One of the major sources of catastrophic failures and deterioration of the mechanical properties of metals such as ductility, toughness, and strength, of various engineering components during application is hydrogen embrittlement (HE). It occurs as a result of adsorption, diffusion, and interaction of hydrogen with various metal defects like dislocations, voids, grain boundaries and oxide/matrix interfaces due to its small atomic size. Over the years, extensive effort has been dedicated to understanding hydrogen embrittlement sources, effects, and mechanisms. This research aimed at assessing the tensile properties; toughness, ductility, and susceptibility to hydrogen embrittlement, of cold-finished mild steel. Steel coupons were subjected to electrochemical hydrogen charging in a carefully chosen alkaline solution over a particular time and at various charging current densities. Tensile property tests were conducted immediately post the charging process, and the results were compared with those of uncharged steel. The findings revealed a clear drop in toughness and ductility with increasing hydrogen content. Fracture surfaces were examined to determine failure mechanisms. This evaluation has enabled the prediction of the steel's ability to withstand environments with elevated hydrogen concentrations during practical applications.

Introduction: In the year 2022, 4.9 million children died worldwide before five years of age. United Nations General Assembly has set the target of bringing down under-five child mortality to 25 deaths per 1000 live births by 2030. However, the United Nations Inter-Agency Group for Child Mortality Estimation highlights, that without rapid action many low and Lower Middle-Income Countries (LMICs) will not be able to achieve this target and 35 million under-five children will die before 2030. In such a scenario understanding the determinants that bring down preventable deaths in children is important. Design: Anonymized, publicly available data from the India National Family Health Survey (NFHS-5) is collected. The sample consisted of 724,115 women in the age group of 15-49 years has been sub-grouped as urban and rural women. Data on the number of Anganwadi centers per state has been collected from the Ministry of Women and Child Development. For better analysis of data, the country is divided into regions. Union territories are grouped in these regions as per their geographical locations. Descriptive statistical analysis, correlation coefficient analysis, and linear regression analysis were done. Results: Results of the Pearson correlation indicated that there is a significantly large positive relationship between operational AWCs (%) and U5MR (r = 0.542, p < .001) whereas there is a significantly large negative relationship between women with Internet access (%) and U5MR, (r = -0.738, p < .001). For our data, the multiple regression equation for y is U5MR (per 1000 live births) = 0.77266. AWCs (%) - 0.58788. women with Internet access (%) + 53.68073. Conclusion: Compared to NFHS-4 (2015-16) U5MR has reduced in almost all states of the country. The study shows more urban women have access to the Internet as compared to rural women. Child mortality is higher in rural areas in every state as compared to urban areas. Urban women have more access to health information because of internet access which may be the reason for lesser child mortality in urban areas compared to rural areas. Internet access for women (individual level) is far more effective in bringing down U5MR if compared to the community-level approach of Daycare centers.

Background- In India, 26 million children are born every year. These Children (0-6 years) comprise 13% of the country's population. Undernutrition is fallout of malnutrition, malabsorption, and nutritional imbalance which causes problem of underweight in children. It can affect child’s brain development and other developmental milestones. Methods- We used anonymized, publicly available secondary data from the India National Family Health Survey (NFHS-5). Descriptive statistical analysis, correlation coefficient analysis, and regression analysis of the data have been done. Results- Multiple linear regression for independent variables, operational AWCs (%) and women with Internet access (%), and dependent variable underweight children per state (%) developed the model, Underweight children (%) = 37.1607 + 0.5659. operational AWCs (%) – 0.2907. women with Internet Access (%). It shows Ꞵ0= 37.1607, Ꞵ1= 0.5659, and Ꞵ2= -0.2907 as well as R squared value as 0.5709. This shows independent variables have a significant influence on the number of underweight children in the state. Results of the Pearson correlation indicated that there is a significant large positive relationship between operational AWCs (%) and the percentage of underweight children in the state, (r(34) = .58, p < .001). Whereas there is a significant large negative relationship between Internet access to women (%) and the percentage of underweight children in the state, (r(34) = .733/-0.733, p < .001). Conclusion- The study clearly shows that when compared, community daycare centers (AWCs) have a limited role in the child's nutrition, but Internet access to the mothers can be a determinant of the child's nutrition. The internet access to women can help to reduce the number of underweight children under five years and improve overall maternal and child health as well as public health.

The enzyme-linked immunosorbent assay (ELISA) coupled with surface-enhanced Raman spectroscopy (SERS) detection is a growing area of analytical chemistry emerged as a solution to a problem of sensitivity improvement. SERS-based ELISA with horseradish peroxidase as an enzymatic label, o-phenylenediamine (oPD) substrate, and 2,3-diaminophenazine (DAP) enzymatic product was one of the first examples of such systems. Surprisingly, the full potential of this long-known approach has not been revealed yet. The current study addresses a previously neglected problem of SERS detection stage performance. Using silver nanoparticles and model mixtures of oPD and DAP, the effects of pH, concentration of aggregating agent, and particle surface chloride stabilizer were extensively evaluated. At optimal mildly acidic pH of 3, 0.93 to 1 M citrate buffer, and AgNPs stabilized with 20 mM chloride, at least two orders of magnitude advantages in the detection limits of SERS over colorimetry both for DAP and HRP were demonstrated. We suppose that this improved detection system could become a useful tool for the development of SERS-based ELISA protocols.

Numerous types of oligonucleotide modifications have been developed since automated synthesis of DNA/RNA became a common instrument in the creation of synthetic oligonucleotides. Despite the growing number of types of oligonucleotide modifications under development, only a few of them, and moreover, their combinations have been studied wide enough in terms of their in-fluence on the properties of corresponding NA constructions. In the present study, a number of oligonucleotides with combinations of 3′ end lipophilic (single cholesteryl or pair of dodecyl residues) and phosphate backbone modifications were synthesized. The influence of the combi-nation of used lipophilic groups with phosphate modifications of various nature and different position on the efficiency of cell penetration was evaluated. Obtained results indicate that even a couple of phosphate modifications are able to affect a set of oligonucleotide properties in a complex manner and can remarkably change cellular uptake. These data clearly show that the strategy of using different patterns of modification combinations has great potential for the ra-tional design of oligonucleotide structures with desired predefined properties.

Crinoids (Echinodermata) exhibit unique characteristics that facilitate a wide range of symbiotic relationships with diverse organisms. Nonetheless, the comprehension of their interactions with microscopic copepod crustaceans is still in a nascent and fragmented state. Our analysis identifies 166 instances involving 35 copepod species representing in 6 families in association with 33 species of the Comatulida. The majority of these associations have been singularly reported, with their distribution covering five out of the 12 World Ocean ecoregions. A notable concentration of diversity is observed in the Central and Western Indo-Pacific regions, while documentation of Atlantic copepod-crinoid associations is markedly limited. Copepods are predominantly found in ectosymbiotic relationships, with a lesser incidence of endosymbiotic interactions. Among these, the genus Collocheres and Pseudanthessius emerge as particularly prominent, and the Comasteridae family is distinguished by its diverse copepod associations. While certain copepod families exhibit a specialization towards crinoids, others demonstrate specificity at the species level. The current scope of knowledge encompasses merely 5% of the potential crinoid host diversity, underscoring the critical need for more extensive research in this area.

Recent advancements in experimental and computational methods for RNA secondary structure detection have revealed the crucial role of RNA structural elements in diverse molecular processes within living cells. It has been demonstrated that the secondary structure of the entire viral genome is often responsible for performing crucial functions in the viral life cycle and also influences virus evolution. To investigate the role of viral RNA secondary structure, alongside experimental techniques, the use of bioinformatics tools is important for analyzing various secondary structure patterns, including hairpin loops, internal loops, multifurcations, external loops, bulges, stems, and pseudoknots. Here, we have introduced a Python package for analyzing RNA secondary structure elements in viral genomes, which includes the recognition of common secondary structure patterns, the generation of descriptive statistics for these structural elements, and the provision of their basic properties. We applied the developed package to analyze the secondary structures of complete viral genomes collected from the literature, aiming to gain insights into viral function and evolution. Both the package and the collection of secondary structures of viral genomes are available at http://github.com/KazanovLab/RNAsselem.

Aquaculture is a fast-emerging food-producing sector in which fishery production plays an im-perative socio-economic role, providing ample resources and tremendous potential worldwide. However, aquatic animals are exposed to the deterioration of the ecological environment and in-fection outbreaks, which represent significant issues nowadays. One of the reasons for these threats is the excessive use of antibiotics and synthetic drugs that have harmful impacts on the aquatic atmosphere. It is not surprising that functional biotic feeds such as probiotics, prebiotics, postbiotics, and synbiotics have been developed as natural alternatives to sustain a healthy microbial envi-ronment in aquaculture. These functional feed additives possess several beneficial characteristics, including gut microbiota modulation, immune response reinforcement, resistance to pathogenic organisms, improved growth performance, and enhanced feed utilization in aquatic animals. Nevertheless, their mechanisms in modulating the immune system and gut microbiota in aquatic animals are largely unclear. This review discusses current research advancements to fill research gaps and promote effective and healthy aquaculture production.

Major depressive disorder (MDD) is a highly prevalent, debilitating disorder with a high rate of treatment resistance. One strategy to improve treatment outcomes is to identify patient-specific, pre-intervention factors that can predict treatment success. Neurophysiological measures such as electroencephalography (EEG), which measures the brain’s electrical activity from sensors on the scalp, offer one promising approach for predicting treatment response for psychiatric illnesses, including MDD. In this study, a secondary data analysis was conducted on the publicly available Two Decades-Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) database. Specifically, hierarchical regression modeling was used to predict treatment response from baseline demographics, symptom severity, and resting-state EEG features in 119 MDD patients receiving repetitive transcranial magnetic stimulation (rTMS). Across models, both age and baseline symptom severity, assessed by the Beck’s Depression Inventory, were significant predictors of rTMS treatment response, with older individuals and more severe depression scores associated with decreased odds of a positive treatment response. EEG measures contributed predictive power to these models; however, these improvements in outcome predictability only trended towards statistical significance (p~0.07 in multiple models). These findings provide confirmation of previous demographic and clinical predictors, while pointing to EEG metrics that may provide predictive information in future studies.

The hydrodynamics of plasma formed in the interaction of 100-ns UV KrF laser pulses with foam targets with volume densities from 5 to 500 mg/cm3 was studied. Initial and dynamic transmittance at 248-nm wavelength have been measured. At intensities about 1012 W/cm2, the propagation rates of radiation through foam targets reached 80 km/s, while plasma stream velocities from both front and rear sides of targets were approximately the same ~ 75 km/s, which confirms a volumetric absorption of radiation within the target thickness and the explosive nature of the plasma formation and expansion.

As cancer remains resistant to several modes of treatment, novel therapeutics are still under active investigation to overcome treatment inefficacy in cancer. Given the high attrition rate of de novo drug discovery, drug screening, and drug repurposing have offered time- and cost-effective alternative strategies for the identification of potentially effective therapeutics. In contrast to large-scale drug screens, computational approaches for drug repurposing leverage the increasing amounts of biomedical data to predict candidate therapeutic agents prior to testing in biological models. Current studies in drug repurposing for cancer therapy prediction have increasingly focused on the prediction of combination therapies, as combination therapies have numerous advantages over monotherapies. These include increased effect from synergistic interactions, reduced toxicity from lowered drug doses, and a reduced risk of resistance due to multiple non-overlapping mechanisms of action. This review provides a summary of several classes of computational methods used for drug combination therapy prediction in cancer research, including networks, regression-based machine learning, classifier machine learning models, and deep learning approaches, with the goal of presenting current progress in the field, particularly to non-computational cancer biologists. We conclude by discussing the need for further advancements in technologies that incorporate disease mechanisms, drug characteristics, multi-omics data, and clinical considerations to generate effective patient-specific drug combinations, as holistic data integration will inevitably result in optimal targeted therapeutics for cancer.

Response of tomato and eggplant to continuous lighting (CL) and abnormal light/dark (L/D) cycles was studied to elucidate the role of the absence of the dark period in the diurnal cycle in the development of leaf injuries under CL. Four light treatments were set: 16/8 h (control), 24/0 h (CL), 6/6 h, and 24/24 h (abnormal L/D cycles). These light treatments provided average daily light integrals of 17.3, 25.9, 13.0 and 13.0 mol m-2 day-1, respectively. Results of this work have shown that in both tomato and eggplant abnormal L/D cycles caused photoinhibition and leaf injuries similar to those in CL-grown plants. Induced defense mechanisms were not strong enough to contend against oxidative stress caused by light treatments that provided plants with even smaller DLI than 16/8 h photoperiod did. Half time during abnormal L/D cycles were dark periods. Despite these facts, abnormal L/D cycles were injurious. It is concluded that photooxidative stress induced by CL can not be attributed to excessive DLI or the continuity of light itself (the absence of dark periods). Therefore, we believe that the hypothesis suggesting circadian asynchrony to be the main triggering factor of CL-induced leaf injuries is the most plausible among many others proposed.

The development of anti-pain technologies in the complex treatment of pain syndromes is one of the most urgent tasks of modern medicine. We have undertaken a placebo-controlled experimental study of the therapeutic potential of low-intensity laser radiation when applied to acupuncture points, which are directly related to the autonomic nervous system. The adaptation effect of puncture photobiomodulation on the induction of stress-mediated autonomic reactions, oxidative metabolism and microcirculation in animals during the acute phase of pain stress was revealed. The data obtained are of interest for use in the complex rehabilitation of patients with pain syndrome.

