Biological invasions have reached an unprecedented level and the number of introduced species is still increasing worldwide. Despite major advances in invasion science, the determinants of success of introduced species, the magnitude and dimensions of their impact, and the mechanisms sustaining successful invasions are still debated. Empirical studies show divergent impacts of non-native populations on ecosystems and contrasting effects of biotic and abiotic factors on the dynamics of non-native populations; this is hindering the emergence of a unified theory of biological invasions. We propose a synthesis that merges perspectives from population, community, and ecosystem levels. Along a timeline of ecosystem transformation driven by non-native species, from historical to human-modified ecosystems, we order invasion concepts and theories to clarify their chaining and relevance during each step of the invasion process. This temporal sorting of invasion concepts shows that each concept is relevant at a specific stage of the invasion. Concepts and empirical findings on non-native species may appear contradictory. However, we suggest that, when mapped onto an invasion timeline, they may be combined in a complementary way. An overall scheme is proposed to summarise the theoretical dynamics of ecosystems subjected to invasions. For any given case study, this framework provides a guide through the maze of theories and should help choose the appropriate concepts according to the stage of invasion.

Heavy metals, including arsenic from abandoned mines, are easily transported with sediment and deposited in water bodies such as reservoirs and lakes, creating critical water quality issues when they are released. Understanding the leaching of heavy metals is necessary for developing efficient water quality improvement plans. This study investigated how arsenic leaches from different soil types and responds to hydrologic conditions to identify areas susceptible to arsenic contamination. In this study, batch- and column-leaching tests and sequential extraction procedures were used to examine arsenic leaching processes in detail. The results showed that most arsenic-loaded sediments accumulated in the vicinity of a reservoir inlet, and arsenic in reservoir beds have a higher leaching potential than those from agricultural land and river beds. Arsenic deposited at the bottom of reservoirs had higher mobility than that in the other soils, and arsenic leaching was closely associated with the acidity of water. In addition, arsenic leaching was found to be responsive to seasons (wet or dry) as its mobilization is controlled by organic compounds that vary over time. The results suggested that temporal variations in the hydrochemical composition of reservoir water should be considered when defining a management plan for reservoir water quality.

This paper models and estimates the volatility of nonfinancial, innovative and hi-tech focused stock index, the Nasdaq-100, using univariate symmetric and asymmetric GARCH models. We employ GARCH, EGARCH and GJR-GARCH using daily data over the period January 4, 2000 through March 19, 2019. We find that the volatility shocks on the index returns are quite persistent. Furthermore, our findings show that the index has leverage effect, and the impact of shocks is asymmetric, whereby the impacts of negative shocks on volatility are higher than those of positive shocks of the same magnitude.

Plants Microbial Fuel Cells (PMFC) is a new technology that generates electricity in a renewable, clean and sustainable way. In spite of these advantages, it still faces limitations in power generation and current density, reaching lower production values than other renewable technologies. Different studies maintain that the high resistivity of the cathode is the main limitation in the generation of energy; therefore, non-metallic materials to obtain a better performance are replacing the metallic electrodes. The implementation of these materials applied to PMFC requires a complex interdisciplinary work. Through three experimental tests using metallic electrodes for the extraction of electrons, this research study shows that the treatment of the substrate with natural materials, the volume plant roots, and substrate temperature and humidity control have a significant influence in the increase of the electric potential and the generated current.

Education for Sustainable Development (ESD) is a global initiative towards transforming education for sustainability. The integration of SD into the education portfolio is considered to be an important approach that ensures strategic alignment of higher education with SDGs. A document review was used to identify and discuss the difference between transmissive and transformative education in relation to SDGs and in the context of Somali education. In this trajectory, it is expected that the concept of ‘‘transformative education is likely to become more common to meet the emerging social, economic and environmental issues, yet practical challenges remain in Somaliland HE sector. The roadmap towards addressing transformative education for sustainability is not included in the Somaliland national portfolios; particularly ESD has not been presented. In this regard, this paper proposed a generic framework that spotlights the integration of HEIs and the national development goals (NDGs) in Somaliland. Meanwhile, developed and developing countries are prioritizing structural transformation in their HEIs that are tailored to national and regional development programs. Consistent with the Rio + 20 outcomes, the authors analyzed the concept of the ‘‘sustainable university’’ and identified the fact that it is practically divided into three interrelated and complementary categories, namely social-, environmental-, and economic-oriented university in pursuit of actualizing SD. The paper recommends major reforms in the education sector including availing investment portfolios for R&D, renovation of education goals and transforming universities for sustainability

This study aimed to assess the foodborne diseases (FBD) outbreaks reported in Brazil between 2000 and 2018, based on data from the Brazilian Ministry of Health (official data) and from the scientific literature. According to official data, 13,163 FBD outbreaks were reported in the country during this period, involving 247,570 cases and 195 deaths. The largest prevalence of FBD outbreaks was observed in the Southeast region of Brazil (45.6%). In most outbreaks it was not possible to determine the food implicated (45.9%) but among those identified, water was the most frequently associated (12.0%). The etiological agent was not identified in most outbreaks (38.0%), while Salmonella (14.4%) was the most frequently reported, among those identified. Homes were the main site of FBD occurrence (12.5%). Regarding data obtained from the scientific literature, 57 articles dealing with FBD in the country throughout the same period were selected and analyzed. Based on these articles, mixed foods were the most prevalent in the outbreaks (31.6%), Salmonella spp. was the pathogen most frequently reported (22.8%) and homes were also the main site of FBD occurrence (45.6%). Despite under-notification, the records of FBD outbreaks that have occurred in Brazil in the past recent years show alarming data, requiring attention from health authorities. The notification of outbreaks is essential to facilitate public health actions.

This paper focused on the oxidative leaching process of vanadium from vanadium-chromium reducing residue in alkaline medium with MnO₂. The effect of experimental parameters including reaction time, reaction temperature, dosage of MnO₂, dosage of NaOH, and liquid-to-solid ratio on the leaching efficiency of vanadium had been studied. The results indicated that MnO₂ was an efficient oxidant for leaching out of vanadium. The leaching efficiency of vanadium was up to 97.25% under optimal reaction conditions: reaction temperature of 90 ℃, reaction time of 60 min, dosage of MnO₂ at 50 wt.%, concentration of NaOH at 30 wt.% and liquid-to-solid at 5:1 mL/g.

Objectives: The aim of this study was to describe potential factors contributing to neonatal mortality in Takeo, Cambodia through assessment of verbal autopsies collected following newborn deaths in the community. The mortality review was nested within a trial of a behavioral intervention to improve newborn survival, and was conducted after the close of the trial, within the study setting. The World Health Organization standardized definition of neonatal mortality was employed, and two pediatricians independently reviewed data collected from each event to assign a cause of death. Results: Thirteen newborn deaths of infants born in health facilities participating in a community based, behavioral intervention were reported during February 2015–November 2016. Ten deaths (76.92%) were early neonatal deaths, two (15.38%) were late neonatal deaths, and one was a stillbirth. Five out of 13 deaths (38.46%) occurred within the first day of life. The largest single contributor to mortality was neonatal sepsis; six of 13 deaths (46.15%) were attributed to some form of sepsis. Twenty-three percent of deaths were attributed to asphyxia. The study highlights the continuing need to improve quality of care and infection prevention and control, and to fully address causes of sepsis, in order to effectively reduce mortality in the newborn period.: The study highlights the continuing need to improve both intrapartum and postnatal quality of care and infection prevention and control, and to fully address causes of sepsis, in order to effectively reduce mortality in the newborn period.

Bauxite residue is the voluminous by-product of alumina production after Bayer process. Its high alkalinity causes disposal problems and harmful environmental impacts. However, the residue contains significant amounts of valuable elements such as rare earth elements including scandium. Greek bauxite residue contains a high amount of scandium close to its main resources. Taking into account scandium limited availability coupled with its high demand in modern technology, bauxite residue could be considered as a potential resource for scandium recovery. In this study, the optimization of scandium extraction from bauxite residue with sulfuric acid is investigated using Taguchi methodology. Based on previous studies acid molarity, leaching time, solid/liquid ratio and reaction temperature were selected as control parameters for the selective Sc recovery. Method optimization targeted the highest concentration of scandium combined with the lowest concentration of iron without taking into account applications constraints. The predicted values resulted by Taguchi methodology were affirmed by a confirmation experiment conducted at optimal conditions. Regression analysis provided the respective equations to be applied on several conditions depending on different applications.

Age-in-place can reduce the progress of dementia syndrome and improve the quality of life of the sufferers and their families. This work proposes an innovative information home support system to be established at the houses of people suffering from dementia. The main innovation of the system are its transparent character that overcomes the need for training of the sufferer, as well as the exploitation of a well-known technique for dementia, namely music therapy. It addresses the need of people suffering from dementia as well as their familiars to be recognized by them and have better interaction and collaboration. The system offers a ubiquitous recognition system, just by using smart devices like smart-phones or smart-wristbands. When a familiar person is detected in the house, then a sound file is reproduced on smart speakers placed in the house, in order to trigger the memory, based on the principles of music therapy. The system reproduced the appropriate time at 100% of the cases and the benefits of music therapy are evident daily. To the best of the authors' knowledge, this is the first system of its kind ever reported in the literature.

We evaluate the complexity of Colombian climate from extreme behavior of gauge temperature and precipitation, using the the novel Tsallis' non-extensive entropy principle based on physical information through the q-index. We find the spatial structure of non additive universal categories (q-index) and compare with some complex systems with the potential to have some degree of dynamical affinity. Our results evidence the great dynamical variability of regional climate expressed in the large range of values of $q$-index, and the high degree of non-extensitivity for both temperature and precipitation.

In this paper we analyze the relationship between bankruptcy risk and the corporate life cycle in Pakistan from 2005 to 2014. For this purpose, we run a Hierarchical Linear Mixed Model (HLM) for a sample of 301 non-financial listed firms in 12 different sectors. The empirical outcomes reveal that firms during introduction, growth and, decline stages (mature stage) of life-cycle experience higher (lower) bankruptcy risk. Moreover, in juxtaposition with growth stage, bankruptcy risk is higher at the introduction stage of life-cycle. These findings suggest that financial managers should be cautious about the financial fragility of the firm at each stage of corporate life-cycle. The results also entail that Pakistani firms do not follow a sequential pattern in their life-cycle rather they have the tendency to revert to a previous stage or jump to the next stage of life-cycle. This is the first study that empirically examines the association between firm life-cycle stage and corresponding bankruptcy risk and asserts that managers must incorporate the life-cycle effects into their financial planning and decision making for sustainable working of an enterprise.

This study was undertaken to derive and analyze the Advanced Microwave Scanning Radiometer - EOS (AMSR-E) sea surface temperature (SST) footprint associated with the Remote Sensing Systems (RSS) Level-2 (L2) product. The footprint, in this case, is characterized by the weight attributed to each 4  4 km square contributing to the SST value of a given AMSR-E pixel. High-resolution L2 SST fields obtained from the MODerate-resolution Imaging Spectroradiometer (MODIS), carried on the same spacecraft as AMSR-E, are used as the sub-resolution “ground truth“ from which the AMSR-E footprint is determined. Mathematically, the approach is equivalent to a linear inversion problem, and its solution is pursued by means of a constrained least square approximation based on the bootstrap sampling procedure. The method yielded an elliptic-like Gaussian kernel with an aspect ratio  1.58, very close to the AMSR-E 6.93GHz channel aspect ratio,  1.7. (The 6.93GHz channel is the primary spectral frequency used to determine SST.) The semi-major axis of the estimated footprint is found to be alignedwith the instantaneous field-of-view of the sensor as expected fromthe geometric characteristics of AMSR-E. Footprintswere also analyzed year-by-year and as a function of latitude and found to be stable – no dependence on latitude or on time. Precise knowledge of the footprint is central for any satellite-derived product characterization and, in particular, for efforts to deconvolve the heavily oversampled AMSR-E SST fields and for studies devoted to product validation and comparison. A preliminarly analysis suggests that use of the derived footprint will reduce the variance between AMSR-E and MODIS fields compared to the results obtained.

Regeneration is a fundamental perpetual tissue process much attributed to functions of adult stem cell. In last decades delivery of adult stem cells to restore tissue structure is widely adopted in regenerative medicine. However, delivery of stem cells can not complete the task of human body regeneration effectively as far as cells need a basis to form a tissue. Certain improvement can be achieved when cells are organized to cells sheets (CS) – primitive tissue-engineered structures comprising of viable cells and ECM proteins. This led us to an assumption that after damage an intermediate feeder is structure formed as a ground for future tissue resulting in gradients of stimuli required to attract other cells (vascular, neural, epithelial, parenchyma etc.) in an organized manner. This feeder acquires increasing heterogeneity and becomes a guiding feeder that provides basic level of organization to increase complexity of structure up to normal tissue. We also highlight potential role of adult mesenchymal stromal cells (MSC) as the main source of guiding feeder and support it by our recent knowledge of their biological function. Finally, we assume that CS known to be a feasible delivery tool in therapeutics resemble guiding feeder and show our own data indicating properties of MSC-based CS. Furthermore, this concept shifts our understanding of therapeutic mechanism underlying a widely known delivery method for regenerative medicine.

