Graphene quality for use in biosensors was assessed in fabricated chips by a set of methods that includes atomic force microscopy (AFM), Raman spectroscopy, and low-frequency noise. It is shown that local areas of residues on the graphene surface, which arisen due to the interaction of graphene with a photoresist at the initial stage of chips development, leads to a spread of chips resistance (R) within 1-10 kΩ and to an increase in the root mean square (RMS) roughness up to 10 times that can significantly impair reproducibility of graphene parameters in biosensors chips. It was observed that the control of the photoresist residues after photolithography (PLG) by AFM and subsequent additional cleaning allow reducing the spread of R values in chips to 1–1.6 kΩ and obtaining RMS roughness similar to the roughness in pristine graphene before PLG. Monitoring of the spectral density of low-frequency voltage fluctuation (SU), which provides integral information about the defect system and quality of the material, makes it possible to identify chips with low graphene quality and with inhomogeneously distributed compressive stresses areas by the type of frequency dependence SU (f).

A Invasive emerging pollutants from wastewater effluent discharge, such as dyes, pesticides, etc., pose a serious threat to the ecosystem. Advanced oxidation processes (AOPs) under visible light irradiation have emerged as a promising technology to overcome toxic and recalcitrant organic compounds. In this work, the impact of operational factors, including the concentration of Fe3+ or Fe2+, [H2O2], the molar ratio (Oxalate/ Fe3+ or Fe2+), and the initial pH, was studied to obtain high efficiency in the degradation and mineralization of such a food dye to reduce their pollution. The study deals with the comparison of the efficiency of UV, LED, and sunlight irradiation on the photocatalytic degradation of the dye using Fe3+/Lig and Fe2+/Lig complexes. The results showed that sunlight irradiation gave a very rapid kinetic and higher degradation efficiency of over 70%. The optimized conditions for the maximum elimination of the dye with a photocatalytic degradation efficiency (98%) and a mineralization rate of 96% were obtained with the Fe3+/Lig complex, based on the Box Benhken surface design analysis. In the presence of H2O2, the degradation reached an equilibrium stage after 15 min (97.57%) for the Fe(III)/Lig system. Moreover, the inhibition effect of inorganic ions on the photo-Fenton performance of Fe3+/Lig and Fe2+/Lig was studied. The study suggests that the use of nanocrystals of hematite as a Fenton reagent for treating textile effluents needs further investigation. The results showed that the proposed models were well-suited to batch treatment under sunlight. This study not only proposes a Fe3+/Lig and Fe2+/Lig system for the elimination of a food dye without adjusting the pH of the medium, but it also provides insight into the best source of light irradiation for the photocatalytic degradation process.

A chairside polishing kit is an alternative to a laboratory polishing technique. This study aimed to evaluate the effects of different polishing techniques on the surface roughness of three-dimensional (3D)-printed acrylic denture bases (ADB). One hundred twenty disc-shaped specimens were fabricated from one conventional heat-polymerized (HP) ADB resin and two 3D-printed (Asiga (AS) and NextDent (ND)) ADB resins (n=40 per ADB resin). Each group was furtherly divided based on the polishing protocol (n=10) as follows: convectional polishing protocol (C), Microdont chairside polishing kit (M), Shofu chairside polishing kit (S), and unpolished group (U). The surface roughness (surface roughness average (Ra) and average maximum profile height (Rz)) of the printed specimens were measured using an optical profilometer, and the scanning electron microscope (SEM) was used to capture the surface at ×1000. Two-way ANOVA and post hoc tests were used for data analysis (α = 0.05) at significant levels. In unpolished groups, there was a statically significant difference between HP vs 3D-printed ADBs (p < 0.0001). For Ra values, the lowest values were presented in HP-C, AS-S, and ND-C. While the highest values were shown in all unpolished groups. Within the material, there were statistically significant differences between the three polishing protocols (C, M, and S) vs unpolished (p < 0.0001), while there was no significant between C, M, and S groups (p = 0.05). The Rz values had the same pattern as the Ra values. The two chairside polishing kits were comparable to conventional polishing technique, and it could be recommended for the clinical application.

The synthesis 2-tert-butyl-4-methylphenol is of great significance because of its widely application in industry, and the development of highly efficient catalyst is necessary to the alkylation of p-cresol and tert-butyl alcohol. Here, an efficient and mild method was established, caprolactam was chosen as hydrogen-bonding acceptor, p-toluenesulfonic acid was employed as hydrogen-bonding donor, and deep eutectic solvent (DES) was prepared to catalyze the alkylation reaction. The structure of the DES catalyst was characterized by 1H NMR spectra, thermogravimetric analysis and fourier transform infrared spectra (FT-IR). In addition, response surface design based on Box-Behnken method was employed to optimize the alkylation reaction process parameters, the study of reaction kinetics was also carried out subsequently. The recycle performance of the catalyst was evaluated by recovery experiments, and a good result was obtained. Comparing with the literature reported, we here provide a mild method to the synthesis of 2-tert-butyl-4-methylphenol.

Hydrogeological maps must synthesize the scientific knowledge about the hydraulic features and the hydrogeological behavior of a specific area, and, at the same time, they must meet the expectations of land planners and administrators. Thus, especially in complex interconnected systems, hydrogeological maps can be fully effective when they are purpose-designed. In these contexts, usual graphical approaches in creating hydrogeological maps could result uncomplete and/or ineffective. Therefore, in case of complex systems and/or specific management/protection aims, new and purpose-designed graphical solutions must be applied to enhance the maps effectiveness. In the case study, these solutions show and emphasize all the hydraulic interconnections playing significant roles in recharging the multilayered alluvial aquifer, where the majority of wells have been drilled for drinking/industrial/agricultural purposes, artificial channels are used for agricultural purposes, and the shallow groundwater feeds protected groundwater-dependent-ecosystems. The hydrogeological map was then designed to be the synthesis of three different and hydraulically interconnected main contexts: (i) the main heterogeneous alluvial aquifer (the main target of the purpose-designed map), (ii) the hydrographic basin of a losing river that feeds the main alluvial aquifer, and (iii) those hard-rock aquifers (mainly turbiditic and ophiolitic) whose springs feed the same river.

Substantial reductions of the human and economic activities like road traffic for several months in 2020 were one of the consequences of the Coronavirus disease. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown over 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5) as well as on land surface temperature (LST), and the surface urban heat island intensity (SUHII), using satellite, modelled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change of the variables under study. In general, the results indicate a significant decrease in NO2 concentrations in most of the studied cities compared to the reference period 2015-2019. However, reductions could not be attributed to mobility changes like less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown mainly influenced by the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar as the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences. Therefore, single city case studies may be misleading.

Once on Mars, maintenance and repair will be crucial for humans as supply chains including Earth andMars will be very complex. Consequently, the raw material available on mars must be processed and used. Factors such as the energy available for material production play just as important a role as the quality of the material that can be produced and the quality of its surface. With the aim of developing and technically implementing a process chain that meets the challenge of producing spare parts from oxygen-reduced Mars regolith, this paper addresses the issue of low-energy handling. Expected statistically distributed high roughnesses of sintered regolith analogs are approximated in this work by parameter variation in the PBF-LB/M process. For low-energy handling, a dry-adhesive microstructure is used. Investigations are carried out to determine the extent to which the rough surface resulting from the manufacturing process can be smoothed by deep rolling in such a way that the microstructure adheres and enables samples to be transported. For the investigated AlSi10Mg samples (12 mm x 12 mm x 10 mm), the surface roughness varies in a wide range from Sa 7.7 µm to Sa 64 µm after the additive manufacturing process, pull-off stresses of up to 6.99 N/cm² could be realized after deep rolling. This represents an increase in pull-off stresses by a factor of 392.94 compared to the pull-off stresses before deep rolling, enabling handling of even larger specimens. It is noteworthy that specimens with roughness values that were previously difficult to handle can be treated post-deep rolling, indicating a potential influence of additional variables that describe roughness or ripples and are associated with the adhesion effect of the microstructure of the dry adhesive.

Abstract Chaga´s disease caused by Trypanosoma cruzi infections is included in the group of neglected diseases, and efforts to develop new therapeutic or immunoprevention approaches have not been successful. After the publication of the T. cruzi genome, the number of molecular and biochemical studies on this parasite have increased considerably, many of which are focused on families of variant-surface-proteins, especially the trans-sialidases, mucins and mucin-associated proteins. The disperse gene protein 1 family (DGF-1) is one of the most abundant families in the T. cruzi genome, however, the large gene size, high copy numbers, and low antibody titers detected in infected humans make it an unattractive study target. Here, we argue that the DGF-1 gene family although not being the most obvious participant of the host-parasite immunological gamble, where T. cruzi appears to have the upper hand, it may play an important role in more basic host-parasite interactions that deserve further examination.

Background: Implant surface topography is a key element in achieving osseointegration. Nanostructured surfaces have shown promising results in accelerating and improving bone healing around dental implants. The main objective of the present clinical and histological study is to compare, at 4 and 6 weeks, (w) bone-to-implant contact in implants having either machined surface (MAC), SLA medium roughness surface or a Nanostructured Calcium-Incorporated sur-face (XPEED®). Methods: 35 mini-implants with 3 different surface treatments (XPEED® (n=16) – SLA (n=13) – Machined (n=6), were placed in the posterior maxilla of 11 patients then, retrieved at either 4 or 6w in a randomized split-mouth study design. Results: The BIC rate measured at 4 and 6w respectively, was: 16.8 % (±5.0) and 29.0 % (±3.1) for MAC surface; 18.5 % (±2.3) and 33.7 % (±3.3) for SLA surface; 22.4 % (±1.3) and 38.6 % (±3.2) for XPEED® surface. In all types of in-vestigated surfaces, the time factor appeared to significantly increase the BIC rate (p < .05). XPEED® surface showed a significantly higher values when compared to both SLA and MAC values at 4w (p < .05). Also, at 6w, both roughened surfaces (SLA and XPEED® ) showed signifi-cantly higher values (p < .05) than turned surface (MAC). Conclusion: Nanostructured Calcium titanate coating is able to enhance bone deposition around implants at early healing stages.

Mapping and prediction of inundated areas is increasingly important for climate change adaptation and emergency preparedness. Flood forecasting tools and flood risk models have to be compared to observed flooding patterns for training, calibration, validation and benchmarking. At regional to continental scale, satellite earth observation is the established method for surface water extent (SWE) mapping and several operational global-scale data products are available. However, the spatial resolution of satellite-derived SWE maps remains a limiting factor, especially in low-lying areas with complex hydrography, such as Denmark. We collected thermal imagery using an unmanned airborne system (UAS) for three areas in Denmark shortly after major flooding events. We combined the thermal imagery with an airborne lidar-derived high-resolution digital surface model of the country to retrieve high-resolution (40 cm) SWE maps. The resulting SWE maps were compared to low-resolution SWE maps derived from satellite earth observation (EO). We conclude that UAS have significant potential for SWE mapping at intermediate scales, can bridge the scale gap between ground observations and satellite EO and can be used to benchmark and validate SWE mapping products derived from satellite EO as well as models predicting inundation.

Climate and land use changes are two factors affecting the hydrology of watersheds. The greatest effect of climate change is probably the change in the hydrological cycle, thus water availability for human consumption, industry, and power generation. While the change in land use can cause changes in the hydrological components of the basin, such as evapotranspiration, runoff, and groundwater recharge. From these projections, it is necessary to understand the processes involved in climate change and land use and its impact on water systems. In this context, the objective of this study was to simulate climate change scenarios combined with the land use change and to analyze the impacts on the hydrology in the Piracicaba basin. Two periods were selected based on the preliminary result of detection of the abrupt change point of the annual flow series, using Petitt's non-parameter test. The first period selected prior to the occurrence of the point of the change was from 1985 to 2000. The other period after the point of the change was 2001 to 2015. Land use maps of the years 1990 and 2010 were used to represent the two periods. The results showed a good performance of the SWAT model. The NS (Nash-Sutcliffe coefficient) was 0.88 in calibration for both periods. In the validation, the NS was 0.92 and 0.94 for the first and second periods respectively. We then simulate climate and land use changes scenarios and compare them to the current scenario (baseline). The simulation results showed that the hydrological processes in the Piracicaba basin in the period 1985-2015, had more intense responses to land use change than climate.

Near-surface humidity (Qa) is a key parameter that modulates oceanic evaporation and influences the global water cycle. Remote sensing observations act as feasible sources for long-term and large-scale Qa monitoring. However, existing satellite Qa retrieval models are subject to apparent uncertainties due to model errors and insufficient training data. Based on in situ observations collected over the China Seas over the last two decades, a deep learning approach named Ensemble Mean of Target deep neural networks (EMTnet) was proposed to improve the satellite Qa retrieval over the China Seas for the first time. The EMTnet model outperforms five representative existing models by nearly eliminating the mean bias and significantly reducing the root-mean-square error in satellite Qa retrieval. According to its target deep neural networks selection process, the EMTnet model can obtain more objective learning results when the observational data are divergent. The EMTnet model was subsequently applied to produce a 30-year monthly gridded Qa data over the China Seas. It indicates that the climbing rate of Qa over the China Seas under the background of global warming are probably underestimated by current products.