This paper uses preliminary studies of archaeological sites (burial mounds and settlements) from the Iron Age through Medieval periods (ca. 800 BCE to 1200 CE) in the Juuku Valley on the South side of Lake Issyk-Kul to model land-use across vertical mountain zones. To do so, we have established a radiometric chronology, conducted test excavations of an Iron Age settlement and a Turkic period burial, undertaken preliminary archaeobotanical research, and pedestrian surveys. Seed remains of wheat (Triticum aestivum), barley (Hordeum vulgare), broomcorn millet (Panicum milaceum) and foxtail millet (Setaria italica) and legumes were recovered in very small quantities from an Iron Age upland settlement at 2100 m asl and a Turkic period burial mound at 1934 m asl. These preliminary archaeobotanical results are compared to the Talgar Iron Age settlements on the north side of the Tian Shan Mountain range in Kazakhstan studied earlier by Robert Spengler. Small samples of faunal remains found at the Turkic period kurgan and from a profile at the upland Iron Age settlement indicate livestock herding of sheep/goats, cattle, and horses in Juuku Valley. The goal of this paper is to test the hypothesis that pastoral transhumance and agropastoralism were economic strategies used by ancient societies during the Iron Age through Medieval periods in mountain-river valley areas between 750 m to 2500 m asl. These economic strategies that combined the pasturing of sheep, goats, cattle and horses with the cultivation of cereals were adapted to the use of different vegetational zones along a vertical gradient. This paper based on preliminary research of upland sites of the Juuku Valley in Kyrgyzstan, initiates a long-term research study of four millennia of settlements that ranged from pastoral transhumance, pastoral nomadism, and combined mountain agriculture using survey data and test excavations.

The review analyzes the studies published mainly in the last 10-15 years, on the synthesis, structure, and sensor properties of semiconductor nanocomposites. Particular attention is paid to the interaction between nanoparticles of the sensitive layer and its effect on the structure, sensitivity, and selectivity of semiconductor sensor systems. Various mechanisms are considered of interaction between nanoparticles in metal oxide composites including incorporation of metal ions of one component into the structure of another, heterocontacts between different nanoparticles, and core-shell systems, as well as their influence on the characteristics of gas sensors. The experimental data and studies on the modeling of charge distribution in semiconductor nanoparticles, which determine the conductivity and sensor effect in one- and two-component systems, are also discussed. It is shown that the model which considers the interactions of nanoparticles best describes the experimental results. Some mechanisms of detection selectivity are considered in the conclusion.

Elastic properties of materials and their changes with temperature are important for their applications in engineering. A study on the influence of phase composition of AISI 4130 alloy on Young's modulus (Ed), shear modulus (Gd), and damping (Q-1) was carried out by Impulse Excitation Technique (IET). The material characterization was carried out using confocal microscopy, XRD, MET, HV, and dilatometry. A stable structure, composed of ferrite (BCC) and pearlite (α-Fe+Fe3C), was obtained by annealing. Metastable structure of martensite (BCT) was obtained by quenching. The Ed, Gd, and Q-1 were measured, varying the temperature from RT to 900 °C. The values of Ed and Gd, at RT, were determined as 201.5 and 79.2 GPa (annealed), and 190.13 and 76.5 GPa (quenched), respectively. In the annealed steel, the values Ed and Gd decrease linearly on heating up to 650 °C, with the thermal expansion. In the quenched steel, weak changes in the dilatometric curve, Ed, Gd, and Q-1, in the range of 350-450 °C, indicated decompositions of the martensitic phase. Sharp decrease in the moduli and high peak of Q-1, was observed for both samples around 650-900 °C, revealing low lattice elastic stability of the phases during transformations α(BCC)+Fe3C↔γ(FCC).

Retinitis pigmentosa-59 (RP59) is a rare, recessive form of RP, caused by mutations in the gene encoding DHDDS (dehydrodolichyl diphosphate synthase). DHDDS forms a heterotetrameric complex with Nogo-B Receptor (NgBR; gene NUS1) to form a cis-prenyltransferase (CPT) enzyme complex, which is required for synthesis of dolichol, which in turn is required for protein N-glycosylation as well as other glycosylation reactions in eukaryotic cells. Herein, we review the published phenotypic characteristics of RP59 models extant, with an emphasis on their ocular phenotypes, based primarily upon knock-in of known RP59-associated DHDDS mutations as well as cell type- and tissue-specific knockout of DHDDS alleles in mice. We also briefly review findings in RP59 patients with retinal disease and other patients with DHDDS mutations causing epilepsy and other neurologic disease. We discuss these findings in the context of addressing “knowledge gaps” in our current understanding of the underlying pathobiology mechanism of RP59, as well as their potential utility for developing therapeutic interventions to block the onset, or to dampen the severity or progression, of RP59.

Alzheimer’s disease is the most common neurodegenerative disease and affects persons of all races, ethnic groups, and sexes. The disease is characterized by neuronal loss leading to cognitive decline and memory loss. There is no cure and the effectiveness of existing treatments is limited and depends on the time of diagnosis. The long prodromal period, during which patients’ ability to live a normal life is not affected despite neuronal loss, often leads to a delayed diagnosis because it can be mistaken for normal aging of the brain. In order to make a substantial impact on AD patients, early diagnosis may provide a greater therapeutic window for future therapies to slow AD-associated neurodegeneration. Current gold standards for disease detection include magnetic resonance imaging and positron emission tomography scans, which visualize amyloid β and phosphorylated tau depositions and aggregates. Liquid biopsies, already an active field of research in precision oncology, are hypothesized to provide early disease detection through minimally or non-invasive sample collection techniques. Liquid biopsies in Alzheimer’s disease have been studied in cerebrospinal fluid, blood, ocular, oral, and olfactory fluids. However, most of the focus has been on blood and cerebrospinal fluid due to biomarker specificity and sensitivity attributed to the effects of the blood-brain barrier and inter-laboratory variation during sample collection. Many studies have identified amyloid β and phosphorylated tau levels as putative biomarkers, however, advances in next-generation sequencing-based liquid biopsy methods have led to significant interest in identifying nucleic acids species associated with Alzheimer’s disease from liquid tissues. Differences in cell-free RNAs and DNAs have been described as potential biomarkers for AD and hold the potential to affect disease diagnosis, treatment, and future research avenues.

Plant geneticists and breeders have used marker technology since the 1980s in quantitative trait locus (QTL) identification. Marker-assisted selection is effective for large-effect QTL but has been challenging to use with quantitative traits controlled by multiple minor effect alleles. Therefore, genomic selection (GS) was proposed to estimate all markers simultaneously, thereby capturing all their effects. However, breeding programs are still struggling to identify the best strategy to implement it into their programs. Traditional breeding programs need to be optimized to implement GS effectively. This review explores the optimization of breeding programs for variety release based on aspects of the breeder’s equation. Optimizations include reorganizing field designs, training populations, increasing the number of lines evaluated, and leveraging the large amount of genomic and phenotypic data collected across different growing seasons and environments to increase heritability estimates, selection intensity, and selection accuracy. Breeding programs can leverage their phenotypic and genotypic data to maximize genetic gain and selection accuracy through GS methods utilizing multi-trait and, multi-environment models, high-throughput phenotyping, and deep learning approaches. Overall, this review describes various methods that plant breeders can utilize to increase genetic gains and effectively implement GS in breeding .

Wheat (Triticum aestivum L.) breeding programs can take over a decade to release a new variety. However, new methods of selection such as genomic selection (GS) must be integrated to decrease the time it takes to release new varieties to meet the demand of a growing population. The implementation of GS into breeding programs is still being explored, with many studies showing its potential to change wheat breeding through achieving higher genetic gain. In this review, we explore the integration of GS for a wheat breeding program by redesigning the traditional breeding pipeline to implement GS. We propose implementing a two-part breeding strategy by differentiating between population improvement and product development. The implementation of GS in the product development pipeline can be integrated into most stages and can predict within and across breeding cycles. Additionally, we explore optimizing the population improvement strategy through GS recurrent selection schemes to reduce crossing cycle time and significantly increase genetic gain. The recurrent selection schemes can be optimized for parental selection, maintenance of genetic variation, and optimal cross-prediction. Overall, we outline the ability to increase the genetic gain of a breeding program by implementing GS and a two-part breeding strategy.

Epilepsy is one of the most common disorders of the central nervous system, impacting nearly 50 million people around the world. Heterogeneous in nature, epilepsy presents in children and adults alike. Currently, surgery is the only treatment that can cure epilepsy. However, not all individuals are eligible or have successful outcomes. Difficulty in accessing samples of human brain tissue along with advances in sequencing technology have driven researchers to investigate sampling liquid biopsies in blood, serum, plasma, and cerebrospinal fluid within the context of epilepsy. Liquid biopsies provide minimal or non-invasive sample collection approaches and can be assayed relatively easily across multiple time points, unlike tissue-based sampling. Various efforts have investigated circulating nucleic acids from these samples including microRNAs, cell-free DNA, transfer RNAs, and long non-coding RNAs. Here, we review nucleic acid-based liquid biopsies in epilepsy to improve understanding of etiology, diagnosis, prediction, and therapeutic monitoring.

This study examined the effect of an educational hybrid physical education (PE) intervention on cognitive performance and academic achievement in adolescents. A 9-month group-randomized controlled trial was conducted in 150 participants (age: 14.63 ± 1.38) allocated into control group (CG, n = 37) and experimental group (EG, n = 113). Inhibition, verbal fluency, planning and academic achievement were assessed. Significant differences were observed in the post-test for cognitive inhibition, verbal fluency in animals, and the average from verbal fluency in favour of the EG. With regard to the intervention, verbal fluency in animals, verbal fluency in vegetables, the average of verbal fluency, cognitive inhibition, language, the average of all subjects, the average of all subjects except PE, and the average from the core subjects) increased significantly in the EG. The last five variables (the academic ones and cognitive inhibition) also increased in the CG, in addition to mathematics. This study contributes to the knowledge by suggesting that both methodologies produced improvements in the measured variables, but the use of a hybrid program based on TPSR and gamification strategies produce improvements in cognitive performance, specifically through the cognitive inhibition and verbal fluency.

The potential of Neural Stem Cells (NSCs) to provide therapeutic benefit for a variety of neurological disorders, including brain malignancies, has been long recognized and has inspired many scientists to design, test and successfully demonstrate that NSCs are efficient and effective therapeutic agents. Glioblastoma, the deadliest form of primary brain tumor, despite extensive and sustained efforts to find better therapies, remains a disease without cure, with a median survival after diagnosis of less than two years. Treatment resistance in glioblastoma is in large part attributed to limitations in the delivery and distribution of therapeutic agents administered either systemically or directly into the tumor due to the highly invasive nature of this cancer and its abnormal intratumoral vasculature. Stem Cells (SCs) have an innate tumor-tropic migratory behavior, can be modified to deliver a variety of therapeutic agents and efficiently distribute their cargo into brain tumors, pursuing invading streams of tumor cells, deep into the brain parenchyma. Over the last twenty years, numerous preclinical trials have demonstrated the feasibility and efficacy of SCs as antiglioma agents, leading to the development of trials to test these therapies in the clinic. In this review we present and analyze these studies and discuss mechanisms underlying their beneficial effect, highlighting experimental progress, limitations and the emergence of promising new therapeutic avenues. We hope to increase awareness of the advantages of using SCs for the treatment of glioblastoma and inspire further studies that will lead to accelerated implementation of effective therapies.

Magnetic Particle Imaging (MPI) is a new imaging modality that sensitively and specifically detects superparamagnetic iron oxide nanoparticles (SPIONs). Many labs have been developing cellular magnetic resonance imaging (MRI) tools using both SPIONs and fluorine-19 (19F)-based contrast agents for numerous important applications, including tracking of immune and stem cells used for cellular therapies. SPION-based MRI cell tracking has very high sensitivity, but low specificity. SPIONs produce negative contrast in MRI, or signal voids. SPIO is not directly detected by MRI, but indirectly through its relaxation effects on protons, therefore, it is not possible to reliably quantify the local tissue concentration of SPION particles and cell number cannot be determined. 19F based cell tracking uses perfluorocarbons (PFC) to label cells. The number of 19F atoms can be directly measured from 19F MR images and related to cell number. 19F MRI has high specificity, but low sensitivity. MPI cell tracking displays great potential for overcoming the challenges of MRI-based cell tracking allowing for both high cellular sensitivity and high specificity and quantification of SPIO labeled cell number. In this paper we describe nanoparticle and MPI system factors that influence MPI sensitivity and resolution, quantification methods and give our perspective on testing and applying MPI for cell tracking.

Astroviruses (AstVs) are occurs globally and are common causes of gastroenteritis in human and animals. The genetic diversity and epidemiology of AstVs in Africa is not well known, hence, we aimed to genetically characterize astroviruses in asymptomatic smallholder piglets in East Africa. Twenty-four samples randomly selected from 446 piglets (<6 months old), initially collected for rotavirus study, was sequenced for metagenomic analysis. Thirteen (13/24) samples had contigs with high identity to genus Mamastrovirus. Analysis of 7 strains with complete (or near complete) genome revealed variable nucleotide and amino acid sequence identities with known PoAstV strains. The U083 and K321 strains had nucleotide sequence similarities ranging from 66.4 to 75.4 % to the known PoAstV2 strains, nucleotide sequence similarity of U460 strain with known PoAstV3 ranged 57.0 to 65.1 % to the, while K062, K366, K451, and K456 strains showed nucleotide sequence similarities of 63.5 to 80 % to the known PoAstV4 strains. The low sequence identities (<90 %) indicate that novel genotypes of PoAstVs are circulating in the study area. Multiple recombination events were detected in our PoAstV4 strains, indicating that the genetic diversity observed in these strains may be due to recombination. Importantly, we identified potential candidate epitopes with conserved peptides in our PoAstV strains that could aid in the design of immune diagnosis tools and subunit vaccines. Our data provide new intuitions into the genetic structure of porcine astroviruses in East African.

Osteoarthritis is a painful, disabling condition which is increasing in prevalence as a result of an ageing population. With no recognised disease limiting therapeutics, arthroplasty of the hip and knee is the most common and effective treatment for lower limb osteoarthritis, however lower limb arthroplasty has a finite life-span and a proportion of patients will require revision arthroplasty. With increasing life expectancy and an increasing proportion of younger (<65 years) patients undergoing arthroplasty, the demand for revision arthroplasty after implant failure is also set to increase. Statins are cholesterol modulating drugs widely used for cardiovascular risk reduction which have been noted to have pleiotropic effects including potentially influencing arthroplasty survival. In vitro studies have demonstrated pleiotropic effects in human bone cells, including enhancement of osteoblastogenesis following simvastatin exposure, and in vivo studies have demonstrated that intraperitoneal simvastatin can increase peri-implant bone growth in rats following titanium tibial implant insertion. There is evidence also that statins may also influence osseointegration, enhancing bone growth at the bone-implant interface, subsequently improving the functional survival of implants. Data from the Danish Hip Arthroplasty Registry and Clinical Practice Research Datalink in the UK suggest a reduction in the risk of lower limb revision arthroplasty in statin ever-users vs never users, and a time dependent effect of statin administration on reduction in risk of revision. In this article we review the clinical and scientific evidence linking statins and risk of revision arthroplasty.