Numerous protocols have been published for extracting DNA from phlebotomines. Nevertheless, their small size is generally an issue in terms of yield, efficiency, and purity, for large-scale individual sand fly DNA extractions when using traditional methods. Even though this can be circumvented with commercial kits, these are generally cost-prohibitive for developing countries. We encountered these limitations when analysing parasite infection in Lutzomyia spp. by PCR [1] and, for this reason, we evaluated various modifications on a previously published protocol ([2] and Acardi personal communication). The most significant variation was the use of a different lysis buffer [3] to which added Ca2+ (buffer TESCa), because this ion protects proteinase K against autolysis, increases its thermal stability, and could have a regulatory function for its substrate-binding site [4]. Individual sand fly DNA extraction success was confirmed by amplification reactions using internal control primers that amplify a fragment of the cacophony gene [5,6]. To the best of our knowledge, this is the first time a lysis buffer containing Ca2+ has been reported for the extraction of DNA from sand flies.

In mathematics, one always aims to obtain new frameworks from specific ones. This also stratified to the regality of graphs, where one can produce numerous new graphs from a specific set of graphs. In this work we define some classes of pyramid graphs created by a gear graph and we derive straightforward formulas of the complexity of these graphs, using linear algebra matrix analysis techniques and employing knowledges of Chebyshev polynomials.

Soil moisture (SM) plays an essential role in environmental studies related to wetlands, an ecosystem sensitive to climate change. Hence, there is the need for its constant monitoring. SAR (Synthetic Aperture Radar) satellite imagery is the only mean to fulfill this objective regardless of the weather. The objective of the study was to develop the methodology for SM retrieval under wetland vegetation using Sentinel-1 (S-1) satellite data. The study was carried out during the years 2015–2017 in the Biebrza Wetlands, situated in northeastern Poland. At the Biebrza Wetlands, two Sentinel-1 validation sites were established, covering grassland and marshland biomes, where a network of 18 stations for soil moisture measurement was deployed. The sites were funded by the European Space Agency (ESA), and the collected measurements are available through the International Soil Moisture Network (ISMN). The NDVI (Normalized Difference Vegetation Index) was derived from the optical imagery of a MODIS (Moderate Resolution Imaging Spectroradiometer) sensor onboard the Terra satellite. The SAR data of the Sentinel-1 satellite with VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) polarization were applied to soil moisture retrieval for a broad range of NDVI values and soil moisture conditions. The new methodology is based on research into the effect of vegetation on backscatter () changes under different soil moisture and vegetation (NDVI) conditions. It was found that the state of the vegetation may be described by the difference between  VH and  VV, or the ratio of  VV/VH, as calculated from the Sentinel-1 images. The most significant correlation coefficient for soil moisture was found for data that was acquired from the ascending tracks of the Sentinel-1 satellite, characterized by the lowest incidence angle, and SM at a depth of 5 cm. The study demonstrated that the use of the inversion approach, which was applied to the new developed models and includes the derived indices based on S-1, allowed the estimation of SM for peatlands with reasonable accuracy (RMSE ~ 10 vol. %). Due to the temporal frequency of the two S-1 satellites’ (S-1A and S-1B) acquisitions, it is possible to monitor SM changes every six days. The conclusion drawn from the study emphasizes a demand for the derivation of specific soil moisture retrieval algorithms that are suited for wetland ecosystems, where soil moisture is several times higher than in agricultural areas.

In recent years, with the increasing research and development of the LED industry which contains GaN, it is expected that there will be a large amount of related wastes in the future. Especially the gallium has extremely high value of economic, therefore, it is necessary to establish the recycling system of the GaN waste. However, GaN is a direct-gap semiconductor and with high energy gap, high hardness, and high melting point make it difficult to recycle. Therefore, this study will analyze the physical characteristics of LED wastes containing GaN and carry out various leaching method to leach the valuable metals from the waste optimally. Different acids are used to find out the best reagent for leaching the gallium. Different experimental parameters are discussed such as the effect of the different acid agents , concentration, pressure, solid-liquid mass ratio, temperature, and time which influence the leaching efficiency of the gallium. In this study, various leaching methods which effect the leaching efficiency of the gallium are compared and the advantages and disadvantages are discussed. Finally, pressurized acid leaching method is preferred to leach the GaN waste, and hydrochloric acid is used as the leaching solution because of its better leaching efficiency of gallium. Eventually, the leaching efficiency of the gallium can reach to 98%.

Bauxite residue (BR) is a well promising resource for critical metals and especially scandium (Sc), a rare and expensive metal with increasing applications in advanced technology. Particularly, Greek BR’s composition indicates a sound possibility for a commercially viable recovery of Sc under the conditions of an optimized leaching process and the subsequent use of advanced separation techniques. Leaching with mineral acids emerges as the dominant selection with comparison to other techniques. This study investigates an optimized leaching condition set on Sc recovery, using sulfuric acid as the most suitable among different acids tested, in the context of process economics and environmental constraints. Several variables were studied individually or combined in order to achieve high Sc concentration in the leachate as well as to ensure selectivity, especially in respect to iron. The most significant parameters proved to be the solid to liquid ratio (S/L), the final pH value as well as the use of recycling of leachate on fresh BR batches. The proposed process, using sulfuric acid at low acid molarities under ambient conditions was integrated rapidly leading to high and selective Sc recovery. A flow diagram of the developed leaching process in industrial scale was proposed based on continuous operation.

We describe the draft genome of a Bovine enterovirus (EV) recovered from sewage in Nigeria. The virus replicates on both RD and L20B cell lines, but is negative for all EV screens in use by the GPEI. It contains 7,368nt, with 50.2% G+C content and an ORF with 6,525nt (2,174aa).

Abstract: Characterization the 3-D structure of clouds is needed for a more complete understanding of the Earth's radiative and latent heat fluxes. Here we develop and explore a “ray casting” algorithm applied to the Multi-angle Imaging SpectroRadiometer (MISR) on board the Terra satellite, to reconstruct 3-D cloud volumes for observed clouds. The ray casting algorithm is first applied to geometrically simple synthetic clouds to show that, under the assumption of perfect, clear-conservative cloud masks, the reconstruction method yields overestimation whose magnitude depends on the cloud geometry and the resolution of the reconstruction grid relative to the image pixel resolution. The method is then applied to two select MISR scenes, fully accounting for MISR’s viewing geometry for reconstructions over the Earth’s ellipsoidal surface. The MISR Radiometric Camera-by-camera Cloud Masks at 1.1 km resolution and custom cloud masks at 275 m resolution independently derived from MISR RGB channels are used as input cloud masks. A wind correction method, termed “cloud spreading”, is devised and applied to the cloud masks to offset potential cloud movements over short time intervals (around 7 minutes at maximum) between the cameras. The MISR cloud top height product is used as a constraint to reduce the overestimation at the cloud top. The reconstruction results show that their uncertainty is significant when the wind correction is applied, and that they have more refined structures when the input cloud mask has a higher resolution. Recommendations for improving the presented cloud volume reconstructions as well as for future passive remote sensing satellite missions are discussed.

As one of the most prominent seasonally recurring atmospheric circulation patterns, the Asian Summer Monsoon (ASM) plays a vital role for the life and livelihood of about a third of the global population. Changes in the strength and seasonality of the ASM significantly affect the region, yet the drivers of change and the varied regional responses of the ASM are not well understood. In the last two decades, there have been a number of studies reconstructing the ASM using stalagmite-based proxies such as oxygen isotopes (18O). Such reconstructions allow examination of the drivers and responses, increasing monsoon predictability. In this review paper, we focus on stalagmite 18O records from India at the proximal end of the ASM region. Indian stalagmite 18O records show well dated, high amplitude changes in response to the dominant drivers of the ASM on orbital to multi-centennial timescales and indicate the magnitude of monsoon variability in response to these drivers. We examine Indian stalagmite records collated in SISAL_v1 (version 1) database (http://researchdata.reading.ac.uk/139/) and support the database with a summary of record quality and regional climatic interpretations of the 18O record during different climate states. We highlight current debates and suggest the most useful time periods (climatic events) and locations for further work using tools such as data-model comparisons, spectral analysis methods, multi-proxy investigations and monitoring work

The research objectives of this study are to analyse the volatile compositions of different basil types available in Thai markets and to descriptively determine their aromatic qualities. Essential oils were hydro-distillated from fresh leaves of 2 Holy basil (Ocimum sanctum) varieties namely, white and red and other basil species, including Tree basil (O. gratissimum), Sweet basil (O. basilicum var. thyrsiflorum) and Lemon basil (O. citriodorum). Oil physicochemical characteristics and volatile chromatograms from Gas Chromatography-Mass Spectrometry (GC-MS) were used to qualitatively and quantitatively describe the chemical compositions. Methyl eugenol, estragole and eugenol were among the major chemicals found in the essential oils of these basil types. Classification by Principal Component Analysis (PCA) advised that these Ocimum spp. samples are grouped based on either the distinctive anise, citrus aroma (estragole, geranial and neral) or spice-like aroma (β-methyl eugenol, caryophyllene and α-cubebene). The essential oil was also used for descriptive sensorial determination by five trained panelists, using the following developed terms: anisic, citrus, herb, spice, sweet and woody. The panelists were able to differentiate essential oil of white Holy basil from red Holy basil based on the intensity of the anisic attribute, while the anise and citrus scents were detected as dominant in the Lemon basil, Tree basil and Sweet basil essential oils. The overall benefit from this research was the elucidation of aromatic qualities from Thai common Ocimum species in order to assess their potential as the raw materials for future food research and development.

Background. Nanotechnology is promising field for generating new applications. A green synthesis of nanoparticles through biological methods using plant extract have a reliable and ecofriendly approach to improve our global environment. Methods. Silver nanoparticles (AgNPs) were synthesized using aqueous extract of Anagalis arvensis L and silver nitrate and were physicochemically characterized. Results. The stability of AgNPs toward acidity, alkalinity, salinity and temperature showed that they remained stable at room temperature for more than two months. The SEM and TEM analysis of the AgNPs showed that they have a uniform spherical shape with an average size in the range of 40–78 nm. Further 1-Dibhenyl-2-Picrylhydrazl radical in Anagalis arvensis L.mediated AgNPs showed a maximum activity of 98% at concentration of 200μg/mL. Hydrogen peroxide scavenging assay in Anagalis arvensis L. mediated AgNPs showed a maximum activity of 85% at concentration of 200μg/mL. Reducing power of Anagalis arvensis L.Ag NPs exhibited a higher activity of 330 μg/mL at concentration of 200 μg/mL. These NPs have cytotoxic effects against brine shrimp (Artemia salina) nauplii with a value of 53% LD 178.04μg/mL. Conclusion. The AgNPs synthesized using Anagalis arvensis L. extract demonstrate a broad range of applications.

Theories of quantum gravity suggest that Lorentz invariance, the fundamental symmetry of the Theory of Relativity, may be broken at the Planck energy scale. While any deviation from conventional Physics must be minuscule in particular at attainable energies, this hypothesis motivates ever more sensitive tests of Lorentz symmetry. In the photon sector, astrophysical observations, in particular polarization measurements, are a very powerful tool because tiny deviations from Lorentz invariance will accumulate as photons propagate over cosmological distances. The Standard-Model Extension (SME) provides a theoretical framework in the form of an effective field theory that describes low-energy effects due to a more fundamental quantum gravity theory by adding additional terms to the Standard Model Lagrangian. These terms can be ordered by the mass dimension d of the corresponding operator and lead to a wavelength, polarization, and direction dependent phase velocity of light. In this paper, we analyze optical polarization measurements from 63 Active Galactic Nuclei (AGN) and Gamma-ray Bursts (GRBs) in order to search for Lorentz violating signals. We derive the first set limits on each of the 10 individual birefringent coefficients of the minimal SME with d = 4, with 95% confidence limits on the order of 10⁻³⁴ on the dimensionless coefficients.

Water pollution in developing countries affects the public health of humans and the environment. It is therefore essential to develop environmentally friendly biopolymer, sustainable and low-cost membranes. Biopolymer nanofiber membranes are made by an electrospinning process of polylactic acid (PLLA) with additives. The main objective of this study is to manufacture biodegradable nanofiber membranes for use in filtering the suspended elements in wastewater at the level of drinkable or in agricultural fields. It is known that PLLA is brittle and therefore it is difficult to apply in industry. To solve this problem and enhance its flexibility. Flexible biopolymer polypropylene carbonate (PPC) and plasticizer are the addition in PLLA to reduce its glass transition and enhance its crystallization by adding Poly(3-hydroxy butyrate) PHB. In this work, 20 wt% of PPC was added to PLLA matrix to improve its elasticity and elongation at break. DSC shows that the addition of PPC, PHB, and TEC did affect the thermal properties like T_g, T_cc and T_m of the PLLA blends. The position of the T_g, T_cc, and T_m is shifting, the consequence the chain mobility is increased, therefore the crystallinity is enhanced. Electrospun fibers of PLLA/PPC/PHB/TEC were successfully manufactured. Tensile tester showed the increase in elongation at break of PLLA blend films, the elongation at break increases by 285 times. It observed with the increasing the elongation at break, a decrease in stress strength. After improving the mechanical properties with the higher elongation at break values, this blend is optimal for filtrations process.