This paper presents a robust method based on graph topology to find the topologically correct and consistent subset of inter-robot relative pose measurements for multi-robot map fusion. However, the absence of good prior gives a severe challenge to distinguish the inliers and outliers, and wrong loop closures can seriously corrupt the fused global map. Existing works mainly rely on the consistency of spatial dimension to select inter-robot measurements, which does not always hold. In this paper, we propose a fast inter-robot loop closure selection method that integrates the consistency and topology relationship of measurements, which both conform to the continuity characteristics of similar scenes and spatiotemporal consistency. The traditional high-dimensional consistency matrix is decomposed into the sub-matrix blocks corresponding to the overlapping trajectory area. Building on this logic, a clustering method involving topology correctness of inter-robot loop closures is introduced to split the entire measurement set into multiple clusters. We define the weight function to find the maximum cardinality subset with topologically correct and consistent, then convert the weight function to a maximum clique problem in the graph and solve it. We evaluate the performance of our method in a simulation and in a real-world experiment. Compared to state-of-the-art methods, the results show that our method can achieve competitive performance in accuracy while reducing computation time by 75%.

Using the above results from RMS analysis the optimum values were predicted for the independent significant variables (Figure 3) the optimized levels of these variables in combination with other media variables the maximum production was predicted to be 199.90 U/mL. The predicted data were validated through confirmatory experiments performed in triplicates. A 1.29-fold increase in amylase activity against un-optimized (OVAT) medium was achieved in the present study authenticating the efficacy of RSM in process optimization (Figure 4). 2.6 Model validation and scale-up at laboratory scale (5L) bioreactor Once the parameters were standardized in the shake-flasks culture, the experiment was scaled-up to a laboratory-scale bioreactor (5 L). The yield of amylase increased by 1.01 fold (205.69 U/mL), it could be possible because the enzyme production in a bioreactor is higher than in shake-flasks culture as the various critical variable factors such as the dissolved oxygen (DO) and the pH can be optimally controlled at the desired levels [22].

Layer-wise 3D surface morphology information is critical for the quality monitoring and control of additive manufacturing (AM) processes. However, most of the existing 3D scan technologies are either contact or time consuming, which are not capable of obtaining the 3D surface morphology data in a real-time manner during the process. Therefore, the objective of this study is to achieve real-time 3D surface data acquisition in AM, which is achieved by a supervised deep learning-based image analysis approach. The key idea of this proposed method is to capture the correlation between 2D image and 3D point cloud, and then quantify this relationship by using a deep learning algorithm, namely, convolutional neural network (CNN). To validate the effectiveness and efficiency of the proposed method, both simulation and real-world case studies were performed. The results demonstrate that this method has strong potential to be applied for real-time surface morphology measurement in AM, as well as other advanced manufacturing processes.

Taking a typical forest underlying surface as the research area, this study employed the unmanned aerial vehicle (UAV) photogrammetry to explore more accurate canopy parameters including tree height and canopy radius, which were used to improve the Noah-MP land surface model conducted in Dinghushan Forest Ecosystem Research Station (CN-Din). While the canopy radius was fitted as a Burr distribution, the canopy height of CN-Din forest followed a Weibull distribution. The replacement of the parameters by these observed UAV would result in the Noah-MP model. It was found that the influence on the simulation of the energy fluxes could not be negligible, and the main influence of these canopy parameters was on the latent heat flux which could decrease up to -11% in the midday while increase up to 15% in the nighttime. Additionally, this work indicated that the description of the canopy characteristics for the land surface model should be improved to accurately deliver the heterogeneity for the underlying surface.

Bio-surfactants are surface-active molecules which are produced by the wide range of microbes including bacteria, fungi, and yeast. This study was conducted to identify bio-surfactants by Bacillus subtilis combined with use of cheap substrates and industrial wastes (Mustard cake, Whey and Soya cake) which are found locally in Nepal. Bacillus subtilis, one of the most potential bio-surfactants producer; was isolated from soil sample of hydrocarbon contaminated site. Isolates were grown in a Minimal Salt Media (MSM) with 10% (v/v) mustard oil cake, whey and soya cake separately. The presence and potential of surfactant was determined by the oil spreading technique, emulsification index (%E24) and surface tension measurement. It was revealed that the surface tensions of cell free extract were 54.41, 60.02 and 56.64 mN/m for from mustard cake, whey and soya cake respectively as compared to distilled water (72.09) at 25oC. The emulsification index values are was found to be highest in engine oil from the bio-surfactant extracted from mustard cake, soya cake and whey respectively. Similarly, mustard oil showed the lowest value of emulsification index. The highest emulsification activity was shown in mustard oil i.e. 1.13 from the cell free extract from mustard oil and lowest in engine oil i.e., 0.07, by the extract from soya cake medium, when measured in spectrophotometer at 540 nm. In conclusion, strain of Bacillus subtilis was found to be the potential surface active agent producers on the mustard oil cake, which can be useful medium for various environmental, food and industrial processes.

Solids in the interstellar medium consist of an intimate mixture of silicate and carbonaceous grains. Because 99% of silicates in meteorites were reprocessed at high temperatures in the inner regions of the Solar Nebula, we propose that similar levels of heating of carbonaceous materials in the oxygen-rich Solar Nebula would have converted nearly all carbon in dust and grain coatings to CO. We discuss catalytic experiments on a variety of grain surfaces that not only produce gas-phase species such as CH4, C2H6, C6H6, C6H5OH or CH3CN, but also produce carbonaceous solids and fibers that would be much more readily incorporated into growing planetesimals. CO and other more volatile products of these surface mediated reactions were likely transported outwards along with chondrule fragments and small Calcium Aluminum Inclusions (CAIs) to enhance the organic content in the outer regions of the nebula where comets formed. Carbonaceous fibers formed on the surfaces of refractory oxides may have significantly improved the aggregation efficiency of chondrules and CAIs. Carbonaceous fibers incorporated into chondritic parent bodies might have served as the carbon source for the generation of more complex organic species during thermal or hydrous metamorphic processes on the evolving asteroid.

Microalgal harvesting is one of the most challenging processes in the development of algal research and development. Several methods, such as centrifugation, flocculation, and filtration, are available at the laboratory scale. However, the requirement of expensive pieces of equipment and the possibility of biomass contamination are recurring gaps that hinder the development of microalgae I+D in different parts of the world. Recently, the electroflotation has been proved as a suitable method for the harvesting of different species of microalgae and cyanobacteria. To this day, there are no companies that sell laboratory-scale electroflotation equipment; this is mainly due to the gap in the knowledge on which factors (time, mixing rate, number of electrodes, and others) will affect the efficiency of concentration without reducing the biomass quality. This paper aims to build an innovative low-cost electroflotation system under 300 USD with cheap and resistant materials. To achieve our goal, we test the interaction of three variables (time, mixing rate, and amount of electrodes) were evaluated. Results showed that an efficiency closer to 100% could be achieved under 20 minutes using >10 electrodes and 150 rpm. We hope this innovative approach can be used by different researchers to improve our knowledge of the concentration and harvesting of algae and cyanobacteria.

In this paper, we study the sensing performance of metasurfaces comprised by spiral-disk-shaped metallic elements patterned on polypropylene substrates, which exhibit localized surface plasmon resonances in the low-frequency region of the THz spectrum (0.2-0.5 THz). Optimal designs of spiral disks with C-shaped resonators placed near the disks were determined and fabricated. The experimentally measured transmittance spectra of samples coated with very thin photoresistive layers (d ~ 10^-4-10^-3 λ) showed good agreement with simulations. The resonance frequency shift Δf increases with increasing d, while saturating near d = 50 µm. The narrow-band magnetic dark modes excited on symmetrical spiral disks with a 90⁰-C-resonator demonstrated very high FOM values reaching 1670 [RIU·mm]^-1 at 0.3μm-thick analyte. The hybrid high order resonances excited on asymmetrical densely packed spiral disks showed about two times larger FOM values (up to 2950 [RIU·mm]^-1) as compared to symmetrical distantly spaced spirals that resembles the best FOM results found in literature for metasurfaces fabricated with a similar technique. The demonstrated high sensing performance of spiral disks is evaluated to be promising for bio-sensing applications in the THz range.

Carbon dioxide (CO2), a major greenhouse gas, capture and separation has recently become a crucial technological solution to reduce atmospheric emissions from fossil fuel burning. Thereafter, many efforts have been put forwarded to reduce the burden on climate change by capturing and separating them especially from larger power plants by the utilization of different technologies. Those technologies have often suffered from high operating cost and huge energy consumption. On right side, physical process such as adsorption is very cost effective process which have been widely used to adsorb different contaminants including CO2. Henceforth, this review covers the overall efficacies of CO2 capture by the utilization of carbon based materials through adsorption technology. Subsequently, we also address the associated challenges and future opportunities of carbon based materials (CBMs). For CO2 capture, it was found that CBMs followed the order of carbon nanomaterials (i.e., graphene, graphene oxides, carbon nanotubes and their composites) < mesoporous -microporous or hierarchical porous carbons < biochar and activated biochar < activated carbons.

This paper presents several novel designs of underwater portable radio antennas operating in the 2 MHz, 50 MHz and 2.4 GHz bands and efficient for launching surface electromagnetic waves at the seawater/air interface. The antenna operation is enabled by an impedance matching antenna enclosure, which is filled with de-ionized water. Enhanced coupling to surface electromagnetic waves is based on the field enhancement at the antenna tip. These design features allow us to reduce antenna dimensions and improve the coupling of electromagnetic energy to the surrounding saltwater medium. Since surface wave propagation length far exceeds the skin depth of conventional radio waves at the same frequency, this technique is useful for broadband underwater wireless communication over distances, which far exceed the skin depth in seawater. We conclude that the developed broadband underwater radio communication technique will be useful in networking of unmanned underwater vehicles.

High frequency knowledge of the spatio-temporal distribution of the Downwelling Surface Shortwave Flux (DSSF) and its diffuse fraction (fd) at the surface is nowadays essential for understanding climate processes at the surface-atmosphere interface, plant photosynthesis and carbon cycle, and for the solar energy sector. The EUMETSAT Satellite Application Facility for Land Surface Analysis operationally delivers estimation of the MDSSFTD (Downwelling Surface Short-wave radiation Fluxes – Total and Diffuse fraction) product with an operational status since the year 2019. The method for the retrieval was presented in the companion paper [40]. The part 2 now focuses on the evaluation of the MDSSFTD algorithm and presents the comparison of the corresponding outputs, i.e. total DSSF and diffuse fraction (fd) components, against in-situ measurements acquired at four BSRN stations over a seven-month period. The validation is performed on an instantaneous basis. We show that the satellite estimates of DSSF and fd meet the target requirements defined by the user community for all-sky (clear and cloudy) conditions. For DSSF, the requirements are 20Wm^-2 for DSSF<200Wm^-2, and 10% for DSSF>=200Wm^-2. The MBE and rMBE compared to the ground measurements are 3.618Wm^-2 and 0.252%, respectively. For fd, the requirements are 0.1 for fd<0.5, and 20% for fd>=0.5. The MBE and rMBE compared to the ground measurements are -0.044 and -17.699%, respectively. The study also provides a separate analysis of the product performances for clear sky and cloudy sky conditions. The importance of representing the cloud-aerosol radiative coupling in the MDSSFTD method is discussed. Finally, it is concluded that the quality of the Aerosol Optical Depth (AOD) forecasts currently available is enough accurate to obtain reliable diffuse solar flux estimates. This quality of AOD forecasts was still a limitation a few years ago.

The reserves of water, which is one of the most important requirements for human life, gradually decreases under current conditions and rapidly depletes despite being one of the renewable resources. Considering the global water reserves, it became imperative to implement measures to protect the anticipated water reserves. The fact that the amount of quality water per capita decreases every day in the world and the increasing competition in water management could be considered among the indicators of the above-mentioned case. In recent years, as the effects of this adversity became increasingly more evident, several sustainable methods were adopted all over the world such as rain gardens and rainwater storage facilities. These sustainable techniques could be observed in many areas, especially in urban centers. In the present study, the area with the highest water collection was determined at Karadeniz Technical University Kanuni Campus and identified as the study area. Precipitation per square meter and surface runoff volume were identified based on the GIS (Geographic Information System) data, annual water collection volume was calculated, and information on economic and ecological recycling of the water was provided. In conclusion, the precipitation data for 11 years were compared, and it was calculated that the average annual precipitation was 64.06 kg/m² and annual surface runoff water was 552.77 m³. Based on the surface runoff water volume in the months when no irrigation is conducted, a reservoir was designed under the vehicle road and water recycling recommendations were developed.