The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec. 2019. The COVID-19 pandemic has spread over 215 countries and areas in the world, and has significantly affected every aspect of our daily lives. At the time of writing this article, the numbers of infected cases and deaths still increase significantly and have no sign of a well-controlled situation, e.g., as of 14 April 2020, a cumulative total of 1,853,265 (118,854) infected (dead) COVID-19 cases were reported in the world. Motivated by recent advances and applications of artificial intelligence (AI) and big data in various areas, this paper aims at emphasizing their importance in responding to the COVID-19 outbreak and preventing the severe effects of the COVID-19 pandemic. We firstly present an overview of AI and big data, then identify their applications in fighting against COVID-19, next highlight challenges and issues associated with state-of-the-art solutions, and finally come up with recommendations for the communications to effectively control the COVID-19 situation. It is expected that this paper provides researchers and communities with new insights into the ways AI and big data improve the COVID-19 situation, and drives further studies in stopping the COVID-19 outbreak.

A simple and rapid positive–negative colorimetric approach to determine the presence of antimony ions based on the use of gold nanoparticles conjugated with oligonucleotide (poly-A sequence) is developed. Colorimetric measurements reveal that the aggregates of modified gold nanoparticles were afforded after adding antimony ions, thus changing the solution color from pink to blue. The results of aptamer’s interaction on the gold nanoparticle surface with target analyte can be detected either by photometry or by the naked eye. The realized assay provides rapid (2 min), sensitive (detection limit 10 ng/mL), specific, and precise (variation coefficient less than 3.8%) detection of antimony (III) in drinking water

The article is devoted to the assessment of the network community as a collective subject, as a group of interconnected and interdependent persons performing joint activities. According to the main research hypothesis, various forms of group subjectness, which determine its readiness for joint activities, are manifested in the discourse of the network community. Discourse constitutes a network community, mediates the interaction of its participants, represents ideas about the world, values, relationships, attitudes, sets patterns of behavior. A procedure is proposed for identifying discernible traces of the subjectness of a network community at various levels (lexical, semantic, content-analytical scales, etc.). The subjective structure of the network community is described based on experts’ implicit representations. The revealed components of the subjectness of network communities are compared with the characteristics of the subjectness of offline social groups. It is shown that the structure of the subjectness of network communities for some components is similar to the structure of the characteristics of the subjectness of offline social groups: the discourse of the network community represents a discussion of joint activities, group norms and values, problems of civic identity. The specificity of network communities’ subjectness is revealed, which is manifested in the positive support of communication within the community, the identification and support of distinction between “us” and “them”. Two models of the relationship between discursive features and the construct “subjectness” are compared: additive-cumulative and additive. The equivalence of models is established based on the discriminativeness and the level of consistency with expert evaluation by external criteria.

This work investigates how the user-controlled parameters of the 3D printing process define temperature conditions on the boundary between layers of the part being fabricated and how these conditions influence the structure and strength of the part. The process studied is fused filament fabrication with a desktop 3D printer and the material utilized is PLA (polylactic acid). As a characteristic of the part strength the fracture load in the case of a three-point bend and calculated related stress were used. During the printing process parts were oriented with the long side along the Z axis, thus, in the bend tests, the maximum stress occurred orthogonally to the layers. During the fabrication process, temperature distribution on the sample surface was monitored with thermal imager. Sample mesostructure was analyzed using SEM. The influence of the extrusion temperature, the intensity of part cooling, the printing speed and the time between printing individual layers were considered. The influence of all the parameters can be expressed through two generalizing factors: the temperature of the previous layer and the flow efficiency, determining the ratio of the amount of extruded plastic to the calculated. A regression model was proposed that describes the effect of the two factors on the printed part strength. Along with interlayer bonding strength, these two factors determine the formation of the part mesostructure (the geometry of the boundaries between individual threads). It is shown that the optimization of the process parameters responsible for temperature conditions makes it possible to approximate the strength of the interlayer cohesion to the bulk material strength.

Background: Aging impacts semantic abilities, therefore semantic exercises might be a valuable tool for cognitive stimulation in healthy older adults. However, programs in this area are limited. Methods: In the current paper, we adapted the BOX linguistic semantic program for online use via the CerUp platform. Our goal was to prepare the optimization future experience of CerUp users, including potential changes in task structure, level of difficulty and instructions, and participants’ adherence, engagement, performance accuracy, perceived difficulty, and adequacy ratings assigned to the instructions we provided that might guide future changes. Additionally, we created a map of hypothesized task-specific features that may guide tailor-made uses of the program. Results: To that end, we present preliminary results on the usability of CerUp. By analyzing task-specific usability data alongside the hypothesized map of task-specific features, we also tested the validity of the latter. Conclusions: These preliminary results on the usability of the CerUp platform highlight the potential of programs for semantic stimulation. Such findings can inform future optimizations of the program, tailored to users’ needs and effectively supporting overall language skills and general cognition.

Bacteria of the genus Staphylococcus are a significant a challenge for medicine, as many species are resistant to multiple antibiotics and even to all of the antibiotics used. One of the approaches to develop new therapeutics to treat staphylococcal infections is the use of bacteriophages specif-ic to these bacteria or lysins of such bacteriophages capable to hydrolyze the cell walls of these bacteria. In this study, a new bacteriophage St_134 specific to Staphylococcus epedermidis was de-scribed. This small podophage belonging to the Andhravirus genus showed relatively wide host range and was able to infect more than 60 strain of Staphylococcus spp., including a clinical strain from the Staphylococcus aureus complex. Two genes encoding different phage lysins were identi-fied in the Ste134 genome. Both lysins LysSte134_1 and LysSte134_2 were produced in Escherichia coli cells. Endolysin LysSte134_1 was demonstrated catalytic activity against a wide panel of staphylococcal peptidoglycans (4 species, 6 strains), was active against S. aureus and S. epidermidis planktonic cultures and destroyed biofilms formed by clinical strains of S. aureus and S. epider-midis.

The study focuses on a novel porous TiNi-based material for ophthalmic orbital implants which was produced by self-propagating high-temperature synthesis (SHS) and, after proper surface modification, possesses a specific microstructure of its surface pores, which makes it attractive for biomedical use in implants. After preparation via SHS, the obtained porous TiNi material was etched in acidic environment, to get rid of its surface Ti2Ni secondary-phase particles. This was found to improve the material’s surface morphology, adding micro-roughness to its macro-rough pores. As a result, cell growth tests conducted on the material demonstrated improved cell adhesion and growth kinetics on such a porous material with improved roughness. Finally, the material was tested in vivo as an ophthalmic orbital implant, demonstrating good biocompatibility, good degree of biointegration with surrounding eyeball tissues, and no signs of rejection after as long as 180 days. Thus, the novel porous TiNi-based material shows promise for its use in ophthalmic implantology, for instanse for manufacturing musculoskeletal stumps of the eyeball after evisceration, as it is biocompatible, has a high tissue-implant integration potential and demonstrates reduced risks of exposure and rejection of the implant.

This work deals with a novel porous TiNi-based material for ophthalmic orbital implants that was produced by high-temperature synthesis (SHS) and possesses a specific microstructure of its surface pores, which makes it attractive for biomedical use in implants. After preparation via SHS, the obtained porous TiNi material was etched in acidic environment, to get rid of its surface Ti2Ni secondary-phase particles. This was found to improve the material’s surface morphology, adding micro-roughness to its macro-rough pores. As a result, cell growth tests conducted on the material demonstrated improved cell adhesion and growth kinetics on such a porous material with improved roughness. Finally, the material was tested in vivo as an ophthalmic orbital implant, demonstrating good biocompatibility, good degree of biointegration with surrounding eyeball tissues, and no signs of rejection after as long as 180 days. Thus, the novel porous TiNi-based material shows promise for its use in ophthalmic implantology, for instanse for manufacturing musculoskeletal stumps of the eyeball after evisceration, as it is biocompatible, has a high tissue-implant integration potential and demonstrates reduced risks of exposure and rejection of the implant.

The creation of mitochondria-targeted vector systems is a new tool for the treatment of socially significant diseases. Phosphonium groups provide targeted delivery of drugs through biological barriers to organelles. For this purpose, a new class of alkyl(diethylamino)(phenyl) phosphonium iodides (bromides) 1 containing one, two, or three diethylamino groups were obtained by the reaction of alkyl iodides (bromides) with (diethylamino)(phenyl)phosphines under mild conditions and high yields. The structure of compounds 1 was established by NMR and XRD. In vitro a high cytotoxicity against the lines M-Hela, HuTu 80, PC3, DU-145, PANC-1 and MCF-7 was found. Selectivity index are in the range of 0.06-4.0 M (SI 17-277) for the most active compounds. ROS production, mitochondrial localization and the process of cellular apoptosis were investigated. Decorated by 1 of lipid systems (liposomes and solid lipid nanoparticles) improve the cytotoxicity and a decrease in toxicity against normal cell lines. Compounds 1 induce apoptosis proceeding along the mitochondrial pathway. Aminophosphonium salts 1 also exhibit a high selective activity against the Gram-positive bacteria strains S. aureus 209P, B. segeus 8035, including methicillin-resistant strains of S. aureus (MRSA-1, MRSA-2), comparable to the activity of the fluoroquinolone antibiotic norfloxacin. A moderate in vivo toxicity in CD-1 mice was established for the lead compounds.

Kaposi’s sarcoma associated-herpesvirus (KSHV, also known as human herpesvirus-8) is a gammaherpesvirus that establishes life-long infection in human B lymphocytes. KSHV infection is typically asymptomatic but immunosuppression can predispose KSHV-infected individuals to primary effusion lymphoma (PEL); a malignancy driven by aberrant proliferation of latently infected B lymphocytes, and supported by pro-inflammatory cytokines and angiogenic factors produced by cells that succumb to lytic viral replication. Here, we report the development of the first in vivo model for a virally-induced lymphoma in zebrafish, whereby KSHV-infected PEL tumour cells engraft and proliferate in the yolk sac of zebrafish larvae. Using a PEL cell line engineered to produce the viral lytic switch protein RTA in the presence of doxycycline, we demonstrate drug-inducible reactivation from KSHV latency in vivo, which enabled real-time observation and evaluation of latent and lytic phases of KSHV infection. In addition, we developed a sensitive droplet digital PCR method to monitor latent and lytic viral gene expression and host cell gene expression in xenografts. The zebrafish yolk sac is not well-vascularized and using fluorogenic assays we confirmed that this site provides a hypoxic environment that may mimic the microenvironment of some human tumors. We found that PEL cell proliferation in xenografts was dependent on the host hypoxia-dependent translation initiation factor, eukaryotic initiation factor 4E2 (eIF4E2). This demonstrates that the zebrafish yolk sac is a functionally hypoxic environment and xenografted cells must switch to dedicated hypoxic gene expression machinery to survive and proliferate. The establishment of the PEL xenograft model enables future studies that exploit the innate advantages of the zebrafish as a model for genetic and pharmacologic screens.

Zoo conditions are unique for reindeer, since even domestic reindeer are not kept in captive facilities like cattle. In the zoo, reindeer are usually surrounded by many different animals they would never encounter naturally. Thus they might pick up some new helminths. Numerous petting zoos raise an issue of safety of tactile communications for human visitors. Out study is the first large-scale one. Qualitative and quantitative fecal analysis was carried out for 233 reindeer distributed over 50 Russian zoos according to National Standard of the Russian Federation (GOST R 54627-2011) Ruminant animals—Methods of Laboratory Helminthological Diagnostics. Where possible, DNA analyses of helminths were performed targeting internal transcribed spacer region. In result, F. hepatica, Paramphistomum sp., Moniezia sp. (including M. expansa), gastrointestinal strongylids (including Nematodirus spp.), Dictyocaulus sp., E. rangiferi, Trichuris sp., and Capillaria sp. were found in 106 (45%) zoo reindeer. All these helminths were previously reported for reindeer and pose no direct danger for humans. Intensity of invasions was mostly low. Fecal examination might be considered as an indirect method for mange diagnostics, as Chorioptes and Demodex mites were found in reindeer fecal samples. The latter may represent a novel species of mite specific for reindeer.

Blackberry (Rubus fruticosus spp) is a fruit that has a significant antioxidant activity, due to its content in anthocyanins and antioxidant compounds. Emerging technologies are required as the thermoultrasound technique that ensures microbial reduction and release of compounds with antioxidant properties. The objective of this study was to evaluate changes in the antioxidant content and fatty acid profile of blackberry juice when it is subjected to conservation treatment (pasteurization and thermoultrasound). The blackberry juice and the extracted oil of blackberry juice with n-hexane (control, pasteurized and thermoultrasonicated) were evaluated in antioxidant activity, fatty acid profile and antioxidant content. The thermoultrasound juice had the highest (p < 0.05) amount of total phenols (1011 mg GAE/L), anthocyanins (118 mg Cy-3-GlE/L); antioxidant activity by ABTS (44 mg VCEAC/L) and DPPH (2665 µmol TE/L) compared to the control and pasteurized samples, as well as, as well as, oil extract of obtained of the thermoultrasound juice presented high antioxidant activity (177.54 mg VCEAC/L to ABTS and 1802.60 µmol TE/L to DPPH). The fatty acid composition of the oil extract showed the presence of myristic, linolenic, stearic, oleic, and linoleic acid, the fatty acid profile was similar in the different samples with the exception of stearic acid where this was higher in control sample. The thermoultrasound treatment can be an alternative to pasteurization treatments because keeps and releases antioxidant bioavailable compounds, preserving their fatty acids.

