Background This paper draws learnings and successes based on field implementation experience spanning four years (2016–2019) of implementing CLTS by Prince of Peace Orphans and Widows Vision, a community-based organization located in Kaberamaido district in eastern Uganda. Methods The study aimed to document, disseminate and inform from an evidence-based point of view how adaptation and collaborative engagements triggers learning from mistakes to inform iterative changes from improvements and success.This is a descriptive paper that used project documents review based on field implementation experience. Existing project reports were synthesised, collated and curated for evidence. Data were drawn from project reports and records to inform narratives in writing. Implementation of the project was executed in homogenous rural communities occupied by people of the same dialect, cultural and social settings. Results We note that success in CLTS implementation can hardly be achieved by merely following prescriptions in handbooks and guidelines but rather by devising innovative community engagement and other participatory and community-driven techniques that foster adaptive management, promote ownership, and buy-in.Having learned from our failures, we used data to inform decisions and transformatively deviated from traditional CLTS implementation and introduced high impact and innovative approaches such as the use of CLTS helpdesks and Situation room, the Pamoja approach, learning labs and iterative feedback loops, innovatively tackling slippage and carefully introducing the follow-up mandona approach. These enhanced experiential learning and ultimately resulted in sustained sanitation behaviour. Conclusions The CLTS approach as outlined in the handbook needs to be flexibly adapted to address contextual needs. Reflective and learning sessions reinforced with routine feedback loops from implementers and beneficiaries yields tremendous results, propagates experiential learning, and ultimately results in a transformative deviation from undesirable to desired sanitation behaviours. These innovative approaches once carefully blended have proved to be sustainable, are adaptable and can work in an even larger scale and in a variety of contexts.

In this study, a composite flame retardant was created by combining fish scale (FS), fishery waste, and ammonium polyphosphate (APP), a commercially available flame retardant. The composite flame retardant was added to epoxy resin (EP) to form an EP/APP/FS composite that prevents burns and is environmentally friendly. The use of FS conforms to the concept of circular economy and lowers costs by reducing the consumption of APP. Thermogravimetric analysis (TGA), integral procedural decomposition temperature (IPDT), pyrolysis kinetics, limiting oxygen index (LOI), the Underwriters Laboratories 94 (UL94) flammability test, scanning election microscopy, Raman spectroscopy, and energy-dispersive X-ray spectroscopy were used to determine the thermal properties, flame retardant properties, flame retardant mechanism, char morphology, and composition of the composites. The TGA results indicated that the addition of 40% flame retardant raised the char residue from 16.45 wt% (pure EP) to 36.07 wt%, IPDT from 685.6 °C (pure EP) to 1143.1°C, LOI from 21% (pure EP) to 30%, and UL94 classification from fail (pure EP) to V-0. These results suggest an increase in char residue, which indicates better protection of the polymer matrix material. The improvements in IPDT, LOI, and UL94 classification, which indicate greater thermal stability, lower flammability (from flammable to fireproof), and higher flammability rating (from fail to V-0), respectively, suggest that the composite material has favorable thermal properties and is less inflammable.

Eco-friendly and low-cost water-based nanolubricants containing rutile TiO2 nanoparticles (NPs) were developed for accelerating their applications in industrial-scale hot steel rolling. The lubrication performance of developed nanolubricants was evaluated in a 2-high Hille 100 experimental rolling mill at a rolling temperature of 850 ℃ in comparison to that of pure water. The results indicate that the use of nanolubricant enables to decrease the rolling force, reduce the surface roughness and the oxide scale thickness, and enhance the surface hardness. In particular, the nanolubricant consisting of 4 wt% TiO2, 10 wt% glycerol, 0.2 wt% sodium dodecyl benzene sulfonate (SDBS) and 1 wt% Snailcool exhibits the best lubrication performance by lowering the rolling force, surface roughness and oxide scale thickness up to 8.1%, 53.7% and 50%, respectively. The surface hardness is increased by 4.4%. The corresponding lubrication mechanisms are attributed to its superior wettability and thermal conductivity associated with the synergistic effect of rolling, mending and laminae forming that are contributed by TiO2 NPs.

Biological gels (bio-gels) are hydrated polymer networks that serve diverse biological functions, which often lead to intentional or unintentional exposure to particulate matter. In this work, we derive a microscopically motivated framework that enables the investigation of penetration mechanisms into bio-gels. We distinguish between two types of mechanisms: spontaneous (unforced) penetration and forced penetration. Using experimental data available in literature, we exploit the proposed model to characterize and compare between the micro-structures of respiratory, intestinal, and cervicovaginal mucus and two types of biofilms. Next, we investigate the forced penetration process of spherical and ellipsoidal particles into a locally quadrilateral network. The proposed framework can be used to improve and complement the analysis of experimental findings in vitro, ex vivo, and in vivo. Additionally, the insights from this work pave the way towards enhanced designs of nano-medicines and allow to assess risk factors related to the nano-pollutants exposure.

Huge filaments with scales from several hundred megaparsecs to gigaparsecs are detected in the distribution of galaxies and clusters, quasars, gamma-bursters. The hypothesis on the nature of the huge filaments as regions of space-time deformation is proposed. An anisotropic deformation of the local region is described by the strain tensor, it depends on the velocities of matter. Galaxies get an extra velocity in the region, which leads to the formation of filamentary structures. The class of exact solution of the GR equations is constructed by introducing the special definition of the Christoffel symbols as function of the velocity of matter. With a definition of these symbols, the motion matter equation turns into identity. For the sake of simplicity, an ideal fluid is considered.

Severe postoperative pain affects most patients after thoracotomy and is a risk factor for post-thoracotomy pain syndrome (PTPS). This randomized controlled trial compared preemptively administered ketamine versus paravertebral block (PVB) versus control in patients undergoing posterolateral thoracotomy. The primary outcome was acute pain intensity on the visual analog scale (VAS) on the first postoperative day. Secondary outcomes included morphine consumption, patient satisfaction, and PTPS assessment with Neuropathic Pain Syndrome Inventory (NPSI). Acute pain intensity was significantly lower with PVB compared to other groups at four out of six time points. Patients in the PVB group used significantly less morphine via a patient-controlled analgesia pump than participants in other groups. Moreover, patients were more satisfied with postoperative pain management after PVB. PVB, but not ketamine, decreased PTPS intensity at 1, 3, and 6 months after posterolateral thoracotomy. Acute pain intensity at hour 8 and PTPS intensity at month 3 correlated positively with PTPS at month 6. Bodyweight was negatively associated with chronic pain at month 6. Thus, PVB but not preemptively administered ketamine decreases both acute and chronic pain intensity following posterolateral thoracotomies. The trial was prospectively registered at the Australian New Zealand Clinical Trial Registry (https://www.anzctr.org.au/; ACTRN12616000900415; 07 July 2016).

In this work a modified version of the well-known Simple Water Balance (SWB) model, comprising here three parameters instead of one, was used. Although simple, the model was tested in large-scale river basins in east-central Greece, upstream two hydrometric stations. The available historic runoff records comprised 19 hydrologic years each, on a monthly basis. Thirteen among them were used for calibrating the model, whereas the six subsequent, for validating it. Two different efficiency criteria were used as a measure of performance of the modified model. Their values, calculated for both calibration and validation stages, were close and relatively high. Thus, keeping in mind both the size and complexity of the river basins studied, one can conclude that the modified model, despite its simplistic concept and lumped form, fits satisfactorily the historic runoff series.

Mill scale is the by-product of iron and steel industry. It can be recycled via sinter plant or solid as sinter feed materials. 85 to 90% of the constituent particles are more than 0.008 inches. The iron content is near around 70 %, with a very small amount of alkaline compounds and non-ferrous metals. Mill scale is polluted and contaminated with lubricants, oils and greases from the equipment. In this experiment for recovering of oil from mill scale, it is treated with three different methods. Then all methods were compared according to the ability of oil elimination and iron recovered. After washing and boiling with surfactants, large amount of polluted waste water becomes a problem for environment so this wastewater was utilized for making of Microbial Fuel Cells (MFCs), production of electricity in MFC depends on the biodegradation of organic materials, so different waste were added in wastewater for making MFC. The remaining of MFC was converted in bioethanol, biodiesel and biofertilizer. So this research is economical and environmentally friendly and fulfilled the important aspect of green environment with zero waste. It will be a mile stone in the research of metallurgy, environmental engineering, recycling technology and zero waste management.

While deforestation rates decline globally they are rising in the Western Amazon. Artisanal-scale gold mining (ASGM) is a large cause of this deforestation and brings with it extensive environmental, social, governance, and public health impacts, including large carbon emissions and mercury pollution. Underlying ASGM is a broad network of factors that influence its growth, distribution, and practices such as poverty, flows of legal and illegal capital, conflicting governance, and global economic trends. Despite its central role in land use and land cover change in the Western Amazon and the severity of its social and environmental impacts, it is relatively poorly studied. While ASGM in Southeastern Peru has been quantified previously, doing so is difficult due to the heterogeneous nature of the resulting landscape. Using a novel approach to classify mining that relies on a fusion of CLASlite and the Global Forest Change dataset, two Landsat-based deforestation detection tools, we sought to quantify ASGM-caused deforestation in the period 1984–2017 in the southern Peruvian Amazon and examine trends in the geography, methods, and impacts of ASGM across that time. We identify nearly 100,000 ha of deforestation due to ASGM in the 34-year study period, an increase of 21% compared to previous estimates. Further, we find that 10% of that deforestation occurred in 2017, the highest annual amount of deforestation in the study period, with 53% occurring since 2011. Finally, we demonstrate that not all mining is created equal by examining key patterns and changes in ASGM activity and techniques through time and space. We discuss their connections with, and impacts on, socio-economic factors, such as land tenure, infrastructure, international markets, governance efforts, and social and environmental impacts.

The thermal lubrication of an entangled polymeric liquid in wall-driven shear flows between parallel plates is investigated by using a multiscale hybrid method coupling molecular dynamics and the hydrodynamics (i.e., the synchronized molecular dynamics method). The temperature of the polymeric liquid rapidly increases due to viscous heating once the drive force exceeds a certain threshold value. The rheological properties of the polymeric liquid drastically change at around the critical drive force. In the weak viscous-heating regime, the conformation of polymer chains is dominated by the local shear flow so that the anisotropy of the bond orientation tensor grows as the drive force increases. However, in the large viscous-heating regime, the conformation dynamics is dominated by the thermal agitation of polymer chains so that the bond orientation tensor recovers more uniform and random structures as the drive force increases, even though the local shear flows are further enhanced. Remarkably, these counter-intuitive transitional behaviors give an interesting re-entrant transition in the stress--optical relation, where a linear formalism in the stress--optical relation approximately holds even though each of the macroscopic quantities behaves nonlinearly. The robustness of the linear stress--optical relation is also confirmed in the spatiotemporal evolution at the hydrodynamic level.

