals were euthanized 7 days after colitis induction. Analyzes demonstrated colocalization of GPR41 with neurons immunoreactive (-ir) to nNOS and ChAT-ir, and absence of colocalization of the GPR41 with GFAP-ir glia. Quantitative results demonstrated losses of nNOS-ir, ChAT-ir, and GPR41-ir neurons in Colitis group, and Butyrate treatment attenuated neuronal loss. The number of GFAP-ir glia increased in Colitis group, whereas Butyrate reduced the number of these cells. In addition, morphological alterations observed in Colitis group were attenuated in Butyrate group. The presence of GPR41 in myenteric neurons was identified and the treatment with Butyrate attenuated the damage caused by experimental ulcerative colitis.

Unmetamorphosed carbonaceous chondrites provide important information concerning the formation and evolution of organic matter, such as amino acids. However, terrestrial contamination remains a valid concern when investigating the organic inventory of meteorites that have fallen to Earth. Accordingly, JAXA’s Hayabusa2 and NASA’s OSIRIS-REx have been launched with the task of returning uncontaminated C-type asteroid material to Earth. The successful Hayabusa2 mission has a very limited sample size (5.4 g). Therefore, many conventional compound specific techniques will struggle to detect amino acids above detection limit with available sample amounts (~several mg to 10’s of mg) being much smaller than those typically used. Here a novel method utilizing ultrahigh performance liquid chromatography-Orbitrap-mass spectrometry is validated and applied to very small meteorite samples, thus providing an approach that can overcome the small sample size constraints of sample return missions. The method is highly sensitive, enabling the detection of amino acids in the carbonaceous chondrites Murchison (2.28 mg) and Orgueil (2.30 mg). Furthermore, quantitation was possible for many of the detected amino acids in Murchison and Orgueil. Using the data presented here, both the amino acid reservoirs of Murchison and Orgueil and the potential application of this method to sample return samples are discussed.

Traditional dry fermented meat products are obtained artisanally in many countries, where they represent a gastronomic heritage well distinguished from industrial counterparts. This food category is most often obtained from red meat, a food commodity that is under attack because of evidences of increased risk of cancer and degenerative diseases with high consumption. However, traditional fermented meat products are intended for moderate consumption and gastronomic experience and, as such, their production must be continued also to safeguard culture and economy of the geographical areas of origin. In this review, the main risks attributed to these products are considered and how these risks are minimized by following precise production norms, respectful of the ancient manufacturing processes is described. Moreover, results obtained in studies reporting use of autochthonous microbial cultures of lactic acid bacteria (LAB), coagulase negative staphylococci (CNS), Debaryomyces hansenii and Penicillium nalgiovense to improve safety and quality of traditional fermented meats are summarized. The role of these products as a source of microorganisms that can be beneficial to the host are also considered. From the results of the studies reviewed here it appears that the development of autochthonous cultures for these foods ensure safety and stabilize sensory characteristics with possibility to be extended to the large variety of traditional productions.

This study is the first report of the successful cultivation of Dinophysis norvegica isolated from Japanese coastal waters (7 of 48 isolated cells were established as the clonal cultures, 14.5%) and their toxin content and production. The strains were maintained at relatively high abundance (>2,000 cells mL-1) for more than one year when fed on Mesodinium rubrum with the addition of Teleaulax amphioxeia. At the end of the one-month incubation, the total amounts of pectenotoxin-2 (PTX2), dinophysistoxin-1 (DTX1) and okadaic acid (OA) were 132.0-375.0 ng mL-1 (n = 7), 0.7-3.6 ng mL-1 (n = 3) and trace level OA (n = 1), respectively. Similarly, the cell quota of PTX2 and DTX1 were 60.6-152.4 pg cell-1 (n = 7) and 0.5-1.2 pg cell-1 (n = 3), respectively. These data indicated that toxin production varies depending on the strains in this species. In the growth experiment, D. norvegica grew, but it was very slow first 12 days. However, after that they grew exponentially with the maximum growth rate of 0.56 divisions day-1 (during Day 24-27), reaching a maximum concentration of 3,000 cells mL-1 at the end of incubation (Day 36), suggesting that they have a long lag phase. In the toxin production, OA was not at a detectable level (≤ 0.010 ng mL-1) during the 36 days of incubation except for Day 6. The concentration of DTX1 and PTX2 showed similar patterns as described for vegetative growth, but the toxin production still increased on Day 36 (1.3 ng mL-1 and 154.7 ng mL-1 in DTX1 and PTX2, respectively). The findings of this study provide novel information on the toxin content and production in D. norvegica as well as details on the culturing and maintenance of the species.