We design an asymmetric nonlinear optical nanoantenna composed of a dielectric nanodisk and an adjacent nanobar. The proposed composite structure made of AlGaAs exhibits resonant response at both the fundamental and doubled frequencies. Being driven by the strong magnetic dipole resonance at the pump wavelength and a high-quality mode at the harmonic wavelength, the efficient second-harmonic radiation is generated predominantly along the vertical directions under the normally incident plane-wave excitation.

Concentrations of six polycyclic aromatic hydrocarbons (benzanthrone, benz[a]anthracene, chrysene, fluoranthene, pyrene, and triphenylene) of soil samples from Diboll, an East Texas city (USA), were analyzed with gas chromatography-mass spectrometry (GC-MS). Samples were collected from five sites; Old Orchard Park, two heavy traffic intersections (Judd Street and Lumberjack Drive), an industrial site (West Borden Drive), and a truck stop. Acetone and dichloromethane extracts in all samples showed the presence of fluoranthene and pyrene. The sum of fluoranthene and pyrene concentrations in sites followed the order West Borden Drive > Judd Street > Lumberjack Drive > Old Orchard Park > truck stop. Concentrations of fluoranthene and pyrene were in the range 12.3 – 396.5 μg kg^-1 (ppb) and 13.6 – 209.8 μg kg^-1 ₍in dry soil₎, respectively. Benzanthrone, benz[a]anthracene, chrysene, and triphenylene concentrations were < 2 ppb levels. The higher concentrations in soils were associated with sites close to heavy traffic and vehicular emissions.

β-dicalcium silicate (β-Ca₂SiO₄, or β-C₂S in cement chemistry notation) is one of the most important minerals in cement. An improvement of its hydration rate would be the key point for developing environmentally friendly cements with lower energy consumption and CO₂ emissions. However, there is a lack of fundamental understanding on the water/β-C₂S surface interactions. In this work we aim to evaluate the water adsorption on three β-C₂S surfaces at the atomic scale using density functional theory (DFT) calculations. Our results indicate that thermodynamically favorable water adsorption takes place in several surface sites, with a broad range of adsorption energies (−0.78 to −1.48 eV), depending on the particular mineral surface and adsorption site. To clarify the key factor governing the adsorption, the electronic properties of water at the surface were analyzed. The partial density of states (DOS), charge analysis, and electron density difference analyses suggest a dual interaction of water with β-C₂S (100) surface: a nucleophilic interaction of the water oxygen lone pair with surface calcium atoms, and an electrophilic interaction (hydrogen bond) of one water hydrogen with surface oxygen atoms. Despite the elucidation of the adsorption mechanism, no correlation was found between the electronic structure and the adsorption energies.

Immobility during hospitalization is widely recognized as a contributor to deconditioning, functional loss, and increased need for institutional post-acute care. Several studies have demonstrated that inpatient walking programs can mitigate some of these negative outcomes, yet hospital mobility programs are not widely available in U.S. hospitals. STRIDE is a supervised walking program for hospitalized older adults that fills this important gap in clinical care. Herein we describe how STRIDE works and how it is being disseminated to other hospitals using the Replicating Effective Programs (REP) framework. Guided by REP, we define core components of the program and areas where the program can be tailored to better fit the needs and local conditions of its new context (hospital). We describe key adaptations made by 4 hospitals who have implemented the STRIDE program and discuss lessons learned for successful implementation of hospital mobility programs.

Pheochromocytoma and sympathetic paraganglioma (PPGL) are rare neuroendocrine tumors characterized by catecholamine production in the adrenal medulla and extra-adrenal paraganglia. PPGL with metastasis was termed malignant PPGL. However, the distinction between “benign” and “malignant” PPGLs has been debated. Currently, all PPGLs are believed to have some metastatic potential and are assigned malignant tumors (ICD-O/3) by the WHO Classification of Endocrine Organs (2017, 4th edition). Therefore, the previous categories benign and malignant PPGL have been eliminated in favor of a risk stratification approach. The Grading of Adrenal Pheochromocytoma and Paraganglioma (GAPP) is a tool for risk stratification for predicting metastasis and the prognosis of patients. At least 30% of PPGLs are hereditary, with 20 genes identified and genotype-phenotype correlations clarified. Of these, VHL, RET, and NF1 have been well investigated and are the primary cause of bilateral PCC. In addition, succinate dehydrogenase gene subunits SDHB and SDHD are strongly correlated with extra-adrenal location, younger age, multiple tumors, metastasis, and poor prognosis. Disease stratification by catecholamine phenotype and molecular profiling correlates with histological grading by GAPP. PPGLs should be understood comprehensively based on clinical, biochemical, molecular, and pathological data for patient care. A flow chart for pathological diagnosis is included.

Measuring farms sustainable innovativeness is a big challenge for both practitioners and academics. The need of sustainable innovativeness assessment in the agricultural business is reasoned in the article. Unfortunately, the features of the farms sustainable innovativeness measurement have not yet been investigated, and any objective methodology for innovativeness assessment is not presented as well. The objective of this article is to find possibility of use some methodology for measuring farm sustainable innovativeness, which would allow ranking farms by this aspect. The article demonstrates the need for multi-criteria method of innovativeness measurement and substantiates the complex proportional assessment method (Copras) as the most appropriate for solution of indicated problem. The model for use of offered method is presented and the practical application of the model is submitted. The final result refuted the opinion that farm innovation depends only on the possibilities to invest funds in a certain area. Indeed, staff creativity and the position of the management regarding certain areas of business make an essential contribution to the sustainable innovativeness level in the agricultural organizations.

We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. We review large deviations techniques useful in this context to describe properties of accuracy and convergence in terms of sampling size. We use these results to study the statistical fluctuation of correlations, distinguishability and irreversibility of maximum entropy Markov chains. We illustrate these applications using simple examples where the large deviation rate function is explicitly obtained for maximum entropy models of relevance in this field.

This paper includes some new investigations and results for post quantum calculus, denoted by (p,q)-calculus. A chain rule for (p,q)-derivative is developed. Also, a new (p,q)-analogue of the exponential function is introduced and some its properties including the addition property for (p,q)-exponential functions are investigated. Several useful results involving (p,q)-binomial coefficients and (p,q)-antiderivative are discovered. At the final part of this paper, (p,q)-analogue of some elementary functions including trigonometric functions and hyperbolic functions are considered and some properties and relations among them are analyzed extensively.

Ticks are key vectors of some important diseases of humans and animals. Although they are carriers of disease agents, the viability and development of ticks are not harmed by the infectious agents due to their innate immunity. Antimicrobial peptides directly protect hosts against pathogenic agents such as viruses, bacteria, and parasites. Among the identified and characterized antimicrobial peptides, defensins have been considerably well studied. Defensins, which contain intramolecular disulfide bridges between cysteine residues, are commonly found among fungi, plants, invertebrates, and vertebrates. The sequence of the tick hemolymph defensin (HEdefensin) gene from the hard tick Haemaphysalis longicornis was analyzed after identification and cloning from a cDNA library. HEdefensin has a predicted molecular mass of 8.15 kDa and a theoretical isoelectric point of 9.48. Six cysteine residues were also identified in the amino acids. The synthetic HEdefensin peptide only showed antibacterial activity against Gram-positive bacteria such as Micrococcus luteus. A fluorescence propidium iodide exclusion assay also showed that HEdefensin increased the membrane permeability of M. luteus. Additionally, an indirect fluorescent antibody test showed that HEdefensin binds to M. luteus. These results suggested that HEdefensin strongly affects the innate immunity of ticks against Gram-positive bacteria.

The purpose of the present study is survey of extraction conditions and exploring antioxidant potential of the non-traditional for the Bulgarian ethno-medicine wild herb Cistus incanus widespread in Strandja Mountain. The influence of the extraction time (0–500 min) and solvent composition (0–50% ethanol in water) on the polyphenols, flavonoids yields and on antioxidant capacity of the extracts of leaves, stalks (wood parts) and buds mixture were studied. The antioxidant capacity (AOC) was evaluated by use of scavenging assays of 2,2-diphenyl-1-picrylhydrazyl (DPPH) radicals. Total polyphenol and flavonoid contents were quantified using UV–vis spectrometry. Optimal yield of desired components has been obtained with 30% ethanol in water solvent at 390^th min extraction time. In addition, the influence of the seasonality (winter and summer Cistus incanus), and of the different areal parts - hard-coated seeds; buds, and mixture of leaves and stalks of the wild plant on the presence of polyphenols, flavonoids and AOC were investigated. Present work revealed the high values of the polyphenols, flavonoids, the high AOC not only in the summer leaves, but also found in the winter leaves, hard-coated seeds, buds and stalks. Based on the obtained results the Cistus incanus from Strandja mountain could be a new excellent source of natural antioxidants in food and pharmaceutical industries.

Wave steepness is presented as an extension and a valuable add-on to the conventional set of sea state parameters retrieved from satellite altimetry data. Following physical model based on recent advances of weak turbulence theory wave steepness is estimated from directly measured spatial gradient of wave height. In this way the method works with altimetry trajectories rather than with point-wise data. Moreover, in contrast to widely used parametric models this approach provides us with instantaneous values of wave steepness and period. Relevance of single-track estimates of wave steepness (period) is shown for wave climate studies and confirmed by a simple probabilistic model. The approach is verified via comparison against buoy and satellite data including crossover points for standard 1 second data of Ku-band altimeters. High quality of the physical model and robustness of the parametric ones are examined in terms of global wave statistics. Prospects and relevance of both approaches in the ocean wave climate studies are discussed.

Sensitivity to weather conditions, and specially to clouds, is a severe limiting factor to the use of optical remote sensing for Earth monitoring applications. A possible alternative, is to resort to weather-insensitive synthetic aperture radar (SAR) images. However, in many real-world applications, critical decisions are made based on some informative spectral features, such as water, vegetation or soil indices, which cannot be extracted from SAR images. In the absence of optical sources, these data must be estimated. The current practice is to perform linear interpolation between data available at temporally close time instants. In this work, we propose to estimate missing spectral features through data fusion and deep-learning. Several sources of information are taken into account - optical sequences, SAR sequences, DEM - so as to exploit both temporal and cross-sensor dependencies. Based on these data, and a tiny cloud-free fraction of the target image, a compact convolutional neural network (CNN) is trained to perform the desired estimation. To validate the proposed approach, we focus on the estimation of the normalized difference vegetation index (NDVI), using coupled Sentinel-1 and Sentinel-2 time-series acquired over an agricultural region of Burkina Faso from May to November 2016. Several fusion schemes are considered, causal and non-causal, single-sensor or joint-sensor, corresponding to different operating conditions. Experimental results are very promising, showing a significant gain over baselines methods according to all performance indicators.

To cope with a projected global population increase from 7.2 bn to 9.6 bn by 2050, many more cities must be built. Although there are great benefits to modern urban living, there also great costs, such as the seemingly unstoppable rise in Type 2 diabetes, obesity, coronary issues and various cancers. The new towns should be designed to contain or constrain the epidemic of those ‘Western Lifestyle Diseases’ that currently plagues today’s cities. But how might this be achieved? It is suggested here that a greater understanding of human evolution combined with the potency of the ‘Palaeolithic genome’ holds the key to our future urban wellbeing. Consequently, a new paradigm is suggested that underpins positive forward thinking on townplanning and city lifestyles to create healthier urban environments. This builds directly on the ‘Evolutionary Determinants of Health’ programme initiated at University College London (UCL). A four-stage model is proposed that integrates and develops both evolutionary-concordant personal and institutional health behaviours with appropriately reconfigured town-planning and building regulations. When integrated, these strands could deliver a healthier urban culture within greened, active townscapes by proactively constraining or eliminating some of the key underlying causes of the so-called ‘Western Lifestyle Diseases’.

Bacteria play a key role in both human health and disease. One of the most prevalent harmful bacteria is E. coli which is responsible for several illnesses ranging from diarrhea, stomach cramp and fever. In this work we explore the application of moderate electric or magnetic fields for treating deionized water that is contaminated with E. coli. We found that moderate alternating electric (AC) fields (10 V/cm to 1kV/cm) and moderate static magnetic fields (10 to 65 mT) can significantly inactivate E. coli by up to 90% or more. This provides the possibilities of developing a low cost and a practical bacteria inactivation technique using electric or magnetic fields.

This paper addresses the atmospheric emissions from oil and gas extraction and production in Greece. The study was carried out in 2014 in the Kavala gulf, which currently is the only location of oil and gas production in Greece and where the exploration activities for hydrocarbons started in the late ‘60’s. This study presents the qualitative and quantitative characteristics of atmospheric emissions, in relation also to the emissions’ control management system. Particular reference is made to sulphur compounds since the existence of volcanic rocks results to increased amounts of H₂S. The results shows that, currently, atmospheric emissions of pollutants during extraction and production of hydrocarbons in Greece are very low and do not have any significant effect on air quality and climate change. Since it is expected that exploitation of hydrocarbons and oil and gas extraction and production will increase in the future, appropriate measures should be taken to ensure environmental protection, such as the development of integrated monitoring systems and the use of up to date emission control technologies.