The objective of this study is to evaluate the effects of the 3D point cloud density derived from unmanned aerial vehicle (UAV) photogrammetry and structure from motion (SfM) and multi-view stereopsis (MVS) techniques, the interpolation method for generating a digital terrain model (DTM), and the resolution (grid size) of the derived DTM on the accuracy of estimated heights in small areas, where a very accurate high spatial resolution is required. A UAV-photogrammetry project was carried out on a bare soil of 13 × 13 m with a rotatory wing UAV at 10 m flight altitude (equivalent ground sample distance = 0.4 cm). The 3D point cloud was derived, and five sample replications representing 1, 2, 3, 4, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80 and 90% of the original cloud were extracted to analyze the effect of cloud density on DTM accuracy. For each of these samples, DTMs were derived using four different interpolation methods (Inverse Distance Weighted (IDW), Multiquadric Radial Basis Function (MRBF), Kriging (KR), and Triangulation with Linear Interpolation (TLI)) and 15 DTM grid size (GS) values (20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0.67, 0.5, and 0.4 cm). Then, 675 DTMs were analyzed. The results showed, for each interpolation method and each density, an optimal GS value (most of the cases equal to 1 cm) for which the Root Mean Square Error (RMSE) is minimum. IDW was the interpolator which yielded best accuracies for all combination of densities and GS. Its RMSE, considering the raw cloud, was 1.054 cm. The RMSE increased 3% when a point cloud with 80% extracted from the raw cloud was used to generate the DTM. When the point cloud included the 40% of the raw cloud, RMSE increased 5%. For densities lower than 15%, RMSE increased exponentially (45% for 1% of raw cloud). The grid size minimizing RMSE for densities of 20% or higher was 1 cm, which represents 2.5 times the ground sample distance of the pictures used for developing the photogrammetry project.

Wave overtopping, i.e., excess of water over the crest of a coastal protection infrastructure due to wave run-up, of a smooth slope can be reduced by introducing slope roughness. A stepped revetment ideally constitutes a slope with uniform roughness. Apart from reducing overtopping, a stepped revetment provides safer access to a beach compared to conventional rubble. In recent years, research studies on stepped revetments have provided valuable findings regarding the performance and design optimization of stepped revetments as a typical mean of coastal protection. A stepped revetment can reduce overtopping volumes of breaking waves up to compared to a smooth slope. The effectiveness of the overtopping reduction decreases with increasing Iribarren number. However, up to date a unique approach applicable for a wide range of boundary conditions is still missing. The present paper critically reviews previous findings, gathers and analyzes data from previous studies and proposes a new formula for robust prediction of overtopping of stepped revetments. By means of this approach a critical assessment based on beforehand disclosed parameter ranges between a smooth slope on the one hand and a plain vertical wall on the other are contrasted. By analysis of a new data set compounded from different original studies a novel empirical formulation is derived to predict the roughness reduction coefficient of a stepped revetment for breaking and non-breaking waves. This coefficient is developed and adjusted for a direct incorporation into the present design guidelines. Underlying uncertainties are clearly addressed and quantified. Scale effects are highlighted.

Recently a new class of experiments in the field of surface gravity waves has emerged. These experiments serve as demonstration of an analogy to a broad variety of phenomena in optics and quantum mechanics. In particular, experiments involving Airy water-wave packets were carried out. The Airy wave packets have attracted tremendous attention in optics and quantum mechanics owing to their unique properties, spanning from an ability to propagate along parabolic trajectories without spreading, and to accumulating a phase that scales with the cubic power of time. Non-dispersive Cosine-Gauss wave packets and self-similar Hermite-Gauss wave packets, also well known in the field of optics and quantum mechanics, were recently studied using surface gravity waves as well. These wave packets demonstrated self-healing properties in water wave pulses as well, preserving their width despite being dispersive. Finally, this new approach also allows to observe diffractive focusing from a temporal slit with finite width.

The process of preparing anti-glare thin films by spray-coating silica sol-gel to soda-lime glass was exclusively and statistically studied in this paper. The effects of sol-gel deliver pressure, air transport pressure, and spray gun displacement speed on the gloss, haze, arithmetic mean surface roughness, and total transmittance light were analyzed. The experimental results indicate that the factors of sol-gel deliver pressure, air transport pressure, and displacement speed exhibit significant effect on the haze, gloss, and Ra. In contrast, the variation of total transmittance light with these three factors are insignificant. Because the anti-glare property is predominantly determined by low gloss and high haze, therefore, we aim to minimize gloss and maximize haze to achieve high anti-glare. Central composite design and response rurface methodology are employed to analyze the main and interaction effects of the three factors through quadratic polynomial equations, which are confirmed by the analysis of variance and R². The response surface methodology predict the lowest gloss and highest haze are 9.2 GU and 57.0%, corresponding to the sol-gel deliver pressure, air-transport pressure, and displacement speed of 250 kPa, 560 kPa, and 140 mm/s, and 340 kPa, 620 kPa, and 20 mm/s, respectively. Comparing the predicted optimal data with the real experimental results validates the applicability of the mathematical model. This study provides an important basis for the subsequent production of anti-glare glass with different specifications to satisfy the market demand.

Earth’s land surface area is raised from conventionally flat 15 to 64 Gha to account for hilly undulation and soil relief detail. Three main aspects are: topography, rugosity/tortuosity and micro-relief/porosity of vegetation-free ground. Recalibration is arrived at from four approaches: first, direct empirical estimates from the few compiled satellite or LiDAR data with means of +2.5–26% progressively overlain by +94% at cm² scale for soil ruggedness then +108% for mm² micro-relief; second, from digital elevation models with 1.6–2.0 times flat areas; third, by ‘reverse engineering’ global soil bulk densities and carbon reserves requiring x 2–6 land. Finally, a Fermi estimation conveniently sets the World’s new surface area – that exposed to Sun, air and rain – at 100 Gha (with 36 Gha flat ocean). Soil organic carbon (SOC) is thence raised to 8,580 Gt mainly in SOM/humus with its biotic complexity plus roots, VAM-fungi and leaf-litter, that itself = 17,800 Gt. Although four to six times IPCC’s or NASA/NOAA’s calculations of just 1,500–2,300 Gt SOC, this is likely an underestimation. Global biomass and biodiversity are at least doubled (x 2–3.5) and net primary productivity (NPP) similarly increased on land to >270 Gt C yr^-1 due to terrain.

A great improvement in food safety and quality controls worldwide has been achieved through the development of biosensing platforms. Foodborne pathogens continue to cause serious outbreaks due to the ingestion of contaminated food. The development of new, sensitive, portable, high-throughput, and automated platforms is a primary objective to allow detection of pathogens and their toxins in foods. Listeria monocytogenes is one common foodborne pathogen. Major outbreaks of listeriosis have been caused by a variety of foods, including milk, soft cheeses, meat, fermented sausages, poultry, seafood and vegetable products. Due to its high sensitivity and easy setup, electrochemical impedance spectroscopy (EIS) has been extensively applied for biosensor fabrication and in particular in the field of microbiology as a mean to detect and quantify foodborne bacteria. Here we describe a miniaturized, portable EIS platform consisting of a microfluidic device with EIS sensors for the detection of L. monocytogenes in milk samples, connected to a portable impedance analyzer for on-field application in clinical and food diagnostics but also for biosecurity purposes. To achieve this goal microelectrodes were functionalized with antibodies specific for L. monocytogenes. The binding and detection of L. monocytogenes was achieved in the range 2.2 x 103 cfu/ml to 1 x 102 with a Limit of Detection (LoD) of 5.5 cfu/ml.

Lanthanide ion doped upconversion nanoparticles (UCNPs) that can convert low-energy infrared photons into high-energy visible and ultraviolet photons, are becoming highly sought-after for advanced biomedical and biophotonics applications. Their unique luminescent properties enable UCNPs to be applied for diagnosis, including biolabeling, biosensing, bioimaging and multiple imaging modality, as well as therapeutic treatments including photothermal and photodynamic therapy, bio-reductive chemotherapy and drug delivery. For the employment of the inorganic nanomaterials into biological environment, it is critical to bridge the gap in between nanoparticles and biomolecules via surface modifications and subsequent functionalisation. This work reviews the various ways to surface modify and functionalise UCNPs so as to impart different functional molecular groups to the UCNPs surfaces for a board range of applications in biomedical areas. We discussed commonly used base functionalities, including –COOH, -NH2 and –SH, that are typically imparted to UCNP surfaces so as to provide further functional capacity.

In the present study, Electrocoagulated Metal Hydroxide Sludge (EMHS) was analyzed as adsorbent material to remove both fluoride ion (F-) and arsenic V (As(V)) from aqueous effluents. This material was generated during an electrocoagulation process using Aluminum anode. It was characterized by using specific surface areas and the surface morphology was studied by scanning electron microscopy (SEM). Adsorbent fixed-beds are generally studied to remove different class of contaminants. EMHS was evaluated using a continuous flow rate column test with an experimental design. The effect of initial concentration of F- (2.5–10 mg L⁻¹) and the Empty Bed Contact Time (EBCT (0.4–0.8 min)) was studied following a central composite design methodology. The experimented parameters had a significant influence on saturation time, breakthrough volume, and breakthrough time. A response surface analysis was a tool for analyzing the adsorption study, showing interactions that are complicated to identify by others methods. The results, here reported, revealed that EMHS is an efficient and promising adsorbent material in order to remove F- and As(V) from water contaminated by these pollutants.

There are some limitations in the null test measurement in the stitching interferometry. In order to meet the null test conditions, the moving distance between the sub-apertures often deviates from the theoretical preset distance, which leads to a position deviation of sub-apertures under measurements. To overcome this problem, an algorithm for data processing is proposed. We used iterative calculation of the deviations between the sub-apertures to adjust their positions, to ensure the local validity of the linear approximation algorithm and realize the exact stitching. A cylindrical lens as an object for experimental examination of the proposed method was taken. The obtained results demonstrate the validity, reliability and feasibility of our iterative stitching algorithm.

In this paper we will present a simplified approach for extracting the ground level – a digital terrain model (DTM) – from the surface provided in a digital surface model (DSM). Most existing algorithms try to find the ground values in a digital surface model. Our approach works the opposite direction by detecting probable above ground areas. The main advantage of our approach is the possibility to use it with incomplete DSMs containing much no data values which can be e.g. occlusions in the calculated DSM. A smoothing or filling of such original derived DSMs will destroy much information which is very useful for deriving a ground surface from the DSM. Since the presented approach needs steep edges to detect potential high objects it will fail on smoothed and filled DSMs. After presenting the algorithm it will be applied to a test area in Salzburg and compared to a terrain model freely available from the Austrian government.

African trypanosomes are an early branch in eukaryotic evolution and developed a unique endomembrane system as an adaptation to their parasitic life style. The key virulence mechanism of many pathogens is successful immune evasion to enable survival within the host, which is a feature requiring both genetic events and membrane transport in African trypanosomes. Intracellular trafficking not only plays a role in immune evasion, but also in homeostasis of intracellular and extracellular compartments and interactions with the environment. Significantly, historical and recent work has unravelled some of the connections between these processes and highlighted how immune evasion mechanisms associated with adaptations in membrane trafficking may have, paradoxically, provided specific sensitivity to drugs. Here we explore these advances in understanding the membrane composition of the trypanosome plasma membrane and organelles and provide a perspective for how transport could be exploited for therapeutic purpose.

We investigated the structural evolution of the two-phase blends of polycarbonate (PC) and poly(methyl methacrylate) (PMMA) at various blend compositions by simultaneous biaxial stretching using optical microscopy and SEM observation. The spherical PMMA domains and PC matrix in 30/70 PC/PMMA were enlarged uniformly at all in-plane direction, while the anisotropic-shaped co-continuous structure in 50/50 PC/PMMA was deformed to crosshatched one by in-plane bimodal orientation. In 70/30 PC/PMMA, the phase inversion was found to occur by simultaneous biaxial stretching; i.e., the spherical PMMA domains were changed to crosshatched matrix by in-plane bimodal orientation due to coalescence of the PMMA domains during the stretching. Owing to the phase inversion, the surface hardness estimated by pencil hardness test became harder from 2B to 2H with increasing the strain from 1.0 to 2.0.

A simple fabrication method in the surface modification of electroosmotic silicon microchannel using thermal dry oxidation is presented. The surface modification is done by coating the silicon surface with a silicon dioxide (SiO₂) layer using thermal oxidation process. The process is aimed not only to improve the surface quality of the channel to be suitable for electroosmotic fluid transport but also to reduce the channel width using a simple technique. Initially, the parallel microchannel array with dimensions of 0.5 mm length and width ranging from 1.8 µm to 2 µm are created using plasma etching on the 2x2 cm <100> silicon substrate. The oxidation of silicon channel in a thermal chamber is then conducted to create the SiO₂ layer. The layer properties and the quality of the surface are analyzed using SEM and surface profiler, respectively. The results show that the maximum oxidation growth rate occurs in the first 4 hours of oxidation time and the rate decreases by time as the oxide layer becomes thicker. It is also found that the surface roughness is reduced with the increase of process temperature and oxide thickness. The scallop effect on the vertical wall due to plasma etching process also improved with the presence of the oxide layer. After the oxidation, the channel width is reduced by ~40%. The demonstrated method is suggested for the fabrication of a uniform channel cross section with high aspect ratio in sub-micro and nanometer scale that will be useful for the electroosmotic flow (EOF) manipulation of the biomedical fluid sample.