This work presents the results of a comprehensive physico-chemical and biological study of hu-mic substances samples – an extract of humic and fulvic acids. The performed loss on drying test showed a 22 times different dry matter content between EHS and FA. The morphology and dis-tribution of particles in the dry residue of the samples assessed using the methods of optical and digital microscopy demonstrated differences in the qualitative features of the microstructures of their surfaces and granulometries. Shimadzu X-ray fluorescence spectrometry revealed Si (8.1 and 1.7%), P (33.5 and 2.7%), S (4.3 and 59.5%), K (1.35 and 2.5%), Ca (10.9 and 3.2%), Mn (0.27 and 0.06%), Fe (11 and 0.05%), Cu (0.16 and 0.45%), Zn (0.06 and 0.02%) in the dry residues of the EHS and FA samples, respectively. A high intensity of the X-ray fluorescence signal for Fe atoms in the EHS sample was demonstrated. The FT-IR spectra for EHS and FA are characterized by simi-lar vibration frequencies that are characteristic of the chromone derivatives (1-benzopyran-4-one). The UV absorption spectrum is characterized by max = 281 nm for FA. The EHS solution showed a fluorescence maximum at em = 560 nm at ex = 280 nm. Using the DLS method, nanoparticles of 1 nm and 200 nm were detected in EHS and FA diluted solutions, which are likely to condition the biochemical and physical properties of humic acids. Using the Spiro-tox-test method, the absence of the toxic effect of humic acids on the cell model of ciliates Sp. am-bigua was established. When the cell model was incubated in a solution of a toxicant of the fluo-roquinolone group, a decrease in toxicity was demonstrated when diluted with the EHS solu-tion. The results of the study of the antiviral activity of EHS and FA showed that the study ob-jects in the culture of Vero-E6 cells, in doses non-toxic to cells, suppress the reproduction of the SARS-CoV-2 virus both in the study of the virucidal effect and in the study of the antiviral activ-ity according to the therapeutic and prophylactic model scheme of injection. The results obtained suggest that standardized drugs based on humic acids may open up new perspectives in their biomedical application as antiviral drugs.