Experimental recordings of the collective activity of interacting spiking neurons exhibit random behavior and memory effects, thus the stochastic process modeling the spiking activity is expected to show some degree of time irreversibility. We use the thermodynamic formalism to build a framework, in the context of spike train statistics, to quantify the degree of irreversibility of any parametric maximum entropy measure under arbitrary constraints, and provide an explicit formula for the information entropy production of the inferred Markov maximum entropy process. We provide examples to illustrate our results and discuss the importance of time irreversibility for modeling the spike train statistics.

Clinical metagenomics (CMg), referred to as the application of next-generation sequencing (NGS) to clinical samples, is a promising tool for the diagnosis of hospital-acquired pneumonia (HAP). Indeed, CMg allows identifying pathogens and antibiotic resistance genes (ARGs), thereby providing the information required for the optimization of the antibiotic regimen. Hence, provided that CMg would be faster than conventional culture, the probabilistic regimen used in HAP could be tailored faster, which should lead to an expected decrease of mortality and morbidity. While the inference of the antibiotic susceptibility testing from metagenomic or even genomic data is challenging, a limited number of antibiotics are used in the probabilistic regimen of HAP (namely beta-lactams, aminoglycosides, fluoroquinolones, glycopeptides and oxazolidinones). Accordingly in the perspective of applying CMg to the early diagnostic of HAP, we aimed at reviewing the performances of whole genomic sequencing (WGS) of the main HAP-causing bacteria (Enterobacteriaceae, Pseudomonas aeruginosa, Acinetobacter baumannii, Stenotrophomonas maltophilia and Staphylococcus aureus) for the prediction of susceptibility to the antibiotic families advocated in the probabilistic regimen of HAP.

Rice is currently the most important food crop in the world and we are only just beginning to study the bacterial associated microbiome. It is of importance to perform screenings of the core rice microbiota and also to develop new plant-microbe models and simplified communities for increasing our understanding about the formation and function of its microbiome. In order to begin to address this aspect, we have performed the isolation of hundreds bacterial isolates obtained from endorhizosphere of two rice cultivars from Venezuela. The validation of plant-growth promoting bacterial activities in vitro has led us to select and characterize 15 isolates for in planta studies such as germination test, endophytism ability and plant growth promotion. Consequently, a set of 10 isolates was selected for the set-up of an endophytic consortium as a simplified model of the natural rice bacterial endomicrobiota. Upon inoculation, the colonization and abundance of each strain within the rice roots was tracked by a culture-independent technique in gnotobiotic conditions in a 30 days period. Four strains belonging to Pseudomonas, Agrobacterium and Delftia genera have shown a promising capacity for colonizing and coexistence in root tissues. On the other hand, a bacterial community taxonomic profiling of the rhizosphere and the endorhizosphere of both cultivars were obtained and are discussed. This study is part of a growing body of research on core crops microbiome and simplified microbiomes, which strengthens the formation process of the endophytic community leading to a better understanding of the rice microbiome.

The purpose of this paper is to describe a new way of producing renewable energy based on fjords as a water heater. We will call this system the Water-thermal Energy Production System (WEPS), because the basic idea is to extract heating and cooling energy from water. Although a prototype of WEPS has existed in Norway for more than ten years, a WEPS currently in operation has not been financially analyzed in the literature. Coastal parts of Norway have a potential of 5 TWh of profitable WEPS-facilities [9], due to convenient access to fjords containing water with stable all-season temperatures of about 4–12C when the depth of the water is about 50 meters. This stability of the water temperature makes it possible to extract energy from the fjord in a very efficient way. The potential for economically-profitable WEPS in other parts of the world has not been estimated. In order to answer such a question, more research is required. We have conducted a case study of a WEPS located in the Norwegian municipality of Eid. This is the first full-scale Norwegian WEPS, and it has been operating since 2006. The nascent years have passed, and the technology has been in operation for some years. In this paper, we have made an estimate of the business profitability and the external effects based on past empirical evidence and some assumptions about future development in some key figures. The results suggests that WEPS-Eid has been a profitable investment carrying a positive internal rate of revenue, even if the present underutilization in production capacity will continue in the future. Stability in energy prices for heating purposes has also gained customers compared to the more volatile prices of alternative renewable energy, like hydropower or wind turbines. The negative, external effects in the operating phase from WEPS-Eid are insignificant. Despite the significant profitability of the WEPS facility in Eid, there are two main obstacles for new entrants. There is a lack of relevant operational information for potential investors due to few facilities. This leads to uncertainty, and investments in WEPS appear as a risky business. Secondly, construction of a WEPS requires both big financial investments in digging and facilitating long trenches for a pipeline system and time and effort spent on acquiring the licenses needed for doing this work. A coordinating unit is probably required in order to get the necessary public and private licenses and to reduce fixed costs by coordinating other tasks in the same trenches, like pipes for water and sewer, fiber cables and tele-cables. In Eid, the local municipal administration was the coordinating unit.

Thermal plasma technique is becoming prominent in the treatment of variety of waste ranging from municipal solid waste, incinerator residue, hospital waste, electronics waste and industrial sludge. Application of the new treatment technology to petroleum sludge requires information on the nature and characteristics of the sludge that will be use to optimize the treatment system. In this investigation, petroleum sludge obtained from Petronas Melaka was characterized for its physical and chemical features. Proximate and ultimate analysis as well as determination of elemental composition were carried out. The sludge was found to contain high moisture (78.91%), low ash (5.06%), low volatiles (5.52%) and high fixed carbon (10.51%). The sludge has a TOC of 54.48% and HHV of 23.599MJ/kg. Despite the high moisture content, the higher heating value (HHV) is high when compared to literature values. The high value of HHV may be associated with the high fixed carbon, low ash content and high value of TOC. The apparent density of the sludge is slightly lower. Fourteen heavy metals are detected in significant quantities. Proper waste management that will safely dispose the sludge is required. The waste disposal technique should take into cognizant the possibility of leaching of heavy metals into ground water on one hand and the gasification of lighter ones on the other.

Fumaric acid is a chemical building block with many applications, namely in the polymer industry. The fermentative production of fumaric acid from renewable feedstock is a promising and sustainable alternative to petroleum-based chemical synthesis. The use of existing industrial side-streams as raw-material within biorefineries potentially enable production costs competitive against current chemical processes, while preventing the use of refined sugars competing with food and feed uses and avoiding purposely grow crops requiring large areas of arable land. However, most industrial side streams contain a diversity of molecules that will add complexity to the purification of fumaric acid from the fermentation broth. A process for the recovery and purification of fumaric acid from complex fermentation medium containing spent sulfite liquor (SSL) as carbon source was developed and is herein described. A simple two-stage precipitation procedure involving separation unit operations, pH and temperature manipulation and polishing through the removal of contaminants with activated carbon allowed the recovery of fumaric acid with 68.3% recovery yield with specifications meeting the requirements of the polymer industry. Further, process integration opportunities were implemented that allowed minimizing the generation of waste streams containing fumaric acid which enabled increasing the yield to 81.4% while keeping the product specifications.

In pattern recognition domain, deep architectures are widely used nowadays and they have achieved fine grades. However, these deep architectures need special demands, especially big datasets and GPU. Aiming to gain better grades without deep networks, we propose a simplified algorithm framework using fusion features extracted from the salient areas of faces. Furthermore, the proposed algorithm has achieved a better result than some deep architectures. For extracting more effective features, this paper firstly defines the salient areas on the faces. This paper normalizes the salient areas of the same location in the faces to the same size, therefore it can gain more similar features from different subjects. LBP and HOG features are extracted from the salient areas, fusion features’ dimensions are reduced by Principal Component Analysis( PCA) and we apply softmax to classify the six basic expressions at once. This paper proposes a salient areas definitude method which uses peak expressions frames to compare with their neutral faces. This paper also proposes and applies the idea of normalizing the salient areas to align the specific areas which express the different expressions. This makes the salient areas found from different subjects have the same size. Besides, gamma correction method is firstly applied on LBP features in our algorithm framework which improves our recognition rates significantly. By applying this algorithm framework, our research has gained state-of-the-art performances on CK+ database and JAFFE database.

In the paper, the authors view some ordinary differential equations and their solutions from the angle of (the generalized) derivative polynomials and simplify some known identities for the Bernoulli numbers and polynomials, the Frobenius-Euler polynomials, the Euler numbers and polynomials, in terms of the Stirling numbers of the first and second kinds.

The intentional damages to local Cultural Heritage sites carried out in recent months by the Islamic State have received wide coverage from the media worldwide. Earth Observation data provide important information to assess these damages in such non-accessible areas, and automated image processing techniques would be needed to speed up the analysis if a fast response is desired. This paper shows the first results of applying fast and robust change detection techniques to sensitive areas, based on the extraction of textural information and robust differences of brightness values related to pre- and post-disaster satellite images. A map highlighting potentially damaged buildings is derived, which could help experts at timely assessing the damages to the Cultural Heritage sites of interest. Encouraging results are obtained for two archaeological sites in Syria and Iraq.

Seaweeds are considered as one of the largest biomass producers in marine environment that is rich in bioactive metabolites and a source of natural ingredients for functional foods. The potential antioxidant activity and the potential inhibition of Caco2 cell proliferation, of crude extracts of: Chlorophyta (Ulva lactuca, and Codium tomentosum), Phaeophyta (Cystoseira crinita, Cystoseira stricta, and Sargassum vulgare), and Rhodophyta (Gelidium latifolium, Hypnea musciformis, and Jania rubens) collected from western Libyan coast were evaluated in vitro. The antioxidant activity was determined by reducing power and DPPH assays while cell proliferation, morphological changes and the cell cycle arrest were assessed by MTT, inverted light microscope and flow cytometry methods respectively. The polyphenols and flavonoids rich extracts showed remarkable reducing power and antiradical properties. After exposure of Caco2 cells to; various concentrations of extracts (50, 100,150 and 200 µg/mL) especially from brown algae for 72 h, significantly reduced cell proliferation. The antiproliferative effect of algae extracts was correlated with their polyphenol and flavonoid contents. Cell cycle analysis further showed that cells were arrested in G phases along with an increment in sub-diploidal cell population (sub-G) after extract application. These results imply that seaweeds which are rich in bioactive compounds may be in anticancer drug research programs. However, further investigations are essential to reveal the molecular mechanisms of the anticancer activities of these algae.

Carotid atherosclerotic lesions are a major cause of cerebrovascular disease (CVD). Identification and quantification of carotid plaques are important for categorizing the vulnerability of plaques for rupture and assessing the impact of treatments. The irregularity of plaque surface is associated with previous plaque rupture and plays an important role in the risk of stroke. Thus, the aim of this study is to develop and validate novel vulnerability biomarkers from three-dimensional ultrasound (3DUS) images by analyzing the surface morphological characterization of carotid plaque using fractal geometry features. 3D box-counting and 3D blanket are the two types of 3D fractal dimension that were employed to describe the smoothness of plaques. This fractal dimension analysis tool was used to evaluate the effect of atorvastatin using 3DUS carotid images, which were acquired from 6 patients treated with atorvastatin with 80 mg daily and 5 patients with placebo. The Student's T Test results showed that those two fractal features were effective for detecting the statin-related changes in carotid atherosclerosis with p<0.0068 and p<0.015 respectively, suggesting that 3D fractal dimension measurements can be used effectively to analyze the surface characteristics of carotid plaques, especially for evaluating the impact of the treatment.

Radio loud active galactic nuclei are composed of different spatial features, each one characterized by different spectral properties in the radio band. Among them, blazars are the most common class of sources detected at gamma-rays by \fermi, and their radio emission is dominated by the flat spectrum compact core. In this contribution, we explore the connection between emission at high energy revealed by \fermi\ and at radio frequency. Taking as a reference the strong and very highly significant correlation found between gamma rays and cm-$\lambda$ radio emission, we explore different behaviours found as we change the energy range in gamma rays and in radio, therefore changing the physical parameters of the zones involved in the radiation emission. We find that the correlation weakens when we consider (1) gamma rays of energy above 10 GeV (except for high synchrotron peaked blazars) or (2) low frequency radio data taken by the Murchison Widefield Array; on the other hand, the correlation strengthens when we consider mm-$\lambda$ data taken by ALMA.