We focus on macromolecules which are modelled as sequentially growing dual scale-free networks. The dual networks are built by replacing star-like units of the primal treelike scale-free networks through rings, which are then transformed in a small-world manner up to the complete graphs. In this respect, the parameter γ describing the degree distribution in the primal treelike scale-free networks regulates the size of the dual units. The transition towards the networks of complete graphs is controlled by the probability p of adding link between non-neighbouring nodes of the same initial ring. The relaxation dynamics of the polymer networks is studied in the framework of generalized Gaussian structures by using the full eigenvalue spectrum of the Laplacian matrix. The dynamical quantities on which we focus here are the averaged monomer displacement and the mechanical relaxation moduli. For several intermediate values of the parameter’s set (γ, p) we encounter for these dynamical properties regions of constant in-between slope.

It is important to realize the transformation behavior of wüstite because it greatly affects the final structure of the oxide layer and the surface quality of the steel products. In the present study, the transformation behaviors of the wüstite layer are examined under nearly-oxygen-free conditions, to simulate the cooling processes after the hot rolled strip is coiled. As the single phase wüstite was prepared at 950˚C, the 460˚C transformed oxide layer was composed of a mixture of iron and magnetite formed through eutectoid reactions. For the 750˚C-fabricated wüstite, only magnetite was observed after transformation, without iron precipitates and residual wüstite. It is speculated that the unusual transformation behavior of the low-temperature-made wüstite results from the pseudo-structural intermediate phase transformation between wüstite and magnetite. This pseudo-structure is a pre-transformed wüstite and of various concentration of ferrous ion, which is determined by the fabrication conditions. During the hot strip mill process, the so-called wet scale, wüstite, is produced continuously from finish mill to laminar flow sections and ended at 570˚C. Consequently, the final eutectoid transformation below 570˚C is dominantly controlled by the surface temperature ranged from 750˚C to 950˚C for low carbon steel.

TThe following three objectives were tested in this study: (1) investigate the utility of low-altitude remote sensing using UAS technology to compare the effects of different N application systems in rice production; (2) use spatial extrapolation to scale up plot-level generated to farmer field rice yield data based on crop spectral signatures, and (3) predict and map out rice productivity as a function of N placement systems. Images were captured on a UAV platform at midseason of the rice crop. Orthomosaics were developed for selected fields in rice-producing zones. Grain yields were assessed from low, medium, and high crop health plots delineated based on NDVI values. On the plot scale, UDP outyielded non-UDP by 0.84%. Individual plot yield data were scaled up to the farmer field level through Jenks natural breaks classification and es-tablishing an empirical relationship between OSAVI and plot yields. Assessment of the scaled-up field levelfield-level data also confirmed the superiority of UDP N man-agement over the non-UDP systems in promoting rice yields. Scaling up plot scale da-ta to whole field levels also facilitated generating and mapping expected yield maps for individual farmer fields in the three zones studied. This study has established a tangible simple but tangible protocol protocol for predicting and mapping rice yields in small-scale farmer fields using UAS data.

Evolution remains an incessant process in viruses, allowing them to elude host immune response and induce severe diseases, impacting the diagnostic and vaccine effectiveness. Predicting emerging viral genomes is crucial, particularly in diseases like dengue, where viruses disrupt host cells, leading to fatal outcomes. Deep learning has been applied to predict dengue fever cases; there has been relatively less emphasis on its significance in forecasting emerging Dengue Virus (DENV) serotype. While Recurrent Neural Networks (RNN) were originally designed for modeling temporal sequences, our proposed DL-DVE generative and classification model, trained on complete genome data of DENV, transcends traditional approaches by learning semantic relationships between nucleotides in a continuous vector space instead of representing contextual meaning of nucleotide characters. Leveraging 2000 publicly available DENV complete genome sequences, our Long Short-Term Memory (LSTM) based generative and Feedforward Neural Network (FNN) based classification DL-DVE model showcases proficiency in learning intricate patterns and generating sequences for emerging serotype of DENV. The generative model showed accuracy of 93% and the classification model provided insight into the specific serotype label, corroborated by BLAST search verification. Evaluation metrics such as ROC-AUC value 0.818, accuracy, precision, recall and F1 score all to be around 99.00%, demonstrated the classification model’s reliability.  Our model classified the generated sequences as DENV-4, exhibiting 65.99% similarity to DENV-4 and around 63-65% similarity with other serotypes, indicating notable distinction from other serotypes. Moreover, the intra-serotype divergence of sequences with a minimum 90% similarity underscored their uniqueness. We analyzed the conserved motifs in the genome through MEME Suite (version 5.5.5). Our research strives to contribute to the ongoing fight against the Dengue virus by offering predictive insights into its genomic evolution. Looking ahead, proactive predictive modeling before mutations occur holds potential for guiding vaccine design and diagnostic kit development.

Heteroresistance (HR) to colistin is especially concerning in settings where multi-drug resistant (MDR) K. pneumoniae are prevalent and empiric use of colistin might lead to treatment failures. This study aimed to assess the frequency of occurrence of colistin HR (CHR) among (MDR) K. pneumoniae (n=676) isolated from patients hospitalized in 13 intensive care units (ICUs) in 6 European countries in a clinical trial assessing the impact of decolonization strategies. All isolates were whole-genome-sequenced and studied for in vitro colistin susceptibility. Majority were colistin-susceptible (CS) (n=597, MIC 2 µg/ml). 288 CS isolates were randomly selected for population analysis profiling (PAP) to assess CHR prevalence. CHR was detected in 108/288 CS K. pneumoniae. No significant association was found between the occurrence of CHR and country, MIC-value, K-antigen type and O-antigen type. Overall, 92% (618/671) of the K. pneumoniae were MDR with high prevalence among CS (540/592) and CR (98.7%, 78/79) isolates. In contrast, proportion of carbapenemase-producing K. pneumoniae (CP-Kpn) was higher among CR (72.2%, 57/79) than CS isolates (29.1%, 173/594). Proportions of MDR and CP-Kpn were similar among CHR (MDR: 85%, 91/107; CP-Kpn: 29.9%, 32/107) and CS isolates (MDR: 91%, 539/592; CP-Kpn: 29.1%, 153/59). WGS analysis of PAP isolates showed diverse insertion elements in mgrB or even among technical replicates underscoring the stochasticity of the CHR phenotype. CHR isolates showed high ST diversity (Simpson’s diversity index, SDI: 0.97, in 52 of the 85 STs tested). CR (SDI: 0.85) isolates were highly associated with specific STs (ST101, ST147, ST258/ST512, P ≤ 0.003). The widespread nature of CHR among MDR K. pneumoniae in our study urge the development of rapid HR detection methods to inform on the need for combination regimens.

Whole genome alignment (WGA) is a critical process in comparative genomics, facilitating the detection of genetic variants and aiding our understanding of evolution. This paper offers a detailed overview and categorization of WGA techniques, encompassing suffix tree-based, anchors-based, and graph-based methods. It elaborates on the algorithmic properties of these tools, focusing on performance and methodological aspects. The paper underscores the latest progress in WGA, emphasizing the increasing capacity to manage the growing intricacy and volume of genomic data. However, the field still grapples with computational and biological hurdles affecting the precision and speed of WGA. We explored these challenges and potential future solutions. This paper aims to provide a comprehensive resource for researchers, deepening our understanding of WGA tools and their applications, constraints, and prospects.

Opossums, native to the Americas, are unique marsupials with over 100 species. The Common Opossum and Virginia Opossum are notable species. They are nocturnal, omnivorous, and adapt to various habitats. Their reproduction involves a short gestation and marsupial pouch development. Despite their ecological benefits like seed dispersal and insect control, their proximity to human habitats exposes them to pathogens, posing public health risks. These include protozoa, helminths, and arthropods that can spread zoonotic parasites and vector-borne diseases. The marsupial immune system, including opossums, is complex, rivaling eutherian mammals. Key immune genes were identified in the grey short-tailed opossum genome. CD1 protein and VpreB surrogate light chain were also found. Marsupials are proposed as ideal models for studying developmental immunology. A West Indian opossum (Didelphis marsupialis) was found and examined. Blood tests revealed abnormalities, including a low white blood cell count and signs of anemia. The results contribute to understanding the species’ health and adaptability in the wild.

Gene editing is now easy to make new disease models through in-vivo and in vitro tests. It can potentially be used to make animals with single-gene or multiple-gene changes. The mutant strains with changed germlines are no longer needed with in vivo gene editing, which uses the CRISPR-Cas9 system to target cells of interest in their normal tissues. Whereas, the AAVs and other viral vectors have made it possible to change cells selectively. Gene editing hade made it possible to use human induced pluripotent stem cells (iPSC) to model diseases that run in families. Researchers can compare and contrast the human genomes of many different ethnic and racial groups using this method. Scientists may be able to make a disease in a lab dish using iPSCs from a patient. Using CRISPR, iPSCs made from patient cells can be fixed if they have certain problems. This shows that gene therapy is possible and shows what happens when cells aren't working right. The fact that CRISPR-Cas9 can change the DNA by just one nucleotide has had a huge effect on biological studies. CRISPR is becoming more and more popular, which shows how useful, easy, and effective it is. With the broad use of CRISPR-based apps, the tool is now used for much more than just changing genes. This method can be used to screen the whole genome, control the translation of genes based on their sequence, and edit several genes at the same time. Scientists can now model diseases in different species and learn more about how genes work because of these advances. Genome-wide association studies and genome-editing tools like CRISPR are giving us a good look at the future of personalized medicine.

Mercury (Hg) pollution not only poses a threat to the environment but also adversely affects the growth and development of plants, with potential repercussions for animals and humans through bioaccumulation in the food chain. Maize, a crucial source of food, industrial materials, and livestock feed, requires special attention in understanding the genetic factors influencing mercury accumulation. Developing maize varieties with low mercury accumulation is vital for both maize production and human health. In this study, a comprehensive genome-wide association study (GWAS) was conducted using an enlarged SNP panel comprising 1.25 million single nucleotide polymorphisms (SNPs) in 230 maize inbred lines across three environments. The analysis identified 111 significant SNPs within 78 quantitative trait loci (QTL), involving 169 candidate genes under the Q model. Compared to the previous study, the increased marker density and optimized statistical model led to the discovery of 74 additional QTL, demonstrating improved statistical power. Gene Ontology (GO) enrichment analysis revealed that most genes participate in arsenate reduction and stress responses. Notably, GRMZM2G440968, associated with the significant SNP chr6.S_155668107 of axis tissue, encodes a cysteine proteinase inhibitor, suggesting its potential role in alleviating Hg toxicity by inhibiting cysteine. Haplotype analyses provided further insights, indicating that lines carrying hap3 exhibited the lowest mercury content compared to other haplotypes. In summary, our study significantly enhances the statistical power of GWAS, identifying additional genes related to mercury accumulation and metabolism. These findings offer valuable insights into unraveling the genetic basis of mercury content in maize and contribute to the development of maize varieties with low mercury accumulation.