The phenylpropanoid pathway is a major secondary metabolite pathway that helps plants overcome biotic and abiotic stress and produces various by-products that promote human health. Its byproduct, chloroquinic acid (CQA), is a soluble phenolic compound present in many angiosperms. Hy-droxycinnamate-CoA shikimate/quinate transferase(BAHDs superfamily enzyme) is a significant en-zyme that plays a role in accumulating CQA biosynthesis. This study analyzed transcriptome-wide identification of the phenylpropanoid to chloroquinic acid biosynthesis candidate genes in A. spathulifolius flowers and leaves. Transcriptomic analyses of the flowers and leaves showed a differential expression of the PPP and CQA biosynthesis regulated unigenes. An analysis of PPP captive unigenes revealed the following: the major duplication of the key enzyme, PAL, 120 unigenes in leaves and 76 in flowers; the gene encoding C3’H, 169 unigenes in leaves and 140 unigenes in flowers; duplicated unigenes of 4CL, 41 in leaves and 27 in flowers. In addition, C4H unigenes had 12 unigenes in the leaves of A. spathulifolius and four in the flowers. The characterization of the BAHDs superfamily members identified 82 in leaves and 72 in flowers. Among them, phylogenetic analysis showed that five unigenes encoded HQT and three en-coded HCT in A. spathulifolius. The three HQT are common to both leaves and flowers, whereas the two HQT were specialized for leaves. The pattern of HQT synthesis was upregulated in flowers, whereas HCT was expressed strongly in the leaves of A. spathulifolius. Overall, 4CL, C4H, and HQT are expressed strongly in flowers, and caffeic acid and HCT show more expression in leaves. Therefore, CQA biosynthesis occurs in the flowers of A. spathulifolius rather than leaves.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the etiological agent of the current pandemic worldwide. The pathological condition induced by this pathogen is known as COVID-19 disease. SARS-CoV-2 associated pandemic has been defined as a “public health emergency of international concern” by the International Health Regulation Emergency Committee of the World Health Organization. To date, considerable efforts are in progress to develop more advanced strategies against SARS-CoV-2. Despite the numerous scientific studies published, our knowledge regarding this pathogen is still incomplete, as this virus has been identified only recently. Therefore, scientific investigation of the SARS-CoV-2 has been possible only for a short period of time and effective management of the serious forms of this disease is still lacking. Considerable efforts are in progress worldwide with the purpose to develop more advanced strategies against this pathogen. In this review, we have analyzed the structural and the biological SARS-CoV-2 characteristics and those of other well-known RNA viruses, with the aim to identify possible similarities and analogies between all these pathogens, may be a very useful approach. These infectious agents have been widely studied since several years ago and, a large series of scientific reports are available in the literature regarding this topic. Therefore, focusing on the Human Immunodeficiency Virus (HIV), Hepatitis C Virus (HCV) and Influenza viruses (IVs), we have collected their historical data, clinical manifestations, pathogenetic mechanisms and related infections. Taking advantage of the results of our research, we have assembled this narrative review, with the aim to get useful insights and lessons from HIV, HCV and IVs characteristics and, consequently, to transfer the obtained knowledge to the study of SARS-CoV-2 biology. There are well known differences between all these pathogens. In particular, they present a distinct mode of transmission, as SARS-CoV-2 and Influenza viruses are airborne pathogens, whereas HIV and HCV are bloodborne infectious agents. However, these viruses exhibit some potential common clinical manifestations and pathogenetic mechanisms and their understanding may contribute to establishing preventive measures and new therapies against SARS-CoV-2. Accordingly, we have analysed and discussed the following points: 1) the biology, the pathogenesis and the clinical manifestations of SARS-CoV-2, HIV, HCV and IVs in mankind; 2) the onset and spreading of pandemics caused by respiratory viruses according to a perspective historical point of view; 3) the possible development of a persistent SARS-CoV-2 reservoir worldwide; 4) the possibility of SARS-CoV-2 reinfection/reactivation; 5) the possible involvement and impact of climatic factors in increasing the risk of SARS-CoV-2 spreading.

The major auxin, indole-3-acetic acid (IAA), is associated with a plethora of growth and developmental processes including embryo development, expansion growth, cambial activity, and the induction of lateral root growth. Accumulation of the auxin precursor indole-3-acetamide (IAM) induces stress related processes by stimulating abscisic acid (ABA) biosynthesis. How IAM signaling is controlled is, at present, unclear. Here, we characterize an ami1/rooty double mutant, that we initially generated to study the metabolic and phenotypic consequences of a genetic blockade of the indole glucosinolate and IAM pathways in Arabidopsis thaliana. Our mass spectrometric analyses of the mutant revealed that the combination of the two mutations is not sufficient to fully prevent the conversion of IAM to IAA. The detected strong accumulation of IAM was, however, recognized to substantially impair seed development. We further show by genome-wide expression studies that the double mutant is broadly affected in its translational capacity, and that a small number of cell proliferation and plant growth regulating transcriptional circuits are repressed by the high IAM content in the seed. In accordance with the previously described growth reduction in response to elevated IAM levels, our data support the hypothesis that IAM is a growth repressing counterpart to IAA.