In mobile robotics, laser scanners have a wide spectrum of indoor and outdoor applications, both in structured and unstructured environments, due its accuracy and precision. Most works that use this sensor have their own data representation and their own case-specific modeling strategies, and no common formalism is adopted. To address this issue, this manuscript presents an analytical approach for identification and localization of objects using a 2D LiDARs Our main contribution lies in formally defining laser sensor measurements and their representation, the identification of objects, their main properties and their location in a scene. We validate our proposal with experiments in generic semi-structured environments common in autonomous navigation, and we demonstrate its feasibility on multiple object detection and identification, following strictly its analytical representation. Finally, our proposal further encourages and facilitates the design, modeling and implementation of other applications that use laser scanners as a distance sensor.

This paper offers a comprehensive examination of the process involved in developing and automating supervised end-to-end machine learning workflows for forecasting and classification purposes. It offers a complete overview of the components (i.e. feature engineering, model selection, etc), principles (i.e. bias-variance decomposition, model complexity, overfitting, model sensitivity to feature assumptions and scaling, output interpretability, etc), models (i.e. neural networks, regression models, etc), methods (i.e. Cross-Validation, data augmentation, etc), metrics (i.e. Mean Squared Error, F1-score, etc) and tools that rule most supervised learning applications with numerical and categorical data, as well as their integration, automation, and deployment. The end goal and contribution of this paper is the education and guidance of the non-AI expert academic community over complete and rigorous machine learning pipelines and data science practices, from problem scoping to design and state-of-the-art automation tools, including basic principles and reasoning in the choice of methods. The paper delves into the critical stages of supervised machine learning workflow development, many of which are often omitted by researchers due to brevity, and covers foundational concepts essential for understanding and optimizing a functional machine learning workflow, thereby offering a holistic view of task-specific application development for applied researchers who are not AI experts.

Pyrolysis is a combustion process of woody biomass conducted under low or no oxygen conditions. New innovations and the need to limit open burning has resulted in numerous mobile and fixed plant pyrolysis methods that burn a variety of woody residues. Production technologies that reduce the need for open burning, the main source of potential pollutants, fall under the regulations in the Clean Air Act of 1990. This Act is the legal instrument to regulate air pollution at its source across the United States of America and it is implemented and enforced through the Environmental Protection Agency, in coordination with sister agencies. One newer innovation for reducing woody residues and emissions is an air curtain incinerator. Currently, the Clean Air Act regulates stationary solid waste incinerators, and this is also applied to mobile air curtain incinerators burning woody biomass. However, other woody biochar production methods (e.g., flame cap kilns) are not subject to these regulations. Discrepancies in the interpretation of definitions related to incineration and pyrolysis and the myriad of differences related to stationary and mobile air curtain incinerators, type of waste wood from construction activities, forest residues, and other types of clean wood make the permitting regulations confusing as permits can vary by jurisdiction. This review summarizes the current policies, regulations, and directives related to in-woods biochar production and the required permits.

Allylbenzenes (apiol, dillapiol, myristicin and allyltetramethoxybenzene) are individual components of plant essential oils that demonstrate antitumor activity, as well as enhancing effect on cytotoxic drugs such as paclitaxel, doxorubicin, cisplatin, etc. Triphenylphosphine (PPh3) derivatives of allylbenzenes are 2-3 orders of magnitude more potent than allylbenzenes in terms of IC50. Inhibition of efflux pumps has been reported for allylbenzenes, and PPh3 moiety is deemed to be responsible for preferential mitochondrial accumulation and depolarization of mitochondrial membranes. However, due to poor solubility the practical use of these substances has never been an option. Cyclodextrin-based (CD) molecular containers suggested here provided solubilization of allylbenzenes and its PPh3-derivatives. So, in this study we have observed an increase antitumor activity of paclitaxel in the presence of PPh3-derivatives adjuvants by an order of magnitude (in terms of IC50) against adenocarcinomic human alveolar basal epithelial cells A549. At the same time, they are quite powerful cytostatics themselves against A549 cells. On the other hand, the cytotoxic formulations developed show pronounced selectivity of the antiproliferation activity: high against tumor cells line (A549) and low toxicity of these composition was demonstrated on normal cells HEK293T, red blood cells, and sea urchin embryos (a model close to the human genome). On non-cancer HEK293T cells, it was shown that PPh3-derivatives of allylbenzenes at a concentration of 100 µM cause the death of about 20% of cells, while on A549 cancer cells, 85% of cells die. PPh3 derivatives of allylbenzenes, when solubilized in CD molecular containers, show remarkable potential as adjuvants to some of the widely used cytotoxic drugs.

Regulation at the level of translation plays an essential role in modulating gene expression. Given the importance of knowledge about translationally active mRNAs as an indicator of translation efficiency, it is crucial for researchers to have at their disposal organised sources of functional information on translation - plant translatomic maps similar to transcription maps. The development of a general experimental and computational methodology for constructing translatome maps is essential to address this challenge. In this manuscript, we discuss what researchers can do to design plant translatome maps, namely, we review: (i) experimental methods to obtain translationally active mRNA fractions, considering their advantages and limitations; (ii) additional methodological approaches to obtain complete pools of translationally active mRNAs; (iii) sequencing methods to qualitatively and quantitatively assess different mRNA fractions; and (iv) multivariate analyses of sequencing results by bioinformatics methods, including metrics for assessing mRNA translational activity.

This article presents the development and validation of a new instrument measuring social, cultural, and behavioral factors influencing exposure to occupational zoonoses in agricultural settings. The Social Ecological Model (SEM) and the Standards for Educational and Psychological Testing were used as guiding frameworks to ensure the instrument's validity. The instrument's content was compiled by combining the results of a scoping literature review and an expert qualitative study. The instrument items were drafted, organized, and underwent a meticulous process of revision and adjustment. It was translated into Spanish and tested in one-to-one cognitive interviews with five volunteer agricultural workers. Exploratory factor analysis was conducted for construct discrimination, and bivariate regression analyses were conducted to explore the association with exposure indicators. Evidence of validity was obtained from four out of five sources of validity evidence according to the AERA/APA’s Standards of Educational and Psychological Testing. The Social Ecology of Occupational Zoonoses (SEOZ) was successfully used to determine social and behavioral factors associated with a higher risk of exposure to occupational zoonoses. Further use of the SEOZ can provide valuable insights into developing effective interventions to improve the health and well-being of agricultural workers.

Sentiment analysis of public opinion expressed in social networks has been developed into various applications, especially in English. Hybrid approaches are potential models for reducing sentiment errors on increasingly complex training data. This paper aims to test some hybrid deep learning models' reliability in some domains' Vietnamese language. Our research questions are to determine whether it is possible to produce hybrid models that outperform the Vietnamese language. Hybrid deep sentiment-analysis learning models are built and tested on reviews and feedback of the Vietnamese language. The hybrid models outperformed the accuracy of Vietnamese sentiment analysis on Vietnamese datasets. It contributes to the growing body of research on Vietnamese NLP, providing insights and directions for future studies in this area.

Bioelectrochemical systems (BESs) have great potential in renewable energy production technologies. BES can generate electricity via Microbial Fuel Cell (MFC) or use the electric current for the synthesis of valuable commodities in Microbial Electrolysis Cells (MECs). The number of various reactor configurations and operational protocols increasing rapidly although, the industrial scale operation is still facing difficulties. This article reviews the recent BES related to literature, with special attention to electrosynthesis and the most promising reactor configurations. We also attempted to clarify the numerous definitions proposed for BESs. The main components of BES are highlighted. Although the comparison of the various fermentation systems is we collected useful and generally applicable operational parameters to be used for comparative studies. A brief overview to link the appropriate microbes to the optimal reactor design is given.

Iron-containing nickel sulfides, selenides, and sulfoselenides were synthesized via a simple two-step hydrothermal reaction (temperature 160 °C) for their application as electrocatalysts in the oxygen evolution reaction (OER) in an alkaline solution (1 mol L–1 KOH). The study demonstrated that iron-containing nickel cobalt sulfides and selenides exhibit superior OER performance with lower overpotentials compared to iron-free nickel cobalt sulfide and selenide, which highlights the significant role of iron in enhancing OER nickel cobalt electrocatalysts: Fe0.1Ni1.4Co2.9(S0.87O0.13)4, η50 = 318 mV; Fe0.2Ni1.5Co2.8(S0.9O0.1)4, η50 = 310 mV; Fe0.3Ni1.2Co2.5(S0.9O0.1)4, η50 = 294 mV; Fe0.6Ni1.2Co2.5(S0.83O0.17)4, η50 = 294 mV, Fe0.4Ni0.7Co1.6(Se0.81O0.19)4, η50 = 306 mV compared to Ni1.0Co2.1(S0.9O0.1)4, η50 = 346 mV and Ni0.7Co1.4(Se0.85O0.15)4, η50 = 355 mV (all values at current densities η50 of 50 mA cm–2). Furthermore, the iron-containing nickel cobalt sulfoselenide Fe0.5Ni1.0Co2.0(S0.57Se0.25O0.18)4 displayed exceptional OER performance with η50 = 277 mV, surpassing the benchmark RuO2 electrode with η50 = 299 mV. The superior performance of the sulfoselenide was attributed to its low charge transfer resistance (Rct) of 0.8 Ω at 1.5 V vs. the reversible hydrogen electrode (RHE). Moreover, the sulfoselenide demonstrated remarkable stability, with only a minimal increase in overpotential (η50) from 277 mV to 279 mV after a 20 h chronopotentiometry test. These findings suggest that trimetallic iron, nickel and cobalt sulfide, selenide and especially sulfoselenide materials hold promise as high-performance, cost-effective, and durable electrocatalysts for sustainable OER reactions. This study provides a valuable approach for the development of efficient electrocatalytic materials, contributing to the advancement of renewable energy technologies.

Findings on diet-health relationships have led many people to include healthier food items (including snacks) in their diets, e.g. those containing probiotic microorganisms. The purpose of this study was to compare two methods to produce probiotic freeze-dried banana slices - one of them consisting of impregnating slices with a suspension of probiotic Bacillus coagulans, the other based on coating the slices with a starch dispersion containing the bacteria. Both processes have resulted in viable cell counts above 7 log ufc.g-1, although the presence of the starch coating has avoided a significant loss of viability on freeze-drying. The coated slices were less crispy than the impregnated ones, according to the shear force test results. However, the sensory panel (with more than 100 panelists) have not perceived significantly texture differences. Both methods have presented good results, in terms of probiotic cell viability and sensory acceptability (the coated slices having been significantly more accepted than the non-probiotic control slices).

Requirements are predominantly written in Natural Language (NL), which makes them accessible to stakeholders with varying degrees of experience, as compared to a model-based language which requires special training. However, despite its benefits, NL can introduce ambiguities and inconsistencies in requirements, which may eventually result in system quality degradation and system failure altogether. The system complexity that characterizes current systems warrants an integrated and comprehensive approach to system design and development. This need has brought about a paradigm shift towards Model-Based Systems Engineering (MBSE) approaches to system design and a departure from traditional document-centric methods. While, MBSE shows great promise, the ambiguities and inconsistencies present in NL requirements hinder their conversion to models directly. The field of Natural Language Processing (NLP) has demonstrated great potential in facilitating the conversion of NL requirements into a semi-machine-readable format that enables their standardization and use in a model-based environment. A first step towards standardizing requirements consists of classifying them according to the ``type'' (design, functional, performance, etc.) they represent. To that end, a language model capable of classifying requirements needs to be fine-tuned on labeled aerospace requirements. This paper presents the development of an annotated aerospace requirements corpus and its use to fine-tune BERT$_\text{BASE-UNCASED}$ to obtain aeroBERT-Classifier: a new language model for classifying aerospace requirements into design, functional, or performance requirements. A comparison between aeroBERT-Classifier and bart-large-mnli (zero-shot text classification) showcased the superior performance of aeroBERT-Classifier on classifying aerospace requirements despite being fine-tuned on a small labeled dataset.

We present the results on photothermal (PT) and heat conductive properties of nanogranular silicon (Si) films synthesized by evaporation of colloidal droplets (drop-casting) of 100 ± 50 nm sized crystalline Si nanoparticles (NP) deposited on glass substrates. Finite difference time domain (FDTD) and finite element mesh (FEM) modeling of absorbed light intensity and photo-induced spatial temperature distribution across the Si NP films were well correlated with the local temperatures measured by micro-Raman spectroscopy and used for determination of heat conductivities in the films of various thicknesses. Cubic-to-hexagonal phase transition in these films caused by laser heating was found to be heavily influenced by the film thickness and heat conductive properties of glass substrate, on which the films were deposited. Heat conductivities across the drop-casted Si nanogranular films were found to be in the range of lowest heat conductivities of other types of nanostructurely voided Si films due to enhanced phonon scattering across inherently voided topology, weak NP-NP and NP-substrate interface bonding within nanogranular Si films.

This study aimed to characterize the long non-coding RNA (lncRNA) expression in the bovine mammary gland and to infer their functions in dietary response to 5% linseed oil (LSO) or 5% safflower oil (SFO). Twelve cows (six per treatment) in mid lactation were fed a control diet for 28 days followed by a treatment period (control diet supplemented with 5% LSO or 5% SFO) of 28 days. Mammary gland biopsies were collected from each animal on day-14 (D-14, control period), D+7 (early treatment period) and D+28 (late treatment period) and were subjected to RNA-Sequencing and subsequent bioinformatics analyses. Functional enrichment of lncRNA was performed via potential cis regulated target genes located within 50 Kb flanking regions of lncRNAs and having expression correlation of >0.7 with mRNAs. A total of 4955 lncRNAs (325 known and 4630 novel) were identified which potentially cis targeted 59 and 494 genes in LSO and SFO treatments, respectively. Enrichments of cis target genes of lncRNAs indicated potential roles of lncRNAs in immune function, nucleic acid metabolism and cell membrane organization processes as well as involvement in Notch, cAMP and TGF-β signaling pathways. Thirty-two and 21 lncRNAs were differentially expressed (DE) in LSO and SFO treatments, respectively. Six genes (KCNF1, STARD13, BCL6, NXPE2, HHIPL2 and MMD) were identified as potential cis target genes of six DE lncRNAs. In conclusion, this study indicated potential roles for lncRNAs in mammary gland immune functions and development and provided potential candidate genes and pathways via which lncRNAs can function in diet responses.