Background: Genome-wide association studies (GWAS) have shed light on various complex diseases and traits, by detecting more than 400,000 associated genetic loci. This number is expected to drastically increase because of the use of novel artificial intelligence methods offering new ways to study the effects of variants. Deep learning using artificial neural networks (ANN) is a sub-field of artificial intelligence, which simulates how the human brain learns. We aimed at assessing the potential of deep learning in human genetic studies of Alzheimer’s Disease (AD) and how these compare to the traditional statistical methods used in GWAS, by simultaneously testing the two approaches on the same dataset, while discovering new genetic loci associated to AD. Methods: To address this aim, phenotypic and genome-wide SNP data from the UK Biobank was analysed on a binary outcome, AD diagnosis, in two different data balance options, of one-to-one and one-to-two case-control datasets, using 2,764 cases vs 2,764 controls and 5,528 controls respectively matched on gender, age, ethnicity, PC1-20 and genotyping array. Genetic data handling and GWAS were performed using PLINK, whereas neural networks were trained using GenNet, a new ANN tool, with the same datasets, separated into training (60%), validation (20%) and test (20%) sets. Neural network layers were determined using biological knowledge, by annotating SNPs to genes and genes to AD related pathways, using ANNOVAR annotations followed by GeneSCF and KEGG. Results: Significant associations were detected between four SNPs linked to two different genes and AD for the 1 to 1 case-control study design and six SNPs linked to four different genes for the 1 to 2 case-control study design by using PLINK. All identified regions have been previously associated to AD. GenNet identified twelve SNPs on seven genes to be associated with AD, all with biological plausibility, achieving an AUC of 0.80 when using three biologically determined layers and 0.73 when using two layers at the neural networks. No common top SNPs were identified between the machine learning and GWAS models. Conclusion: This is one of the first studies attempting to compare the traditional GWAS to more sophisticated state-of-art methods for understanding the genetic architecture of complex phenotypes using the same dataset. More systematic comparisons with such approaches on real data are needed to enable best practises for machine learning in the analysis of genome-wide genetic data.

Goji berries, long valued in Chinese medicine and cuisine for their wide range of medicinal benefits, are considered a 'superfruit' and functional food. Out of the nearly 100 Lycium species known for their genetic diversity, L. barbarum and L. chinense currently dominate the market. Due to increasing market demand and concerns about food safety and sustainability, Europe and the Americas are expanding the local goji berry production, using as starting material plants originated from China. European breeding programs are focusing on Lycium to develop varieties adapted to local conditions, especially in response to climate change. By 2023, Romania registered seven goji berry varieties, both from L. barbarum and L. chinense species, without incorporating local germplasm. Advanced genomic studies, including NGS sequencing of five cultivated and three wild goji berry plant genomes, have been conducted to analyse their genetic variation, with a particular focus on the BODYGUARD 3 and 4 genes. This research uncovered significant differences between cultivated and wild genotypes, both in the entire genome and specifically in the BODYGUARD genes, providing crucial insights for goji berry breeders to support the development of goji berry cultivation in Romania.

In the modern era of genomic research, the scientific community is witnessing an explosive growth in the volume of published findings. While this abundance of data offers invaluable insights, it also places a pressing responsibility on genetic professionals and researchers to stay informed about the latest findings and their clinical significance. Genomic variant interpretation is currently facing a challenge in identifying the most up-to-date and relevant scientific papers, while also extracting meaningful information to accelerate the process from clinical assessment to reporting. Computer-aided literature search and summarization can play a pivotal role in this context. By synthesizing complex genomic findings into concise, interpretable summaries, this approach facilitates the translation of extensive genomic datasets into clinically relevant insights. To bridge this gap, we present VarChat (varchat.engenome.com), an innovative tool based on generative AI, developed to find and summarize the fragmented scientific literature associated with genomic variants into brief yet informative texts.VarChat provides users with a concise description of specific genetic variants, detailing their impact on related proteins and possible effects on human health. Additionally, VarChat offers direct links to related scientific trustable sources, and encourages deeper research. Availability: VarChat is freely available at varchat.engenome.com

Since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan, China in December 2019, it has spread rapidly, and many coronavirus disease (COVID-19) cases have occurred in Gwangju, South Korea. Viral mutations following the COVID-19 epidemic have increased interest in the characteristics of epidemics in this region, and pathogen genetic analysis is required for infection control and prevention. In this study, SARS-CoV-2 whole-genome analysis was performed on samples from patients with COVID-19 in Gwangju from 2020 to 2022 to identify the trends in COVID-19 prevalence and to analyze the phylogenetic tree of dominant variants. B.41 and B.1.497 prevailed in 2020, the early stage of the COVID-19 outbreak; then, B.1.619.1 mainly occurred until June 2021. B.1.617.2, classified as sublineage AY.69 and AY.122, occurred continuously from July to December 2021. Since strict measures to strengthen national quarantine management had been implemented in South Korea until this time, mutations phylogenetic analysis was also able to infer the epidemiological relationship between infection transmission routes. Since the first identification of the Omicron variant in late December 2021, the spread of infection has been very rapid, and weekly whole-genome analysis of specimens has enabled us to monitor new Omicron sublineage occurring in Gwangju. Our study suggests that conducting reginal surveillance in addition to nation-level genomic surveillance will enable more rapid and detailed variant surveillance, which will be helpful in the overall prevention and management of infectious diseases.

Standardized protocols were specifically designed and developed for clinical information collection and obtaining trio genomic information from infants affected with congenital anomalies (CA) and their parents, as well as securing human biological resources. Two large areas of these protocols include clinical and genomic information collection on CA which were difficult to diagnose using pre-existing screening methods. The following are three essential items for the clinical information collection protocol: establishment of a consent system for collecting and utilizing research resources, establishment of criteria for target patient selection, and collection of clinical and epidemiological information. A total of 138 cases consisting of 45 families of infants with CA and their parent trios have provided human-derived resources and genomic information. Whole genome sequencing data have been generated for all participants, and standardized protocols for resource collection and manufacturing have been developed. Phenotype information according to the Human Phenotype Ontology term and major test findings were recorded. It is important to keep updating and recording clinical symptoms and genetic diagnosis that are newly added or changed over time. The unique significance of this study is to develop a protocol that enables long-term tracking by adding growth and development tests that reflect important characteristics of newborns. By using these clinical and genetic information collection protocols for CA, it will be possible to establish an essential platform for early genetic diagnosis and diagnostic research, and further present new genetic diagnostic guidelines in the near future.

Aphelids are a holomycotan group, represented exclusively by parasitoids infecting algae. They form a sister lineage to Fungi in the phylogenetic tree and represent a key group for reconstruction of the evolution of Holomycota and for analysis of the origin of Fungi. The newly assembled genome of Aphelidium insullamus (Holomycota, Aphelida) with a total length of 18.9Mb, 7820 protein-coding genes and a GC percentage of 52.05% was obtained by a hybrid assembly based on Oxford Nanopore long reads and Illumina paired reads. In order to trace the origin and the evolution of fungal osmotrophy and its presence or absence in Aphelida, we analyzed the set of main fungal transmembrane transporters, which are proteins of the Major Facilitator superfamily (MFS), in the predicted aphelid proteomes. This search has shown an absence of a specific fungal protein family Drug:H+ antiporters-2 (DAH-2) and specific fungal orthologs of the sugar porters (SP) family, and the presence of common opisthokont's orthologs of the SP family in four aphelid genomes. The repertoire of SP orthologs in aphelids turned out to be less diverse than in free-living opisthokonts, and one of the most limited among opisthokonts. We argue that aphelids do not show signs of similarity with fungi in terms of their osmotrophic abilities, despite the sister relationships of these groups. Moreover, the osmotrophic abilities of aphelids appear to be reduced in comparison with free-living unicellular opisthokonts. Therefore, we assume that the evolution of fungi-specific traits began after the separation of fungal and aphelid lineages, and there are no essential reasons to consider aphelids as a prototype of the fungal ancestor.

Vernonia amygdalina is an important nutritional and medicinal plant that is used to treat various diseases such as malaria and diabetes in Nigeria. In this study, we sequenced, assembled, and annotated the complete nucleotide sequence of the chloroplast genome of a V. amygdalina species isolated in Awka, Nigeria. The chloroplast genome is 153 149 bp in length and has a conserved structure that includes the LSC (84261 bp) region, the SSC (13152 bp) region, and the IR (27868 bp) regions. A total of 131 genes were identified, including 86 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Comparative analysis of the genome revealed species variations in the LSC region associated with the geographical location of the V. amygdalina plant. Phylogenetic analysis of the chloroplast genomes using FastTree showed that V. amygdalina clustered closest to the chloroplast of the Crepidiastrum genus. This study identifies the characteristics of the V. amygdalina chloroplast genome, which will improve our understanding of intraspecies diversity and the identification of potential molecular markers to determine geographical origin.

Repetitive elements are a major component of DNA sequences due to their ability to propagate through the genome. Characterization of Metazoan repetitive profiles is picking up, however, current pipelines are failing to identify a significant proportion of divergent repeats in non-model organisms. The order Decapoda, for which repeat content analyses are largely lacking, is characterized by extremely variable genome sizes that suggest an important presence of repetitive elements. Here we developed a new standardized pipeline to annotate repetitive elements in non-model organisms, which we applied on 20 Decapoda and 6 other crustacean genomes. With our new tool we identify 10% more repetitive elements than standard pipelines. Repetitive elements were more abundant in Decapoda species than in other crustaceans, with an incredibly large number of highly repeated satDNA families. Moreover, we demonstrated a high correlation between assembly size and transposable elements and a different repeat dynamics between Dendrobranchiata and Reptantia. The patterns of repetitive elements largely reflect the phylogenetic relationships of Decapoda and the distinct evolutionary trajectories within Crustacea. In summary, our results highlight the impact of repetitive elements on genome evolution in Decapoda and the value of our novel annotation pipeline, which will provide a baseline for future comparative analyses.

Rabies, caused by the rabies virus (RABV), remains a significant public health issue in the Philippines despite efforts to control it. To eliminate rabies by 2030, effective surveillance strategies are crucial. In this study, we examined RABV evolution and phylodynamics in the Davao Region using genome sequences from Davao City and nearby provinces. We adapted the RABV ARTIC Protocol for Oxford Nanopore High-Throughput Sequencing to optimize workflow efficiency under limited resources. Comparing new virus samples collected from June 2019 to June 2021 (n=38) with baseline samples from June 2018 to May 2019 (n=49), new sub-clades were observed in the phylogenetic tree, suggesting divergence from older variants that were previously undetected. Most of the new viruses belonged to the Asian SEA4_A1.1.1 lineage, but new (SEA4_B1 and SEA4_B1.1) and emerging (SEA4_B1.1_E1) lineages that have never been reported in the Philippines were also identified. The baseline study reported phylogeographic clustering of RABV isolates from the same areas. However, this pattern was disrupted in the current biosurveillance, with variants detected in areas outside the original cluster. Furthermore, our findings revealed significant transmission routes between Davao City and neighboring provinces, contrasting with the predominantly intra-city transmission observed in the baseline study. These results underscore the need for ongoing and timely genomic surveillance to monitor genetic diversity changes and the emergence of novel strains, as well as to track alterations in transmission pathways. Implementing cost-effective next generation sequencing workflows will facilitate the integration of genomic surveillance into rabies control programs, particularly in resource-limited settings. Collaborations between different sectors can empower local laboratories and experts in genomic technologies and analysis.