The aim of this study was to determine the correlation between the external friction angle of cereal kernels and the roughness of a steel friction plate. The experiment was performed on the kernels of five principal cereals: wheat, rye, barley, oats and triticale. Flat seed units composed of three spaced kernels joined by adhesive tape were analyzed in each experimental variant. The external friction angle of flat seed units was determined on 9 steel friction plates with different roughness. Measurements were performed in 3 replications with a photosensor device which registered the external friction angle of cereal kernels. On friction plates with surface roughness Ra=0.36 to Ra=6.72, the average values of the angle of external friction ranged from 17.56° in rye kernels to 34.01° in oat kernels. The greatest similarities in the angle of external friction were observed between wheat and triticale kernels, whereas the greatest differences were noted between barley and oat kernels and between barley and triticale kernels. Friction plates made of ST3S steel should be characterized by the lowest surface roughness to minimize energy consumption during grain processing. The optimal surface roughness of steel friction plates was determined at Ra=0.9.

The aim of this study was to determine the correlation between the external friction angle of cereal kernels and the roughness of a steel friction plate. The experiment was performed on the kernels of five principal cereals: wheat, rye, barley, oats and triticale. Flat seed units composed of three spaced kernels joined by adhesive tape were analyzed in each experimental variant. The external friction angle of flat seed units was determined on 9 steel friction plates with different roughness. Measurements were performed in 3 replications with a photosensor device which registered the external friction angle of cereal kernels. On friction plates with surface roughness Ra=0.36 to Ra=6.72, the average values of the angle of external friction ranged from 17.56° in rye kernels to 34.01° in oat kernels. The greatest similarities in the angle of external friction were observed between wheat and triticale kernels, whereas the greatest differences were noted between barley and oat kernels and between barley and triticale kernels. Friction plates made of ST3S steel should be characterized by the lowest surface roughness to minimize energy consumption during grain processing. The optimal surface roughness of steel friction plates was determined at Ra=0.9.

The design of curved surface sliders (CSS) based on the elastic response spectrum is done by iteration to find the combination of friction coefficient and displacement capacity which satisfies the condition that the maximum horizontal CSS force is equal to the horizontal force of the structure. Although this CSS design is valid it does not necessarily minimize structural acceleration. This paper therefore describes the optimum CSS design for minimum structural acceleration. All valid CSS designs and the optimum CSS design are represented by their associated trajectory in the elastic response spectrum plane which visualizes the optimization problem. The results demonstrate that the optimum CSS design is not obtained at maximum tolerated effective damping ratio. The subsequent sensitivity analysis describes how much the structural acceleration increases if the actual friction coefficient of the real CSS deviates from its optimum design value. The analysis points out that the increase in structural acceleration is approximately one order of magnitude smaller than the deviation in friction. The sensitivity data may be used by structural engineer to determine tolerable deviations in friction coefficient which still results in acceptable structural accelerations.

Analysis of water resources of this area was carried out in order to assessing the water quality by determining the concentrations of Cations, Anions, Heavy metals, Trace elements, PH, Alkalinity, Total Dissolved Solids and microbial loads in water samples. Ten (10) water samples were collected from the study area - samples each of rain water, two pond waters - 1 and 2, stream water, four (4) hand-dug wells, hand pump water and a motorized borehole. The results obtained were compared with WHO standards and it showed that all the cations in water samples are within the limits. The water samples at locations B, E, F, G, H, I, and J have high alkalinity and HC0^-₃ content. The heavy metals (Pb, Ni and Cd) and trace elements (Fe and Cu) are dominantly high in the surface waters. Microbiological substances in the water samples from the study area revealed indicator organisms higher than the WHO standard for drinking water. Samples obtained from location G, I and J recorded an absence of E. coli and are fit for human consumptions but needed to be treated due to high MPN (Most Probable Number) index of viable microorganisms as against WHO standard. This research showed that the water resources of the study area are gradually polluted and in the near future may not be good for drinking.

Plasma treatment of soft polymers is the promising technique to improve biomedical properties. The response to the deformation of such materials is not yet clear. Soft elastic polyurethane treated with plasma immersion ion implantation is subjected to fatigue uniaxial loading (50000 cycles, frequency – 1 Hz, strain amplitude – 10, 20, 40%). The influence of the strain amplitude and the plasma treatment regime on damage character is discussed. Surface defects are studied in unloaded and stretched states of the material. As a result of fatigue loading, transverse cracks (with closed overlapping edges as well as with open edges deeply propagating into the polymer) and longitudinal folds which are break and bend inward, appear on the surface. Hard edges of cracks cut the soft polymer which is squeezed from the bulk to the surface.

In this work, the apparent shear strength at the interface between a bamboo fiber and the surrounding poly(lactic acid) (PLA) matrix is quantified. A method for processing pull-out test samples within a controlled embedded length is proposed and the details of the test procedure are presented, along with a critical discussion of the results. Two series of samples are considered: untreated and mercerized bamboo fibers from the same batch, embedded in the same polyester matrix. Electron and optical microscopy are used to observe the fiber-matrix interface before and after the test, and to identify the failure mode of each sample, especially as regards the occurrence of fibrillation in the fiber bundles. The values of apparent interfacial shear strength are calculated only for regular fibers successfully pulled out from the matrix, and reported with their statistical variations. Mercerization, whose efficiency was proven by Fourier Transform InfraRed (FTIR) spectroscopy, did not appear though to improve the quality of the interface (τ_app = 7.0 ± 3.1 MPa for untreated fibers and τ_app = 5.3 ± 2.4 MPa for treated fibers).

Regional heat capacity change is calculated from the ratio between the addition or subtraction of heat (ΔQ) with the increase or decrease in temperature (ΔT) region. The purpose of this study is to calculate the regional heat capacity change due to the changes of land cover composition with forest, shrubs, oil palm plantation and bare soil using Landsat-5 TM satellite data on 1994, 2000 and 2010. Total area that used on ​​this study is 12971 ha. In 1994-2000, 4 % of forest area and 2% shrubs were increased, followed by additional of biomass forest 4.01 tons/ha and 2.83 tons/ha for shrubs. The increased of forest area and biomass (tons/ha) caused by forest and shrubs growth processing towards climax that added the canopy volume. So that, the regional heat capacity in 1994 amounted 19384 MJC^o-1 increased to 19929 MJC^o-1 in 2000. Data observation for 2000-2010 showed that forest area decreased by 66% due to forest’s clearing into oil palm plantations (47%), shrubs (8%) and bare soil (11%). But, plant’s biomass continue to increased, i.e 1.48 ton/ha for forest, 2.73 tons/ha for shrubs and 4.63 tons/ha for bare soil. Before 2000, there was no land cover by oil palm plantations, so the increasing rate from this land was the biggest than the three other lands, amounting to 122.29 tons/ha. Decreasing in the percentage of forest area does not cause a decrease in the heat capacity of the region. Intensive maintenance on oil plam plantation such as water management, fertilizer and planting space made it biomass productivity and ability to save the heat is greater than the forest. As the result, in 2010 regional heat capacity increased to 22508 MJC^o-1.

A simple and effective surface modification of polyester fabrics with sulfuric acid to improve the interfacial deposition of polypyrrole was presented in our work. A range of sulfuric acid concentrations were analyzed by studying water contact angle. Effect of sulfuric acid modification on the deposition of polypyrrole was investigated by sheet resistance and color depth of fabric samples. Polyester fabrics coated with polypyrrole layer were confirmed by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), X-Ray diffraction spectra (XRD), Fourier transform infrared spectroscopy (FTIR). XPS showed that sulphur containing functional groups were obviously appeared on the polyester fiber surface after modification, which were advantageous to promote the deposition of polypyrrole onto polyester fabrics. The improved deposition increased electrical conductivity of fabric samples.

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for 15-5PH Stainless steel by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of machining variables such as concentration of cutting fluid , temperature of cutting fluid , feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error and material removal rate, the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is shown that the most significant factor is cutting speed, followed by feed rate, concentration of cutting fluid, radial depth of cut and temperature of cutting fluid. Finally, confirmation tests were carried out to make a comparison between the experimental results and developed model. Experimental results have shown that machining performance in the turn-boring process can be improved effectively through this approach.

Background: The efficacy of sunscreen is evaluated by SPF values, which are quantitatively determined in laboratories on the backs of human subjects according to a standardized procedure. However, SPF cannot be directly translated to sunburn protection under real-life situations because actual efficacy depends on various factors related to human behaviors and environmental conditions. This study clinically evaluated the efficacy of two sunscreen sprays (SPF 30 and SPF 70) under natural sunlight exposure on healthy subjects at the beach. Methods: Twenty subjects were divided into two cells for the two sunscreen sprays (SPF 70 and SPF 30) in a single-center, actual usage test. The primary endpoint of the study was sunburn protection on the dorsal arms and the secondary endpoint was protection on the face and neck. Subjects stayed at the beach for 4 h after application of the sunscreens with normal beach activities. Subjects’ behavior at the beach, the amounts of sunscreen applied and reapplied, and environmental conditions were all recorded. Results: There was no significant sunburn for a majority of the subjects in either cell. However, neither sunscreen completely blocked the sunburn, especially for the face/neck area. We found that the SPF 70 sunscreen was more effective than the SPF 30 sunscreen. Conclusion: Modern sunscreen sprays, applied liberally, are effective in providing sunburn protection for the body in a beach setting.

The urbanization effects on land surface phenology (LSP) have been investigated by many studies, but few studies focused on the temporal variations of urbanization effects on LSP. In this study, we used the MODIS EVI, MODIS LST data and China’s Land Use/Cover Datasets (CLUDs) to investigate the temporal variations of urban heat island intensity and urbanization effects on LSP in Northeast China during 2001–2015. Land surface temperature (LST) and phenology differences between urban and rural areas represented the urban heat island intensity and urbanization effects on LSP, respectively. Mann-kendall nonparametric test and Sen's slope were used to evaluating the trends of urbanization effects on LSP and urban heat island intensity. The results indicated that the average land surface phenology (LSP) during 2001–2015 was characterized by high spatial heterogeneity. The start of the growing season (SOS) in old urban area had become earlier and earlier than rural area and the differences of SOS between urbanized area and the rural area changed greatly during 2001–2015 (−0.79 days/year, p < 0.01). Meanwhile, the length of the growing season (LOS) in urban and adjacent areas had become increasingly longer than rural area especially in urbanized area (0.92 days/year, p < 0.01), but the differences of the end of the growing season (EOS) between urban and adjacent areas did not change significantly. Next, the UHII increased in spring and autumn during the whole study period. Moreover, the correlation analysis indicated that the increasing urban heat island intensity in spring contributed greatly to the increases of urbanization effects on SOS, but the increasing urban heat island intensity in autumn did not lead to the increases of urbanization effects on EOS in Northeast China.

Background: This study provides a comprehensive analysis of Acinetobacter baumannii in aquatic environments and fish microbiota by integrating culture-dependent methods, 16S metagenomics, and antibiotic resistance profiling. Methods: A total of 83 A. baumannii isolates were recovered using culture-dependent methods from intra-hospital infections (IHI), wastewater (WW) and surface water (SW) samples from two southern Romanian cities in august 2022. The antibiotic susceptibility was screened using disc diffusion, microdilution, PCR and Whole Genome Sequencing assays. Results: The highest microbial load in the analyzed samples was found in Glina, Bucharest for both WW and SW samples across all investigated phenotypes. For Bucharest isolates, the resistance levels corresponded to fluoroquinolones &gt; aminoglycosides &gt; β-lactam antibiotics. In contrast, A. baumannii from upstream SW samples in Targoviste showed the highest resistance to aminoglycosides. The blaOXA-23 gene was frequently detected in IHI, WW, and SW isolates in Bucharest but was absent in Targoviste. Molecular phylogeny revealed presence of ST10 in Târgoviște isolates and ST2 in Bucharest isolates, while other minor STs were not specifically correlated with a sampling point. Using 16S rRNA sequencing, significant differences in microbial populations between the two locations was identified. The low abundance of Alphaproteobacteria and Actinobacteria in both locations suggests environmental pressures or contamination events. Conclusions: These findings indicate significant fecal contamination and potential public health risks, emphasizing the need for improved water quality monitoring and management.

The rising prevalence of food intolerances and increased health and environmental consciousness has driven demand for free-from (FF) and organic products. This study aims to analyze consumer needs, motivations, and challenges related to these products in Portugal through an online survey with 2268 eligible responses, with a participants’ median age of 41 years, predominantly women (76.9%). Results show that 97.4% of respondents are aware of FF products, with 60.0% being regular consumers, particularly of lactose-free milk and gluten-free bread and biscuits. Significant market gaps were identified in the variety of FF bread (62.8%), pastries (49.0%), and cookies (38.4%). Consumers identified high prices (84.9%) and excessive sugar/fat content (52.1%) as the main drawbacks of FF products currently on the market. Women showed greater knowledge and purchase levels compared to men. Trust in organic certification was low (21.4%), with skepticism higher among lower-income and male participants. Despite this, 78.1% believed in the health benefits of organic products, and 72.2% agreed that increased demand could lower prices. Overall, the study highlights the need for greater products’ variety, improved transparency, and consumer education to enhance market trust and accessibility.