This interdisciplinary work presents a novel patent pending method of inertial electrostatic confinement (IEC) fusion called the Nuclear Electromagnetic Shaping Accelerator Reactor (NESAR) that addresses all of the major failure problems with currently known methods of IEC fusion. A brief background of previous IEC methods that generate a negative potential well to accelerate ions for fusion will be reviewed and compared to the NESAR method of magnetic confinement. In addition, a direct comparison will be presented between the NESAR and the tokamak method of fusion. The NESAR method of fusion obtains the plasma oscillation and compression capabilities of a tokamak without producing the catastrophic magnetic reconnection disruptions that currently plague tokamaks. Since the NESAR can oscillate charged particles comparable to the tokamak, this work will briefly review the history of the tokamak, how sawtooth magnetic reconnection occurs, and how the NESAR precludes the occurrence of magnetic reconnection. This work will also review the beginnings of a novel unified field theory that has obtained interest from the Defense Advanced Research Projects Agency (DARPA). This unified field theory is based upon the trajectory of charged particle movements within the NESAR, which is the only concept of magnetic confinement in the world that may allow charge particles to collectively interact relatively to a solitary location. Due to this possible capability, the confined charged particles have the potential to experience curved trajectories; allowing for the effects of curvature deviation to be placed upon the charged particle within the magnetic confines of the NESAR. If charged particles can experience curvature deviation then deviated acceleration is generated; allowing the electromagnet field to be propelled to a higher spatial dimension that could influence spacetime. Finally, this work will review another theory that explains how magnetic pole reversals are observed by the National Aeronautics and Space Administration’s (NASA) coiled magnetic field detectors. This theory requires little to no postulations to be framed and it is purely based upon the trajectory of charged particles within the NESAR, Michael Faraday’s law of induction, and experimental observations of rotating plasmas.

In this paper we show the results of investigating the presence of organochlorine pesticides in honey and pollen samples from managed colonies of the honey bee, Apis mellifera L. and of the stingless bee Scaptotrigona Mexicana Guérin. We found that 88.44% and 93.33% of honey samples, and 22.22% and 100% of pollen samples of S. mexicana and A. mellifera, respectively, resulted positive to at least one organochlorine. The most abundant pesticides were DDE, DDT, Endrin and heptaclor. Despite the low foraging range of S. mexicana the number of pesticides detected in the honey samples was similar to that of A. mellifera. Paradoxically we a found a small number of organochlorines in pollen samples of S. mexicana, perhaps indicating a rapid turnover of this material as compared to A. mellifera.

Capsaicin, vitamin C, carotenoids and phenolic compounds from cumari-do-Pará peppers (Capsicum chinense Jacq.) harvested from two different locations from Pará, Brazil, and at different ripening stages were extracted employing ultrasonic-assisted extraction (UAE). Edible vegetable oils from soybean (Glycine max), Brazilian nuts (Bertholettia excelsa H.B.), and palm olein were used as the extraction solvent, as an alternative to organic solvents combined with UAE. The proximate composition of the pepper extracts and vitamin C were determined through AOAC methods, while total phenolic compounds and carotenoids were assessed by UV/Vis spectrophotometry, and capsaicin, by high-performance liquid chromatography. The antioxidant activities of cumari-do-Pará extracts were evaluated by the ABTS radical scavenging and β-carotene/linoleic acid system assays. Bioactive compounds and antioxidant activity varied with harvesting location and pepper ripening stage. Soybean oil was the most effective in extracting hydrophobic molecules particularly linoleic acid, corresponding to about 60% of the total fatty acid. Carotenoids were extracted whith highest yields by all oil extracts . Oily cumari-do-Pará extracts can be used as spices in foodstuffs and as additives in pharmaceuticals and nutraceuticals. Edible vegetable oils combined with UAE are, thus, efficient for bioactive compound extraction, also comprising an environmentally friendly, safe, low-cost, and fast alternative.

The Yang-Mills conjecture addresses the fundamental nature of the strong force, one of the four fundamental forces in nature, responsible for binding quarks together to form protons, neutrons, and other hadrons. It was proposed in the early 1950s, the Yang-Mills suggests a mathematical framework for describing the behaviours of gauge fields, which are the carriers of fundamental forces. In particular, it focuses on non-abelian gauge theories, where the gauge fields themselves interact with each other. The non-abelian aspect refers to the fact that the order of operations matters when combining these gauge transformations, leading to a more intricate structure compared to abelian theories. This conjecture posits the existence and significance of certain mathematical structures, known as Yang-Mills fields, which play a crucial role in the formulation of the Standard Model of particle physics. The Standard Model describes the electromagnetic, weak, and strong nuclear forces, as well as the elementary particles that constitute matter. Despite its foundational importance, proving the Yang-Mills conjecture has proven to be a formidable challenge. The conjecture is intimately connected to the concept of mass gap, which refers to the idea that the particles involved in the strong force interactions exhibit mass, in contrast to the photon in electromagnetism, which is massless. The successful resolution of the Yang-Mills conjecture is expected to deepen our understanding of the nature of particle physics and may provide insights into the unification of fundamental forces. In this regard we hereby provide solutions to solve Yang-Mills conjecture using the method of Self Information Entanglement and Quantum Information Transport Equations to elucidate the origin of Universe from Unperceivable Information called “Avyaktham” through the emergence of perceivable information “Vyaktham”. For the first time in the world we provided an empirically verifiable solution to the origin of emergence and existence of Universe based on the methods to predict the emergence using working model of clinical Ayurveda. It is computed that the value of mass gap mentioned in Yang-Mills conjecture is around mYM = mbit ≈ 1.06×10⁻⁴¹kg.

Copper smelting has been the source of soil contamination in trace metals in Penga Penga (Lubumbashi). Residents are exposed to trace metal ingestion and planting trees is challenging in such soil conditions. Nevertheless, planting trees in former household dumps or using various types of amendments allowed the provisioning of fruits in few residences. In the perspective of scaling up the process, a survey has been conducted with the aim of assessing the effectiveness of the planting processes on the trace metal content in fruits and leaves of Mangifera indica L. and Syzygium guineense (Willd) DC. Samples were collected in residential households from Penga Penga and Kalebuka (a non-polluted suburb). The bioconcentration factor (BCF) and the safe weekly consumption (SWC) were calculated for each species. Results showed higher values of total and soluble concentrations of Cu, Pb, and Zn in the rhizosphere of the two species at Penga Penga. Metal concentrations were higher in fruits and leaves from Penga Penga with 47% of samples above FAO and WHO thresholds (vs 18.5% in Kalebuka). The BCF values were below 1 demonstrating the effectiveness of the process to reduce metal translocation to leaves and fruits. Recommendations from the SWC limited by Pb for consumption to 9 kg for mango flesh and by Cd 6.6 kg for S. guineense fruits at Penga Penga (Vs 78 and 68 kg at Kalebuka). Finally, results from this study provide interesting lessons from the scaling up and the technical itinerary of planting tree un Penga Penga.

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

Sleep is a crucial aspect of geriatric assessment for hospitalized older adults, and implementing AI-driven technology for sleep monitoring can significantly enhance the rehabilitation process. Sleepsense, an AI-driven sleep-tracking device, provides real-time data and insights, enabling healthcare professionals to tailor interventions and improve sleep quality. This study explores the perspectives of an interdisciplinary hospital team on implementing Sleepsense in geriatric hospital care. Using the Interpretive Descriptive approach, we conducted focus groups with physicians, nurses, care aides, and an activity worker. The Consolidated Framework for Implementation Research (CFIR) informed our thematic analysis to identify barriers and facilitators to implementation. Among 27 healthcare staff, predominantly female (88.89%) and Asian (74.1%) and mostly aged 30-50 years, themes emerged that Sleepsense is perceived as a timesaving and data-driven tool that enhances patient monitoring and assessment. However, barriers such as resistance to change and concerns about trusting the device for patient comfort and safety were noted, while facilitators included training and staff engagement. The CFIR framework proved useful for analyzing implementation barriers and facilitators, suggesting future research should prioritize effective strategies for interdisciplinary team support to enhance innovation adoption and patient outcomes in rehabilitation settings.

As the number of Uncrewed Aircraft Systems (UAS) operating in our National Airspace System (NAS) increases, so do UAS operations near or at an airport. The accelerating technology in Advanced Air Mobility (AAM) along with the related business opportunities will only further increase UAS operations at airports. This continued growth in new UAS technologies and applications introduces new hazards and risks to the airport environment. This proliferation of UAS highlights the importance of airports developing a robust Safety Management System (SMS) that includes specific UAS risk mitigations. To date, there is currently little empirical data regarding UAS traffic around airports. Nor is there a system to collect this data at a national level. This study attempted to gain insight into the commercial UAS operations across a broader airport population by surveying the airport manager population here in the United States. Research results found that 62% of airports are experiencing an increase in UAS operations in their surrounding airspace. This increase applies to all airspace classifications, with 67% of airports located in controlled airspace experiencing an increase in UAS operations. However, only 27% of airports have some type of UAS safety plan. Similarly, the increase in adverse UAS events near airports suggests that UAS operators may also lack robust safety plans or an understanding of the risks and regulations associated with operating near airports.

We investigate perovskite oxides from different aspects, namely their pseudoharmonic dynamical properties, their dynamical properties when strong anharmonicity exists and the intriguing functionalities arising from domain walls. Taking these viewpoints together yields a rather complex picture of this material class which was not anticipated in previous approaches. It opens pathways to novel applications and reveals the rich ground states beyond the fictitious belief in ‘simplicity of perovskites and such structures’.

The Mixture of Experts (MoE) architecture has evolved as a powerful and versatile approach for improving the performance and efficiency of deep learning models. This survey aims to provide the fundamental principles of MoE in details, a paradigm that harnesses the collective power of multiple specialized "expert" models working in concert to tackle complex tasks.Our exploration is a thorough analysis of the core components that constitute the MoE framework. We begin by dissecting the routing mechanism, a crucial element responsible for dynamically assigning input data to the most appropriate expert models. This routing process is pivotal in ensuring that each expert's specialized knowledge is optimally utilized. The survey places significant emphasis on expert specialization, a key feature that sets MoE apart from traditional architectures. We examine various strategies for developing and training specialized experts, exploring how this specialization enables MoE models to effectively handle diverse and multifaceted problems.Load balancing, another critical aspect of MoE systems, receives thorough attention. We discuss techniques for efficiently distributing computational resources among experts, ensuring optimal model performance while managing hardware constraints. This section provides insights into the delicate balance between model capacity and computational efficiency. Furthermore, we provide an in-depth discussion of the expert models themselves, examining their architectural designs, training methodologies, and how they interact within the larger MoE framework. This includes an analysis of different types of experts, from simple neural networks to more complex, task-specific architectures. The survey also navigates through diverse research avenues within the MoE landscape, highlighting recent advancements and innovative applications across various domains of machine learning. We pay particular attention to the burgeoning use of MoE in two rapidly evolving fields: computer vision and large language model (LLM) scaling. By providing this comprehensive overview, our survey aims to offer researchers and practitioners a deep understanding of MoE's capabilities, current applications, and potential future directions in the ever-evolving landscape of deep learning.The Mixture of Experts (MoE) architecture has evolved as a powerful and versatile approach for improving the performance and efficiency of deep learning models. This survey aims to provide the fundamental principles of MoE in details, a paradigm that harnesses the collective power of multiple specialized "expert" models working in concert to tackle complex tasks.Our exploration is a thorough analysis of the core components that constitute the MoE framework. We begin by dissecting the routing mechanism, a crucial element responsible for dynamically assigning input data to the most appropriate expert models. This routing process is pivotal in ensuring that each expert's specialized knowledge is optimally utilized. The survey places significant emphasis on expert specialization, a key feature that sets MoE apart from traditional architectures. We examine various strategies for developing and training specialized experts, exploring how this specialization enables MoE models to effectively handle diverse and multifaceted problems.Load balancing, another critical aspect of MoE systems, receives thorough attention. We discuss techniques for efficiently distributing computational resources among experts, ensuring optimal model performance while managing hardware constraints. This section provides insights into the delicate balance between model capacity and computational efficiency. Furthermore, we provide an in-depth discussion of the expert models themselves, examining their architectural designs, training methodologies, and how they interact within the larger MoE framework. This includes an analysis of different types of experts, from simple neural networks to more complex, task-specific architectures. The survey also navigates through diverse research avenues within the MoE landscape, highlighting recent advancements and innovative applications across various domains of machine learning. We pay particular attention to the burgeoning use of MoE in two rapidly evolving fields: computer vision and large language model (LLM) scaling. By providing this comprehensive overview, our survey aims to offer researchers and practitioners a deep understanding of MoE's capabilities, current applications, and potential future directions in the ever-evolving landscape of deep learning.

Background: Pediatric neurological disorders include neurodegenerative disease causing cognitive impairment, vision loss to mention a few. They are one of the important causes of morbidity and mortality in children with diverse etiology. Diagnosis is difficult in spite of genetic work and in only 60% of cases final diagnosis can be achieved. Case presentation: We explore three cases of pediatric neurological diseases, viz. Arthrogryposis, congenital bilateral cataract and Autism by analyzing clinical exomes. In this work, we attempted to understand rare neurological disorders in an Indian pediatric cohort using exome studies. Conclusions: We used our benchmarked CONVEX pipeline for screening consensus variants, wherein EIF2B2 was found to be inherently pathogenic. We map the association of variants and genes, disease correlation to neuroleptic malignant syndrome which is a matching phenotype to the cases.