Ningxiang pig is renowned breed for its exceptional meat quality, but it possesses suboptimal carcass traits. To elucidate the genetic architecture of meat quality and carcass traits in Ningxiang pigs, we assessed heritability and executed a genome-wide association study (GWAS) concerning carcass length, backfat thickness, meat color parameters (L.LD, a.LD, b.LD), and pH at two postmortem intervals (45 minutes and 24 hours) within a Ningxiang pig population. Heritability estimates ranged from moderate to high (0.30 ~ 0.80) for carcass traits and from low to high (0.11 ~ 0.48) for meat quality traits. We identified 21 significant SNPs, the majority of which were situated within previously documented QTL regions. Furthermore, the HMGA1 gene emerged as a pleiotropic gene correlated with carcass length and backfat thickness. The ADGRF1, FKBP5, and PRIM2 genes were associated with carcass length, while the NIPBL gene was linked to backfat thickness. These genes hold potential for use in selective breeding programs targeting carcass traits in Ningxiang pigs.

In this study, we de novo assembled whole genomes of two small body-sized West Pacific sciaenids (Larimichthys polyactis and Collichthys lucidus) and compared them with published genome data of two closely-related, large body-sized species (Larimichthys crocea and Miichthys miiuy) and one distantly-related, large body-sized outgroup species (Dicentrarchus labrax). The phylogeny constructed using 7,403 single-copy orthologs shared among the five species indicated that L. crocea and L. polyactis diverged about 42 MYA. The two sibling taxa are more closely-related to C. lucidus than M. miiuy. We further identified four growth-related genes (CDHR2, PGC, PTN and PDGFA) that host five diagnostic amino acid variants on body size traits in the fishes, splitting small-body sized L. polyactis and C. lucidus from large-body sized L. crocea, M. miiuy and D. labrax. The results provide new genomic resources and guidelines to facilitate future endeavors in studying functional genomics and developing selective breeding programs for desirable growth traits in sciaenids.

The integrity of the genome is crucial for the survival of all living organisms. However, genomes need to adapt to survive certain pressures and for this propose use several mechanisms to diversify. Chromosomal instability (CIN) is one of the main mechanism leading to the creation of genomic heterogeneity by altering the number of chromosomes as well as changing their structures. In this review we will discuss the different chromosomal patterns and changes observed in speciation, in evolutional biology as well as during tumor progression. By nature, human genome shows induction of diversity during gametogenesis but as well during tumorigenesis that can conclude in drastic changes such as whole genome doubling to more discrete changes as indels as well as the recent discovered complex chromosomal rearrangement chromothripsis. More importantly, changes observed during speciation are strikingly similar to the genomic evolution observed during tumor progression and resistance to therapy. The different origins of CIN will be treated as the importance of double strand breaks (DSB) or the consequences of micronuclei. We will also explain the mechanisms behind the controlled DSBs and recombination of homologous chromosomes observed during meiosis, to explain how errors lead to similar pattern observed during tumorigenesis. Then, we will also list several diseases associated to CIN resulting in fertility issue, miscarriage, genetic rare diseases and cancer. Understanding better chromosomal instability as a whole is primordial for the understanding of mechanisms leading to tumor progression.

Klebsiella pneumoniae (Kp) has gained prominence in the last two decades due to its global spread as a multi-drug resistant (MDR) pathogen. Further, Carbapenem-Resistant Kp are emerging at an alarming rate. The objective of this study was (1) to evaluate the prevalence of β-lactamases, especially carbapenemases in Kp isolates from India, (2) determine the most prevalent sequence type (ST) & plasmids, and their association with β-lactamases. Clinical samples of K. pneumoniae (n=65) were collected from various pathology lab, drug susceptibility and minimum inhibitory concentrations (MIC) were detected. Whole genome sequencing (WGS) was done for (n=22) resistant isolates and WGS analysis was performed using various bioinformatics tools. Additional Indian MDR Kp genomes (n=187) were retrieved using Pathosystems Resource Integration Center (PATRIC) database. Detection of β-lactamase genes, location, plasmid replicons, and ST type of genomes were carried out using CARD, mlplasmids, PlasmidFinder, and PubMLST respectively. All data were analyzed and summarized using iTOL tool. ST231 was highest, followed by ST147, ST2096 & ST14 among Indian isolates. blaAmpH was detected as the most prevalent gene followed by blaCTX-M-15, blaTEM-1. Among carbapenemase genes, blaOXA-232 was prevalent and associated with ST231, ST2096 and ST14, which was followed by blaNDM-5 which was observed to prevalent in ST147, ST395 &ST437. ST231 genomes were most commonly found to carry Col440I and ColKP3 plasmids. ST16 carried mainly ColKP3, and Col (BS512) was abundantly present in ST147 genomes. One Kp isolate with novel MLST profile was identified, which carried blaCTX-M-15, blaOXA-1 and blaTEM-1. ST16 &ST14 from this study, which is mostly dual producer of carbapenem and ESBL genes, could be emerging high-risk clones in India.

Due to an increase in the consumption of food, feed, and fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to obtain high-yielding crops that can adapt to future climate changes. Currently, the main feed source used for ruminant livestock production is forage grasses. In temperate climate zones, perennial grasses grown for feed are widely distributed and tend to suffer under unfavorable environmental conditions. Gene editing has been shown to be an effective tool for the development of abiotic stress-resistant plants. The highly versatile CRISPR-Cas system enables increasingly complex modifications in genomes while maintaining precision and low off-target frequency mutations. In this review, we provide an overview of forage grass species that have been subjected to gene editing. We offer a perspective view on the generation of plants resilient to abiotic stresses. Due to the broad factors contributing to these stresses the review focuses on drought, salt, heat, and cold stresses. The application of new genomic techniques (e.g., CRISPR-Cas) allows addressing several challenges caused by climate change and abiotic stresses for developing forage grass cultivars with improved adaptation to the future climatic conditions. Gene editing will contribute towards developing safe and sustainable food systems.

Abstract. The increasing frequency of isolation of methicillin-resistant Staphylococcus aureus (MRSA) limits the chances of effective antibacterial therapy of staphylococcal diseases and results in development of persistent infection such as bacteremia and osteomyelitis. The aim of this study was to identify features of the MRSAST239 0943-1505-2016 (SA943) genome, that contribute to the formation of both acute and chronic musculoskeletal infections. The analysis was performed using comparative genomics data of the dominant epidemic S. aureus lineages namely ST1, ST8, ST30, ST36, ST239. SA943 genome encodes proteins that provide resistance to the host immune system, suppress immunological memory and form biofilms. The molecular mechanisms of adaptation responsible for development of persistent infection were as follows: amino acid substitution in PBP2 and PBP2a, providing resistance to ceftaroline; loss of a large part of prophage DNA and restoration of nucleotide sequence of beta-hemolysin, that greatly facilitates escape of phagocytosed bacteria from phagosome and formation of biofilms; dysfunction of the AgrA system due to the presence of psm-mec and several amino acid substitutions in the AgrC; partial deletion of nucleotide sequence in genomic island vSAβ resulting in the loss of two proteases of Spl - operon; deletion of SD repeats in SdrE amino acid sequence.

The emergence of drug-resistant parasitic nematodes of both humans and livestock calls for development of alternative and cost-effective control strategies. For the economically important ruminant strongylid Haemonchus contortus, Barbervax® remains the only registered vaccine available. Here we compared the microbiome, genome-wide diversity and transcriptome of H. contortus adult male populations that survived vaccination with an experimental vaccine after inoculation in sheep. Our genome-wide SNP analysis revealed 16 putative candidate vaccine evasion genes. However, we did not identify any evidence for changes in microbial community profiling based of 16S rRNA gene sequencing results of vaccine surviving parasite populations. A total of 58 genes were identified as significantly differentially expressed with six being long non-coding (lnc) RNAs and no putative candidate SNP associated genes. The genes highly upregulated in surviving parasites from vaccinated animals were associated with GO terms belonging to predominantly molecular function and a few biological processes that may have facilitated evasion or potentially lessened the effect of the vaccine. These included five targets: astacin (ASTL), carbonate dehydratase (CA2), phospholipase A2 (PLA2), glutamine synthetase (GLUL) and fatty acid-binding protein (FABP3). We searched all five DEG targets against the proteomes of selected Nematoda (Clades III, V, IV, C, I) and Platyhelminthes (Clades Monogenea, Trematoda, Cestoda, Rhabditophora) to determine homologs within the H. contortus NZ_HCO_NP v1.0 genome and identified single-copy orthologous groups (OGs) in selected proteomes. All but one (FABP3) demonstrated high levels of duplication and wide-spread occurrence in closely related Caenorhabditis elegans and Pristionchus pacificus, with complete absence of all five gene targets among other Clade III (Toxocara canis) and V (Ascaris suum, Ascaris lumbricoides and Parascaris univalens) nematodes, further supporting their vital biological functions in nematodes. Phylogenetic analyses inferred the presence of only ASTL and CA2 in almost all Nematoda, platyhelminthes and metazoans examined, with loss of GLULs observed among all outgroup vertebrate species and the presence of FABP3 in only three other species (Schmidtea mediterranea, Fasciola gigantica and F. hepatica). Our tertiary structure predictions and modelling analyses were used to perform in silico searches of all published and commercially available inhibitor molecules or substrate analogues with potential broad-spectrum efficacy against nematodes of human and veterinary importance.

From the hospital wastewater, a novel bacteriophage was isolated and characterized. According to characterization properties, this bacteriophage belongs to the Siphoviridae family, the maximum bacteriophage titer was recorded at 37°C and a pH of 7.2, had a 44,789 bp linear double-strand DNA genome, and within the genome sequence, there are 61 genes, all of which are encoded into proteins. Although this bacteriophage does not have any virulence factors or antimicrobial resistance genes and had specific lytic activity against some antimicrobial resistance S. aureus clinical isolates.

Understanding extremophiles and their usefulness in biotechnology involves studying their habitat, physiology and biochemical adaptations , as well as their ability to produce biocatalysts, in environments that are still poorly explored. In northwestern Peru, which saline lagoons of marine origin Pacific Ocean, the other site from the coast of Brazil of the Atlantic Ocean. Both environments are considered extreme. The objective of the present work was to compare two different strains isolated from these extreme environments at the metabolic level using molecular network methodology through the Global Natural Products Molecular Social Network (GNPS). In our study, the MS/MS spectra from the network were compared with GNPS spectral libraries, where the metabolites were annotated. Differences were observed in the molecular network presented in the two strains of Streptomyces spp. coming from these two different environments. Within the annotated compounds from marine bacteria, the metabolites characterized for Streptomyces sp. B-81 from Peruvian marshes were lobophorins A (1) and H (2), as well as divergolides A (3), B (4) and C (5). Streptomyces sp. 796.1 produced different compounds, such as glucopiericidin A (6) and dehydro-piericidin A1a (7). The search for new metabolites in underexplored environments may therefore reveal new metabolites with potential application in different areas of biotechnology.

To assess the genetic diversity of circulating dengue virus 2 in Senegal in 2018 we performed molecular characterization by complete genome sequencing and performing phylogenetic analysis. Sequenced strains belong to Cosmopolitan genotype of DENV-2 we observed intra-genotype variability leading to a divergence in two clades with differential geographic distribution. We report two variants namely; the “Northern variant” harbouring three nonsynonymous mutations (V1183M, R1405K, P2266T) located respectively on NS2A, NS2B and NS4A and the “Western variant” with two nonsynonymous mutations (V1185E, V3214E) located respectively in the NS2A gene and the NS5 gene. Findings calls for in depth in vitro and functional study to elucidate the impact of observed mutations on viral fitness, spread, epidemiology and disease outcome.