The success of deep learning (DL) in offline brain-computer interfaces (BCIs) has not yet translated into efficient online applications. This is due to three primary challenges. First, most DL solutions are designed for offline decoding, making the transition to online decoding complex and unclear. Second, the use of sliding windows in online decoding increases the computational complexity of DL training. Third, DL models typically require large amounts of training data, which are often scarce in BCI applications. To address these issues and enable real-time decoding, even across different subjects without calibration data, we first introduce a novel approach called real-time adaptive pooling (RAP). RAP modifies the pooling layers of existing offline DL models towards the online decoding requirements. Additionally, it significantly reduces the computational demand during training by jointly decoding consecutive windows. To reduce the amount of training data required, our approach leverages different levels of domain adaptation. We show how different settings enable different adaptation solutions. The results demonstrate that our approach is both powerful and can be calibration-free, providing a robust and practical solution for real-time BCI applications. These findings pave the way for the development of co-adaptive and highly efficient DL-based online BCI systems.

Electrolyzed water, which mainly contains hypochlorous acid, is widely used because of its strong microbicidal effects, biosafety, and eco-friendliness. For frequent use in intraoral treatments, we focused on neutral electrolyzed water (NW) produced using two-stage electrolysis and investigated its storage stability. For standard-concentration NWs with free available chlorine concentration (ACC) of 25, 35, and 50 mg/L and high-concentration NWs (100, 200, 300, 500, and 1000 mg/L), changes in the pH, oxidation-reduction potential, and ACC during 126 days of storage and the bactericidal efficacies were examined. Storage under non-shaded conditions at room temperature (LRT) and a higher ACC substantially altered the properties of the NW. NW (≤ 300 mg/L) had a pH of 5.9–7.3 even after storage under LRT; however, NW with higher ACC (500 and 1000 mg/L) had a pH ˂ 5.5, critical for human enamel), even under shaded and refrigerated conditions (SLW). Only NW (25 mg/L) stored under LRT exhibited the lowest ACC (5 mg/L), indicating a decreased bactericidal effect. When stored for use in intraoral treatments, NWs should be prepared with an ACC of 25–300 mg/L and stored in SLW. If diluted NW is used, the ACC should be checked and appropriately diluted every time.

Optimization techniques are pivotal across various scientific domains, typically involving solving problems among feasible alternatives based on specific goals, alternatives, or constraints. In mathematical optimization, traditional methods like Simulated Annealing (SA) do not guarantee finding global minima/optima, especially in cases that contain high dimensions in objective functions. This paper introduces a novel approach where a free-energy driven self-adaptive SA algorithm is designed to handle such cases by incorporating free-energy costs within the Metropolis-Hastings framework. This algorithm not only dynamically adjusts to the changing dimensions of the objective function, but it also enhances a faster optimization process. Furthermore, as examples we demonstrate its capability on a convex unimodal function and the non-convex Rastrigin function, revealing faster convergence to search global minima compared to standard SA algorithm. At last, parameter estimation of noisy exponential data has been executed by our Simulated Annealing driven by the Free-Energy (SAFE) algorithm. Our results suggest that this novel approach may significantly improve optimization speed and accuracy, providing a robust tool for complex multidimensional optimization problems.

The study focuses on the free vibration analysis of beams made of axially functionally graded materials (AFGM) with curvilinear variable cross-sections along their length. The beams encompass various shapes, including concave and convex conic sections, with axial material properties varying according to polynomial and exponential laws. The equations of motion are derived using Hamilton's principle within the framework of Timoshenko beam theory. These governing equations, subjected to various boundary conditions, are solved using the differential transform method (DTM). The proposed solution technique is validated by comparing computed natural frequencies with existing in literature results and those obtained through three-dimensional finite element analysis in ABAQUS. The incorporation of material gradients into the beam finite element models was achieved through the user-defined material subroutine (UMAT). Additionally, a comprehensive study is conducted to examine the influence of various factors on the natural frequencies of functionally graded beams. These factors include parameters of material laws, types of variable beam shapes, slenderness ratio, and specific boundary conditions. This study provides a thorough understanding of the modal dynamics of the considered beams, offering valuable insights into the behavior of FGM structures.

Structural and functional materials are subjected to harsh oxidizing environments that lead to a rapid decline in their surface chemical stability. At high-temperatures, the diffusion of atoms is erratic; thus, the reactive elements (REs) get a chance to migrate to the surface and look for oxygen-reactive sites. Their migration from the lattice sites creates vacancies in the matrix and thus weakens the bond, making the material prone to environmental degrading factors. Subsequently, the inward diffusion of oxygen, sulfur, nitrogen, or carbon may occupy these vacancies, resulting in undesired precipitation at the grain boundary, which is usually brittle. The solubility and dissociation of attacking species and corrosion products play the most critical role in corrosion in high-temperature water. To evade such situations, Ti, Al, and Cr are added in Ni/Fe-based alloys, forming a dense oxide layer on the surface that impedes further surface migration of ions. The stability of the alloys is then determined by the capability of these oxide layers to heal or reform during spalling/cracking. This review attempts to understand the migration of REs at the interfaces to prepare structural materials in any unexpected set of oxidizing service conditions. This review will also try to establish the interaction mechanism of REs novel/conventionally added in the alloys with the oxidizing elements in the environments to design better degradation-resistant high-temperature alloys.

Quantum theory predicts violations of Bell’s inequality. This implies a contradiction with at least one of three statistical conditions, known as “Realism” (joint distribution of relevant observables), “Locality” (conditional separability of pairwise observations, given a set of hidden variables), and “Free Will” (statistical independence between hidden variables and measurement settings). Here we describe a classical system with “clockwork” properties that is unquestionably local. It produces maximal violations of the Clauser-Horne-Shimony-Holt (CHSH) inequality. It contradicts every one of the three listed formal conditions. Nonetheless, it expresses the qualitative markers of ontological Realism, ontological Locality, and ontological Free Will, all at the same time. In other words, the three listed conditions do not correspond to the three ontological concepts with the same names. Therefore, there is no conflict between quantum theory and Local Realism.

Kawasaki disease is a febrile illness characterised by systemic inflammation of small- and medium-sized blood vessels which commonly occurs in young children. Although self-limiting, there is a risk of developing coronary artery lesions as disease progresses with delay in diagnosis and treatment. Unfortunately, the diagnosis of KD continues to remain a clinical dilemma. Thus, this article not only summarises the key research gaps associated to KD, but also evaluates the possibility of using circulating endothelial injury biomarkers such as, circulating endothelial cells, endothelial microparticles and vascular endothelial cell-free DNA, as diagnostic and prognostic tool of KD: a “liquid biopsy” approach. The challenges of translating liquid biopsies to use in KD, and the opportunities for improvement in its diagnosis and management that such translation may provide are discussed. The use of endothelial damage markers, which are easily obtained via blood collection, as diagnostics is promising and we hope this will be translated to clinical applications in the near future.

Perovskite solar cells (PSCs) are vital for their optical and electrical properties, with lead-based PSCs reaching a remarkable efficiency of 26.1%, while tin-based counterparts achieve 18.71%. Due to lead's toxicity, there's a push for alternatives like tin. However, tin-based PSCs suffer from stability issues and high defect density states, necessitating the development of cost-effective, high-performance, and eco-friendly alternatives. In this study, we designed a hetero-junction architecture using MASnI3-based Perovskite, opti-mized with SCAPs-1D. After exhaustive analysis, our device achieved a power conversion efficiency of 24.18%, with enhanced parameters including Voc of 0.09323V, Jsc of 30.8360 mA/cm2, and FF of 84.10%. Recombination rates, particularly Shockley-Read Hall recom-bination, were significantly reduced. Parametric analyses, encompassing absorber layer thickness, band gap, defect density, doping concentration, and operating temperature, in-dicate potential efficiency enhancements. This underscores the viability of Sn-based PSCs as a cost-effective, efficient, and environmentally benevolent alternative to lead-based counterparts, promising advancements in future research and development efforts.

As precision medicine such as targeted therapy and immunotherapy often have limited accessibility, low response rate and evolved resistance, it is urgent to develop simple, low-cost, and quick-turnaround personalized diagnostic technologies for drug response prediction with high sensitivity, speed, and accuracy. Major challenges of drug response prediction strategies employing digital database modeling are the scarcity of labeled clinical data, applicable only to a few classes of drugs, and losing the resolution at the individual patient level. Although these challenges have been partially addressed by large-scale cancer cell line datasets and more patient-relevant cell-based systems, the integration of different data types and data translation from pre-clinical to clinical utilities are still far-fetched. To overcome current limitations of precision medicine with a clinically proven drug response prediction assay, we have developed an innovative and proprietary technology based on in vitro patient testing and in silico data analytics. First, a patient-derived gene expression signature was established via transcriptomic profiling of cell-free mRNA (cfmRNA) from the patient’s blood. Second, a gene-to-drug data fusion and overlaying mechanism to transfer data was performed. Finally, a semi-supervised method was used for database searching, matching, annotation and ranking of drug efficacies from a pool of ~700 approved, investigational or clinical trial drug candidates. A personalized drug response report can be delivered to inform clinical decision within a week. The PGA (Patient-derived Gene expression-informed Anticancer drug efficacy) test has significantly improved patient outcomes when compared to the treatment plans without PGA support. Implementation of PGA, which combines patient-unique cfmRNA fingerprints with drug mapping power, has the potential to identify treatment options when patients are no longer responding to therapy and when standard-of-care is exhausted.

Background/Aim: Stool gluten immunogenic peptides (GIP) determination is now considered a valuable tool for detecting dietary lapses in treated celiac disease (CeD) patients. Our study aims to explore the diagnostic performance of a qualitative lateral flow immunoassay point-of-care test (LFIA/PoCT) compared with a qualitative enzyme-linked immunosorbent assay (ELISA) for detection of stool GIP. Methods: The study is a post hoc analysis of stool samples collected in the real-life conditions from a cohort of gluten-free diet-treated CeD patients. Stool GIP was measured in µg/g of stool using an ELISA kit (iVYLISA GIP S®, Biomedal SL). For the qualitative evaluation of stool GIP, a LFIA/PoCT test (GlutenDetect®; Biomedal S.L) was employed, which reported results as positive or negative. The LFIA/PoCT performance was evaluated against ELISA, considered as the gold standard. GIP concentrations

Immunotherapy, particularly Immune Checkpoint Blockade (ICB), has demonstrated significant efficacy in treating melanoma in recent years. However, accurately predicting treatment success and avoiding ineffective therapies remains an unresolved challenge. Therefore, this study aims to develop statistical models utilizing neural networks to forecast the effectiveness of immune checkpoint therapies for melanoma patients. Our models primarily rely on Artificial Neural Networks (ANN) to anticipate both Overall Survival (OS) and Progression-Free Survival (PFS) among melanoma patients undergoing anti-CTLA4 and anti-PD1/anti-PDL1 therapy. We incorporate gene expression data, measured in Transcripts per Million (TPM), derived from bulk tumor RNA-sequencing datasets. Additionally, clinical variables such as gender, age, and treatment type are factored into our analysis. The ANN underwent optimization to attain the highest feasible precision in anticipating the predetermined survival outcome. Issues stemming from high-dimensional data, such as overfitting, were tackled through regularization and feature selection methods. Consequently, the ANN-based model incorporating feature selection exhibited the capacity to forecast survival (PFS) in response to ICB therapy with a maximal precision of 86%. Conversely, the ANN lacking feature selection but incorporating regularization achieved accuracies of up to 72% for PFS and 71% for OS, correspondingly. In order to confront the challenge posed by limited patient samples and to assess replicability, the model underwent training and validation based on the amalgamation of all five datasets. However, this amalgamation failed to enhance predictive performance, necessitating further investigations.

Cement-free concrete has superior physical performance, such as strength and durability, compared to OPC concrete, however, it has the disadvantage of large shrinkage. Large shrinkage can cause cracks due to shrinkage stress in the long term. In this study, a shrinkage reducing agent (SRA) was used to reduce the shrinkage of cement-free mortar; its content was increased from 0.0 to 1.5 %. For an SRA content of 1.0 %, a calcium sulfoaluminate (CSA) expansive additive (EA) (2.5, 5.0, and 7.5%) was added. To calculate the shrinkage stress of cement-free mortar using the SRA and EA, the compressive strength, elastic modulus, and total and autogenous shrinkage were measured. The unit shrinkage stress of cement-free mortar was obtained by multiplying the elastic modulus by the length change and accumulated to obtain the shrinkage stress acting on the mortar according to the age. The shrinkage stress of cement-free mortar showed different tendencies as the age increased. At early ages, the shrinkage rate of the mortar occupied a large proportion of the shrinkage stress. In the long term, the shrinkage stress was significantly affected by the elastic modulus. As a result, SRA was found to be effective in reducing the shrinkage stress by decreasing both the elastic modulus and shrinkage. However, EA increased the shrinkage stress over the long term due to an increase in elastic modulus even though it compensated for early-ages shrinkage.