FoxP3 is a transcription factor essential for the differentiation and function of T regulatory cells (Tregs). There are two major subsets of Tregs: natural Tregs (nTregs) generated in thymus and inducible Tregs (iTregs) produced in peripheral immune system. It has been documented that iTreg development is dependent on soluble mediators including interleukin 2 (IL2), transforming growth factor β (TGFβ) and all-trans-retinoic acid (ATRA). In our experiments we performed a gene expression array, followed by Real-time PCR experiments, to study the expression of genes regulated by 1,25-dihydroxyvitamin D (1,25D) or ATRA in cells of myeloid origin. Our experiments revealed that ATRA alone, but also a cocktail of mediators consisting of IL2, TGFβ and ATRA, upregulate the expression of FOXP3 gene in lymphoid cells, but also in normal and leukemic myeloid cells. The FoxP3 expression is followed by a phenotypic changes in cells of myeloid origin. Our results indicate that signaling pathways which are used in the late stages of T cell differentiation, are also active in the cells of myeloid lineage

High fructose and sugar-sweetened soft drink (SSSD) intakes are associated with elevated blood uric acid concentrations and increased risk of gout and cardiovascular disease. Fruits are naturally high in fructose but their effect on cardiometabolic risk is unknown. We examined the effect on serum uric acid and cardiometabolic risk factors of consuming fructose from either fruit or SSSD in overweight adults. 48 healthy, overweight (BMI≥ 28 kg/m²) men (n=21) and women (n=20) were randomised to either a fruit (n = 19) or SSSSD (n = 22) intervention for 4 weeks. The fruit group received 6 items of fresh and dried fruit per day and the SSSD group received 955ml of SSSD per day with treatments matched for energy and fructose content. Serum uric acid concentrations were significantly reduced in men in the fruit group compared to the SSSD group (difference 57.2 μmol/L [95% CI: 16.4, 98.0], p= 0.008) but there was no difference amongst women (1.3 μmol/L [95%CI: -9.5, 6.9], p= 0.295). There differences in weight change or other cardiometabolic risk factors. These findings suggest no need to restrict fruit intake in individuals with elevated serum uric acid concentrations, such as those with gout.

Field implementations of inductive power transfer (IPT) face many practical challenges that dramatically reduce power transmission effectiveness. Coil misalignment is a persistent issue in IPT systems, especially in applications involving vehicles or nonvisible coils. Furthermore, magnetic field symmetry convolutes the decomposition of misalignment measurements in multiple dimensions and frequently impedes the efficacy of traditional position correction strategies. This paper presents an automated methodology to sense misalignments and align IPT coils using robotic actuators and sequential Monte Carlo methods. The misalignment of a Class EF inverter-driven IPT system was modeled by tracking changes as its coils move apart laterally and distally. These models were integrated with particle filters to estimate the location of a hidden coil in 3D, given a sequence of sensor measurements. During laboratory tests on a Cartesian robot, these algorithms aligned the IPT system within 1 cm (0.025 coil diameters) of peak lateral alignment. On average, the alignment algorithms required less than four sensor measurements for localization. After laboratory testing, this approach was implemented with an agricultural sensor platform at the Utah Agricultural Experiment Station in Kaysville, Utah. In this implementation, a buried sensor platform was successfully charged using an aboveground, vehicle-mounted transmitter.

This research presents a comprehensive framework for efficiently generating forest fire datasets from Google Earth Engine data sources. The primary contribution of this work lies in providing a methodology to swiftly extract forest fire factors without the need for permissions or access to private datasets, rendering the dataset openly accessible and shared without barriers. Furthermore, given that the remote sensing data used is a global dataset, it can be applied in any region without restrictions. In this study, Peninsular Malaysia is chosen as a case study to demonstrate the framework's effectiveness. The generated dataset includes essential variables including the climate and environment, landcover, topography, and anthropogenic factors facilitating the analysis of fire occurrences. The methodology empowers data scientists, enabling them to leverage their analytical skills on the extracted dataset without requiring specialized remote sensing knowledge. Additionally, this study also showcases the adoption of large language models, specifically GPT-4 with the Noteable plugin, as a tool for conducting preliminary analyses on the generated dataset. Sample analyses reveal that several key features, including the KBDI, LST, PDSI, climate water deficit, and precipitation, significantly impact forest fire occurrences in Peninsular Malaysia. Despite the successful application of the GPT-4 with Noteable plugin, certain limitations and challenges are identified, highlighting the necessity for further validation of the tool's applicability and limitations. This study encourages future research to (1) adopt the proposed framework in other regions, (2) explore more detailed analyses encompassing all variables, and (3) leverage machine learning for advanced forecasting.