Thousands of new bacterial and archaeal species and higher-level taxa are discovered each year through the analysis of genomes and metagenomes. The Genome Taxonomy Database (GTDB) provides hierarchical sequence-based descriptions and classifications for new and as-yet-unnamed taxa. However, bacterial nomenclature, as currently configured, cannot keep up with the need for new well-formed names. Instead, microbiologists have been forced to use hard-to-remember alphanumeric placeholder labels. Here, we exploit an approach to the generation of well-formed arbitrary Latinate names at a scale sufficient to name tens of thousands of unnamed taxa within GTDB. These newly created names represent an important resource for the microbiology community, facilitating communication between bioinformaticians, microbiologists and taxonomists, while populating the emerging landscape of microbial taxonomic and functional discovery with accessible and memorable linguistic labels.

The genus Rhodotorula includes basidiomycetous oleaginous yeast species. R. babjevae can produce compounds of biotechnological interest such as lipids, carotenoids and biosurfactants from low value substrates such as lignocellulose hydrolysate. High-quality genome assemblies are needed to develop genetic tools and to understand fungal evolution and genetics. Here, we combined short- and long-read sequencing to resolve the genomes of two R. babjevae strains, CBS 7808 (type strain) and DBVPG 8058 at chromosomal level. Both genomes have a size of 21 Mbp and a GC content of 68.2%. Allele frequency analysis indicated tetraploidy in both strains. They harbor 21 putative chromosomes with sizes ranging from 0.4 to 2.4 Mb. In both assemblies, the mitochondrial genome was recovered in a single contig, which shared 97% pairwise identity. The pairwise identity between the majority of chromosomes ranges from 82% to 87%. We found indications for strain-specific extrachromosomal endogenous DNA. 7,591 protein-coding genes and 7,607 associated transcripts were annotated in CBS 7808 and 7,481 protein-coding genes and 7,516 associated transcripts in DBVPG 8058. CBS 7808 has accumulated a higher number of tandem duplications than DBVPG 8058. We identified large translocation events between putative chromosomes and a high genetic divergence between the two strains.

The article is devoted to the new results of the author, which add his previously published ones, of studying hidden rules and symmetries in structures of long single-stranded DNA sequences in eukaryotic and prokaryotic genomes. The author uses the existence of different alphabets of n-plets in DNA: the alphabet of 4 nucleotides, the alphabet of 16 douplets, the alphabet of 64 triplets, etc. Each of such DNA alphabets of n-plets can serve for constructing a text as a chain of these n-plets. Using this possibility, the author represents any long DNA nucleotide sequence as a bunch of many so-called n-texts, each of which is written on the basis of one of these alphabets of n-plets. Each of such n-texts has its individual percents of different n-plets in its genomic DNA. But it turns out that in such multi-alphabetical or multilayer presentation of each of many genomic DNA, analyzed by the author, universal rules of probabilities and symmetry exist in interrelations of its different n-texts regarding their percents of n-plets. In this study, the tensor product of matrices and vectors is used as an effective analytical tool borrowed from the arsenal of quantum mechanics. Some additions to the topic of algebra-holographic principles in genetics are also presented. Taking into account the described genomic rules of probability, the author puts also forward a concept of the important role of stochastic resonances in genetic informatics.

During the last decades West Nile Virus (WNV) outbreaks have continuously occurred in the Mediterranean area. In August 2020 a new WNV outbreak affected 71 people with meningoencephalitis in Andalusia and 6 more cases in Extremadura (south-west of Spain), causing a total of eight deaths. The whole genomes of four viral isolates were obtained and phylogenetically analyzed in the context of recent outbreaks. The Andalusian viral samples belonged to the lineage 1 and were relatively similar to previous outbreaks occurred in the Mediterranean region. Here we present a detailed analysis of the outbreak, including an extensive phylogenetic study.

Polyploidy means having more than two basic sets of chromosomes. Polyploid plants may be artificially obtained through chemical, physical and biological (2n gametes) methods. This approach allows an increased gene scope and expression, thus resulting in phenotypic changes such as yield and product quality. Nonetheless, breeding new cultivars through induced polyploidy should overcome deleterious effects that are partly contributed by genome and epigenome instability after polyploidization. Furthermore, shortening the time required from early chromosome set doubling to the final selection of high yielding superior polyploids is a must. Despite these hurdles, plant breeders have successfully obtained polyploid bred-germplasm in broad range of forages after optimizing methods, concentration and time, particularly when using colchicine. These experimental polyploids are a valuable tool for understanding gene expression, which seems to be driven by dosage dependent gene expression, altered gene regulation and epigenetic changes. Isozymes and DNA-based markers facilitated the identification of rare alleles for particular loci when compared with diploids, and also explained their heterozygosity, phenotypic plasticity and adaptability to diverse environments. Experimentally induced polyploid germplasm could enhance fresh herbage yield and quality, e.g. leaf protein content, leaf total soluble solids, water soluble carbohydrates and sucrose content. Offspring of experimentally obtained hybrids should undergo selection for several generations to improve their performance and stability.

Whole genome pooled sequence data of 12 Pakistani Teddy goats is analyzed for positive selection signatures as their breed defining characteristics. Selection imprints left in the Teddy genome are unveiled by genomic differentiation after the successful paired-end alignment of 635,357,043 reads with (ARS1) reference genome assembly. Pooled-heterozygosity ( ) and Tajima’s D (TD) are applied for validation and getting better hits of selection signals, while pairwise F_ST statistics is conducted on Teddy vs. Bezoar (wild goat ancestor) for genomic differentiation. Annotation of regions under positive selection reveals 59 genes underlying production and adaptive traits. score ≥ 5 detected six windows having highest scores on Chr. 29, 9, 25, 15 and 14 that harbor HRASLS5, LACE1 and AXIN1 genes which are candidate for embryonic development, lactation and body height. Secondly, TD value of ≤ -2.2 showed 4 windows with very strong hits on Chr.5 & 9 harbor STIM1 and ADM genes related to body mass and weight. Lastly, F_ST analysis generated three strong signals with threshold ≤ 0.42 on Chr.12 & 5 harbor ITGB1 gene associated with milk production & lactation traits. Other significant selection signatures encompass genes associated with wool production, prolificacy, immunity and coat colors. In brief, this study identified the genes under selection in this Pakistani goat breed that will be helpful to refining future breeding policies and converging required productive traits within and across other goat breeds and to explore full genetic potential of this valued livestock species.

Proteins are the primary effectors of function in biology, and thus complete knowledge of their structure and properties is fundamental to deciphering function in basic and translational research. The chemical diversity of proteins is expressed in their many proteoforms, which result from combinations of genetic polymorphisms, RNA splice variants and post-translational modifications. This knowledge is foundational for the biological complexes and networks that control biology, yet remains largely unknown. We propose here an ambitious initiative to define the human proteome; that is to generate a definitive reference set of the proteoforms produced from the genome. Several examples of the power and importance of proteoform-level knowledge in disease-based research are presented, along with a call for improved technologies in a two-pronged strategy to accomplish the Human Proteoform Project.

COVID-19 manifests regarding extreme acute respiratory conditions caused by a novel beta coronavirus (SARS-CoV-2) which is reported to be the seventh coronavirus to infect humans. Like other SARS-CoVs it has a large positive-stranded RNA genome. But specific furin site in the spike protein, mutation prone and phylogenetically mess Orf1ab separates SARS-CoV-2 from other RNA viruses. Since, the outbreak (February - March 2020) which originated in China, researchers, scientists, and medical professionals are inspecting all possible facts from every possible aspect including its replication, detection, and prevention strategies. This led to the prompt identification of its basic biology, genome characterization, structural based functional information of proteins, and strategies to prevent its spread. Due to the rapid mutation rate, the functional characterization of a few proteins is still lagging. This review summarizes the recent updates on the basic molecular biology of SARS-CoV-2 and prevention strategies undertaken worldwide to tackle COVID-19. This recent information can be implemented for the development and designing of therapeutics against SARS-CoV-2.

Chickens have extensive phenotypic variation. The Wuhua yellow chicken (WHYC) is an important traditional yellow-feathered chicken in China, characterized by white tail feathers, white flight feathers, and strong disease resistance. However, the genomic basis of traits associated with WHYC is still poorly understood. In this study, whole genome resequencing was performed with an average coverage of 20.77-fold to investigate heritable variation and identify selection signals in WHYC. Reads were mapped onto the chicken reference genome (Galgal5) with a coverage of 85.95%. After quality control, 11,953,471 SNPs and 1,069,574 InDels were obtained. In addition, 41,408 structural variants and 33,278 copy number variants were found. A comparative genomic analysis of WHYC and other yellow-feathered chicken showed that selected regions were enriched in genes involved in transport and catabolism, immune system, infectious diseases, signal transduction, and signaling molecules and interaction. Several genes associated with disease resistance were identified, including IFNA, IFNB, CD86, IL18, IL11RA, VEGFC, and ATG10. Furthermore, PMEL and TYRP1 may contribute to the coloring of white feathers in WHYC. These findings improve our understanding of the genetic characteristics of WHYC and may contribute to future breed improvement.

Background: SARS-CoV-2 infection has spread to over 200 countries since it was first reported in December of 2019. Significant country-specific variations in infection and mortality rate have been noted. Although country-specific differences in public health response have had a large impact on infection rate control, it is currently unclear as to whether evolution of the virus itself has also contributed to variations in infection and mortality rate. Previous studies on SARS-CoV-2 mutations were based on the analysis of ~ 160 SARS-CoV-2 sequences available until mid-February 2020.^{2, 3, 4, 5} By mid-April, > 550 SARS-CoV-2 sequences had been deposited in GenBank, and over 8,200 in the GISAID database. Methods: We performed a sequence analysis on 474 SARS-CoV-2 genomes submitted to GenBank up to April 11, 2020 by multiple alignment using Map to a Reference Assembly and Variants/SNP identification. The results were verified on a larger scale, 8,126 hCoV-19 (SARS-CoV-2) sequences from GISAID database. Results: We identified 5 recently emerged mutations in many isolates (up to 40%). Our analysis highlights 5 frequent new mutations that have emerged since late February 2020. These mutations are: one each missense (non-synonymous) mutation in orf1ab (C1059T), orf3 (G25563T) and orf8 (C27964T), one in 5’UTR (C241T), one in a non-coding region (G29553A). The final mutation (G29553A) was found to be almost exclusive to the US isolates. The first 3 mutations are non-synonymous, leading to amino acid substitutions in the viral protein sequence. Except for C241T, all the novel mutations identified are absent in the isolates from Italy and Spain in the SARS-CoV-2 genomes deposited in GenBank and GISAID by April 13, 2020. Conclusion: The results of current study indicate that new mutations are emerging as COVID-19 pandemic are spreading to different countries and that geography specific mutants may exist. The findings of current study lay the foundation for further investigation into the impact of SARS-CoV-2 mutations on disease incidence, severity, and host immune response. In addition, it may also provide insights into vaccine development and serological response detection for the virus.