This paper introduces a novel architecture—bidirectional optical neural network (BONN)—for providing backward connections alongside forward connections in artificial neural networks (ANNs). BONN incorporates laser diodes and photodiodes and exploits the properties of Köhler illumination to establish optical channels for backward directions. Thus, it has bidirectional functionality that is crucial for algorithms such as the backpropagation algorithm. BONN has a scaling limit of 96 × 96 for input and output arrays, and a throughput of 8.5 × 1015 MAC/s. While BONN's throughput may rise with additional layers for continuous input, limitations emerge in the backpropagation algorithm as its throughput doesn't scale with layer count. Successful BONN-based implementation of the backpropagation algorithm requires the development of fast spatial light modulator to accommodate frequent data flow changes. A two-mirror-like BONN and its cascaded extension are alternatives for multilayer emulation, and they help save hardware space and increase the parallel throughput for inference. An investigation into the application of the clustering technique to BONN revealed its potential to help overcome scaling limits and to provide full interconnections for backward directions between doubled input and output ports. BONN's bidirectional nature holds promise for enhancing supervised learning in ANNs and increasing hardware compactness.

This paper investigates the impact of debt financing on dividend payments when they face the agency costs of free cash flow. Focusing on a sample of 120 firms listed on the Saudi Stock Exchange during the period 2011-2021. The study found a negative association between agency cost of free cash flow and dividend payment. More importantly, our research highlights the significant role of long-term debt in making more prudent use of free cash flow. The obligation to meet interest and principal payments acts as an incentive for them to steer clear of unprofitable expenses and risky investments. Concurrently, long-term debt imposes restrictive clauses in debt contracts, such as minimum dividend distribution requirements, which further encourage higher dividend payments. Since interest and debt repayments are fixed obligations, using free cash flow for dividend disbursement is considered a more profitable and beneficial approach for shareholders in the context of Saudi Arabia.

Machine Learning deals with creating algorithms capable of learning from the provided data. These systems have a wide range of applications and can also be a valuable tool for scientific research which in recent years has been focused on finding new diagnostic techniques for particle accelerator beams. In this context SPARC_LAB is positioned, a facility located at the Frascati National Laboratories of INFN, where the progress of beam diagnostics is one of the main developments of the entire project. With this in mind, you aim to present the design of two neural networks aimed at predicting the spot size of the electron beam of the plasma-based accelerator at SPARC_LAB, which powers an undulator for the generation of x-ray Free Electron Laser (XFEL). Data-driven algorithms use two different data preprocessing techniques, namely autoencoder neural network and PCA. With both approaches, the predicted measurements can be obtained with an acceptable margin of error and most importantly without activating the accelerator, thus saving time, even compared to a simulator that can produce the same result but much more slowly. The goal is to lay the groundwork for creating a digital twin of linac and conducting virtualized diagnostics using an innovative approach.

Circulating cell-free DNA (cfDNA) refers to small fragments of DNA molecules released after programmed cell death and necrosis in several body fluids such as blood, saliva, urine, and cerebrospinal fluid. The discovery of cfDNA has revolutionized the field of non-invasive diagnostics in the oncologic field, in prenatal testing, and in organ transplantation. Despite the potential of cfDNA and the solid results published in recent literature, several challenges remain, represented by low abundance, need for highly sensitive assays and analytical issues. In this review, the main technical advances in cfDNA analysis are presented and discussed, with a comprehensive examination of the current available methodologies applied in each field. Considering the potential advantages of cfDNA, this biomarker is increasing its consensus among clinicians, as it consents to monitor patients’ conditions in an easy and non-invasive way, offering a more personalized care. Nevertheless, cfDNA analysis is still considered a research marker to be further validated, and very few centers are implementing its analysis in the real-life assistance. As technical improvements are enhancing the performances of cfDNA analysis, its application will transversally improve patients’ quality of life.

Patient-derived tumor organoids (PDTOs) are a novel preclinical model of non-small cell lung cancer (NSCLC) for studying tumor biology and precision medicine, which recapitulates tumor morphology and gene expression profile. However, some issues such as low establishment rates, long-term production, and the loss of the immune microenvironment have hindered their widespread practical use. In this study, we investigated the efficacy of a recently introduced free-floating organoid production method to address these issues. The free-floating approach provided PDTO establishment success rate of over 90 % resulting in organoid formation within a short period of one week. These organoids retained the elements of the parental tumor morphology and contained stroma and immune cell populations, as confirmed by flow cytometry analysis. Importantly, we found that the cytokine and growth factor expression profiles of the free-floating organoids correlated with those of the original tumors in 58 % of cases, indicating the preservation of tumor-associated signaling pathways. Obtained organoids exhibited different responses to anticancer chemotherapeutics that might be a result of variable expression of drug resistance-associated genes. Considering the high establishment rate and short time of free-floating organoid production, this technique provides a valuable tool for a more accurate evaluation of therapeutic strategies and cancer biology studies.

The growing adoption of distributed energy production technologies, and the potential of energy underutilization when it is produced by non-connected groups, has raised interest in ‘sharing economy’ concepts in the electricity sector. We suggest that mechanisms, such as peer-to-peer (P2P) energy trading, will allow users to exchange their surplus energy for mutual benefits, stimulate the adoption of renewable energy, encourage communities to ‘democratically’ control their own energy supplies for local development, and improved energy efficiency, and create many other benefits This approach is receiving increasing attention across the world, particularly in Germany, the Netherlands and Australia. Nevertheless, the actual development and implementation of these platforms is slow and mostly limited to trial activities. This study investigates the challenges and barriers facing P2P energy trading developments based on previous academic and industry studies. We provide a comprehensive multidimensional barrier analysis through a PESTLE approach to assess the barriers from a variety of perspectives, including the political (P), economic (E), social (S), technological (T), legal (L), and environmental (E) aspects. This approach clarifies the many intersecting problem fields of P2P trading in renewable energy, and the paper identifies a list of such barriers, and discusses the prospects for addressing these issues. We also elaborate on the importance of incentive-based P2P market design.

Accurate pathogenic detection in wastewater is critical for safeguarding public health and the environment. However, the presence of free nucleic acids in wastewater samples poses significant challenges to molecular detection accuracy. This comprehensive review explores the current status and future potential of pretreatment methods to remove free nucleic acids from wastewater samples. The study contributes a comprehensive analysis of the mechanisms, strengths, and limitations of various pretreatment approaches, including physical, chemical, and enzymatic processes. The effect of various factors on the removal efficiency of these pretreatment methods is also discussed. This review enhances our comprehension of pretreatment techniques and their vital role in achieving precise pathogenic detection in complex wastewater matrices. Furthermore, it outlines future perspectives and developments for improving the speed and effectiveness of pathogenic detection, contributing significantly to disease surveillance, early warning systems, and environmental protection.

Determination of the fetal gender in the first trimester is important in twin pregnancy cases of familial X-linked genetic syndromes and helps determine chorionicity. We assessed and compared the accuracy of first-trimester ultrasound scans, and circulating cell-free fetal DNA (cffDNA) performed by non-invasive prenatal screening (NIPS) in determining fetal gender in the first trimester of twin pregnancies. For this purpose, we enrolled prospectively pregnant women with twin during the first trimester, gestational week (GA) 11-13. The fetal gender was determined using both ultrasound scans and cffDNA screening. Both results were compared to the newborn gender at delivery. A total of 113 women with twin pregnancies were enrolled. There was 100% sensitivity and specificity in Y chromosome detection using cffDNA. The accuracy of gender assignment using ultrasound in any first-trimester scans was 79.7%. Accuracy level increased from 54.2% in CRL 45-54 mm to 87.7% in CRL 55-67 mm and 91.5% in CRL 67-87 mm. Male fetuses had significantly higher chances of a gender assignment error compared to female fetuses, odds ratio = 23.57 (CI 7.356 - 75.66). This is the first study that compared the accuracy of gender determination in the first trimester by cffDNA and by ultrasound scanning in twin pregnancy. It was concluded that the cffDNA is highly sensitive and specific in determining the presence of the Y chromosome in twin pregnancies in the first trimester. Between CRL 67-87 mm, ultrasound scanning offers a highly accurate determination of fetal gender in twin pregnancies. Larger cohorts of multi-center studies are warranted.

This research evaluated the role and feasibility of the granular nanocellulose particles (GNC) from sugarcane bagasse obtained from enzymatic hydrolysis in reducing lipid digestibility and permeability in the in vitro simulated gastrointestinal (GI) system. GNC concentration (0.02%, w/v) had significantly affected the released free fatty acid (FFA) reduction of approximately 20%. The Pick-ring emulsion of the GNC and olive oil simulation mixture revealed higher oil droplet size distribution and stability in the initial stage than the vortexed mixture formation. The difference in particle size distribution and zeta potential of the ingested GNC suspension and GNC-olive oil emulsion were displayed during the in vitro gastrointestinal simulation. GNC particles interacted and distributed surrounding the oil droplet leading to the interfacial emulsion. The GNC concentration (0.01-0.10%, w/v) showed low toxicity on the HIEC-6 cell, ranging from 80.0 to 99% of cell viability. The release of FFA containing the ingested GNC suspension and GNC-olive oil emulsion was about 30% reduction compared to without GNC digest solution. The FFA and triglyceride permeability through the HIEC-6 intestinal epithelium monolayer were deceased in the digesta containing the ingested GNC and emulsion. This work indicated that GNC represented a significantly critical role and properties in the GI tract and reduced lipid digestion and absorption. This GNC could be utilized as an alternative food additive or supplement in fatty food for weight control due to their inhibiting lipid digestibility and assimilation.

A scalable optical convolutional neural network (SOCNN) based on free-space optics and Koehler illumination was proposed to address the limitations of the previous 4f correlator system. Unlike Abbe illumination, Koehler illumination provides more uniform illumination and reduces crosstalk. SOCNN allows for scaling up of the input array and the use of incoherent light sources. Hence, the problems associated with 4f correlator systems can be avoided. We analyzed the limitations in scaling the kernel size and parallel throughput and found that SOCNN can offer a multilayer convolutional neural network with massive optical parallelism.

This study aimed to compare the prognosis and characteristics of patients with advanced hepatocellular carcinoma treated with first-line atezolizumab plus bevacizumab (AB) combination therapy and hepatic artery infusion chemotherapy (HAIC). We retrospectively assessed 179 and 72 patients treated with HAIC and AB combination therapy, respectively, between January 2018 and January 2023. The progression-free survival of patients treated with HAIC was significantly superior than that of patients treated with AB (P&lt;0.05), but there was no significant difference in overall survival and objective response rate (ORR) between the two groups (P=0.1056 and P=0.137, respectively). After propensity score matching (PSM), our data revealed that there was no significant difference in PFS between patients who received AB combination therapy and HAIC therapy (P=0.8888). However, patients who received AB combination therapy had significantly better overall survival than those who received HAIC therapy (P=0.0133). In addition, after PSM, significant differences in ORR and disease control rate were not observed. In conclusion, our propensity score study reveals that patients treated with AB therapy have a significantly longer OS than those treated with HAIC.

In the last years, a recent growing line of research has been developed with fruitful results by using fractional and conformable derivatives in the iterative procedures of classical methods for solving nonlinear equations. In that sense, the use of conformable derivatives has shown better behavior than fractional ones, not only in the theory, but also in the practice. In this work, we adapt the approximation of conformable derivatives in order to design the first conformable derivative-free iterative schemes to solve nonlinear equations: a Steffensen’s type method and a Secant type method; the latter with memory. Convergence analysis is made, preserving the order of classical cases, and the numerical performance is studied in order to confirm the results in the theory. It is shown that these methods can present some numerical advantages versus their classical partners, with wide sets of converging initial estimations.

Background: Liquid biopsies are revolutionary tools to detect tumor-specific genetic alterations in body fluids, and cell-free DNA (cfDNA) can be used for molecular diagnosis in cancer patients. In brain tumors cerebrospinal fluid (CSF) cfDNA might be more informative than plasma cfDNA. Here, we assess the use of CSF cfDNA in pediatric embryonal brain tumors (EBT) for molecular diagnosis. Methods: CSF cfDNA of pediatric patients with medulloblastoma (n=18), ATRT (n=3), ETMR (n=1), CNS NB FOXR2 (n=2) and pediatric EBT NOS (n=1) (mean cfDNA concentration 48 ng/mL; range 4-442 ng/mL) and matched tumor genomic DNA were sequenced by WES, and/or a targeted sequencing approach, to determine single nucleotide variations (SNVs)/copy number alterations (CNA). A specific capture covering transcription start sites (TSS) of genes of interest was used for nucleosome footprinting in CSF cfDNA. Results: 15/25 CSF cfDNA samples yielded informative results, with informative CNA and SNVs in 11 and 15 cases, respectively. For cases with paired tumor and CSF cfDNA WES (n=15), a mean of 83 (range 1-160) shared SNVs was observed, including SNVs in classical medulloblastoma genes such as SMO and KMT2D. Interestingly, tumor-specific SNVs (mean 18; range 1-62) or CSF-specific SNVs (mean 5; range 0-25) were observed suggesting clonal heterogeneity. The TSS panel resulted in differential coverage profiles across all 112 studied genes in 7 cases, indicating distinct promoter accessibility. Conclusion: CSF cfDNA sequencing yielded informative results in 60% of cases (15/25), with WES feasible in 83% (15/18). These results pave the way for implementation of these novel approaches for molecular diagnosis and minimal residual disease monitoring.