In this study, Silicon Carbide (SiC) nano-particle based serigraphic printing inks were formulated to fabricate highly sensitive and wide temperature range SiC printed thermistors. Initially, commercial silver ink was screen printed to fabricate inter-digitated electrodes (IDE’s) onto flexible Kapton® substrate via screen printing. Thermistor inks with different weight ratios of SiC nano- particles dispersed in polyimide resin matrix were fabricated. The SiC-polyimide temperature sensing inks were screen printed atop the IDE structures to form fully printed thermistors and encapsulated with a adhesive backed polyimide film for humidity inhibition. The high temperature tolerance of the Kapton® allowed the the sensors to be tested over a wide temperature range form 25◦C to 170◦C. The printed SiC thermistors exhibit excellent repeatability and stability over 15 hours of continuous operation. Optimal device performance was achieved with 30 wt.% SiC-polyimide ink. We report highly sensitive devices with a temperature coefficient of Resistance (TCR) of -0.556 %/◦C, a thermal coefficient of 502 K (β-index) and an activation energy of 0.08 eV which are comparable with printed thermistors previous reported. Further, the thermistor demonstrates an accuracy of ±1.35◦C which is well within the range offered by commercially available high sensitivity thermistors. SiC thermistors exhibit a small 6.5% drift due to changes in relative humidity between 10-90 %RH and a 4.2 % drift in baseline resistance after 100 cycles of aggressive bend testing at a 40°angle. The use of commercially available low cost materials, simplicity of design and fabrication techniques coupled with the chemical inertness of the Kapton® substrate and SiC nanoparticles paves the way to use all-printed SiC thermistors towards a wide range of applications where temperature monitoring is vital for optimal system performance.

In this article, we combine datasets from multiple research projects and remote sensing tech-nologies to evaluate the conservation conditions of La Fortaleza de Kuelap, a pre-Hispanic monument in Peru’s northeastern Andes that suffered significant damage during historically high seasonal rains in April 2022. Our analyses seek to identify the main causes of the collapse and locate places where the monument is likely at risk of further deterioration. To do so, we model surface hydrology using a digital elevation model (DEM) derived from drone LiDAR data, re-construct a history of previous collapses, and calculate the volume of the most recent by fusing terrestrial LiDAR and photogrammetric datasets. In addition, we examine subsurface water ac-cumulation through electrical resistivity data, reconstruct the stratification of the monument from seismic refraction data, and analyze vegetation loss and ground moisture accumulation using high resolution satellite imagery. Our results point to water accumulation as the most significant source of risk for La Fortaleza’s perimeter walls. Combined with adverse contemporary conser-vation interventions and natural conditions, this led to the collapse of April 2022. This integration of analytical results demonstrates how multi-scalar and multi-instrumental approaches provide comprehensive and timely assessments of conservation needs.

The World Meteorological Organization (WMO) recommends that the most recent 30-year period, i.e. 1991-2020, shall be used to compute climate normals of geophysical variables. A unique aspect this recent 30-year period is that the satellite-based observations of many different essential climate variables are available during this period, thus opening up new possibilities to provide a robust, global basis for the 30-year reference period in order to allow climate monitoring and climate change studies. Here, using the satellite-based climate data record of cloud and radiation properties, CLARA-A3, for the month of January between 1981 to 2020, we illustrate the difference between climate normal, as defined by guidelines from WMO on calculations of 30-yr climate normals, and climatology. It is shown that this difference is strongly dependent on the climate variable in question. We discuss the impacts of the nature and availability of satellite observations, variable definition, retrieval algorithm and programmatic configuration. It is shown that the satellite-based climate data records show enormous promise in providing climate normal for the recent 30-year period (1991-2020) globally. We finally argue that the holistic perspectives from the global satellite community should be increasingly considered while formulating the future WMO guidelines on computing climate normals.