A novel coronavirus COVID-19 was first emerged in Wuhan city of Hubei Province in China in December 2019. The COVID-19, since then spreads to 213 countries and territories, and has become a pandemic. Genomic analyses have indicated that the virus, popularly named as corona, originated through a natural process and is probably not a purposefully manipulated laboratory construct. However, currently available data are not sufficient to precisely conclude the origin of this fearsome virus. Genome-wide annotation of thousands of genomes revealed that more than 1,407 nucleotide mutations and 722 amino acids replacements occurred at different positions of the SARS-CoV-2. The spike (S) glycoprotein of SARS-CoV-2 possesses a functional polybasic (furin) cleavage site at the S1-S2 boundary through the insertion of 12 nucleotides. It leads to the predicted acquisition of 3-O-linked glycan around the cleavage site. Although real-time RT-PCR methods targeting specific gene(s) have widely been used to diagnose the COVID-19 patients, however, recently developed more convenient, rapid, and specific diagnostic tools targeting IgM/IgG or newly developed plug and play methods should be available for resource-poor developing countries. Some drugs, vaccines and therapies have shown great promise in early trials, however, these candidates of preventive or therapeutic agents have to pass a long path of trials before being released for the practical application against COVID-19. This review updates current knowledge on origin, genomic evolution, development of the diagnostic tools and the preventive or therapeutic remedies of the COVID-19, and discusses on scopes for further research and effective management and surveillance of COVID-19.

The importance of genome organization at the supranucleosomal scale in the control of gene expression is increasingly recognized today. In mammals, Topologically Associating Domains (TADs) and the active / inactive chromosomal compartments are two of the main nuclear structures that contribute to this organization level. However, recent works reviewed here indicate that, at specific loci, chromatin interactions with nuclear bodies could also be crucial to regulate genome functions, in particular transcription. They moreover suggest that these nuclear bodies are membrane-less organelles dynamically self-assembled and disassembled through mechanisms of phase separation. We have recently developed a novel genome-wide experimental method, High-salt Recovered Sequences sequencing (HRS-seq), which allows the identification of chromatin regions associated with large ribonucleoprotein (RNP) complexes and nuclear bodies. We argue that the physical nature of such RNP complexes and nuclear bodies appears to be central in their ability to promote efficient interactions between distant genomic regions. The development of novel experimental approaches, including our HRS-seq method, is opening new avenues to understand how self-assembly of phase separated nuclear bodies possibly contributes to mammalian genome organization and gene expression.

Beta-lactam resistant bacteria, commonly resident in tertiary hospitals, have emerged as a worldwide health problem because of ready-to-eat vegetable intake. We aimed to characterize the genes providing resistance to beta-lactam antibiotics in Enterobacteriaceae, isolated from five commercial salad brands for human consumption in Mexico City. 25 samples were collected, grow in blood agar plates, the bacteria were biochemistry identified and antimicrobial susceptibility testing was done, the carried family genes were identified by endpoint PCR and the specific genes were confirmed with WGS by NGS. 12 positive cultures were identified and their microbiological distribution was as follows, 8.3% for Enterobacter aerogene (n=1), 8.3% for Serratia fonricola (n=1), 16.7% for Serratia marcesens (n=2), 16.7% for Klebsiella pneumoniae (n=2), and 50% (n=6) for Enterobacter cloacae. The endpoint PCR results showed 11 colonies positive for blaBIL (91.7%), 11 for blaSHV (91.7%), 11 for blaCTX (97.7%), 12 for blaDHA (100%),4 for blaVIM (33.3%), 2 for blaOXA (16.7%), 2 for blaIMP (16.7%), 1 for blaKPC (8.3%) and 1 for blaTEM (8.3%) gene, all samples were negative blaROB, blaCMY, blaP, blaCFX and blaLAP gene. The sequencing analysis revels a specific genotypes for Enterobacter cloacae (blaSHV-12, blaCTX-M-15, blaDHA-1, blaKPC-2); Serratia marcescens (blaSHV-1, blaCTX-M-3, blaDHA-1, blaVIM-2); Klebsiella pneumoniae (blaSHV-12, blaCTX-M-15, blaDHA-1); Serratia fonticola (blaSHV-12, blaVIM-1, blaDHA-1) and Enterobacter aerogene (blaSHV-1, blaCTX-M-1, blaDHA-1, blaVIM-2, blaOXA-9). Our results indicate that beta-lactam resistant bacteria have acquired integrons with a different number of genes that providing panresistance to beta-lactam antibiotics, including penicillins, oxacillins, cefalosporins, monobactams, carbapenems and imipenems.

We describe the genomes of two Echovirus isolates from Nigeria as reference enterovirus species B genomes for the region. These Echovirus 7 and 19 genomes have 7,411nt and 7,426nt, and were recovered from sewage contaminated water (in 2010) and an acute flaccid paralysis case (in 2014), respectively.

Genus Clematis is one of the largest within Ranunculaceae. Here we report the chloroplast genome of two Clematis species, C. brachyura and C. trichotoma endemic to Korea. The chloroplast genome lengths of C. brachyura and C. trichotoma are 159,532 bp and 159,170 bp, respectively. Gene contents in the complete chloroplast genomes of these two Clematis species are identical to that of most Ranunculaceae and other angiosperms. However, our data results demonstrated that genus Clematis has inversion and rearrangement events concerning gene rps4 gene, rps16 to trnH region, and trnL to ndhC region, and IR regions expansion. Comparison of IR regions among Ranunculaceae species revealed that Clematis species contained six protein coding genes (infA, rps8, rpl14, rpl16, rps3, and rpl22) usually found in the long single copy (LSC) region of other species. Phylogenetic analysis demonstrated that genus Clematis is closely related to genus Ranunculus. Differences in repeat structure, substitution rates, and IR expansion in genera Clematis and Ranunculus, explained their relationship. Clematis species showed slightly higher tandem repeats content than Ranunculus species. The six protein-coding genes showed lower synonymous substitution rates in the IR of Clematis species than in the LSC of Ranunculus species. Overall, the chloroplast genomes and results presented here provide important information on the evolution of Ranunculaceae.

Previous high throughput screening studies indicated trans-eQTLs tend to be tissue specific. In this study, I probed if this feature can be used to identify tissue-specific gene regulatory networks. eQTL data (P<5e-8) for 16,259 genes were identified and their summary association statistics were obtained from the eQTLGene database. Next, eQTLs that display both cis and trans regulatory effects were selected and the association between their corresponding genes were examined using Mendelian randomization. A total of 169 genes that exerted trans-regulatory impacts on 692 genes were identified. 90% of the genes (N=749) aggregated into a gene regulatory network significantly enriched in hemo-immune processes. The robustness of finding was confirmed through simulation. The identified network displayed the scale-free topology. This provided the reason to examine the association of the network’s hub genes with the phenome. The outcome of analyses revealed GSDMB and ORMDL3 impact several disorders of immune origin and ALDH2 overexpression contributes to obesity. This study reports trans-eQTLs can be used to identify tissue-specific gene regulatory networks and describes a workflow to achieve this purpose. The network identified in this study showed scale-free topology indicating the hub genes of a GRN could be targeted to prevent disease outcomes.

Dynamic crossflow filtration (DCF) is the state-of-the-art technology for solid-liquid separation from viscous and sensitive feed streams in the food and biopharma industry. Up to now, the potential of industrial processes is often not fully exploited because fixed recipes are usually applied to run the processes. Therefore, a digital twin has been developed to optimize an industrial brownfield DCF plant. The core of the digital twin is a mechanistic-empirical process model combining fundamental filtration laws with process expert knowledge. The effect of variation of selected process and model parameters on plant productivity has been assessed using a model-based design-of-experiments approach and a regression metamodel has been trained with the data. A cyclic program that bidirectionally communicates with the DCF asset serves as frame of the digital twin. It monitors the process dynamics membrane torque and transmembrane pressure and feeds back the optimum permeate flow rate setpoint to the physical asset in almost real-time during process runs. The presented digital twin framework is a simple example how an industrial established process can be controlled by a hybrid model-based algorithm. With a digital process dynamics model at hand, the presented metamodel optimization approach can be easily transferred to other (bio)chemical processes.

In this study, the distribution patterns of southern horse mackerel are examined using commercial fine-scale resolution data. Using landings by size category and VMS data from the Portuguese commercial bottom trawl fishery, which consistently targets horse mackerel, this study provides a comprehensive analysis of horse mackerel age distributions spanning a decade (2010-2020). Importantly, the study addresses potential biases in commercial effort data and establishes the usefulness of commercial bottom-trawl gear as a suitable method for sampling and evaluate southern horse mackerel stock dynamics. Ordered regression models were applied to allow for the modelling of the distribution of multiple age categories and investigate spatio-temporal migrations off the Portuguese coast. Southern horse mackerel shows a widespread age distribution range and stable abundance with indications of seasonal and spatial patterns in the distribution of specific age groups. The insights derived from this research contribute valuable knowledge for understanding the dynamics and distribution patterns of fish populations.

Climate change is unpredictable and can change rapidly or over time; anthropogenic stressors work synergistically to strengthen their impact on vulnerable ecosystems and the fisheries sector. This study documented the past occurrence of extreme climate change impacts, such as supertyphoon Pablo (ST: Bopha), which severely affected Baganga, Davao Oriental, about ten years ago. A mixed-methods data collection was used, combining semi-structured interviews with small-scale fishers (N=120) in four fishing villages and focus group discussions (N=4, participated by about 4 focus groups) on assessing the impacts and their adaptation after climatic events occurred. Our findings indicate that the four selected fishing villages were exposed to common factors of climate change events that destroyed many lives and their livelihood. Including a decrease in catch per trip and the fishing operations disruption (98%). However, due to the impact of the supertyphoon, small-scale fishers in Baganga developed psychological distress (emotional 44% and physical 24%) due to the extreme event or disaster and economic losses (32%). In order to survive, their adaptation strategies relied on government and non-government-provided provisions and projects, e.g., planting trees, constructing a sea wall with wave breakers, cash for work, and tourism as an alternative livelihood. Despite this, our study revealed that the community had limited knowledge on the impacts of climate change, lack clear management goals especially for fishers, and the widespread use of illegal fishing gears. The local government must strongly implement rules, policies, and adaptation measures that will contribute to better and more resilient communities. This can help them to withstand future shocks and provide sustainable fisheries resources that will benefit all the fishers. The study will be useful to policymakers, disaster management group and organization that will help assist affected communities highly affected by climatic events.

Semiconductors play a very important role in modern society. The improvement in performance of semiconductors is what has enabled the world to grow at such a fast pace. For decades scaling has been done through Moore’s law i.e performance improvements have been obtained due to transistor scaling where the number of transistors per unit area increase is what has contributed to the increase in performance. However, with transistor scaling reaching its limitations we need to find alternate methods to enhance silicon design to suit the computational need of modern society. To address this problem we will be looking into a few methods that enable performance scaling with a focus on analysing the most popular implementation of each in the industry.

As smoke toxicity is unregulated outside of the mass transport industry, there is no set methodology for assessing smoke toxicity of construction products, like OSB, on a large-scale. This research aims to assess the novel design of a modified ISO 9705 room corner test designed for smoke toxicity quantification. Three tests conditions will be assessed to determine if restriction of ventilation is enough to force a fire to transition to under-ventilated flaming, or if the fuel loading is much more important in affecting the fire severity and fire condition. The research found that fuel loading and test geometry has more significant impact on the fire condition than restricting the ventilation. While imposing restrictions on the test rooms ventilation did increase the equivalence ratio, it was not sufficient enough to force the transition into under-ventilated flaming. The addition of a door to the test room did not force the fire to transition to under-ventilated flaming. When doubling the fuel loading, there was sufficient fuel for the fire to transition to under-ventilated flaming. This research has provided the experimental methodologies to assess smoke toxicity at a range of ventilation conditions on a large-scale.