This paper proposes an optimal trading algorithm based on a novel application of the conventional Control Engineering (CE). We consider a fundamental CE concept, namely, the feedback control and apply it to the Algorithmic Trading (AT). The concrete feedback control strategy is designed in a form of the celebrated Proportional-Integral-Derivative (PID) model. The highly fluctuating nature of the modern financial markets has led to the adoption of a model-free realisation of the generic PID framework. The control theoretical methodology we propose is combined with the advanced statistics for the historical market data. We obtain a specific log-normal probability distribution function (pdf) associated with the specific quantities associated with the available stock data. The empirical log-normal pdf mentioned above makes it possible the necessary PID gains optimization. For this aim, we apply the data-driven optimization approaches and consider the corresponding Monte Carlo solution procedure. The optimized PID trading algorithm we propose is also studied in the Fourier analysis framework. This equivalent frequency domain representation involves a new concept in the financial engineering, namely, the "stock market energy" concept. For the evaluation, we implement the proposed PID optimal trading algorithm and develop a Python based prototype software. We finally apply the corresponding prototype software to a dataset from the Binance BTC / USDT stock market. The experimental result illustrates the implementability of the proposed optimal PID trading scheme and also shows the effectiveness of the proposed CE methods in the modern AT.

Ageing is the strongest known risk factor for many of the neurodegenerative diseases causing cognitive decline and dementia. Identification of cognitive impairment may be a prelude to appropriate treatment, hopefully disease-modifying. Use of cognitive screening instruments may be an equitable way to identify cognitive impairment. This study examined the use of two such instruments, Free-Cog and Mini-Addenbrooke’s Cognitive Examination (MACE), in patient cohorts referred to a dedicated cognitive disorders clinic based at a tertiary neurosciences centre. Results showed that: (1) specificity and positive predictive value increased with patient age for both tests with some loss of sensitivity and negative predictive value. (2) In the oldest age groups (≥75 and ≥70 years respectively) where specificity was at maximum, a positive test result (i.e. below the specified test cut-off) rules in the diagnosis of cognitive impairment. (3) Values of an “Efficiency Index” for each test indicated qualitatively a moderate change in the probability of correct diagnosis and quantitatively an approximately 15-25% increase in the probability of correct diagnosis. These findings show that both Free-Cog and MACE may be used with confidence for the identification of cognitive impairment and dementia in older patient cohorts. These findings may have implications for public health policies directed to case-finding in clinical practice as opposed to population-based screening.

Cotton cationization with low molecular-weight/polymeric cationic modifiers allows the effective dyeing of fabrics with reactive dyes under salt-free and more environmentally-friendly conditions. The current work focuses on the spectroscopic study of the intermolecular interactions, which dictate the physicochemical process associated with dyeing. Water-soluble copolymers of vinyl benzyl chloride and vinyl benzyl triethylammonium chloride (VBCTEAM) have been used as cellulose cationic modifiers. Dye uptake was assessed using Remazol Brilliant Blue and Novacron Ruby dyes. The study involves ATR-FTIR, UV-Vis, fluorescence and XPS spectroscopy. The results of binary polymer-rich dye-polymer aqueous solutions or dye-polymer precipitates at stoichiometric charge-ratio revealed that the sulfonate/sulfate anions of the dyes interact with the cationic VBCTEAM units of the polymer via electrostatic interactions. Moreover, the comparative study of unmodified/modified dyed cotton indicates that the dye reactive sites remain unaffected for cationized cotton, suggesting that electrostatic interactions are the main driving force for the high dyeing performance observed.

Precise binding affinity predictions are essential for structure-based drug discovery (SBDD). Focal adhesion kinase (FAK) is a member of the tyrosine kinase protein family and is overexpressed in a variety of human malignancies. Inhibition of FAK using small molecules is a promising therapeutic option for several types of cancer. Here, we conducted computational modeling of FAK targeting inhibitors using 3-dimensional structure-activity relationship (3D-QSAR), molecular dynamics (MD), and hybrid topology-based free energy perturbation (FEP) methods. The structure-activity relationship (SAR) studies between the physicochemical descriptors and inhibitory activities of the chemical compounds were performed with reasonable statistical accuracy using CoMFA and CoMSIA. These are two well-known 3D-QSAR methods based on the principle of supervised machine learning (ML). Essential information regarding residue-specific binding interactions was determined using the MD and MM-PB/GBSA methods. Finally, physics-based relative binding free energy (〖∆∆G〗_RBFE^(A→B)) values of analogous ligands were estimated using the alchemical FEP simulation. An acceptable agreement was observed between the experimental and computed relative binding free energies. The overall results using ML and physics-based hybrid approaches could be useful for the rational optimization of accessible lead compounds with similar scaffolds targeting the FAK receptor.

Ischemia/reperfusion (I/R) injury results in cell death by inducing apoptosis. During I/R, early generation of mitochondrial reactive oxygen species (mtROS) can induce neighboring mitochondria to release additional ROS, a toxic cycle resulting in significant mitochondrial and cellular injury. Oxidative damage in the mitochondria contributes to various pathologies, including I/R injury. Accordingly, preventing mitochondrial oxidative damage should be therapeutically relevant for many disorders, including cardiovascular diseases. We recently discovered an Indole-Peptide-Tempo Conjugate (IPTC) that served as a novel bifunctional agent with both antioxidant and autophagy-modulating capacity. Here, we demonstrate that IPTC can protect H9C2 cardiomyocytes from hypoxia/reoxygenation (H/R) injury that results from mtROS overproduction due to impaired mitophagy and resultant mitochondrial dysfunction. We hypothesize that the mechanism of action of IPTC involves the capacity to decrease mtROS combined with induction of mitophagy.

Cancer stem cells play a crucial role in tumor initiation, metastasis and therapy resistance. Cellular heterogeneity and plasticity challenge the isolation of cancer stem cells. The impact of intratumoral cellular heterogeneity in the context of treatment resistance using a label-free approach remains understudied. Here, we use the sedimentation field-flow fractionation technique to separate, without labeling, cell subpopulations of colorectal cancer cell lines and primary cultures according to their biophysical properties. One of the three cell subpopulations sorted by SdFFF exhibits cancer stem cell traits, including high tumorigenicity in vivo, and a higher frequency of tumor-initiating cells compared to the other subpopulations. In vitro two- and three-dimensional chemosensitivity assays emphasize the therapeutic relevance of this cancer stem cell-like subpopulation due to its chemoresistance. Therefore, our findings highlight a label-free cell sorting approach to reveal intratumoral cellular heterogeneity and its implication in therapy resistance. This approach enables the study of the individualized response of each sorted cell subpopulation by breaking down the tumor, thus offering new perspectives for personalized therapy.

Zika virus (ZIKV) has been characterized as one of the potential pathogens and placed under future epidemic outbreaks by the WHO. However, lack of potential therapeutics can result in uncontrolled pandemic like other human pandemic viruses; therefore, prioritized effective therapeutics development has been recommended against ZIKV. In this context, the present study adopted the strategy to explore the lead compounds from Azadirachta indica against ZIKV via concurrent inhibition of the ZIKVpro and ZIKVRdRp proteins using molecular simulations. Initially, structure-based virtual screening of 44 bioflavonoids reported in Azadirachta indica against the crystal structures of targeted ZIKV proteins resulted in the identification of top four common bioflavonoids, viz. rutin, nicotiflorin, isoquercitrin, and hyperoside. These compounds showed substantial docking energy (-7.9 to -11.01 kcal/mol) and intermolecular interactions with essential residues of ZIKVpro (His51, Asp74, and Ser135) and ZIKVRdRp (Asp540, Ile799, and Asp665) by comparison to the reference compounds, O7N inhibitor (ZIKVpro) and Sofosbuvir inhibitor (ZIKVRdRp). Long interval molecular dynamics simulation (500 ns) on the selected docked poses reveals the stability of respective docked complexes contributed by intermolecular hydrogen bonds and hydrophobic interactions. The predicted complex stability was further supported by calculated end-point binding free energy using molecular mechanics generalized born surface area (MM/GBSA) method. Consequently, the identified common bioflavonoids are recommended as promising therapeutic inhibitors of ZIKVpro and ZIKVRdRp for further experimental assessment.

Currently, old-style personal medicare techniques rely mostly on traditional methods, such as cumbersome tools and complicated processes, which can be time-consuming and inconvenient in some circumstances. Furthermore, such old methods need the use of heavy equipment, blood draws, and traditional bench-top testing procedures. Invasive ways of acquiring test samples can potentially cause patients discomfort and anguish. Wearable sensors, on the other hand, may be attached to numerous body areas to capture diverse biochemical and physiological characteristics as a developing analytical tool. Physical, chemical, and biological data transferred via the skin is used to monitor health in various circumstances. Wearable sensors can assess the aberrant conditions of the physical or chemical components of the human body in real-time, exposing the body state in time, thanks to unintrusive sampling and high accuracy. Most commercially available wearable gadgets are mechanically hard components attached to bands and worn on the wrist, with form factors ultimately constrained by the size and weight of the batteries required for the power supply. Wearable gadgets with “skin-like” qualities are a new type of automation that is only starting to make its way out of research labs and into pre-commercial prototypes. In this paper, we studied the recent advancement in battery-powered wearable sensors established on optical phenomena and skin-like battery-free sensors which brings a breakthrough in wearable sensing automation.

Vertically aligned Fe, S, and Fe-S doped anatase TiO₂ nanotube arrays are prepared by electrochemical anodization process using an organic electrolyte in which lactic acid is added as an additive. In the electrolyte, nanotube layers of greater length (12 μm) and high order with inner diameter of approx. 90 nm and outer diameter of approx. 170 nm are achieved. Doping of Fe, S, and Fe-S via simple wet impregnation method substituted Ti and O sites with Fe and S, which leads to enhance the rate performance at high discharge current densities. Discharge capacities of TiO₂ tubes increased from 82 mAh g-1 (bare) to 165 mAh g-1 for Fe-S doped TiO₂ at high current densities of 0.3 mAcm-2 after 100 cycles with exceptional capacity retention of 85% after 100 cycles. Owing to the enhancement of thermodynamic and kinetic properties by doping of Fe-S, Li-diffusion increas2ed resulting in remarkable discharge capacities of 143 mAh g-1 and 89 mAh g-1 at a current density of 7.4 mA cm-2 and 19 mA cm-2, respectively.

This article presents, for the first time, comprehensive model based on the proposed mechanism of Rahal et al [17], Bonardi {20], Tar et al [20], and Mau et al [24], for 3-component systems of G1/Iod/EDB, G1/Iod/amine (in gold chloride), and Iod/Benzoic/Borate (for reduced oxygen inhibition) for the hybri free radical (FRP) and cationic (CP) photopolymerization of interpenetrated polymer network (IPN) systems. Analytic formulas are developed to explore the new features including: (i) conversion efficacy(CE) of FRP is an increasing function of the light intensity (I), the effective absorption coefficient (b), for transient state, whereas, CE at steady-state is independent to the light intensity; (ii) initiator regeneration (RGE)
provides a catalytic cycle for improved CE for FRP and CP; (iii) in the IPN system, the synergic effects due to the co-exist of FRP and CP include: (i) CP can increase the medium viscosity limiting the diffusional oxygen replenishment, such that OIH is reduced; (ii) the cationic monomer also acts as a diluting agent for the radical polymer network, and (iii) the exothermic property of the CP polymerization. We have proposed ascaling law for the transient and steady-state dependence of CE on the key parameter P=bIC₀, given by a an m-order power law of P^m, with m = 0.5 to 1.5, depending on various conditions. The CE also has an optimal value for maximum CE. The presented comprehensive model (with minimum mathematics) focusing on the enhancement mechanisms/pathways, provides analytic formulas which can be used to analyze reported data, and, more importantly, serves as guidance for exploring new functional materials or new kinetic schemes for improved conversion or procedures for both industrial and medical applications such as additive manufacturing (AM), 3D and 4D bioprinting. Finally, we have proposed new directions/experiments based on our theoretical predictions.

The calculation of the vapour pressure of organic molecules at 298.15K is presented using a commonly applicable computer algorithm based on the group-additivity method. The basic principle of this method rests on the complete breakdown of the molecules into their constituting atoms, further characterized by their immediate neighbour atoms. The group contributions are calculated by means of a fast Gauss-Seidel fitting algorithm using the experimental data of 2036 molecules from literature. A ten-fold cross-validation procedure has been carried out to test the applicability of this method, which confirmed excellent quality for the prediction of the vapour pressure, expressed in log(pa), with a cross-validated correlation coefficient Q2 of 0.9938 and a standard deviation  of 0.26. Based on these data, the molecules' standard Gibbs free energy G°vap has been calculated. Furthermore, using their enthalpies of vaporization, predicted by an analogous group-additivity approach published earlier, the standard entropy of vaporization S°vap has been determined and compared with experimental data of 1129 molecules, exhibiting excellent conformance with a correlation coefficient R2 of 0.9598, a standard error  of 8.14 J/mol/K and a medium absolute deviation of 4.68%.