Cassava brown streak disease (CBSD) threatens cassava production in sub-Saharan Africa despite the availability of resistant varieties since extreme environmental factors weakens plant defenses hence reduce CBSD resistance. This study examined the inheritance of CBSD in cassava populations, assessed genetic variability and identified superior sources of resistance through F1, S1 and half-sib offspring of populations derived from resistant sources. The offsprings underwent field evaluation at two distinct sites from 2019 to 2021, and the symptoms free genotypes were analyzed using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Resistance to CBSD was categorized as most resistant, resistant, most tolerant and tolerant based on symptoms and virus titer. The findings of the study indicate that the resistance to Cassava Brown Streak Disease (CBSD) is highly influenced by genotypes, F1/S1 types, and environmental conditions. The analysis of combining abilities revealed significant general combining abilities (GCA) for CBSD, cassava mosaic disease (CMD), and traits associated with yield. The heritability estimates for resistance to CBSD varied between 43.4% to 63.2% for foliar symptoms and 14.6% to 57.9% for root necrosis across locations. The inheritance pattern involved a combination of additive and recessive genes and selfed (S1) populations displayed stronger and effective resistance to the disease. There was a high prevalence of cassava brown streak virus (CBSV) and a low prevalence of Ugandan cassava brown streak virus (UCBSV). Four genotypes were identified to be highly resistant to Cassava Brown Streak Disease (CBSD) that could be used as key sources of resistance to CBSD.

This study investigates the implementation of equipment to obtain pyroligneous acid as an alternative to control aphids in mandarin cultivation on the El Arrayanal farm, Monte Olivo parish, Carchi province, Ecuador. Derived from mandarin pruning biomass using a dry distillation pilot oven, pyroligneous acid is an ecological option compared to synthetic phytosanitary products, with less impact on the environment and human health. Using a DBCA design, different concentrations of pyroligneous acid (250 ml, 500 ml, 750 ml, and 1000 ml) applied to immature shoots affected by aphids were analyzed. The 1000 ml concentration achieved 98% control of the pest. Analysis by Gas Chromatography and Mass Spectrometry (GC-MSD) and Total Polyphenols confirmed the effectiveness of pyroligneous acid. The results of the study, carried out in the research and linkage laboratories of the State University of Bolívar, Guaranda, Ecuador, demonstrated significant differences between the doses applied (p-value

The purpose of this disquisition is to analyze bullfighting, its advances and setbacks at a global and local level in terms of animal law. It was developed as a descriptive documentary research with a non-experimental design, using the observation and interpretation of documents related to the subject, from the global level, to the local, the national, specific to the regions and communities, being interpreted through the hermeneutic method. In the analysis, results were reached such as: every day more countries are willing to assume that bulls, because they are living beings that feel, are being attended to from the legal and the ethical, propitiating changes in the way of thinking of people in terms of wanting to consider bullfighting, a sport, art and hobby considered cultural heritage of many countries. For this reason, different actions have been generated from surveys, to define the acceptance or not of these events. It is concluded that there are important advances in this regard, as bullfighting is being prohibited in different parts of the world, taking into account the protection that protects animals, but the laws do not establish specific prohibition in this regard worldwide.

The objective of this research was to analyze the evolution and trend of the generation gap and nursing education from 1968 to 2021 through bibliometric indicators. The method used is a bibliometric, descriptive and retrospective study of documents in Scopus, with descriptors “Nursing educat*”, “generation* and the Boolean operator “AND”, N= 653 web documents from 1968 to 2021, and filters of the type bib, csv. The search was carried out on October 9, 2021, using the Bibliometrix R Package software and the Biblioshiny tool. The Results indicate high scientific production in 2020 (54 articles disclosed). This study demonstrates patterns and lines of research in nursing education, such as educational models, interpersonal relationships, and organizational innovation.

This study evaluates the comprehensive biological activities of anthocyanins isolated from Andean blueberry (Vaccinium floribundum Kunth) and Andean blackberry (Rubus glaucus Benth), focusing on their antimicrobial, antioxidant, antitumoral, anti-inflammatory, and hemolytic properties. Chemical characterization revealed significant anthocyanin content with complex mass spectrometric profiles indicating diverse glycosylation patterns, which might influence their bioactivity. The antimicrobial assays demonstrated that the extracts were particularly effective against Gram-positive bacteria, with minimal inhibitory concentrations (MICs) as low as 1 mg/mL for Rubus glaucus, indicating strong potential for therapeutic use. The berries' antioxidant capacity was assessed and found to be substantial, though slightly lower than that of ascorbic acid. Furthermore, the extracts exhibited notable antitumoral activities in various cancer cell lines, showing promise as adjunctive or preventative treatments against cancer. The anti-inflammatory effects were confirmed by inhibiting nitric oxide production in macrophage cells, highlighting their potential in managing inflammatory diseases. Regarding hemolytic activity, Rubus glaucus displayed dose-dependent hemolytic activity due to anthocyanins and phenolics, while Vaccinium floribundum showed no significant hemolytic activity, confirming its safety. These findings suggest that anthocyanins from Andean berries possess potent biological activities that could be harnessed for multiple health benefits in pharmaceutical and nutraceutical applications. Further studies are warranted to isolate specific bioactive compounds and explore their synergistic effects in clinical and real-world scenarios.

The search for active cellulolytic consortia among soil microorganisms is of significant applied interest, while the dynamics of the formation of such communities remain insufficiently studied. To gain insight into the formation of an active cellulolytic community, the experiment was designed to study the colonization of a sterile substrate (cellulose) by microorganisms from two soil types: sod-podzolic and chernozem. To achieve this, the substrate was placed in the soil and incubated for six months. To assess microbiome dynamics, the experiment employed sequencing of 16S rRNA and ITS2 amplicon libraries at four-time points. It was demonstrated that from the second month of the experiment, the prokaryotic component of the communities reached a state of stability, with a community composition that was specific to each soil type. The results demonstrated that there was no relationship between changes in community diversity and soil respiration. There also was no significant shift in community diversity throughout the chronosequence. Furthermore, the taxonomic composition of the community shifted towards a decrease in the proportion of Proteobacteria and an increase in representatives of the Bacteroidota, Bacillota, and Verrucomicrobiota phyla. The network analysis of the community demonstrated that, in contrast to sod-podzolic soil, chernozem is distinguished by a higher modularity, with the formation of taxon-specific groups of microorganisms at each stage of the chronoseries. These differences are attributed to alterations in the eukaryotic component of the community, particularly in the prevalence of nematodes and predatory fungi, which in turn influenced the cellulolytic community.

The growing deforestation of tropical forests requires the implementation of restoration actions capable of assisting the recovery of biodiversity and functioning of these ecosystems. This research aimed to identify the environmental factors that influence woody plant recruitment abundance and diversity in an Andean forest restoration project in Medellin (Colombia). Data from all individuals taller than 80 cm was collected in 22 plots of 200 m2. The environmental factors selected were edaphic variables, plantation structure, slope, elevation, prior land use and landscape forest cover. A generalized linear model was adjusted for recruitment density, and linear mixed models were built for recruited species richness, diversity and dominance. Woody plant recruitment attributes in our study area were similar to a typical secondary succession in an Andean forest, but planted trees contributed little to these attributes. While recruitment density was affected by slope, canopy closure and landscape forest cover, recruitment diversity was influenced by physical (bulk density) and chemical (pH, aluminum, CEC) edaphic factors, planted trees diversity (species richness and composition), canopy closure and mortality rate of planted trees. We conclude that a good development of planted trees enhances both recruitment attributes, indicating a synergy between active restoration and passive regeneration processes.

Electromagnetic interference (EMI) generated by switching operations within high voltage DC (HVDC) converter stations is an issue that has been addressed by CIGRE and methods to manage EMI should be considered in the design phase using electromagnetic modeling techniques. It is shown that method of moments-based techniques that have been used in many previous studies may not be sufficient. Here, the finite-difference time-domain method is used to study the properties of single switching events using a realistic model of an HVDC converter station with special emphasis on determining the impact of the valve hall on shielding EMI. It is shown that the valve hall does not confine high frequency electromagnetic fields to the valve hall; rather it delays them from exiting through bushings in the wall. Further, it is shown that incorporating electromagnetic absorbing material into the valve hall design can significantly reduce EMI outside the converter station.

The utilization of black mulberry fruit as a precursor for C-dot synthesis represents a novel ap-proach to biosynthesizing C-dots. Through the implementation of a hydrothermal autoclave, we successfully produced C-dots using the fruit extract. This environmentally conscious and sustain-able method of synthesis presents a promising avenue for C-dot production. Our findings demon-strate the remarkable photocatalytic activity of the C-dots, as evidenced by their effective degra-dation of pollutants under visible light irradiation. This discovery holds significant implications for addressing water contamination issues and promoting environmental remediation efforts. Fur-thermore, we conducted a thorough investigation to determine the optimal doping concentration of C-dots, ultimately identifying 0.2 M as the ideal concentration. At this specific concentration, the photo catalytic degradation of pollutants reached an impressive rate of 95.8%. The enhanced photocatalytic activity can be attributed to the increased electron trapping resulting from the presence of additional surface sites and the absorption of different wavelengths of light. In sum-mary, this research contributes to the sustainable synthesis of carbon dots using black mulberry fruits as a precursor, while also providing a comprehensive analysis of their optical and photo-catalytic properties.

This qualitative research explores the role of digital transformation in procurement through insights gathered from interviews with industry leaders. Digital technologies such as Robotic Process Automation (RPA), Big Data Analytics, Artificial Intelligence (AI), and Blockchain are examined for their impact on operational efficiency, strategic procurement management, supplier relationships, and sustainability practices. Findings reveal that these technologies streamline processes, enhance decision-making capabilities, and improve transparency, thereby enabling organizations to achieve greater agility and competitive advantage. Strategic factors including leadership commitment, strategic investments, and digital skills development emerge as crucial for navigating challenges such as organizational resistance, data security, and integration complexities. The study underscores the transformative potential of digital transformation in procurement, emphasizing its role in driving innovation, fostering sustainability, and aligning procurement practices with broader organizational goals. Looking forward, the research suggests that organizations must continue to innovate and adapt to technological advancements to maintain resilience and leadership in a digital economy. By integrating digital strategies effectively, organizations can enhance operational efficiencies, strengthen supplier relationships, and promote ethical business practices, ultimately positioning themselves for sustained success.

This study investigates how organizations adapt their procurement practices in response to supply chain disruptions, aiming to enhance resilience and ensure operational continuity. Through qualitative research involving interviews with procurement professionals and industry experts, the study identifies key adaptive strategies employed by organizations, including supplier diversification, enhanced inventory management, digital transformation, supplier collaboration, and contingency planning. These strategies are explored in depth, highlighting their implementation challenges and the outcomes achieved. Despite facing obstacles such as financial constraints, technological barriers, and supplier resistance, organizations have demonstrated a proactive approach in leveraging these strategies to mitigate risks and improve supply chain resilience. The findings reveal that adaptive procurement strategies have led to significant outcomes, including strengthened supplier relationships, increased operational efficiency, better risk management, and competitive advantage. These outcomes underscore the strategic importance of agility, technological integration, collaborative partnerships, and effective leadership in responding to disruptions and maintaining competitiveness. The study also discusses implications for practice and policy, emphasizing the need for continued investment in technology, collaboration, and resilience-building initiatives across supply chains. Overall, this research contributes to the understanding of how organizations can adapt and innovate in the face of dynamic supply chain challenges, providing insights that can guide future research and inform strategic decision-making in procurement and supply chain management.

To accurately determine the refractive error of the eye, sufficient relaxation of eye accommodation is essential, either through the fogging technique or pharmacological cycloplegia. This study aimed to evaluate the clinical information revealed after cycloplegia and assess how age and non-cycloplegic refractive status influence the classification of eye refractive error. We analyzed the records of 472 non-population-based subjects aged 3–28 years (mean ± SD: 9.1 ± 4.6) who attended a private ophthalmology practice from January 2018 to December 2020. Cycloplegia was induced with one drop of cyclopentolate 1% in each eye, and refraction was measured 30 ± 5 min later using an objective autorefractometer. The average spherical equivalent (SE) difference (mean ± SD) induced by cycloplegia was 0.72 ± 0.73 D, with the highest difference observed in the 3-5 years age group (1.18 ± 0.85 D). Gender had no significant effect on the SE values before or after cycloplegia (p &gt; 0.05). Cycloplegia caused a hyperopic refractive shift in 83% of participants, no shift in 12%, and a myopic refractive shift in 6%. This study highlights the importance of cycloplegia use in children and young adults.

Industrial buildings have numerous energy-losing equipment, such as engines, ovens, boilers, and heat exchangers. Energy losses are related to inefficient energy use and lousy work conditions for the people inside the buildings. This work is devoted to the recovery of lost energy from industrial buildings. Firstly, the residual energy of the building is extracted to be used to warm water. Consequently, the work conditions of the people inside industrial buildings can be improved by maintaining the adequate temperature. The recovery energy is done by the multipurpose heat pump system (HP system). The working fluid used in the HP system is R134a, which is a traditional and cheap working fluid. The thermophysical properties of R134a are obtained through the PC-SAFT equation of state. This work presents a performance mapping based on the intercepted areas framework to evaluate which working conditions are the optimal operating variables. The latter depends on several key parameters, such as compressor work, heat delivery, heat absorbed, and exergetic efficiency. The results show that the optimal work conditions are found at different condenser and evaporator temperatures, and that may be limited by what the designer considers a good performance of the heat pump system.