The contemporary landscape of education is witnessing a paradigm shift towards innovative instructional methods, with the flipped learning approach gaining considerable attention. The purpose of this research was to investigate the impact of the flipped learning approach on students' perception and acceptance throughout an entire semester in the 'Introduction to Programming with Java' course, using a research design with a quantitative approach, ultimately aiming to inform educational practice and advance our knowledge of innovative teaching methods in higher education. This study was conducted at a university with 174 students involved, divided into two groups, 87 students in the experimental group and 87 students in the control group. The data collected through the scales were analyzed by using descriptive and inferential statistical analysis techniques in statistical software. At the end of the measurements, the technology acceptance level and self-directed learning perceptions of engineering students who received education with flipped learning were high. The results suggest that educators should consider students' readiness for self-directed learning when implementing the flipped learning approach and focus on creating an environment that supports their autonomy and engagement. This research offers valuable guidance for instructors, curriculum designers, and educational policymakers seeking to enhance the effectiveness of flipped learning in higher education courses.

Sensation seeking (SS) is a psychobiological personality trait characterized by an individual’s propensity to engage in various forms of risk-taking behavior. The Brief Sensation Seeking Scale (BSSS-8) is a widely used instrument for assessing SS that has been translated into several languages. However, only outdated and non-validated questionnaires have been used to measure SS in the Slovenian population. The aim of this study was to translate and psychometrically validate the Slovenian version of the BSSS-8. A total of 363 participants aged between 14 and 65 years completed the translated BSSS-8 and the questionnaire on drug abuse. The scale demonstrated good reliability (Cronbach’s α=0.81) and a unidimensional factorial structure, as revealed by confirmatory factor analysis (CFA). The multigroup CFA showed gender-specific measurement invariance. In the nomological network, SS was positively associated with drug-related variables. The Slovenian version of the BSSS-8 scale is a short and simple instrument to assess SS for research and epidemiological purposes.

The emerging industry of offshore wind turbines mounted on floating bases has garnered significant attention from both academia and industry. The desire to understand the complex physics of these floating structures has led to the development of numerical and physical modelling techniques. While physical testing has traditionally been employed, there is a growing focus on cost-effective and accurate high-fidelity numerical modelling as a potential alternative or supplement. However, commonly used numerical engineering tools in the offshore industry are considered mid- to low-fidelity and may lack the desired precision for floating offshore wind turbines (FOWTs). Given the complexity of these simulation codes, it is crucial to validate their accuracy. To address this, the International Energy Agency (IEA) Wind Technology Collaboration Programme initiated various research endeavors, including the Offshore Code Comparison Collaboration (OC3), Offshore Code Comparison Collaboration Continuation (OC4), Offshore Code Comparison Collaboration Continuation with Correlation (OC5), and the recent Offshore Code Comparison Collaboration Continued with Correlation and Uncertainty (OC6) projects. This study offers a comprehensive survey of the simulation tools available for FOWTs which were part of OC projects, focusing particularly on horizontal axis wind turbines (HAWTs) and highlighting their capabilities and fundamental theories.

Deep networks-based hashing has gained significant popularity in recent years, particularly in the field of image retrieval. However, most existing methods only focus on extracting semantic information from the final layer, disregarding valuable structural information that contains important semantic details crucial for effective hash learning. To address this limitation and improve image retrieval accuracy, we propose a novel deep hashing method called Deep Supervised Hashing by Fusing Multiscale Deep Features (DSHFMDF). Our approach involves extracting multiscale features from multiple convolutional layers and fusing them to generate more robust representations for efficient image retrieval. Experimental results on CIFAR10 and NUS-WIDE datasets demonstrate that our method surpasses the performance of state-of-the-art hashing techniques.

The work presents a mathematical model of a thermogravimetric curve for the growth and simultaneous sublimation of scale on a metal or alloy surface. Reduction of the reaction area as a result of the formation of oxides of alloying elements (for obtaining the basic oxide) is considered for the alloy. For metals, the case where this area is increased as a result of powder metal crushing is also considered. The equations that were obtained are employed to explain the kinetic curves of the mass change of the samples.

The sustainability of agroecological systems, biodiversity protection, animal welfare and consumer demand for higher-quality products from alternative and extensive farming methods, have reinforced interest in local breeds that are well adapted to low-input environments. However, food safety needs to be safeguarded to reinforce consumer confidence. The aim of this study was to conduct a preliminary investigation on the occurrence of Salmonella spp. in eggshells, hen’s cloaca and litter materials from autochthonous Portuguese laying hens raised in a semi-extensive system for small-scale production. A total of 279 samples were obtained, with 63 samples from the “Preta Lusitânica” breed, and 72 samples each from the remaining autochthonous breeds, namely “Branca”, “Amarela” and “Pedrês Portuguesa”. None (0%) of the samples analyzed were positive for Salmonella spp.. To the best of our knowledge, these are the first results of Salmonella evaluation from hen’s cloaca, eggshells, and litter materials in autochthonous Portuguese chickens, suggesting that a semi-extensive production system can contribute to better food security and a lower risk to public health and the environment.

Mindfulness interventions have been implemented in many countries. This study aimed to examine the psychometric properties of English and Thai-version of the 15-item mindfulness attention awareness scale (MAAS) across five samples. A descriptive correlation research was conducted in the Philippines and Thailand, and five data sets were generated using self-reported and online questionnaires. Exploratory factor analyses were used to explore the factorial structure of the MAAS. Confirmatory factor analyses were performed to test measurement invariance across samples. Concurrent validity was tested by examining relationships between the MAAS and psychological well-being (PWB). A unidimensional structure of the MAAS was documented across the five samples. The MAAS demonstrated measurement invariance across samples for both English and Thai versions. Concurrent validity was displayed through significant correlations with PWB. This study produced evidence to support the construct validity, concurrent validity, and reliability of the English and Thai versions of MAAS. This study was not registered.

The reagents and raw materials used, as well as the products obtained (bio-oil, reaction condensates, polyols and sugar phases) were characterized by elemental analysis, infrared spectroscopy, thermogravimetry and high performance liquid chromatography with mass spectrometry. The heating value of the bio-oils is higher than that of the original biomass (higher heating value of Eucalyptus sawdust bio-oil 29 MJ/kg versus 19.5 MJ/kg of the original Eucalyptus sawdust). The analyses of the bio-oils allowed to identify the presence of high added-value compounds, such as levulinic acid and furfural. Finally, a study of the accelerated aging of the liquefied biomass showed that the biofuel density increases with the storage time due to the occurrence of repolymerization reactions.

To address the challenges of climate change and food security, the establishment of smart farm complexes is necessary. While there have been numerous studies on the productivity and environmental control of individual greenhouses, research on greenhouse complexes is considerably limited. Conducting environmental studies during the design phase of these complexes poses financial constraints and practical limitations in terms of on-site experiments. To identify potential issues that may arise when developing large-scale greenhouse complexes, it is possible to utilize modeling techniques using Computational Fluid Dynamics (CFD) to assess environmental concerns and location issues before constructing the facilities. Consequently, simulating large-scale CFD models that incorporate multiple greenhouses and atmospheric conditions simultaneously presents significant numerical challenges. The objective of this study was to develop a guideline for verifying CFD models for a large-scale Venlo greenhouse, where acquiring field data before construction is not feasible for designing a greenhouse complex. The verification processes of the CFD models were conducted using 2D and 3D iterative simulations of a 2-hectare greenhouse model, using the improved Grid Independence Test (GIT) and wall Y+ approaches. Subsequently, the aerodynamic characteristics were analyzed in a 3D greenhouse model to access its performance when the wind direction was 90° in summer season. The findings revealed that a grid resolution of 0.8 meters and a first layer height of 0.04 meters were suitable for developing large-scale greenhouse models, resulting in a low Root Mean Square Error (RMSE) of 3.9% and a high coefficient of determination (R2) of 0.968. This process led to a significant reduction of 38% in the number of grid cells. These results will serve as design standards for large-scale greenhouses.

When there are multiple key strata in the overburden of deep coal seam and the surface subsid-ence coefficient after mining is small, it indicates that the overlying key strata fail to break com-pletely after mining. On this occasion, the stress concentration on the working face occurs easily, which in turn leads to the occurrence of dynamic disasters such as rock burst. This study adopted a comprehensive analysis method of field monitoring and numerical simulation to explore the in-fluence of key stratum on the evolution law of mining-induced stress in the working face. Dis-tributed optical fiber sensor (DOFS) and surface subsidence GNSS monitoring system were re-spectively arranged inside and at the mouth of the ground observation borehole. According to the monitoring results of strain obtained from DOFS, the height of broken stratum inside the overlying strata was obtained; according to the monitoring results of surface subsidence, the sur-face subsidence coefficient was proved to be less than 0.1, indicating that the high key stratum does not break completely, but enters a state of bending subsidence instead. In order to reveal the influence of key stratum on the mining-induced stress of working face, two 3DEC numerical models with and without key stratum were established for comparative analysis. As the numeri-cal simulation results show, when there are multiple key strata in the overburden, the stress in-fluence range and stress concentration coefficient of coal seam after mining are relatively large. The study revealed the working mechanism of rock burst accidents after large-scale mining and predicted the potential area of rock burst risk after the mining of the working face, which has been verified by field investigation. The research results are of great guiding significance for the revelation of the working mechanism of rock burst in deep mining condition and its prevention and control.

Blast charge initiation procedures have a significant impact on both mining safety and production rates. In this study, the inventory benefit of an electric initiation system was investigated to assess its influence on both fragmentation and blast-induced damages. The Wipfrag software's was used to examine the size distribution and productivity of 12 small-scale blasts initiated by both non-electric and electric detonators. All blast rounds was initiated with plain type of electric and NONEL detonators. The average burden, spacing, stemming length, and charge weight were, respectively, 0.85 m, 1.10 m, 0.66m, and 1.1kg. The results showed that the mesh through which 80% of the blast fragments will pass for the electric blast is smaller than the mesh through which the material products from the NONEL blast will pass. The results also demonstrate that the generated blast-induced ground vibration (PPV) from all blast rounds for electric blast varies from 0.4–1.2 mm/s and 80–105dB, while that for non-electric blast ranges from 0.05–0.2mm/s and 72–95dB. As a result, the electric blast initiation technique was found to produce good fragmentation, with a higher percentage of optimum fragment sizes on spec than non-electrically initiated blasts.

When undertaking wind assessment around buildings using large eddy simulation (LES), the implementation of the integral length scale at the inlet for inflow generation is controversial, as real atmospheric length scales require huge computational domains. While length scales significantly influence inflow generation in the domain, their effect on the downstream flow field has not yet, been investigated. In this paper, we validate the effectiveness and accuracy of implementing a reduced turbulence integral length scale for inflow generation in LES results at the rooftop of low-rise buildings and develop a technique to estimate the real local length scales using simulation results. We measure the wind locally and calculate the turbulence length scales from the energy spectrum of the wind data and simulation data. According to these results, there is an excellent agreement between the length scale from simulation and measurement when they are scaled with their corresponding freestream/inlet value. These results indicate that a reduced integral length scale can be safely used for LES to provide a reliable prediction of the energy spectrum as well as the length scales around complex geometries. The simulation results were confidently employed to obtain the best location for a wind turbine installation on low-rise buildings.