The objective of this study was to carry out the extraction and characterization of chitin and chitosan from the exoskeletons of the Farfantepenaeus californiensis species of shrimp, as well as its application in the formulation of polymeric films plasticized with glycerol used in the process of food packaging. The characterization of the extracted polymer was made by Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), and physicochemical analysis of chitin and chitosan, resulting in a theoretical performance of 29.33% and 16.46%, respectively. In terms of quality, it was determined that the extracted chitosan had a molecular weight of 1.10 x105 g/mol and a deacetylation degree of 80.23%, which classifies it as a low-molecular weight chitosan, suitable for food packaging. It was shown that the extracted chitosan is fit for the production of the films by using the casting method, presenting a tension resistance of 1 MPa. The Antibacterial analysis was carried out using Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli), bacterial models commonly found in food. The results showed an effective inhibition capability of the polymeric materials. Overall, the results for both chitosan and the films indicate a high potential for application in the food packaging sector.

Coastal environments are complex systems that are influenced by a combination of natural processes and human activities. Scientific interest in the effects of coastal erosion/accretion and climatic change-related processes greatly increased in recent decades due to the growing human development along coastal areas. This paper investigates the state and evolution of beach-dune systems for the 1977-2001 and 2001-2019 periods of the Mediterranean coast of Andalusia (Spain) using two different proxies: the dune toe line, which was used to track foredunes evolution, and the high-water line, which was used to assess shoreline evolution. Results showed a general erosional behavior of the studied beach-dune systems and identified cases where the main trend was altered through human interventions. In the 1977-2001 period, 54% of foredunes showed erosion, 24% accretion and 22% stability while and 34% of shorelines showed erosion, 40% accretion and 34% stability. In the 2001-2019 period, 42% of foredunes showed erosion, 28% accretion and 30% stability, and 40% of shorelines showed erosion, 34% accretion and 26% stability. Combining the evolution classes of each proxy (dune toe/shoreline) allows the behavior of both shoreline proxies to be assed together and provides insights additional to those derive from the use of a single proxy. In this regard, Erosion/Erosion (EE) was the most frequent behavior, with 25% and 27% in the first and second periods respectively, and Accretion/Accretion (AA), with 17% in both periods. Erosion of foredunes combined with stability or accretion of the shoreline (ES and EA) were the most common pairings in the first period, while stability of dunes combined with accretion of the shoreline (SA) and Stability/Stability (SS) dominated in the second period. The results obtained provide additional insights on the nature and drivers of coastal change that aid local coastal managers and administrations in understanding erosion processes. The method can be applied at other areas around the world where a similar data base is available.

Frass generated during the production of black soldier fly larvae is taking the interest of scientists and horticultural producers because it is a material from the biotransformation of organic waste, it has several nutrients that can be used by plants, and its recent focus on its biostimulant capacity. The thermal-composting process is a stabilization that improves physical and chemical properties of treated wastes, allowing better performance in plants compared to its fresh state. In this research, thermocomposted frass was evaluated as a germination substrate for kale seeds (Brassica olerasea). To achieve this, it was evaluated the phytotoxicity in different concentrations on the seeds, and seedlings were grown in a germination substrates mixed with 20, 40, 60, 80 and 100% of frass. The treatment with 20% frass showed the highest values of seedling height, stem diameter, number of leaves, length, and width of first true leaf and length and width of cotyledons, reduced the content of phenols and tannins antioxidants but the content of flavonoids increased compared to the control and the rest of mixtures.

The aims of this research were to know the physicochemical parameters, texture properties and sensory profile of vegetarian sausages through the flash profile, overall liking and purchase intention. Additionally, protein, fat and carbohydrate contents, pH, water activity, color, instrumental texture and descriptive profile were quantified with the overall liking and purchase intention of four sausages: ovo-vegetarian (SO), classic vegan (SC), fine herb vegan (SH) and vegan quinoa (SQ). Regarding the physicochemical properties, significant differences (p &lt; 0.05) were obtained. Using the flash profile, consumers described SO with attributes of elasticity, tamale smell, strange smell, characteristic flavor, pastiness, softness, pastel color. SC described as soft, pale color, characteristic odor, characteristic flavor, porous and flexible; SH and SQ characterized by the presence of ingredients, stew flavor, spices, pale and soft color. The SO sample presented greater overall liking and purchase intention compared to the other samples, and had a better texture and higher protein content. Through the HMFA analysis, a positive correlation was obtained between the texture and descriptive sensory of the flash profile, and on the other hand, a correlation between the physicochemical characteristics pH, aw, color, overall liking and purchase intention.

This study provides an in-depth review of the available literature on metal composite material machining, focusing on traditional machining operations such as turning, milling, shaping, drilling, and grinding. The motivation for the study is that this composite type has emerged as a vital material in applications requiring functionality, resilience, cost-effective operation, low consumption of energy and lightweight. Despite its superior characteristics, the manufacturing complexity and poor machinability of metal matrix composites have been the primary barriers to its adoption. Nevertheless, there is a reduction of exceptional efficiency, increase in surface roughness, tool wear and so on in metal matrix composites throughout machining. As a result, this review gives a comprehensive investigation of metal matrix composite machining and effect on process parameters and procedures. Furthermore, this study distinguishes metal matrix composites towards sustainable manufacturing and the metals employed by the researchers, as well as the gaps discovered for future recommendations in metal-based composites.

The COVID-19 pandemic crisis has brought about unprecedented economic and social consequences worldwide. The implementation of isolation measures, including national and international travel restrictions, significantly affected contact-intensive sectors such as tourism. During this lockdown period, Information and Communication Technology (ICT) was crucial in maintaining connectivity and enabling remote activities. Governments across the world implemented discretionary measures to mitigate the crisis's adverse effects on economic activity. This paper aims to analyze whether the level of ICT adoption and the importance of tourism influence the fiscal policy efforts pursued by governments. Based on the results of a linear regression analysis for 154 countries, the findings suggest that in countries with higher international tourism receipts, the governments had to promote higher fiscal stimulus. At the same time, ICT development diminished the efforts of the fiscal policy response to the crisis since it facilitated economic resilience. The findings of this study can contribute to understanding how governments responded to the pandemic crisis and the factors that influenced their fiscal policy decisions.

Intrahepatic cholangiocarcinoma (ICCA) is a malignant epithelial neoplasm characterized by biliary differentiation within the liver. ICCA is molecularly heterogeneous and exhibits a broad spectrum of histopathological features. It is a highly aggressive carcinoma with high mortality and poor survival rates. ICCAs are classified into two main subtypes: small duct type and large duct types. These two tumor types have different cell origins and clinicopathological features. ICCAs are characterized by numerous molecular alterations, including mutations in KRAS, TP53, IDH1/2, ARID1A, BAP1, BRAF, SAMD4, and EGFR, and FGFR2 fusion. Two main molecular subtypes–inflammation and proliferation–have been proposed. Recent advances in high-throughput assays using next-generation sequencing have improved our understanding of ICCA pathogenesis and molecular genetics. The diagnosis of ICCA poses a significant challenge for pathologists because of its varied morphologies and phenotypes. Accurate diagnosis of ICCA is essential for effective patient management and prognostic determination. This article provides an updated overview of ICCA pathology, focusing particularly on molecular features, histological subtypes, and diagnostic approaches.

The Sm3+/Gd3+ co-doped glasses in the B2O3–GeO2–PbO and B2O3–GeO2–Bi2O3 systems have been synthesized in the composition range of 40B2O3–40GeO2–(15-17)PbO(Bi2O3)–(3-2)Sm2O3–(2-1)Gd2O3 and 42.5B2O3–42.5GeO2–(11.25-12.75)PbO(Bi2O3)–(2.25-1.5)Sm2O3–(1.5-0.075)Gd2O3. The physical, structural, and spectral properties of the produced glasses have been studied. The fabricated glass samples demonstrated changes in temperature-sensitive luminescence parameters in 298-673 K temperature range. We found out several photoluminescence bands attributed with transitions from different Stark sublevels. By using a combination of two temperature sensitive and one non-sensitive transitions we calculated fluorescence intensities ratio (FIR). This procedure made it possible to increase the sensitivity of luminescence thermometry in several times. Such method could be very useful for the luminescent thermometry materials based on Ln3+ ions with multiplied f-f transitions.

A high perovskite activity is sought for use in magnetic applications. In this paper, we present the simple synthesis of (2.5 and 5%) Tellurium-impregnated-LaCoO3 (Te-LCO), Te and LaCoO3 (LCO) by using a ball mill, chemical reduction, and hydrothermal synthesis, respectively. We also explored the structure stability along with the magnetic properties of Te-LCO. Te has a rhombohedral crystal structure, whereas Te-LCO has a hexagonal crystal system. The reconstructed Te was imbued with LCO that was produced by hydrothermal synthesis; as the concentration of the imbuing agent grew, the material became magnetically preferred. According to the X-ray photoelectron spectra, the oxidation state of the cobaltite is one that is magnetically advantageous. As a result of the fact that the creation of oxygen-deficient perovskites has been shown to influence the mixed (Te4+/2-) valence state of the incorporated samples, it is abundantly obvious that this process is of utmost significance. The TEM image confirms the inclusion of Te in LCO. The samples start out in a paramagnetic state (LCO), but when Te is added to the mixture, the magnetic state shifts to a weak ferromagnetic one. It is at this point that hysteresis occurs due to the presence of Te. Despite being doped with Mn in our prior study, rhombohedral LCO retains its paramagnetic characteristic at room temperature (RT). As a result, the purpose of this study was to determine the impacts of RT field dependency of magnetization (M-H) for Te-impregnated LCO in order to improve the magnetic properties of RT because it is a low-cost material for advanced multi-functional and energy applications.

The purpose of this study was to see how feeding cotton gin trash (CGT) as an alternative meal affected the growth performance, carcass features, and meat quality of Mecheri ram lambs. A growth performance trial was conducted with thirty-two weaned Mecheri ram lambs from four months to nine months (180 days) of marketing age and assigned into four groups (T1, T2, T3 and T4) of eight animals in each group. The lambs were fed with CGT at 0 (T1), 25 (T2), 50 (T3) and 75 (T4) per cent inclusion levels in the roughage portion at 60:40 roughage: concentrate ratio. All the group of animals were fed on dry matter requirement basis at four per cent of their body weight. The lambs fed with 75 (T4) and 50 (T3) per cent inclusion level of CGT showed signifi-cantly (P<0.01) higher total body weight gain (kg) than T1 (14.54) and T2 (15.05) groups. The av-erage daily gain (g) of lambs in T3 (99.24) and T4 (105.51) were significantly (P<0.01) higher than T1 (80.77) and T2 (83.61) groups. Over the course of the 180-day trial period, there was no statisti-cally significant difference in the average DMI (g) between the groups (P>0.05), however the lambs in T4 demonstrated higher feed efficiency (7.4) than the T1 (9.3) group. The slaughter studies revealed that the lambs in T4 followed by T3 group registered significantly (P<0.01) higher hot carcass weight, dressing percentage and Meat: Bone ratio than T2 and T1 group ani-mals. The weights of the liver, spleen, head, stomach, and intestines empty were considerably (P<0.05) larger in the T3 and T4 groups than in the other groups, although there was no signifi-cant (P>0.05) difference in the weights of edible and inedible offals. Meanwhile, there were no significant variations (P>0.05) in pH, water holding capacity, shear force value, sensory charac-teristics, or proximate composition of meat across treatment groups. In accordance to the find-ings, CGT can be added up to 75% of the roughage component in sheep feed as an effective un-conventional supplementation, as it improves body weight, feed efficiency, and carcass characteristics in Mecheri ram lambs.

Determining genetic and non-genetic sources of variation in a breed is vital for the formulation of strategies for its conservation and improvement. The present study was aimed at estimating the (co)variance components and genetic parameters of Mecheri sheep by fitting six different animal models in the restricted maximum likelihood method, with a preliminary investigation on the performance of animals for non-genetic sources of variation. A total of 2616 lambs were studied, and varying levels of significance were found for the effect of period, season, parity of dam and birth type on different body weight traits. Direct heritability estimates derived from the best animal model for body weight at birth, 3 months, 6 months, 9 months and 12 months were 0.21, 0.24, 0.10, 0.15 and 0.09, respectively, and maternal heritabilities of the corresponding traits were 0.12, 0.05, 0.04, 0.04 and 0.04, respectively. The genetic correlations between body weight traits were all positive and moderate to strong except for birth weight with the other body weight traits. The significance of non-genetic factors studied in this work demanded a correction to improve the accuracy of the direct selection of lambs for body weight traits. The estimated genetic parameters identified the weaning weight as a selection criterion for the improvement in body weight of Mecheri lambs at different ages. Inbred individuals accounted for approximately 13% of the total population in the Mecheri sheep population studied. There were 877 founders in the population, and the actual effective size of the population was 128.48. The population's mean generation interval was 3.26. The mean inbreeding values ranged from 0.005 to 0.010 across generations. The population's average relatedness ranged from 0.001 to 0.014 across generations. Individual inbreeding was found to be 0.45 per cent for the entire population and 3.4 per cent for the inbred population.

Commercial buildings are a significant consumer of energy worldwide. Logistics facilities, and specifically warehouses, are a common building type yet under-researched in the demand-side energy forecasting literature. Warehouses have an idiosyncratic profile when compared to other commercial and industrial buildings with a significant reliance on a small number of energy systems. As such, warehouse owners and operators are increasingly entering in to energy performance contracts with energy service companies (ESCOs) to minimise environmental impact, reduce costs, and improve competitiveness. ESCOs and warehouse owners and operators require accurate forecasts of their energy consumption so that precautionary and mitigation measures can be taken. This paper explores the performance of three machine learning models (Support Vector Regression (SVR), Random Forest, and Extreme Gradient Boosting (XGBoost)), three deep learning models (Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU)), and a classical time series model, Autoregressive Integrated Moving Average (ARIMA) for predicting daily energy consumption. The dataset comprises 8,040 records generated over an 11-month period from January to November 2020 from a non-refrigerated logistics facility located in Ireland. The grid search method was used to identify the best configurations for each model. The proposed XGBoost models outperform other models for both very short load forecasting (VSTLF) and short term load forecasting (STLF); the ARIMA model performed the worst.