In this paper, the performance of Cu-(In,Ga)-S2 (CIGS2) solar cells with adjusting composite CGI-ratio absorber is explored and compared through an improved three-stage co-evaporation technique. For co-evaporating CIGS2 absorber as a less toxic alternative to Cd-containing film, we analyse the effect of the CGI-ratio stoichiometry and crystallinity, and explore its opto-electric sensing characteristic of individual solar cell. The results of this research signify the potential of high-performance CIGS2-absorption solar cells for photovoltaic (PV)-module industrial applications. For the optimal CIGS2-absorption film (CGI=0.95), the Raman main-phase signal (A1) falls at 291 cm-1, which is excited by the 532-nm line of Ar+-laser. Using photo-luminescence (PL) spectroscopy, the corresponding main-peak bandgaps measured is 1.59 eV at the same CGI-ratio film. Meanwhile, the best conversion efficiency (=3.212%) and the average external quantum efficiency (EQE=51.1% in the visible-wavelength region) of photo-electric properties were achieved for the developed CIGS2-solar cells (CGI=0.95). The discoveries of this CIGS2-absorption PV research provide a new scientific understanding of solar cells. Moreover, this research undeniably contributes to a major advancement towards practical PV-module applications and can help more to build an eco-friendly community.

The emergence of cloud computing, big data analytics, and machine learning has catalysed the use of remote sensing technologies to enable more timely land management of sustainability indicators such as ground cover and grassland biomass, given the uncertainty of future climate and drought conditions. Here, we examine the potential of “regenerative agriculture”, as an adaptive grazing management strategy to minimise bare ground exposure while maximising pasture biomass productivity. High-intensity sheep grazing treatments were conducted in small fields (less than 1 hectare) for short durations (typically less than 1 day). Paddocks were subsequently spelled to allow pasture biomass recovery (treatments comprising 3, 6, 9, 12, and 15 months) with each compared with control treatments with lighter stocking rates for longer periods (2,000 DSE). Pastures were composed of wallaby grass (Austrodanthonia species), kangaroo grass (Themeda triandra), Phalaris (Phalaris aquatica, and cocksfoot (Dactylis glomerata) were destructively sampled to estimate total standing dry matter (TSDM), standing green biomass, standing dry biomass and trampled biomass. We then invoked a machine learning model using Sentinel-2 imagery to quantify TSDM, standing green biomass and standing dry biomass. Faced with La Nina conditions, regenerative grazing did not significantly impact pasture productivity, with all treatments showing similar TSDM and green biomass. However, regenerative treatments significantly impacted litter fall and trampled material, with the high intensity grazing treatments causing more dry matter trampling, increasing litter, enhancing decomposition rates and surface organic matter. Pasture digestibility was greatest for treatments with minimal spelling (3 months), whereas both standing senescent and trampled material were significantly greater for the treatment with 15-month spell periods. Estimates of TSDM using machine learning with Sentinel-2 imagery underestimated TSDM in treatment plots but explained spatiotemporal variability associated within and across treatments. The root mean square error between the measured and modelled TSDM was 903 kg DM/ha, which was less than the variability measured in the field. We conclude that regenerative grazing with short recovery periods (3-6 months) are most conducive to increasing pasture production under high rainfall conditions, and we speculate that high intensity grazing is likely to positively impact on soil organic carbon through increased litterfall and trampling. Our study paves the way forward for using machine learning with satellite imagery to quantify pasture biomass at small scales, enabling management of pastures from afar.