In Lagrangian dynamics, the detection of coherent clusters can help understand the organization of transport by identifying regions with coherent trajectory patterns. Many clustering algorithms, however, rely on user-input parameters, requiring a priori knowledge about the flow and making the outcome subjective. Building on the conventional spectral clustering method of Hadjighasem et al (2016), a new parameter-free spectral clustering approach is developed that automatically identifies parameters and does not require any user-input choices. A noise-based metric for quantifying the coherence of the resulting coherent clusters is also introduced. The parameter-free spectral clustering is applied to two benchmark analytical flows, the Bickley Jet and the asymmetric Duffing oscillator, and to a realistic, numerically-generated oceanic coastal flow. In the latter case, the identified model-based clusters are tested using observed trajectories of real drifters. In all examples, our approach succeeded in performing the partition of the domain into coherent clusters with minimal inter-cluster similarity and maximum intra-cluster similarity. For the coastal flow, the resulting coherent clusters are qualitatively similar over the same phase of the tide on different days and even different years, whereas coherent clusters for the opposite tidal phase are qualitatively different.

The most common type of non-Hodgkin lymphoma in adults is diffuse large B-cell (DLBCL). There is a historical unmet need for more effective therapies in the 2nd and 3rd line setting. Emerging immunochemotherapies have shown activity in small studies of heavily pre-treated patients with prolonged remissions achieved in some patients. Anti-CD19 CAR (chimeric antigen receptor) T cells are potentially curative in the 3rd line and beyond setting and are under investigation in earlier lines of therapy.1 Antibody-drug conjugates (ADC’s) such as polatuzumab vedotin targeting the pan-B-cell marker CD79b has proven effectiveness in multiply-relapsed DLBCL patients. Tafasitamab (MOR208) is an anti-CD19 monoclonal antibody producing prolonged remissions when combined with Lenalidomide in patients who were not candidates for salvage chemotherapy or autologous stem cell transplant. Selinexor, an oral, small-molecule selective inhibitor of XPO1-mediated nuclear export (SINE), demonstrated prolonged activity against heavily-pretreated DLBCL without cumulative toxicity and is being investigated as part of an oral, chemotherapy-free regimen for relapsed aggressive lymphoma. This article reviews current strategies and novel therapies for relapsed/refractory DLBCL.

Conservation history of D614 residue is valuable in predicting the consequences of D614G mutation in the SARS-CoV-2 spike glycoprotein (SGP). We report here that the D614 belonged to an extraordinarily conserved, densely hydrophobic eleven amino acid peptide-motif vavlyqdvnct (11-aa), in the Sarbecovirus group and the variant carrying vavlyqdvnct had appeared in Chinese samples and became predominant in several geographical hotspots in late March, 2020. Interestingly a 2009 annotation of SARS-CoV contained the same mutation.

Structural displacement is an important metric for assessing structural conditions because it has a direct relationship with the structural stiffness. Many bridge displacement measurement techniques have been developed, but most methods require fixed reference points in the vicinity of the target structure which limits field implementations. A promising alternative is to use reference-free measurement techniques that indirectly estimate the displacement by using measurements such as acceleration, and strain. This paper proposes novel reference-free bridge displacement estimation by the fusion of single acceleration with pseudo-static displacement derived from co-located strain measurements. First, we propose a conversion of the strain at the center of a beam into displacement based on the geometric relationship between strain and deflection curves with reference-free calibration. Second, an adaptive Kalman filter is proposed to fuse the displacement generated by strain with acceleration by recursively estimate the noise covariance of displacement from strain measurements which is vulnerable to measurement condition. Both numerical and experimental validations are presented to demonstrate the efficiency and robustness of the proposed approach.

What is the function of cognition? On one influential account, cognition evolved to co-ordinate behaviour with environmental change or complexity (Godfrey-Smith 1996). Liberal interpretations of this view ascribe cognition to an extraordinarily broad set of biological systems – even bacteria, which modulate their activity in response to salient external cues, would seem to qualify as cognitive agents. However, equating cognition with adaptive flexibility per se glosses over important distinctions in the way biological organisms deal with environmental complexity. Drawing on contemporary advances in theoretical biology and computational neuroscience, we cash these distinctions out in terms of different kinds of generative models, and the representational and uncertainty-resolving capacities they afford. This analysis leads us to propose a formal criterion for delineating cognition from other, more pervasive forms of adaptive plasticity. On this view, biological cognition is rooted in a particular kind of functional organisation; namely, that which enables the agent to detach from the present and engage in counterfactual (active) inference.

Despite their obvious differences, biological systems at different scales tend to exhibit common organizational patterns. Unfortunately, these commonalities are usually obscured by the parcelled terminology employed by various scientific sub-disciplines. To explore these commonalities, this papers a comparative study of diverse applications of the maximum entropy principle, ranging from amino acids up to societies. By presenting these studies under a common language, this paper establishes a unified view over seemingly highly heterogeneous biological scenarios.

Extensive phytochemical and chromatographic analysis of different root fractions of Jatropha pelargoniifolia Courb. (Euphorbiaceae) resulted in the isolation and identification of 22 distinct secondary metabolite compounds. Two new compounds, 6-hydroxy-8-methoxycoumarin-7-O-β-D-glycopyranoside and (3-(2-(methylamino) ethyl)-1H-indol-2-yl) methanol, were isolated and identified for the first time from a natural source. In addition, other known compounds, such as hovetricoside C and N-methyltryptamine were isolated from Euphorbiaceae, and hordenine, N-methyltyramine, their salts, cynaroside and linarin were identified in Jatropha spp. for the first time. Some isolated metabolites, such as β-sitosterol, β-sitosterol glucoside, curcusons D and C, naringenin, apigenin, cleomiscosins B and A, spruceanol, propacin, jatrophadiketone, and uracil were previously identified in various Jatropha species. The structures of the isolated compounds were determined using different spectroscopic techniques. The anti-inflammatory, antinociceptive, antipyretic, and antioxidant activities were evaluated for some adequately available isolated compounds. Compounds showed significant antinociceptive activity compared with the standard analgesic drug indomethacin. The edema size was significantly reduced (p< 0.05–0.001) in the animals treated with low doses (5 and 10 mg/kg) of the isolated compounds compared with those treated with a high dose (100 mg/kg) of standard anti-inflammatory drug (phenylbutazone). Furthermore, all tested compounds showed a significant (p< 0.05–0.001) reduction in the rectal temperature of hyper-thermic mice.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

In this article, the research team has systematically developed a method to model the kinematics and dynamics of a 3-wheeled robot subjected to external disturbances and sideways wheel sliding. These models will be used to design control laws that compensate for wheel slippage, model uncertainties, and external disturbances. These are control algorithms developed based on Dynamic Surface Control (DSC). Adaptive trajectory tracking DSC algorithm using fuzzy logic system (AFDSC) and radial neural network (RBFNN) with fuzzy logic system to overcome the disadvantages of DSC and expand the application domain for wheeled Mobile Robots (WMR). However, this Adaptive Fuzzy Neural Network Dynamic Surface Control (AFNNDSC) adaptive controller ensures the closed system is stable and follows the preset trajectory in the presence of wheel slippage model uncertainty and is affected by significant amplitude disturbances. The stability and convergence of the closed-loop system are guaranteed based on the Lyapunov analysis. The AFNNDSC adaptive controller is evaluated by simulation on MATLAB/Simulink software and in a steady state. The maximum position error on the right wheel and left wheel is 0.000572 (m) and 0.000523 (m), and the angular velocity tracking error in the right and left wheels of the control method is 0.000394 (rad/s). The experimental results show the correctness of the theoretical analysis, the effectiveness of the proposed controller, and the possibility of practical application.

This study provides a methodology for optimizing oil production and CO2 sequestration using an integrated asset model of the Farnsworth Unit field, incorporating extensive geological, geophysical, and engineering data. Sensitivity analysis identified critical parameters impacting oil recovery and CO2 storage, leading to the construction of a proxy model using polynomial regression and radial basis function neural networks, with the latter proving more effective for "What-if" analysis. The sensitivity analysis indicated that the Corey parameters impact cumulative oil produced the most. Comprehensive history matching validated the model against historical production data, ensuring reliability for forecasting and optimization. Two scenarios, "Do-Nothing" and development strategy, were forecasted over 15 years (2020-2035). The "Do-Nothing" scenario resulted in 9.57 MMSTB of oil recovery and 2,822.70 MMlbs of CO2 storage. The development strategy case improved outcomes with 13.95 MMSTB of oil recovery and 5,061.68 MMlbs of CO2 stored, and was selected for optimization using particle swarm optimization. The optimized strategy achieved 14,043,372 STB of cumulative oil and 4,832.18 MMlbs of CO2 stored, and increased the field NPV by 25.84% to $114,871,730. This study underscores the significance of integrated asset modeling in enhancing oil recovery and optimizing CO2-EOR processes, providing valuable insights into operational conditions and constraints.

Rapid and extensive urbanization has adversely impacted humans and ecological entities in the recent decades through a decrease in surface permeability and the emergence of urban heat islands (UHI). While detailed and continuous assessments of surface permeability and UHI are crucial for urban planning and management of landuse zones, they have mostly involved time consuming and expensive field studies, and single sensor derived large scale aerial and satellite imageries. We demonstrated the advantage of fusing imageries from multiple sensors for landuse and landcover (LULC) change assessments as well as for assessing surface permeability and UHI emergence in Tirunelveli, Tamilnadu, India. Cartosat-2 and Landsat-7 ETM+ imageries from 2007 and 2017 were fused and classified using a Rotation Forest (RF), while surface permeability and temperature were quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Fused images exhibited higher classification accuracies than non-fused images, i.e. overall kappa coefficient values 0.83 and 0.75, respectively. We observed an overall increase of 20 km2 (45%) in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease of 27 km2 (37%) for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall (0.4) and also for almost all LULC zones. The LST values exhibited an associated overall increase (1.30C) of surface temperature in Tirunelveli with the highest increase (2.40C) for urban built-up areas between 2007 and 2017. The SAVI-LST combined metric depicted the Southeastern built-up areas in Tirunelveli as a potential UHI hotspot, while a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion.

Abstract: This article advances the discourse on sustainable and energy-efficient software by examining the performance and energy efficiency of intelligent algorithms within the framework of green and sustainable computing. Building on previous research, it explores the theoretical implications of Bremermann's Limit on efforts to enhance computer performance through more extensive methods. The study presents an empirical investigation into heuristic methods for search and optimisation, demonstrating the energy efficiency of various algorithms in both simple and complex tasks. It also identifies key factors influencing the energy consumption of algorithms and their potential impact on computational processes. Furthermore, the article discusses cognitive concepts and their interplay with computational intelligence, highlighting the role of cognition in the evolution of intelligent algorithms. The conclusion offers insights into the future directions of research in this area, emphasising the need for continued exploration of energy-efficient computing methodologies.

Recently concluded, large-scale cancer genomics studies involving multiregion sequencing of primary tumors and paired metastases appear to indicate that many or most cancer patients have one or more “clonal" mutations in their tumors. Clonal mutations are those that are present in all of a patient’s cancer cells. Clonally mutated proteins can potentially be targeted by inhibitors or E3 ligase small molecule glues, but developing new small molecule drugs for each patient is not feasible currently. Achilles Therapeutics is currently the only company specifically targeting clonal mutations. However, they are doing so with tumor-derived T cells. To address the potential limitations of immunotherapy, I have devised another approach for exploiting clonal mutations, which I call “Oncolytic Vector Efficient Replication Contingent on Omnipresent Mutation Engagement” (OVERCOME). The ideal version of OVERCOME would likely employ a bioengineered facultative intracellular bacterium. The bacterium would initially be attenuated, but (transiently) reverse its attenuation upon clonal mutation detection.

Cell-free DNA (cfDNA) analysis is a pivotal tool in non-invasive diagnostics, including cancer monitoring and prenatal testing. However, the preanalytical phase, particularly the choice of anticoagulant, significantly impacts cfDNA integrity and yield. This study aims to compare cfDNA yield, stability, and DNase activity across plasma-citrate, plasma-heparin, plasma-EDTA, and serum, to identify the most suitable specimen for cfDNA analysis among the tested anticoagulants. Blood samples from 15 healthy volunteers were collected in four types of tubes (citrate, heparin, EDTA, and serum). cfDNA was extracted and quantified using qPCR, and endogenous DNase activity was assessed through hydrolysis probe assays. Samples were incubated at 37°C for 24 hours to evaluate cfDNA degradation rates. Statistical analyses were performed using repeated measures ANOVA and Sidak's multiple comparison tests. Baseline cfDNA levels were highest in serum, followed by heparin-plasma, while EDTA and citrate-plasma exhibited the lowest levels. DNase activity was fully inhibited in EDTA-plasma, partially inhibited in citrate-plasma, and active in both heparin-plasma and serum. cfDNA degradation was most pronounced in heparin-plasma (85.3%) and serum (55.6%), compared to minimal degradation in EDTA (8%) and citrate-plasma (13.3%). Among the tested anticoagulants, EDTA-plasma proved to be the most suitable specimen for cfDNA analysis due to its low DNase activity and minimal gDNA contamination. Citrate-plasma, with intermediate DNase inhibition, could be an alternative if the citrate concentration were increased. Heparin-plasma and serum showed significant cfDNA degradation, rendering them unsuitable for cfDNA analysis. These findings highlight the importance of anticoagulant selection in preserving cfDNA integrity for diagnostic applications.