Ustilago maydis, member of the Ustilaginaceae family, is a promising host for the production of several metabolites including itaconic acid. This dicarboxylate has great potential as a bio-based building block in the polymer industry, and is of special interest for pharmaceutical applications. Several itaconate overproducing Ustilago strains have been generated by metabolic and morphology engineering. This yielded stabilized unicellular morphology through fuz7 deletion, reduction of by-product formation through deletion of genes responsible for itaconate oxidation and (glyco)lipid production, and the overexpression of the regulator of the itaconate cluster ria1 and the mitochondrial tricarboxylate transporter encoded by mttA from Aspergillus terreus. In this study, itaconate production was further optimized by consolidating these different optimizations into one strain. The combined modifications resulted in itaconic acid production at theoretical maximal yield, which was achieved under biotechnologically relevant fed-batch fermentations with continuous feed.

Microplastics are a fast emerging group of contaminants. Their worldwide occurrence in water, sediment, and aquatic fauna raises questions and concerns as to their probable effects on aquatic life and ecology. This study investigates for the first time presence, abundance, and types of microplastics in water and sediment from a lagoon bordering the large urban agglomeration of Lagos in Nigeria, and renders additional information about grain size and sediment composition. Water and sediment samples were collected from four locations in the Lagos lagoon and a tributary. The abundance and distribution of microplastics in four range classes were determined for the sampled locations. Plastic particles were counted using digital microscopy, and identified with FTIR and pyrolysis GC-MS. The abundance of microplastics ranged from 310-2319 microplastic particles/kg in sediment, and 139-303 particles/m³ in water. The large discrepancy in the sediments can be explained by sediment characteristics as more microplastics were detected in the fine-grained sediments of Makoko. Fibres were the predominant shape found in all samples followed by fragments and few films whereas spheres were missing. Fibres were more abundant in water (92.6 %) than in sediments (32.5 %) while more fragments and foils occurred in sediments. The most commonly used polymers polypropylene and polyethylene were also the most detected ones in both matrices. Compared to other studies in Nigeria, our findings especially in the coarser sediments were lower while the fine-grained site revealed similar results.

The sudden pervasive of severe acute respiratory syndrome Covid-19 has been leading the universe into a prominent crisis. It has influenced each zone, for example, industrial area, horticultural zone, Public transportation, economic zone, and so on. So as to see how Covid-19 affected the globe, we conducted an investigation characterizing the effects of the pandemic over the world using Machine Learning (ML) method. Prediction is a typical data science exercise that helps the administration with function planning, objective setting, and anomaly detection. We propose an additive regression model with interpretable parameters that can be naturally balanced by experts with domain intuition about the time series. We focus on global data beginning from 22^nd January 2020, till 26^th April 2020 and performed dynamic map visualization of Covid-19 expansion globally by date wise and predicting the spread of virus on all countries and continents. The major advantages of this work include accurate analysis of country-wise as well as province/state-wise confirmed cases, recovered cases, deaths, prediction of pandemic viral attack and how far it is expanding globally.

Early detection of cancer increases the probability of recovery. This paper presents an intelligent decision support system (IDSS) for the early diagnosis of cancer based on gene expression profiles collected using DNA microarrays. Such datasets pose a challenge because of the small number of samples (no more than a few hundred) relative to the large number of genes (on the order of thousands). Therefore, a method of reducing the number of features (genes) that are not relevant to the disease of interest is necessary to avoid overfitting. The proposed methodology uses the information gain (IG) to select the most important features from the input patterns. Then, the selected features (genes) are reduced by applying the grey wolf optimization (GWO) algorithm. Finally, the methodology employs a support vector machine (SVM) classifier for cancer type classification. The proposed methodology was applied to two datasets (Breast and Colon) and was evaluated based on its classification accuracy, which is the most important performance measure in disease diagnosis. The experimental results indicate that the proposed methodology is able to enhance the stability of the classification accuracy as well as the feature selection

Bemisia tabaci (Gennadius) is a polyphagous, highly destructive pest capable of vectoring viruses in most agricultural crops. Currently, information on the distribution and genetic diversity of B. tabaci in South Sudan is not available. The objectives of this study were to investigate the genetic variability of B. tabaci infesting sweet potato and cassava in South Sudan. Field surveys were conducted between August 2017 and July and August 2018 in 10 locations in Juba County, Central Equatoria State, South Sudan. Sequences of mitochondrial DNA cytochrome oxidase I (mtCOI) were used to determine the phylogenetic relationships between sampled B. tabaci. Six distinct genetic groups of B. tabaci were identified including three non-cassava haplotypes (Mediterranean (MED), Indian Ocean (IO) and Uganda) and three cassava haplotypes (Sub-Saharan Africa 1 sub-group 1 (SSA1-SG1), SSA1-SG3 and SSA2). MED predominated on sweet potato and SSA2 on cassava in all the sampled locations. The Uganda haplotype was also widespread, occurring in five of the sampled locations. This study provides important information on the diversity of B. tabaci species in South Sudan. A comprehensive assessment of the genetic diversity, geographical distribution, population dynamics and host range of B. tabaci species in South Sudan is vital for its effective management.

In interepidemic periods, a sapronoses typically employs a variety of mechanisms for maintaining viability of its causative agent in terrestrial parasitic systems, associated with different adaptive strategies utilized by its populations to survive. Unlike spore-forming bacteria, causative agents of sapronoses use resistant cell forms, which is a viable but nonculturable (VBNC) state, and persistence. Implementation of these strategies is conditioned by effects of various stress factors of the habitat and is characterized by decreased metabolism, alteration of the morphology and physiology of bacterial cell, and cessation of its replication. It is important that the resistant forms of cells retain virulence and, as favorable conditions come, turn back into the active vegetative form again. The discovery of the genetic modules of bacterial toxin–antitoxin systems in recent years has made it possible to identify a number of complicated regulatory molecular mechanisms responsible for maintaining the pathogenic potential of resistant forms of causative agents of natural-focus sapronoses in interepidemic periods.

The aim of the present study was to monitor implant stability after sinus floor elevation with two biomaterials during the first 6 months of healing by a resonance frequency analysis (RFA), and how physico-chemical properties affect the implant stability quotient (ISQ) at the placement and healing sites. Bilateral maxillary sinus augmentation was performed in 10 patients in a split-mouth design using a bobine HA (BBM) as a control and porcine HA (PBM). Six months after sinus lifting, 60 implants were placed in the posterior maxilla. The ISQ was recorded on the day of surgery from RFA at T1 (baseline), T2 (3 months), and T3 (6 months). Statistically significant differences were found in the ISQ values during the evaluation period. The ISQ (baseline) was 63.8±2.97 for BBM and 62.6±2.11 for PBM. The ISQ (T2) was ~ 73.5±4.21 and 67±4.99, respectively. The ISQ (T3) was ~ 74.65±2.93 and 72.9±2.63, respectively. All the used HAs provide osseointegration and statistical increases in the ISQ at baseline, T2 and T3 (follow-up), respectively. The BBM, sintered at high temperature with high crystallinity and low porosity, presented higher stability, which demonstrates that variations in the physico-chemical properties of a bone substitute material clearly influence implant stability.

Detailed information about graft material characteristic is crucial to evaluate their clinical outcomes. The present study evaluates the physicochemical characteristics of two xenografts manufactured on an industrial scale deproteinized at different temperatures (non-sintered and sintered) in accordance with a protocol previously used in sinus lift procedures. It compares how the physico-chemical properties influence the material performance in vivo with a histomorphometric study in retrieved bone biopsies following maxillary sinus augmentation, in 10 clinical cases. X-ray diffraction analysis revealed typical structure of hydroxyapatite for both materials. Both xenografts are porous and exhibit intraparticle pores. Strong differences were observed in terms of porosity, cristallinity, and calcium/phosphate. Histomorphometric measurements on the bone biopsies showed statistically significant differences. The physicochemical assessment of both xenografts in accordance with the protocol developed at industrial scale confirmed that these products present excelent biocompatibilitity, with characteristics similar to natural bone. The sintered HAs xenograft exhibit higher osteoconductivity although were not complete resorbable (30.80±0.88% residual material). On the other hand, the non-sintered HAs xerograft induced about 25.92±1.61% of new bone and almost complete degradation after 6 months implantation. Differences in physico-chemical characteristics found between the two HAs xenograft determine different behavior of this material.

In computer vision, human action recognition is a hot topic, popularized by the development of deep learning. Current models have achieved high accuracy results on public datasets. Despite this success, they require significant computational resources for training. Given that transfer learning based techniques allow reusing what other models have already learned and training models with less computational resources, in this work we propose using a transfer learning based approach for action recognition in videos. We describe a methodology for human action recognition using transfer learning techniques in a custom dataset. The proposed method consists of four stages: 1) human detection and tracking, 2) video preprocessing, 3) feature extraction (using pretrained models with ImageNet), and 4) action recognition using a two-stream model consisting of TCNs, LSTMs, and CNNs layers. The custom dataset is imbalanced with 189, 390, 490, 854, and 890 videos per class, respectively. For feature extraction, we analyzed the performance of seven pretrained models: Inception-v3, MobileNet-v2, MobileNet-v3-L, VGG-16, VGG-19, Xception, and ConvNeXt-L. We show that the best results were obtained with the last one. Finally, using pretrained models for feature extraction allowed training in a PC with a single GPU with an accuracy of 94.9%.

Trio-based exome sequencing and high-resolution HLA typing were employed to analyze three patients with autoimmune adrenal insufficiency (AAI), including those with autoimmune polyglandular syndrome (APS) type 2, as well as their parents. Benign or likely benign variants of the AIRE gene were identified in all participants of the study. These variants, coupled with clinical data and the results of antibody studies to type I interferons, helped to exclude APS-1. Patients with APS-2, in contrast to patient with AAI, inherited distinct variants of unknown significance in the CLEC16A gene, which is associated with autoimmune diseases including AAI. Various risk alleles in other genes associated with autoimmunity were identified in all patients. HLA typing of second class loci revealed alleles related to APS types 2, 3, and 4. Nevertheless, the frequencies of the haplotypes identified are substantial in the healthy Russian population, precluding from regarding these alleles as genetic determinants linked to APS development. Immunological examination can detect antibody carriers and predict the risk of autoimmune disease development. In the future, to identify genetic predictors of autoimmune endocrinopathies, it is recommended to analyze the whole genome of patients and their relatives, examining clinically relevant variants in non-coding regions.

This paper introduces a rigorous and comprehensive approach for the assessment of marine shafting systems through the utilization of an advanced Pi-Theorem based scaling methodology. Integrating journal bearing similarity assessment and shaft-line scaling methodology with advanced dimensional analysis, the study aims to provide a methodology foundation for systematic replication and analysis of marine shafting systems through scaled models. The proposed scaling methodology ensures geometric and mechanical similarity in terms of shaft-line deflection, considering key scaling parameters such as shaft length, diameter, weight, loads, rotational speed, material properties, bearing locations, and offsets. The advanced dimensional analysis computes specific non-dimensional ratios to guarantee a close resemblance between a real-size system and a scaled lab model, enabling meaningful experimentation. The methodology is analytically derived and validated with numerical simulations for a case study, conducting comparative analysis, evaluating discrepancies, and utilizing the integrated framework for experimentation.

Marine sediment sample was collected and the total aerobic population was counted and probiotic Bacillus cereus was isolated. Then it was mixed with formulated feed by spraying, while control diet was purchased from a local aquarium. 30 days of feeding experiment was conducted. Carassius auratus fishes were randomly divided into two experimental groups in rectangular tanks. The first group served as a control in which fishes were fed with commercial feed. The second group of fish were fed with probiotic incorporated feed. After 40 days, their survival and growth performance were detected. Bacillus cereus incorporated feed significantly yielded higher survival rate of the fish compared to control. Food conversion ratio (FCR) was significantly lower than the control group. The main aim of this work is to investigate the effect of a marine probiotic bacteria, Bacillus cereus on the survival and growth performance of gold fish Carassius auratus.

Enhanced permeation retention (EPR) was a significant milestone discovery by Maeda et al. paving the road for the emerging nanomedicine as a powerful tool in the fight against cancer. Sildenafil is a potent inhibitor of phosphodiesterase 5 (PDE-5) used for treatment of erectile dysfunction (ED) through the relaxation of smooth muscles and the modulation of vascular endothelial permeability. Overexpression of PDE-5 was reported in lung, colon, metastatic breast cancers and bladder squamous carcinoma. Accordingly, there has been a growing interest in using sildenafil as monotherapy or chemoadjuvant in EPR augmentation and management of different types of cancer. Sildenafil had been reported to increase the sensitivity of tumor cells of different origins to the cytotoxic effect of chemotherapeutic agents with augmented apoptosis mediated through inducing the expression of Bad and Bax proapoptotic proteins. It was also reported that the use of sildenafil prior to the administration of Doxorubicin (DOX) increased its EPR-related concentration in breast cancer tissues by 2 folds. Further, a substantial reason of anticancer chemotherapeutic failure is due to multidrug resistance (MDR), exacerbated by the overexpression of ATP-binding cassette (ABC) transporters such as ABCB1 and ABCCs. Sildenafil has demonstrated inhibitory effects on the efflux activity of ABCC4, ABCC5, ABCB1, and ABCG2, ultimately reversing MDR caused by these transporters. In this review, we critically examine the overall potential of sildenafil in enhancing EPR-based anticancer drug delivery pointing up the outcome of the most important related preclinical and clinical studies.