The location and number data of individual fruit trees are critical for planting area investigation, fruit yield prediction, and smart orchard management and planning. These data are conventionally obtained through manual investigation and statistics with time-consuming and laborious effort. Object detection models in deep learning used widely in computer vision could provide an opportunity for accurate detection of individual fruit trees, which is essential for rapidly obtaining the data and reducing human operations errors. This study proposes an approach to detecting individual fruit trees and mapping their spatial distribution by integrating deep learning with unmanned aerial vehicle (UAV) remote sensing. UAV remote sensing collected high-resolution true-color images of fruit trees in the experimental pomelo tree orchards in Meizhou city, South China. An image dataset of deep learning samples of individual pomelo trees (IPTs) was constructed through visual interpretation and field investigation based on the fruit tree images captured by UAV remote sensing. Four different scales of YOLOv5 (YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x) for object detection were selected to train, validate, and test on the image dataset of pomelo trees. The results show that the average precision ([email protected]) of the four YOLOv5 models for validation reach 87.8%, 88.5%, 89.1%, and 90.7%, respectively. The larger the model scale, the higher the average accuracy of the detection result of validation. It suggests that YOLOv5x is a preferred high-accuracy model among the YOLOv5 family and is suitable to realize the detection of IPTs. The number of the IPTs in the study area was counted using YOLOv5x, and their spatial distribution map was made using the non-maximum suppression method and ArcGIS software. This study will provide primary data and technical support for smart orchard management in Meizhou city and other fruit-producing areas.

Oil spillage over a sea or ocean’s surface is a threat to marine and coastal ecosystems. Spaceborne synthetic aperture radar (SAR) data has been used efficiently for the detection of oil spills due to its operational capability in all-day all-weather conditions. The problem is often modeled as a semantic segmentation task. The images need to be segmented into multiple regions of interest such as sea surface, oil spill, look-alikes, ships and land. Training of a classifier for this task is particularly challenging since there is an inherent class imbalance. In this work, we train a convolutional neural network (CNN) with multiple feature extractors for pixel-wise classification; and introduce to use a new loss function, namely ‘gradient profile’ (GP) loss, which is in fact the constituent of the more generic Spatial Profile loss proposed for image translation problems. For the purpose of training, testing and performance evaluation, we use a publicly available dataset with selected oil spill events verified by the European Maritime Safety Agency (EMSA). The results obtained show that the proposed CNN trained with a combination of GP, Jaccard and focal loss functions can detect oil spills with an intersection over union (IoU) value of 63.95%. The IoU value for sea surface, look-alikes, ships and land class is 96.00%, 60.87%, 74.61% and 96.80%, respectively. The mean intersection over union (mIoU) value for all the classes is 78.45%, which accounts for a 13% improvement over the state of the art for this dataset. Moreover, we provide extensive ablation on different Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) based hybrid models to demonstrate the effectiveness of adding GP loss as an additional loss function for training. Results show that GP loss significantly improves the mIoU and F1 scores for CNNs as well as ViTs based hybrid models. GP loss turns out to be a promising loss function in the context of deep learning with SAR images.

This study introduces a remote sensing application using satellite imagery to survey a network-scale aggregate stockpile inventory. First, a real scale aggregate quarry site was surveyed using a small Unmanned Aerial Vehicle (sUAV) to produce digital terrain models that enabled analysis of aggregate pile geometry. Second, a lab experiment was designed and performed to validate the applicability of close-range Structure from Motion (SfM) photogrammetry for measuring aggregate piles' physical properties such as volume and density. The other part of the lab experiment delved into direct measurement of aggregate density under varying compaction efforts. These experimental results, in conjunction with some simplifying assumptions, enabled the calculation of aggregate stockpile volumes and estimated weights from satellite imagery. We estimated that an inventory of 4.4 and 1.1 million metric tons of crushed aggregates and Reclaimed Asphalt Pavement (RAP), respectively, stockpiled in Washington State for asphalt production in 2017. The merit of producing such database was further showcased in an example on the economic and environmental impacts of material transportation. We approximated that hauling aggregates from quarry plants to construction sites within Washington State incurs a cost of about $50 thousand to over $4 million, consumes about 0.25 to 20 TJ of energy, and emits 20 to over 1,500 tons of CO₂-eq per asphalt plant annually.