- Early and accurate detection of pneumonia from chest X-ray images is crucial for timely treatment and patient care. In study presents a robust computational framework leveraging the CheXnet algorithm, a deep learning model, to identify pneumonia from chest X-rays. Developed a neural network architecture trained on a substantial dataset of chest X- ray images labeled as 'Normal' and 'Pneumonia'. The user- friendly interface of the system allows for seamless uploading of images, with the model subsequently providing predictions, a confusion matrix, accuracy metrics, and layer activations visualizations. The algorithm's performance was rigorously evaluated, with a confusion matrix indicating a high number of true positives and true negatives. Specifically, the model detected pneumonia with an accuracy of 92.47%, as shown by the results displayed in the system's interface. The precision, recall, and F1-score for pneumonia detection were 0.90, 0.96, and 0.93 respectively, with the overall system achieving an accuracy of 0.91 across the test set of 624 images. Visualizations of the neural network layers reveal the complex feature mappings the model uses to differentiate between normal and pathological findings. These insights could be vital for enhancing the interpretability of deep learning models in medical diagnostics. The Results indicate that the CheXnet-based neural network is a promising tool for automating pneumonia detection in clinical settings, which can assist radiologists in the diagnostic process and potentially improve patient outcomes through earlier intervention.

Human papillomavirus (HPV), a DNA virus, causes one the most common sexually transmitted infections (STI), spreading through direct sexual contact to the anogenital and oropharyngeal regions. Although most infected individuals may be asymptomatic and naturally undergo viral clearance, in some individuals HPV causes carcinogenesis of the infected epithelia. HPV now accounts for over 70% of oropharyngeal carcinomas (OPC). More than 90% of these OPC are associated with HPV 16, one of the 14 high-risk subtypes. In recent years, HPV positive (HPV+) OPC has been one of the most rapidly rising cancers, by new cancer incidence rates, especially among men. The HPV driven OPCs present some unique infection driven cellular and molecular features, constituting distinct preventive, therapeutic and prognostic strategies, in contrast to HPV negative (HPV-) OPC. In this manuscript, we drive through the role of HPV, from a sexually transmitted infection to malignancy transformation landscape, while parsing through the significant immune response environment. In this comprehensive review we collate key literature around transmission and epidemiology of HPV, while addressing the current state of clinical management, diagnosis, prevention and screening strategies, that can help shed light on this critical area.

Terrestrial orchid tubers are an important source of food in some parts of Africa and are traditionally included in the diets of most rural communities in Malawi. However, there is limited information on the nutritional and phytochemical content of the Malawian orchids to substantiate their traditional use. The present study evaluates the nutritional and phytochemical variation of four orchid species: Disa zombica, Satyrium buchananii, Satyrium carsonii, and Satyrium trinerve, collected from the same ecological zone of Malawi. The proximate content, minerals, phytochemicals, and functional properties were analysed using official procedures. Protein ranged from 2.19% to 4.65%, whereas carbohydrate ranged from 65.24% to 80.22%, with S. carsonii and S. trinerve registering the highest protein and carbohydrate contents, respectively. Iron and potassium were highest in D. zombica, while sodium and calcium were highest in S. buchananii. The total phenolics ranged from 228.56 to 500.00 mg GAE/100 g, with D. zombica registering the highest. The water absorption capacity ranged from 4.10 to 10.88 g/g. Albeit variable levels, the study provides evidence that orchid species contain essential nutrients and phytochemicals important for human nutrition and health. Furthermore, the functional properties can be utilised in the development of food products, such as baked products.

Kyrgyzstan, a landlocked nation in Central Asia, is characterized by its rugged mountainous terrain, which covers approximately 90% of its land area. This unique geography poses specific challenges related to climate vulnerability. To address these challenges, we propose a comprehensive approach that involves gathering meteorological data and making it accessible to decision-makers. By leveraging LoRaWAN communication technology, which efficiently transmits sparse and low-speed data over long distances while minimizing power consumption, we can enhance climate resilience. The Internet Society Kyrgyz Chapter, in collaboration with the International Centre for Theoretical Physics (ICTP) and the Central Asia Institute for Applied Geosciences (CAIAG), has initiated the installation of meteorological sensors and disaster mitigation devices, including river water level sensors, terrain moisture sensors, and tilt detectors. These sensors collect critical data, which is stored within the country on an ad hoc server. Stakeholders can access this data according to their specific requirements. This paper outlines the criteria for selecting the deployed equipment and provides details on the installation process at pilot sites, along with the challenges encountered during project execution.

Ultrasound (US) scans of the inferior vena cava (IVC) provide useful information on the volume status of a patient. However, their investigation is user-dependent and prone to measurement errors. An important technical problem is the objective difficulty in studying a very compliant blood vessel like IVC, which makes large respirophasic movements and shows a complicated three dimensional geometry. Using bi-dimensional (2D) B-mode views either in long or short axis has improved the characterization of IVC dynamics compared to a measurement along a single direction (M-mode). However, specific movements of the IVC can challenge also the information provided by these 2D sections. Thus, these two orthogonal views, provided by an US system in X-plane, are here integrated by an innovative method. It is tested on simulated videos of the IVC performing complicated movements, that are compensated by the new method, overcoming the biased measurements provided by 2D scans. The method is then applied on example experimental data.

This article explores the pressing need for a paradigm shift in economics, challenging the dominance of classical economic theories and models that have long held sway. We delve into the limitations of traditional economic paradigms, which often rely on unrealistic assumptions and fail to capture the complexities of human behavior and the modern global economy. Drawing from insights in behavioral economics, environmental economics, and complexity theory, we argue for a more nuanced and multidisciplinary approach to economic analysis. Our discussion addresses the challenges of breaking away from deeply entrenched academic norms and the resistance to change within the economics profession. We highlight strategies for individuals and groups to advocate for the incorporation of modern economic theories in education and research. By fostering interdisciplinary collaboration, encouraging critical thinking, and engaging with policymakers and the public, we aim to catalyze a shift toward economics that is better equipped to address the intricate challenges of the 21st century. This article serves as a call to action for economists and educators alike to embrace a more dynamic and responsive approach to understanding human behavior and decision-making in the modern world.

This qualitative research explores the intricate relationship between cultural influences on supply chain practices and their implications for marketing strategies. Cultural dimensions such as individualism versus collectivism, uncertainty avoidance, and contextuality significantly shape decision-making processes, risk management strategies, and relationship dynamics within global supply chains. Through semi-structured interviews with supply chain managers, marketing executives, and cultural experts across diverse industries and regions, this study investigates how cultural values impact supply chain operations and consumer engagement strategies. Key findings highlight that collectivist cultures prioritize consensus-building and long-term relationships, fostering trust and collaboration among supply chain partners. In contrast, individualist cultures emphasize efficiency and accountability but may face challenges in relationship building. Risk management practices vary with cultural orientations towards uncertainty, influencing the adoption of structured versus flexible approaches to mitigate disruptions. In terms of marketing implications, the study underscores the importance of cultural sensitivity in crafting effective strategies. High-context cultures require marketing messages that resonate emotionally through implicit communication and cultural symbolism, while low-context cultures prefer clear, direct messaging focusing on product benefits. The study concludes by advocating for cultural competence as a strategic imperative for global businesses, enabling them to leverage cultural diversity for innovation and competitive advantage. It emphasizes the need for continuous adaptation to cultural nuances and market dynamics to foster inclusive collaboration and achieve sustainable growth in a globalized economy.

Discussions and practices on sustainability are actively underway around the world. In this social context, this study conceptualized ESG management values ​​focused on sports organizations, especially professional sports clubs in Korea. Utilizing Q Methodology, suitable for research on individual's subjectivity, we explored ESG management values accepted by consumers of Korean professional sports. As a result, the ESG management values were confirmed as follows: ‘Type I: Trust-Management Emphasis,’ ‘Type II: Local-Community Emphasis,’ and ‘Type III: Safety-Respect Culture Emphasis.’ While each of the three types accepted governance, social responsibility, safety, and respect culture as their main values, they tended to deny environment-related values. Accordingly, this study provided two discussions: ‘Professional sports consumers’ low awareness of the environment’ and ‘Reinterpretation of environmental values ​​among the ESG management values ​​of professional sports clubs’. In conclusion, the three types are significant in that (1) they well reflect the social and cultural context of Korean professional sports and consumers' perceptions, and (2) they provide a new perspective on the ESG management value of professional sports teams.

This paper provides a structured and practical roadmap for practitioners to integrate Learning from Demonstration (LfD) into manufacturing tasks, with a specific focus on industrial manipulators. Motivated by the paradigm shift from mass production to mass customization, it is crucial to have an easy-to-follow roadmap for practitioners with moderate expertise, to transform existing robotic processes to customizable LfD-based solutions. To realize this transformation, we devise the key questions of "What to Demonstrate", "How to Demonstrate", "How to Learn", and "How to Refine". To follow through these questions, our comprehensive guide offers a questionnaire-style approach, highlighting key steps from problem definition to solution refinement. The paper equips both researchers and industry professionals with actionable insights to deploy LfD-based solutions effectively. By tailoring the refinement criteria to manufacturing settings, the paper addresses related challenges and strategies for enhancing LfD performance in manufacturing contexts.

Macroalgae seaweeds such as Ulva lactuca and Gracilaria verrucosa cause problems on the Northern Coast of the Italian Adriatic Sea because their overabundance hinders the growth of cultivated clams, Rudatapes philippinarum. This study focused on the green synthesis of CuO nanoparticles from U. lactuca and G. verrucosa. The biosynthesized CuO NPs were successfully characterized using FTIR, XRD, HRTEM/EDX, and zeta potential. Nanoparticles from the two different algae species are essentially identical, with the same physical characteristics and almost the same antimicrobial activities. We have not investigated the cause of this identity, but it seems likely to arise from the reaction of Cu with the same algae metabolites in both species. The study demonstrates that it is possible to obtain useful products from these macroalgae through a green synthesis approach and that they should be considered as not just a cause of environmental and economic damage but also as a potential source of income.

Asparagus shoots are worldwide consumed, although most of such species have a restricted range, and several taxa still remain unstudied. In this work, a total of four taxa from different locations were scrutinized and compared with cultivated A. officinalis. All shoots were screened for saponins by LC-MS, and in vitro antiproliferative activities against the HT-29 colorectal cancer cell line (by MTT assay). The total saponins (TS) contained in the crude extracts ranged from 710.0 (A. officinalis) to 1258.6 mg/100 g dw (A. acutifolius). It stands out the richness of compounds detected in this work: a total of 47 saponins have been detected and quantified in the edible parts (shoots) of 5 taxa of Asparagus. The structure of all the saponins found present skeletons of the furostane and spirostane type. In turn, the structures with a furostane skeleton are divided into unsaturated and dioxygenated, both in the 20-22 position. The sum of dioscin and derivatives varied largely along the studied taxa. It reached the following percentages of TS: 27.11 (A. officinalis), 18.96 (A. aphyllus), 5.37 (A. acutifolius), and 0.59 (A. albus), while in A. horridus such compound remains undetected. Aspachiosde A, D, and M varied largely among samples, while a total of seven aspaspirostanosides were characterized in the analyzed species. Hierarchical cluster analysis of the saponin profiles clearly separated the various taxa and demonstrated that the taxonomic position is more important than the place from which the samples were acquired. Thus, saponin profiles have chemotaxonomic significance in Asparagus taxa. The MTT assay showed dose- and time-dependent inhibitory effects of several saponins extracts on HT-29 cancer cells, standing out the cell growth inhibition exercised by A. albus and A. acutifolius (GI50 of 125 and 175 µg/mL). This work constitutes a whole approach to evaluate the saponins from shoots of different Asparagus taxa and provide arguments for use them as functional foods.

The spread of micro- (MPs) and nanoplastics (NPs) in the environment has become a significant environmental concern, necessitating effective removal strategies. In this comprehensive scientific review, we examine the use of magnetic nanoparticles (MNPs) as a promising technology for the removal of MPs and NPs from water. We first describe the issue of MPs and NPs and their impact on the environment and human health. Then the fundamental principles of using MNPs for the removal of these pollutants will be presented, emphasizing that MNPs enable selective binding and separation of MPs and NPs from water sources. Furthermore, we provide a short summary of various types of MNPs that have proven effective in the removal of MPs and NPs. These include ferromagnetic nanoparticles, MNPs coated with organic polymers, as well as nanocomposites and magnetic nanostructures. We also review their properties, such as magnetic saturation, size, shape, surface functionalization and stability, and their influence on removal efficiency. Next, we describe different methods of utilizing MNPs for the removal of MPs and NPs. We discuss their advantages, limitations, and potential for further development in detail. In the final part of the review, we provide an overview of existing studies and results demonstrating the effectiveness of using MNPs for the removal of MPs and NPs from water. We also address challenges that need to be overcome, such as nanoparticle optimization, process scalability, and the removal and recycling of nanoparticles after the completion of the process. This comprehensive scientific review offers an extensive insight into the use of MNPs for the removal of MPs and NPs from water. With improved understanding and the development of advanced materials and methods, this technology can play a crucial role in addressing the issue of MPs and NPs and preserving a clean and healthy environment.