Leaf mechanical wounding triggers a rapid, within minutes, release of a blend of volatile organic compounds (VOCs). Wounding-induced VOC blend is mainly composed of oxygenated ubiquitous stress volatiles such as methanol and volatile products of lipoxygenase (LOX) pathway (mainly C5 and C6 alcohols and aldehydes and their derivatives), but also includes multiple minor VOCs that collectively act as infochemicals inducing defences in non-damaged plant leaves, neighbouring plants and attracting herbivore enemies. Till present, interspecific variability of the rate of induction and magnitude of wounding-induced emissions, and the extent to which plant structural traits and physiological activity alter these emissions are poorly known. Particularly scarce is the information of the induced emissions in tropical agricultural plant species despite their economic importance and large area of cultivation at regional to global scales. We chose five tropical crops with varying photosynthetic activity and leaf structural characteristics: Abelmoschus esculentus, Amaranthus cruentus, Amaranthus hybridus, Solanum aethiopicum and Telfairia occidentalis to characterize the kinetics and magnitude of wounding-induced emissions, hypothesizing that the induced emission response is greater and faster in physiologically more active species with greater photosynthetic activity than in less active species. Rapid highly repeatable leaf wounds (12-mm cuts) were generated by a within-leaf-chamber cutting knife. Wounding-induced VOC emissions were measured continuously with a proton-transfer reaction time-of-flight mass spectrometer and gas-chromatography mass spectrometry was used to separate isomers. Twenty-three ion VOCs and twelve terpenoid molecule structures were identified, whereas ubiquitous stress volatiles methanol (on average 40% of total emissions), hexenal (24%), and acetaldehyde (11%) were the main compounds across the species. Emissions of low-weight oxygenated compounds (LOC, 70% of total), and LOX products (29%) were positively correlated across species, but minor VOC components, monoterpenoids and benzenoids were negatively correlated with LOC and LOX, indicating a reverse relationship between signal specificity and strength. There was a large interspecific variability in the rate of induction and emission magnitude, but the hypothesis of a stronger emission response in physiologically more active species was only partly supported. In addition, the overall emission levels were somewhat lower with different emission blend compared to the data reported for wild species, as well as different shares for the VOCs in the blend. The study demonstrates that wounding-dependent emissions from tropical agricultural crops can significantly contribute to atmospheric volatiles, and these emissions cannot be predicted based on current evidence of wild plant model systems.

Macadamia (Macadamia integrifolia) nuts have become an essential commodity crop in Malawi. The nuts are a lucrative commodity and are used for household consumption and income generation among farming families and as a foreign exchange earning crop at country-level. In addition, macadamia production has increased significantly in recent years in the country. Currently, Malawi is the seventh top producer of macadamia nuts, with a global market share of three percent (1,846 metric tonnes on kernel basis). In 2018, exports of macadamia kernel had a value of US$24.3 million (£19.8 million or MKW 18.01 billion). However, the bulk (85%) of the crop is grown on large commercial plantations, but the smallholder sector is emerging as vital for the future growth of the macadamia sub-sector in Malawi. Furthermore, Malawian smallholders consider macadamia production to be a low-input crop with large returns per unit area (US$14.37 kg^-1ha^-1 or MKW 10,701kg^-1ha^-1) thus a lucrative crop with high potential for poverty reduction and wealth creation among these farming families. This paper, therefore, explores: (i) the historical and current trends in macadamia nut production in Malawi; (ii) analyses the country’s macadamia value chain and (iii) discusses the constraints of macadamia production in Malawi for informed policymaking. Thus, the synthesis of the Malawian macadamia sub-sector provides an understanding of the vital contributions of macadamias to Malawi’s economic growth and improvement of livelihoods.

The influence of lignin modification on drug release and pH-dependent releasing behaviour of oral solid dosage form was investigated using three different formulations. The first formulation contains microcrystalline cellulose (MCC101) as excipient and paracetamol as active pharmaceutical ingredient (API). The second formulation includes Alcell lignin and MCC 101 as excipient and paracetamol, and the third formulation consists of carboxylated Alcell lignin, MCC 101 and paracetamol. Direct compaction was carried out in order to prepare the tablets. Lignin can be readily chemically modified due to the existence of different functional groups in its structure. The focus of this investigation is on lignin carboxylation and its influence on paracetamol control release behaviour at varying pH. Results suggest that carboxylated lignin tablets had the highest drug release, which is linked to their faster disintegration and lower tablet hardness.

Growth hormone (GH) deficiency affects up to 1 in 4,000 children and is usually treated with daily injections of GH whilst the child is still growing. With children typically diagnosed around 5 years old, this can mean over 10 years of therapy, which can place a considerable burden on the child and parent. Over three-quarters of children are estimated to be not fully compliant with therapy, which can compromise their chances of attaining their target height. In recent years, interactive mobile health (smart phone or tablet) interventions using game-like concepts, so called ‘gamification’, have increased in popularity and have demonstrated success in promoting positive self-management behaviour in children with chronic conditions, such as diabetes. The application of gamified interventions has the potential to support adherence to therapy and positive behaviour in children with GH deficiency in a number of ways: 1) By providing education in a format that the child understands and accepts (e.g. using behavioural constructs to facilitate explaining why adherence is important); 2) By providing a mechanism to reduce the anxiety and stress associated with administering the injection (e.g. diversion with a virtual pet); and 3) By providing feedback to encourage on-going engagement (e.g. rewards, progression through levels).

Philip Morris International (PMI) has developed the Population Health Impact Model (PHIM) to quantify, in the absence of epidemiological data, the effects of marketing a candidate modified risk tobacco product (cMRTP) on the public health of a whole population. Various simulations were performed to understand the harm reduction impact on the U.S. population over a 20-year period under various scenarios. The overall reduction in smoking attributable deaths (SAD) over the 20-year period was estimated as 934,947 if smoking completely went away and between 516,944 and 780,433 if cMRTP use completely replaces smoking. The reduction in SADs was estimated as 172,458 for the World Health Organization (WHO) 2025 Target and between 70,274 and 90,155 for the gradual cMRTP uptake. Combining the scenarios (WHO 2025 Target and cMRTP uptake), the reductions were between 256,453 and 268,796, depending on the cMRTP effective dose. These results show how a cMRTP can reduce overall population harm additionally to existing tobacco control efforts.

This paper presents a new method : HIVEC to learn latent vector representations of graphs in a manner that captures the semantic dependencies of sub-structures. The representations can then be used in machine learning algorithms for tasks such as graph classification, clustering etcetera. The method proposed is unsupervised and uses the information of co-occurrence of sub-structures. It introduces a notion of hierarchical embeddings that allows us to avoid repetitive learning of sub-structures for every new graph. As an alternative to deep learning methods, the edit distance similarity between sub-structures is also used to learn vector representations. We compare the performance of these methods against previous work.

This study investigates the dynamic characteristics of Natural Rubber (NR)/Polybutadiene Rubber (PBR) based hybrid magnetorheological elastomer (MRE) sandwich composite beams through numerical simulations and finite element analysis, employing Reddy's third-order shear defor-mation theory. Four distinct hybrid MRE sandwich configurations were examined. The validity of finite element simulations was confirmed by comparing them with results from magnetorheo-logical (MR) fluid-based composites. Further, parametric analysis explored the influence of magnetic field intensity, boundary conditions, ply orientation, and core thickness on beam vi-bration responses. Results reveal a notable 10.4% enhancement in natural frequencies in SC4-based beams under a 600mT magnetic field with clamped-free boundary conditions, attributed to in-creased PBR content in MR elastomer cores. However, higher magnetic field intensities result in slight frequency decrements due to filler particle agglomeration. Additionally, augmenting magnetic field intensity and magnetorheological content under clamped-free conditions improves the loss factor by 66% to 136%, presenting promising prospects for advanced applications. This research contributes to a comprehensive understanding of dynamic behavior and performance enhancement in hybrid MRE sandwich composites, holding significant implications for engi-neering applications. Furthermore, this investigation provides valuable insights into the intricate interplay between magnetic field effects, composite architecture, and vibration response.

Genetic adaptation of Hermetia illucens (BSF) to suboptimal single sourced wastes can open new perspectives for insect production. Here, four replicate BSF lines were maintained on a single sourced, low-quality wheat bran diet (WB) or on a high-quality chicken feed diet (CF) for 13 generations. We continuously evaluated evolutionary responses in several performance traits to rearing at the two diets. Subsequently, we tested responses to interchanged diets, i.e. of larvae that had been adapted to low-quality feed and to high quality feed and vice versa to evaluate costs associated with diet adaptation. BSF were found to experience rapid adaptation to the diet composition. While performances on WB diet were always inferior to CF diet, the adaptive re-sponses were stronger to the former diet. This stronger response was likely due to stronger se-lection pressure experienced by BSF fed on the low-quality single sourced diet. The interchanged diet experiment found no costs associated with diet adaptation but confirmed diet adaptation for the larval biomass and insect frass traits for the WB diet treatment. Our results revealed that BSF can rapidly adapt to diet through evolutionary responses, which has potential to be utilized to produce lines tailored to specific diets.

(1) Background: Artificial Intelligence (AI) models have shown potential in various educational contexts. However, their utility in explaining complex biological phenomena, such as Intrinsically Disordered Proteins (IDPs), requires further exploration. This study empirically evaluated the performance of various Large Language Models (LLMs) in the educational domain of IDPs. (2) Methods: Four LLMs, GPT-3.5, GPT-4, GPT-4 with Browsing, and Google Bard (PaLM 2), were assessed using a set of IDP-related questions. An expert evaluated their responses across five categories: accuracy, relevance, depth of understanding, clarity, and overall quality. Descriptive statistics, ANOVA, and Tukey's honesty significant difference tests were utilized for analysis. (3) Results: The GPT-4 model consistently outperformed the others across all evaluation categories. Although GPT-4 and GPT-3.5 were not statistically significantly different in performance (p&gt;0.05), GPT-4 was preferred as the best response in 13 out of 15 instances. The AI models with browsing capabilities, GPT-4 with Browsing and Google Bard (PaLM 2) displayed lower performance metrics across the board with statistically significant differences (p&lt;0.0001). (4) Conclusion: Our findings underscore the potential of AI models, particularly LLMs such as GPT-4, in enhancing scientific education, especially in complex domains such as IDPs. Continued innovation and collaboration among AI developers, educators, and researchers are essential to fully harness the potential of AI for enriching scientific education.

Not in the history of transmissible illnesses has there been an infection as strongly associated with acute cerebrovascular disease as the novel human coronavirus, SARS-CoV-2. While the risk of stroke has known associations with other viral infections, such as influenza and human immunodeficiency virus, the risk of ischemic and hemorrhagic stroke related to SARS-CoV-2 is unprecedented. Furthermore, the coronavirus disease 2019 (COVID-19) pandemic has so profoundly impacted psychosocial behaviors and modern medical care that we have witnessed shifts in epidemiology and have adapted our treatment practices to reduce transmission, address delayed diagnoses, and mitigate gaps in health care. In this narrative review, we summarize the history and impact of the COVID-19 pandemic on cerebrovascular disease, and lessons learned regarding the management of patients as we endure this period of human history.

A well-known result of Posner’s second theorem states that if the commutator of each element in a prime ring and its image under a nonzero derivation is central, then the ring is commutative. In the present paper, we extend this bluestocking theorem to an arbitrary ring with involution involving prime ideals. Further, apart from proving several other interesting and exciting results, we establish *-version of Vukman’s theorem [48, Theorem 1]. Precisely, we describe the structure of quotient ring A/L, where A is an arbitrary ring and L is a prime ideal of A. Further, by taking advantage of the *-version of Vukman’s theorem, we show that if a 2-trosion free semiprime ring A with involution admits a nonzero *-centralizing derivation, then A contains a nonzero central ideal. This result is in a spirit of the classical result due to Bell and Martindale [19, Theorem 3]. As the applications, we extends and unify several classical theorems proved in [6],[25,[42], and [48] . Finally, we conclude our paper with a direction for further research.

Cereals and cassava-based foods serve as major dietary sources for several households in Nigeria. However, these foods are highly prone to contamination by moulds and aflatoxins owing to poor storage and vending practices. We therefore studied the fungal diversity of maize, cassava-based flour (pupuru) and rice vended in markets from Ondo state, Nigeria, and assessed the aflatoxin levels of these using Enzyme-Linked Immunosorbent Assay. Fungi were detected in 93 (88 %) of the 106 food samples. Molecular analysis of 65 representative isolates revealed 26 species belonging to 5 genera: Aspergillus (80.9 %), Penicillium (15.4 %) and Talaromyces (1.9 %) in the Ascomycota; Syncephalastrum (1.2 %) and Lichtheimia (0.6%) in Mucoromycota. Aspergillus flavus was the predominant species in the food samples. Aflatoxins were found in 98 % of the 42 representative food samples and about one half (49.8 %) exceeded the 10 μg/kg threshold adopted in Nigeria for total aflatoxins. Integrated mitigation options, including at post-harvest stages, are suggested to ensure consumer safety.

Cryptococcal meningitis remains a significant opportunistic infection among HIV-infected patients, contributing 15%-20% of HIV-related mortality. A complication of initiating Antiretroviral therapy (ART) following opportunistic infection is Immune Reconstitution Inflammatory Syndrome (IRIS). IRIS afflicts 10-30% of HIV-infected patients with cryptococcal meningitis (CM), but its immunopathogenesis is poorly understood. We compared circulating T cell memory subsets and cytokine responses among 17 HIV-infected Ugandans with CM: 11 with and 6 without CM-IRIS. At meningitis diagnosis, stimulation with cryptococcal capsule component, glucuronoxylomannan (GXM) elicited consistently lower frequencies of CD4⁺ and CD8⁺ T cell memory subsets expressing intracellular cytokines (IL-2, IFN-γ and IL-17) among subjects who subsequently developed CM-IRIS. After ART initiation, T cells evolved to show a decreased CD8⁺ central memory phenotype. At the onset of CM-IRIS, stimulation more frequently generated polyfunctional IL-2⁺/IL-17⁺ CD4⁺ T cells in patients with CM-IRIS. Moreover, CD8⁺ central and effector memory T cells from CM-IRIS subjects also demonstrated more robust IL-2 responses to antigenic stimulation vs. controls. Thus, ART during CM elicits distinct differences in T cell cytokine production in response to cryptococcal antigens both prior to and during the development of IRIS, suggesting an immunologic foundation for the development of this morbid complication of CM infection.