The detection performance of small objects in remote sensing images has not been satisfactory compared to large objects, especially in low-resolution and noisy images. A generative adversarial network (GAN)-based model called enhanced super-resolution GAN (ESRGAN) showed remarkable image enhancement performance, but reconstructed images usually miss high-frequency edge information. Therefore, object detection performance showed degradation for small objects on recovered noisy and low-resolution remote sensing images. Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we applied a new edge-enhanced super-resolution GAN (EESRGAN) to improve the quality of remote sensing images and used different detector networks in an end-to-end manner where detector loss was backpropagated into the EESRGAN to improve the detection performance. We proposed an architecture with three components: ESRGAN, EEN, and Detection network. We used residual-in-residual dense blocks (RRDB) for both the ESRGAN and EEN, and for the detector network, we used a faster region-based convolutional network (FRCNN) (two-stage detector) and a single-shot multibox detector (SSD) (one stage detector). Extensive experiments on a public (car overhead with context) dataset and another self-assembled (oil and gas storage tank) satellite dataset showed superior performance of our method compared to the standalone state-of-the-art object detectors.

Dams are a critical infrastructure system for many communities, but they are also one of the most challenging to inspect. Dams are typically very large and complex structures, and the result is that inspections are often time-intensive and require expensive, specialized equipment and training to provide inspectors with comprehensive access to the structure. The scale and nature of dam inspections also introduces additional safety risks to the inspectors. Unmanned aerial vehicles (UAV) have the potential to address many of these challenges, particularly when used as a data acquisition platform for photogrammetric three-dimensional (3D) reconstruction and analysis, though the nature of both UAV and modern photogrammetric methods necessitates careful planning and coordination for integration. This paper presents a case study on one such integration at the Brighton Dam, a large-scale concrete gravity dam in Maryland, USA. A combination of multiple UAV platforms and multi-scale photogrammetry was used to create two comprehensive and high-resolution 3D point clouds of the dam and surrounding environment at intervals. These models were then assessed for their overall quality, as well as their ability to resolve flaws and defects that were artificially applied to the structure between inspection intervals. The results indicate that the integrated process is capable of generating models that accurately render a variety of defect types with sub-millimeter accuracy. Recommendations for mission planning and imaging specifications are provided as well.

Cash crops are agricultural crops intended to be sold for profit as opposed to subsistence crops, meant to support the producer, or to support livestock. Since cash crops are intended for future sale, they translate into large financial value when considered on a wide geographical scale, so their production directly involves financial risk. At a national level, extreme weather events including destructive rain or hail, as well as drought, can have a significant impact on the overall economic balance. It is thus important to map such crops in order to set up insurance and mitigation strategies. Using locally generated data -such as municipality-level records of crop seeding- for mapping purposes implies facing a series of issues like data availability, quality, homogeneity etc. We thus opted for a different approach relying on global datasets. Global datasets ensure homogeneity and availability of data, although sometimes at the expense of precision and accuracy. A typical global approach makes use of spaceborne remote sensing, for which different land cover classification strategies are available in literature at different levels of cost and accuracy. We selected the optimal strategy in the perspective of a global processing chain. Thanks to a specifically developed strategy for fusing unsupervised classification results with environmental constraints and other geospatial inputs including ground-based data, we managed to obtain good classification results despite the constraints placed. The overall production process was composed using ``good-enough" algorithms at each step, ensuring that the precision, accuracy, and data-hunger of each algorithm was commensurate to the precision, accuracy, and amount of data available. This paper describes the tailored strategy developed on the occasion as a cooperation among different groups with diverse backgrounds, a strategy which is believed to be profitably reusable in other, similar contexts. The paper presents the problem, the constraints and the adopted solutions; it then summarizes the main findings including that efforts and costs can be saved on the side of Earth Observation data processing when additional ground-based data are available to support the mapping task.