Supply chain risk management (SCRM) is a critical aspect of contemporary business operations, necessitated by the complex and interconnected nature of global supply chains. This qualitative research delves into the intricacies of SCRM through in-depth interviews with industry experts, aiming to unravel the multifaceted nature of supply chain risks and the strategies employed for mitigation. Key themes emerged, including the diverse sources of risks encompassing operational, financial, environmental, and geopolitical factors, highlighting the need for a comprehensive approach to risk management. Challenges such as limited visibility, resource constraints, and organizational silos were identified, underscoring the importance of addressing these barriers to enhance SCRM effectiveness. Strategies for risk mitigation encompassed technological investments for enhanced visibility and predictive capabilities, collaboration and information sharing among supply chain partners, and the integration of sustainability principles into risk management practices. Leadership, organizational culture, and continuous learning emerged as critical factors in driving effective SCRM practices, emphasizing the need for proactive and adaptable approaches to navigate evolving risks. Overall, this study contributes to the existing body of knowledge on SCRM by providing valuable insights for practitioners and academics, and underscores the importance of holistic and proactive approaches to enhance supply chain resilience and agility in today's dynamic business environment.

The construction industry, a vital sector of the global economy, is projected to grow significantly over the next 15 years. Despite its importance, this industry struggles with inefficiency, high costs, prolonged timelines, and substantial ecological impacts. These challenges have led governments to advocate for Building Information Modeling (BIM) to enhance Efficiency and sustainability through comprehensive digital representations of physical and functional characteristics. The effective integration of BIM technology hinges on the active participation of industry providers, raising the question of how these providers can positively contribute to improving BIM dimen-sions. This study investigates the potential of coopetition networks within the Portuguese Orna-mental Stone industries (OS-PT) to address this challenge. Coopetition networks, which blend competition and cooperation, foster collaborative networks among companies to enhance their re-sponse to digital supply chains. The research employs an Experimental Pilot Network facilitated by an Industrial Internet of Things (IIoT) artefact to assess the benefits of coopetition networks. The findings demonstrate that transitioning from current practices (CB.P) to coopetition network practices (CN.P) significantly improves operational Efficiency, labour productivity, and sustaina-bility. Specifically, the transition resulted in a 15.6% increase in on-time delivery performance, a 27.38% improvement in labour productivity, and a 21.8% reduction in CO₂ emissions per part produced. These improvements align with Sustainable Development Goals (SDGs) 8, 9, 11, and 13, highlighting the strategic value of coopetition in driving innovation and sustainability in the construction industry. Future research should explore the scalability of these findings across different sectors and further refine methodologies to maximize the benefits of coopetition net-works.

Background: Population studies have shown that prehypertension is associated with adverse cardiometabolic risk profile even among apparently healthy populations. Although associations between serum triglyceride (TG) concentrations and the risk of atherosclerotic cardiovascular disease have been reported, there are lack of data on the association of hypertriglyceridemia with cardiovascular risk (CVR) in a low risk prehypertensive population. Aim: Our aim was to analyze the cardiorenometabolic characteristics of prehypertensives (PHT) compared to normotensives (NT) and untreated hypertensives (HT) and its associations with CVR. Materials and methods: In our cross-sectional study we included 323 apparently healthy untreated subjects 18-45 years who underwent basic anthropometric and standardized blood pressure measurement, fasting blood sampling, spot urine collection and transthoracic echocardiogram. Results: Higher BMI, waist circumference, HOMA-IR, LDL-cholesterol, TG, uric acid and LVMI contribute to higher CVR in PHT compared to true NT (p

Utilizing lignocellulosic biosourced platforms, we synthesized novel cyanostilbene (CS) deriva-tives featuring the 3,4-dimethoxyphenyl moiety. These derivatives were investigated for their emission properties in both solution and solid states. The two simple CS derivatives exhibit very weak luminescence in solution but significant luminescence in the solid state, indicating distinct Aggregation-Induced Emission (AIE) characteristic. Furthermore, combining these two CS units, without conjugation and with quasi perpendicular orientation, results in Dual-State Emission (DSE) fluorophore showing luminescence both in solution and solid states. X-ray crys-tallography studies on the solid-state compounds reveal a structure-emission relationship, demonstrating that the colour emission correlates with the conformations adopted by the mol-ecules in the solid state, which influence the type of stacking.

In an era marked by swift technological progress, the pivotal role of Artificial Intelligence (AI) is increasingly evident across various sectors, including local governments. These governmental bodies are progressively leveraging AI technologies to enhance service delivery to their communities, ranging from simple task automation to more complicated engineering endeavours. While more and more local governments are adopting AI, it is imperative to understand the functions, implications, and consequences of AI. Despite the growing importance of this domain, a significant gap persists within the scholarly discourse. This study strives to bridge this void by exploring the applications of AI technologies within the context of local government service provision and using this inquiry to generate lessons and best practices for similar smart city initiatives. Through a comprehensive grey literature review, we analysed 262 real-world AI implementations across 170 local governments worldwide. The findings underscore several key points: (a) There has been a consistent upward trajectory in the adoption of AI by local governments over the last decade; (b) Local governments from China, the US, and the UK are at the forefront of AI adoption; (c) Among local government AI technologies, Natural Language Processing and Robotic Process Automation emerge as the most prevalent ones; (d) Local governments primarily deploy AI across 28 distinct services; (e) Information management, back-office work, and transportation and traffic management are leading domains in terms of AI adoption. This study enriches the extant body of knowledge by providing an overview of existing AI applications within the sphere of local governance. It offers insights for smart city policymakers and decision-makers considering the adoption, expansion, or refinement of AI technologies in urban service provision. Additionally, it underscores the importance of using these insights to guide the successful integration and optimisation of AI in future smart city projects, ensuring they meet the evolving needs of communities.

SARS-CoV-2 can induce vascular dysfunction and thrombotic events in patients with severe COVID-19; however, the cellular and molecular mechanisms behind these effects remain largely unknown. In this study, we used a combination of experimental and in silico approaches to explore the mechanisms behind the vascular and thrombotic events in COVID-19. Single-cell RNA-sequencing data from patients with COVID-19 and healthy subjects were obtained from the publicly available Gene Expression Omnibus (GEO) repository. In addition, HUVECs were treated with inactivated protein C before exposure to SARS-CoV-2 infection or a severe COVID-19 serum. An RT-qPCR array containing 84 related genes was used, and the candidate genes obtained were evaluated. Activated protein C levels were measured using an ELISA kit. We identified at the single-cell level the expression of several pro-inflammatory and pro-coagulation genes in endothelial cells from the patients with COVID-19. Furthermore, we demonstrated that exposure to SARS-CoV-2 promoted transcriptional changes in HUVECs that were partly reversed by the activated protein C pretreatment. We also observed that the serum of severe COVID-19 had a significant amount of activated protein C that could protect endothelial cells from serum-induced activation. In conclusion, activated protein C protects endothelial cells from pro-inflammatory and pro-coagulant effects during exposure to the SARS-CoV-2 virus.

This paper aims to assess whether the financial performance of Portuguese companies that publish sustainability reports (SR) differs from the financial performance of companies that do not publish SR. We use two methodological procedures. First, we conducted a univariate analysis to test the differences in the financial performance according to the disclosure of SR. Second, we conducted a multivariate analysis using a multiple linear regression that explains financial performance by the disclosure of SR, as well as control variables such as sector, size, leverage, growth, and liquidity. Findings indicate that financial performance of companies that disclose SR does not significantly differ from the financial performance of companies that do not disclose SR. The results are robust to both methodological procedures, as well as to the sample split by sectors.

The Parecis Basin is one of the largest intracratonic basins in Brazil. Despite its considerable size, the basin has yet to be extensively explored, with only five wildcat wells drilled for hydrocarbons. So far, no commercial discoveries have been announced. Regional studies have suggested Paleozoic sedimentation, while recent studies indicate a Neoproterozoic fill. However, no tectonic model accurately describes the basin’s development, and no detailed structural map for the entire basin has been published. The present work presents a new detailed structural map of the Parecis Basin based on a four-step interpretation workflow integrating seismic and gravimetric data. The first step includes converting the public 2D seismic lines to the depth domain. The second step is estimating the residual Bouguer anomaly, where the computed residual anomalies should relate to the basin’s tectonic features. The third step comprises the 2D forward modeling of the gravimetric anomalies using the 2D seismic interpretation as a constraint. The final step compiled all the interpreted features into our new structural map. This map reveals the top of the basement, forming a complex framework of horsts and grabens. Normal faults define the main structural style in the basin. Further, we could recognize thick, high-density bodies embedded in the crystalline basement. These bodies consist of Orosian-Calimian (1.8-1.6 Ga) mafic and ultramafic rocks, which may be a potential source for hydrogen exploration in the basin. Subsequent geophysical and geochemical surveys will assess the hydrogen potential in the area.

Nowadays circular economy trend drives researchers in the recovery of various bioactive compounds from agri-food by-products. Enzyme-assisted extraction (EAE) is shown as an innovative green technology for the effective extraction of various phytochemicals from agri-food section by-products, therefore this study aimed to evaluate the application of EAE as green technology to obtain extracts from olive leaves (Olea europaea) for potential industrial production. EAE was conducted under various enzyme dose combinations, and incubation time (120 min). Obtained extracts were characterized in terms of total polyphenols (TP) and Total Antioxidant Activity (AA). Firstly, the enzyme synergistic effect in enzymatic extraction of polyphenols was evaluated. TP optimal extraction conditions (468.19 mg GAE/L) were achieved after EAE (50-50%) and for AA (69.85 AA%). According to the above results, a second experimental part occurred for the incubation time (min.) and enzyme dose (mL) of optimal extraction conditions of olive leaves. Results indicated EAE as an excellent choice for green extraction of polyphenols from the olive leaves.

The extraction of cell cultures from fresh tissue is a process that requires significant computa-tional resources and is associated with substantial overheads. The objective of our research is to de-vise a rapid, straightforward, and efficient technique for the cultivation of neuronal cells derived from frozen biological material. We utilized freshly isolated hippocampus and cerebral cortex tissue from rats, in addition to whole brain tissue. This tissue underwent digestion and processing to yield a cellular suspension. This suspension was subsequently cryopreserved using a variety of cryopro-tectants: CTS™ Synth-a-Freeze™, SpermFreeze®, and a medium supplemented with 10% DMSO. CTS™ Synth-a-Freeze™ is a commercially available cryoprotectant typically employed in the preservation of cellular cultures, while the addition of 10% DMSO to the medium is a conventional technique for the cryopreservation of cells to mitigate damage. The innovative aspect of our meth-odology is the application of SpermFreeze®, a product used for the cryopreservation of sperm in in vitro clinics. We postulated that SpermFreeze® might enhance the viability and quality of the cryo-preserved neuronal cells, given the delicate and energetically demanding nature of both sperm and neuronal cells. The ultimate objective was to ascertain whether a cryoprotectant formulated for sperm could augment the post-thawing efficacy of our nervous system cells. This investigation intro-duces an innovative methodology for the optimization of neuronal cell isolation and cryopreserva-tion from animal-derived tissues.

A model of space-time is presented, whose origin is set before the appearance of any universe. It uses concepts of previous work, a central one being that the information about the laws of nature is stored locally everywhere in space such that all physical processes obey them. Since information storage is bound to matter or energy, space is assumed to consist of dark energy (DE), which thus assumes an importance far beyond its function as a stopgap for an energy deficit in our universe ( U ). The primordial state (PS) is a timeless and relatively large space of 3 dimensions described by a Wheeler DeWitt (WDW) equation, whose solution is interpreted as an arrangement of very many space quanta and possesses properties that remind of the time-honored concept of the unmoved mover. The comparison of WDW solutions belonging to different mass densities of the DE favors one in which the space quanta are mini black holes. This allows the space quanta to be imagined as mass points which are kept at a distance compatible with the quantum volume by the Pauli principle or something equivalent. Triggered by a dramatic increase in probability, the PS is followed by a time-controlled sequence of quantized expansion states (ES i ). The concomitant emergence of time occurs in a lightning huge crash, consuming almost all DE of the PS. The subsequent quantized ES i emerge from a WDW equation, novelly derived from a solution of the modified cosmic momentum equation, which classically describes an exponential space expansion (CS). The huge volme of the ES i is also used as size of the PS. Information is assumed to be geometrically stored in arrangements of space quanta similar to how genetic information is stored in DNA molecules. During the CS information must be transferred from already existing "information quanta" to new ones. This requires time, slows down the expansion and is taken into account by a friction term in the cosmological momentum equation thus modified. Since the Friedmann-Lemaître (FL) equation remains fully valid, the model is widely based on recognized equations, so that some results may be understood as interpretations.