A remote sensing-based evapotranspiration (ET) study was conducted over the Central Arizona Irrigation and Drainage District (CAIDD), an Arizona agricultural region. ET was assessed means for 137 wheat plots, 183 cotton plots, and 225 alfalfa plots. The remote sensing ET models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. The models produced similar daily ET for wheat, with 6–8 mm/d mid-season. For cotton and alfalfa daily ET showed greater differences, where TSEB produced largest daily ET, METRIC the least, and VISW in the midrange. Modeled cotton ET at mid-season ranged from 9.5 mm/d (TSEB), to 8 mm/d (VISW), and 6 mm/d (METRIC). For alfalfa ET, values at peak cover ranged from 8 mm/d (TSEB), 6 mm/d (VISW), and 5 mm/d (METRIC). Model bias ranged −10% to +18%. Relative to potential ET, FAO-56 ET, and USDA-SW gravimetric-ET, model variability ranged from negligible to 35% of annual crop water use. Model averaging was found a useful way to consider and reconcile all ET estimates.

Structure from Motion with Multi-View Stereo photogrammetry (SfM) is increasingly utilised in geoscience investigations as a cost-effective method of acquiring high resolution (sub-meter) topographic data, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via an Unmanned Aerial Vehicle, ‘UAV’) and ground-based (via a handheld digital camera, ‘Ground’) SfM in modelling a hillslope gully system in dry-tropical savanna, and to assess the strengths and limitations of the approach at different scales. A UAV survey covered an entire hillslope gully system (0.715 km²), whereas a Ground survey covered a single gully within the broader system (650 m²). SfM topographic models, including Digital Surface Models (DSM) and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM). Results indicate UAV SfM can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., 0.1 m resolution with ~ 0.5 – 1.3 m elevation error), while ground-based SfM is more capable of quantifying gully morphology (e.g., 0.01 m resolution with ~ 0.1 m elevation error). Key strengths of SfM for these applications include: the production of high resolution 3D topographic models and ortho-photo mosaics, low survey instrument costs (< $AUD 3,000); and rapid survey time (4 and 2 hours for UAV and Ground survey respectively). Current limitations of SfM include: difficulties in reconstructing vegetated surfaces; uncertainty as to optimal survey and processing designs; and high computational demands. Overall, this study has demonstrated great potential for SfM to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in tropical savanna landscapes and elsewhere.

Some studies have demonstrated that in vivo degradation processes are influenced by the material’s physico-chemical properties. The present study compares two hydroxyapatites manufactured on an industrial scale, deproteinized at low and high temperatures, and how physico-chemical properties can influence the mineral degradation process of material performance in bone biopsies retrieved 6 months after maxillary sinus augmentation. Residual biomaterial particles were examined by field scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) to determine the composition and degree of degradation of the bone graft substitute material. According to the EDX analysis, the Ca/P ratio significantly lowered in the residual biomaterial (1.08±0.32) compared to the initial composition (2.22±0.08) for the low-temperature sintered group, which also presented high porosity, low crystallinity, low density, a large surface area, and poor stability and a high resorption rate compared to the high-temperature sintered material. This demonstrates that variations in the physico-chemical properties of bone substitute material clearly influence the degradation process. Further studies are needed to determine whether the resorption of deproteinized bone particles proceeds slowly enough to allow sufficient time for bone maturation to occur.

Gilbert's syndrome (GS) is a common hereditary condition characterized by mild increases in serum bilirubin levels due to inherited defects in bilirubin metabolism. This review, based on data from peer-reviewed articles and journals spanning from 1977 to January 2024, provides a comprehensive overview of over four decades of research on GS. Early studies primarily focused on defining the clinical and genetic characteristics of the syndrome, laying the foundation for subsequent investigations. More recent research has delved into the genetic mechanisms underlying the reduced expression of bilirubin UDP-glucuronosyltransferase, which has significantly enhanced our understanding of the pathogenesis of GS. Furthermore, recent studies have shed light on the clinical implications of GS, including its association with non-alcoholic fatty liver disease and mortality risk, highlighting the complex interplay between genetic factors, bilirubin metabolism, and clinical outcomes. Despite its generally benign nature, thorough research is essential to fully understand the impact of GS on patients' lives. This review emphasizes the importance of ongoing research to deepen our understanding of GS and its broader implications.

Considering the increasing interest in understanding the biotic component of methane removal from our atmosphere, it becomes essential to study the physiological characteristics and genomic potential of methanotroph isolates, especially their traits allowing them to adapt to elevated growth temperatures. The genetic signatures of Methylocaldum species have been detected in many terrestrial and aquatic ecosystems. A small set of representatives of this genus has been isolated and maintained in culture. The genus is commonly described as moderately thermophilic, with the growth optimum reaching 50oC for some strains. Here, we present a comparative analysis of genomes of three Methylocaldum strains—two terrestrial M. szegediense strains (O-12 and Norfolk) and one marine strain Methylocaldum marinum (S8). The examination of the core genome inventory of this genus uncovers significant redundancy in primary metabolic pathways, including the machinery for methane oxidation (numerous copies of pmo genes) and methanol oxidation (duplications of mxaF, xoxF1-5 genes), three pathways for one-carbon (C1) assimilation, and two methods of carbon storage (glycogen and polyhydroxyalkanoates). We also investigate the genetics of melanin production pathways, as a key feature of the genus.

The recent rise in ocean temperatures, accompanied by other environmental changes, has notably increased the occurrence and spread of diseases in Octocorallia, of which many species are integral to shallow tropical and subtropical coral reef ecosystems. This study focuses on the understanding of these diseases, which has been largely limited to symptomatic descriptions, with clear etiological factors identified in only a fraction of cases. A key example is the multifocal purple spots syndrome (MPSS) affecting the common Caribbean octocoral sea fan Gorgonia ventalina, linked to the gall-forming copepods of the genus Sphaerippe, a member of the widespread family Lamippidae. The specialized nature of these copepods as endoparasites in octocorals suggests the potential for the discovery of similar diseases across this host spectrum. Our investigation employed four molecular markers to study disease hotspots in Saint Eustatius, Curaçao, northwest and southwest Cuba, and Bonaire. This led to the discovery of a group of copepod species in these varied Caribbean locations. Importantly, these species are morphologically indistinguishable through traditional methods, challenging established taxonomic approaches. The observed diversity of symbionts, despite the host species' genetic uniformity, is likely due to variations in larval dispersal mechanisms. Our phylogenetic analyses confirmed that the Lamippidae copepods belong to the order Poecilostomatoida (Copepoda) and revealed their sister group relationship with the Anchimolgidae, Rhynchomolgidae, and Xarifiidae clades, known for their symbiotic relationships with scleractinian corals. These results add to our understanding of the evolutionary and ecological interactions of copepods and their hosts, and the diseases they cause, important data in a changing climate.

The new coronavirus SARS-CoV-2 is the cause of the COVID-19 pandemic, which has created an incomparable global health problem. PLpro is a key protein involved in viral polyprotein processing and immune system evasion, making it a prime target for the development of antiviral drugs to combat COVID-19. The review begins by elucidating the functional and structural properties of SARS-CoV-2 PLpro, underscoring its significance in viral pathogenicity and replication. Employing homology modeling, a tertiary structure model of PLpro is constructed, laying the groundwork for subsequent investigations. To expedite the search for potential therapeutic candidates, the study harnesses computational methodologies. Molecular docking techniques are employed to explore binding sites for antiviral drugs within the catalytic region of PLpro. This computational approach not only aids in drug development but also provides crucial preliminary data before experimental research commences. The stability of drug-PLpro complexes is assessed through comprehensive all-atom molecular dynamics (MD) simulations, affording dynamic insights into drug-PLpro interactions. By evaluating binding energy estimates from MD simulations, stable drug-PLpro complexes with potential antiviral properties are identified. However, it is emphasized that experimental validation is imperative to confirm these computational findings, necessitating in vitro and in vivo tests to assess safety and efficacy. This pivotal stage bridges the computational realm with real-world clinical applications. The review emphasizes the imperative need for enhancements in the existing PLpro-targeting drugs currently on the market. Their actions are insufficient for clinical use and necessitate thorough characterization and improvement. The Supervised Molecular Dynamics (SuMD) simulation technique reveals critical information about drug unbinding pathways, shedding light on opportunities for refinement. In addition to optimizing existing drugs, the investigation of sub-structurally similar molecules emerges as a promising avenue for drug development. In conclusion, the review underscores the pivotal role of targeting SARS-CoV-2 PLpro in the ongoing battle against COVID-19. By integrating molecular dynamics simulations, structural modeling, and computational insights, a robust foundation is established for identifying promising antiviral drug candidates. The continual need for improvement in existing drugs and the exploration of novel compounds remain paramount in the global effort to combat COVID-19. The evolution and management of COVID-19 hinge on the symbiotic relationship between computational insights and experimental validation, illustrating the interdisciplinary synergy crucial to this endeavor.

Smart livestock farming leverages technology to boost production and meet food demand sustainably. This study delves into smart technologies in animal production, covering opportunities, challenges, and solutions. Smart agriculture employs modern technology to enhance efficiency, sustainability, and animal welfare in livestock farming. It includes remote monitoring, GPS-based animal care, robotic milking, smart health collars, predictive disease control, and other innovations to achieve these goals. While smart animal production holds great promise, it does face challenges related to cost, data management, and connectivity. To address these challenges, potential solutions include remote sensing, technology integration, and farmer education. Smart agriculture offers opportunities for increased efficiency, improved animal welfare, and enhanced environmental conservation. A well-planned approach is crucial to maximize the benefits of smart livestock production while ensuring its long-term sustainability. This study confirms the growing adoption of smart agriculture in livestock production, with the potential to support sustainable development goals and deliver benefits such as increased productivity and resource efficiency. To fully realize these benefits and ensure the sustainability of livestock farming, it is essential to address cost and education challenges. Therefore, this study recommends promoting a positive outlook among livestock stakeholders and embracing smart agriculture to enhance farm performance.

BACKGROUND: Cervical cancer is the second most frequent cancer among women worldwide between 14 and 49 years of age including Nigeria. Figures have greatly reduced in developed countries after the introduction and implementation of effective screening and vaccination programs which is greatly undeveloped and inefficient in Nigeria and other developing countries at large. OBJECTIVES: The study assessed the knowledge and attitude of reproductive age women towards cervical cancer prevention in selected tertiary institutions in Osun State. METHODOLOGY: The study was a descriptive cross-sectional study carried out among reproductive age women in selected tertiary institutions in Osun State, Nigeria. A probability based multistage sampling technique was adopted as the sampling technique for the study. Data was collected using a semi-structured, self-administered and interviewer guided questionnaire. RESULTS: Age of respondents was 25.305±8.195. 313(79.0%) of the total respondents were Christians, and 83(21.0%) of the respondents were Muslims. For the overall knowledge score, only 52.0% of the respondents had good knowledge while 48.0% of the respondents had poor knowledge. 52.0% exhibited negative attitude towards cervical cancer prevention while 48% exhibited positive attitude towards cervical cancer prevention. Only 23% of the respondents had taken part in screening and vaccination towards cervical cancer prevention while 77% of the respondents had not. CONCLUSION: The knowledge of reproductive age women towards cervical cancer prevention was above average while their attitude towards cervical cancer prevention was low. This issue could be addressed by increasing the awareness of the effects of cervical cancer among reproductive age women in the country.

Leishmaniasis is one of the Neglected tropical diseases. Studies show that the poor knowledge about epidemiological aspects of Leishmaniasis within communities causes the collapse of existing disease control programs. Therefore, the present study focuses on a detailed survey of the existing awareness among the threatened population in the Medawachchiya PHI Area in the Anuradhapura District, Sri Lanka aiming to assist the health staff to organize community-based vector control programs effectively in the future. Assessment of the awareness of the two hundred and seventy households (n=270) residents from ten GNDs was carried out by using a structured questionnaire. Among 143 females and 134 males, only 75.1% have knowledge about the disease. 5.8%(n=16) of the participants know only about the vector and 28.9% (n=80) know their control methods. The study shows a shortage of a considerable amount of awareness about the disease among the studied population The study found that age and education levels had significant impacts on knowledge, attitudes, and practices. However, factors like gender, marital status, occupation, income, and expenses did not show significant correlations. The present study suggests the huge scope for community-related vector control methods for greater achievements in vector control methods by implementing a continuous educational program.

Fault detection in PV arrays and inverters is critical for ensuring maximum efficiency and performance. Artificial intelligence (AI) learning can be used to quickly identify issues, resulting in a sustainable environment with reduced downtime and maintenance costs. As the use of solar energy systems continues to grow, the need for reliable and efficient fault detection and diagnosis techniques becomes more critical. This paper presents a novel approach for fault detection in photovoltaic (PV) arrays and inverters, combining AI techniques. It integrates Elman Neural Network (ENN), Boosted Tree Algorithms (BTA), Multi-layer Perceptron (MLP), and Gaussian Processes Regression (GPR) for enhanced accuracy and reliability in fault diagnosis. It leverages their strengths for accuracy and reliability of fault diagnosis. Feature engineering-based sensitivity analysis was utilized for feature extraction, the fault detection and diagnosis were assessed using several statistical criteria including PBAIS, MAE, NSE, RMSE, and MAPE. Two intelligent learning scenarios are carried out, the first scenario is done for PV array fault detection with DC power (DCP) as output. The second scenario is done for inverter fault detection with AC power (ACP) as the output. The proposed technique is capable of detecting faults in PV arrays and inverters, providing a reliable solution for enhancing the performance and reliability of solar energy systems. Real-world solar energy dataset is used to evaluate the proposed technique, with results compared to existing detection techniques and obtained results show that it outperforms existing fault detection techniques, achieving higher accuracy and better performance. The GPR-M4 optimization justified reliably among all the models with MAPE=0.0393, and MAE=0.002 for inverter fault detection and MAPE=0.091, and MAE=0.000 for PV array fault detection.