Background: The novel coronavirus (COVID-19) infection is primarily transmitted through respiratory droplets from an infected person and contact with tainted surfaces or items. Social distancing became the primary measure of preventing the spread of COVID-19, with the principal aim being to reduce the probability of contact with an already infected person. Social distancing can be distressing, as it is against the community's way of life. Saudi Arabia imposed a curfew and suspended all religious, entertainment, sporting, and mass congregations. The daily updates on COVID-19 infection and mortality are upsetting and further, aggravate depression and anxiety. With this background, this study was planned with the following objectives. To determine the sociodemographic profile of the study participants, to find the prevalence of psychological morbidity, and to measure the association between the sociodemographic details, COVID-19 associated factors, and psychological effects among Abha citizens during the COVID-19 pandemic. Methodology: A descriptive cross-sectional community-based study was conducted in the Abha city population from August 2021 to July 22. This study followed snowball sampling, the data was collected using an online Google form the link was shared in WhatsApp groups and through emails to contacts, asking friends to share it with their friends, until reaching the adequate sample size the responses were accepted. Results: A total of 530 participated, and their age ranged from 19 -70 years. Many of the participants (34.5%, n=183) belonged to 36-45 years old. Most of the responders were 69.8% married and Females (69.2%, n=367). Half of the participants had been quarantined (49.6%), and 51.5% were scared from fear of COVID-19. 64.8% of the participants had depression; 14.2%, 20.8%, 13.6%, and 16.2% had mild, moderate, severe, and extremely severe depression, respectively. Around 58.2% of participants suffered from anxiety; 5.8% experienced mild anxiety, 21.7% moderate anxiety, and 30.7% severe anxiety. The proportion of stress among the participants was 45.0%; 10.8% had mild stress, 9.4% had moderate stress, and 24.5% had severe to extremely severe stress. Conclusions: COVID-19 poses mental health problems among individuals and communities. There is a need to find the more susceptible individuals for mental health issues or other psychological disorders. Mental health and psychological problems can be resolved with health education, counseling, and appropriate interventions to curb the negative health impacts of COVID-19.

Cerebrovascular and airway structures are tubular structures used for transporting blood and gases, respectively, providing essential support for the normal activities of the human body. Accurately segmenting these tubular structures is the basis of morphology research and patho-logical detection. Nevertheless, accurately segmenting these structures from images presents great challenges due to their complex morphological and topological characteristics. To address this challenge, this paper proposes a framework UARAI based on the U-Net multi-scale reverse at-tention network and sparse convolution network. The framework utilizes a multi-scale structure to effectively extract the global and deep detail features of vessels and airways. Further, it enhances the extraction ability of fine-edge features by a joint reverse attention module. In addition, the sparse convolution structure is introduced to improve the features' expression ability without increasing the model's complexity. Finally, the proposed training sample cropping strategy re-duces the influence of block boundaries on the accuracy of tubular structure segmentation. The experimental findings demonstrate that the UARAI-based metrics, namely Dice and IoU, achieve impressive scores of 90.31% and 82.33% for cerebrovascular segmentation and 93.34% and 87.51% for airway segmentation, respectively. Compared to commonly employed segmentation tech-niques, the proposed method exhibits remarkable accuracy and robustness in delineating tubular structures such as cerebrovascular and airway. These results hold significant promise in facilitating medical image analysis and clinical diagnosis, offering invaluable support to healthcare profes-sionals.

MCrAlYHf bond coats are employed in jet and aircraft engines, stationary gas turbines, and power plants, which require strong resistance to oxidation at high temperatures. The oxidation behavior of a free-standing CoNiCrAlYHf coating was investigated in this study. Isothermal oxidation tests were performed in air at 1050 °C on the specimens with various levels of surface roughness to investigate the oxidation kinetics. X-ray diffraction, focused ion beam, scanning electron microscopy (SEM), and scanning transmission electron microscopy were used to characterize the surface oxides. The surface roughness was examined using a contact profilometer and SEM. An empirical model was proposed to elucidate the impact of surface roughness on the oxidation behavior based on the correlation between the surface roughness level and oxidation rates.

Traceability is the ability to determine the path of a product from purchase to consumption to determine when and where it originated. This paper aimed to determine the factors that influence fishers’ decision-making to participate in tuna traceability program, it also explores the determinants of fish catch for small-scale fishers and the feasibility of implementing tuna traceability in the Davao Gulf, Philippines. The result of the interview showed that the significant factors that highly affected the decision-making of fishers in implementating tuna traceability program: boat capacity, fishing hours and communication of fishers (P≤0.05). Household size, years in community, fishing hours, volume of fish sold, and the fishers' communication in the fishing ground (P≤0.05) were other factors that determined the daily catch of the fishers. The results of this study showed that fishers from the Davao Gulf were willing to be part of traceability program that would sustain and increase the value of their fish catch. Moreover, communication was shown to be critically needed in such programs adjusting it for the fish catch to remain fresh or of good quality. Our study will help in deterring and mitigating illegal, unregulated and unreported fishing (IUU) through fish catch traceability.

We present a new family of Bessel solutions of the paraxial equation. Such solutions keep their form during propagation due to a quadratic phase factor that makes them scaled propagation invariant fields. The Bessel beams we introduce have the particularity that the topological phase is twice the order of the Bessel function and the argument varies quadratically with the radius

Dolomite is a common type of natural soluble rock. The strength of rock decreases under the action of corrosion, which has a significant impact on the self-stability and long-term safety of the tunnel surrounding the rock. To reveal the microscopic structure evolution and strength-damage law of carbonate rock caused by corrosion, chemical corrosion, rock uniaxial compression, and electron microscope scanning tests are conducted at different pH values on the dolomite of the Doushantuo Formation. The rock dissolution at different pH values exhibits four typical stages: the initial dissolution stage, secondary dissolution acceleration stage, stable dissolution rate stage, and dissolution attenuation stage. During the dissolution process, the initial dissolution rate is 25.91 times that of the stable stage, and the maximum strength attenuation is 76.2% after 21 days of dissolution. For macroscopic failure, the rock is developed from 1 to 2 external fractures to multiple internal and external fractures and penetrated, and the specimen transforms from brittle to flexible. For microstructure, the sample exhibits corrosion characteristics along the joint surface, intensified corrosion at the edge, etc. The porosity increase rate is 0.6%/d; however, the length–width ratio of the pores is maintained at 1.7–1.85, indicating that the development rate of pores in different directions is similar. The results of this study have enriched the study of the dolomite dissolution mechanism and have important reference value for the stability evaluation of tunnel surrounding rock in karst environments.

The temporal evolution of pandemics described by the susceptible-infectious-recovered (SIR)-compartment model is sensitively determined by the time dependence of the infection (a(t)) and recovery (u(t)) rates regulating the transitions from the susceptible to the infected and from the infected to the recovered compartment, respectively. Here approximated SIR-solutions for different time dependencies of the infection and recovery rates are derived which are based on the adiabatic approximation assuming time-dependent ratios k(t)=u(t)/a(t) varying slowly in comparison to the typical time characteristics of the pandemic wave. For such slow variations the available analytical approximations from the KSSIR-model, valid for a stationary value of the ratio k, are used to insert a-posteriori the adopted time-dependent ratio of the two rates. Instead of investigating endless different combinations of the time dependencies of the two rates a(t) and u(t) a suitably parameterized reduced time dependence of the ratio k(tau) is adopted. Together with the definition of the reduced time this parameterized ratio k(tau) allows us to cover a great variety of different time dependencies of the infection and recovery rates. The agreement between the solutions from the adiabatic approximation in its four different studied variants and the exact numerical solutions of the SIR-equations is remarkably good providing strong confidence in the accuracy of the proposed adiabatic approximation.

The late universe contains a wealth of information about fundamental physics and gravity, wrapped up in non-Gaussian fields. To make use of as much information as possible it is necessary to go beyond two-point statistics. Rather than going to higher order N-point correlation functions, we demonstrate that the probability distribution function (PDF) of spheres in the matter field (a one-point function) already contains a significant amount of this non-Gaussian information. The matter PDF dissects different density environments which are lumped together in two-point statistics, making it particularly useful for probing modifications of gravity or expansion history. Our approach in Cataneo et. al. 2021 extends the success of Large Deviation Theory for predicting the matter PDF in ΛCDM in these “extended” cosmologies. A Fisher forecast demonstrates the information content in the matter PDF via constraints for a Euclid-like survey volume combining the 3D matter PDF with the 3D matter power spectrum. Adding the matter PDF halves the uncertainties on parameters in an evolving dark energy model, relative to the power spectrum alone. Additionally, the matter PDF contains enough non-linear information to substantially increase the detection significance of departures from General Relativity, with improvements up to six times the power spectrum alone. This analysis demonstrates that the matter PDF is a promising non-Gaussian statistic for extracting cosmological information, particularly for beyond ΛCDM models.

Cancer is one of the leading causes of death and morbidity with a complex pathophysiology. Traditional cancer therapies include chemotherapy, radiation therapy, targeted therapy, and immunotherapy. However, limitations such as lack of specificity, cytotoxicity, and multi-drug resistance pose a substantial challenge for favorable cancer treatment. The advent of nanotechnology has revolutionized the arena of cancer diagnosis and treatment. Nanoparticles (1-100nm) can be used in the treatment of cancer owing to their specific advantages such as biocompatibility, reduced toxicity, more excellent stability, enhanced permeability and retention effect, and precise targeting. Nanoparticles are classified into several main categories. The nanoparticle drug delivery system is particular and utilizes tumor and tumor environment characteristics. Nanoparticles not only solve the limitations of conventional cancer treatment but also overcome multidrug resistance. Additionally, as new multidrug resistance mechanisms are unraveled and studied, nanoparticles are being investigated more vigorously. Various therapeutic implications of nano-formulations have created brand new perspectives for cancer treatment. However, a majority of the research is limited to in vivo and in vitro studies, and the number of nano-drugs that are approved has not much amplified over the years. In this review, we discuss numerous types of nanoparticles, targeting mechanisms along with approved nanotherapeutics for oncological implications in cancer treatment. Further, we also summarize the current perspective, advantages, and challenges in clinical translation.

We utilize how Weber in 1961 initiated the process of quantization of early universe fields to the problem of what may be emitted at the mouth of a wormhole. While the wormhole models are well developed, there is as of yet no consensus as to how, say GW or other signals from a wormhole mouth could be quantized, or made to be in adherence to a procedure Weber cribbed from Feynman, in 1961. In addition, we utilize an approximation for the Hubble parameter parameterized from Temperature using Sarkar’s H ~ Temperature relations, as given in the text . Finally after doing this we go to the Energy as E also ~ Temperature, and from there use E (energy) as ~ signal frequency. This gives us an idea of how to estimate frequency generated at the mouth of a wormhole.

We reduplicate the Book “Dark Energy” by M. Li, X-D. Li, and Y. Wang, given zero-point energy calculation with an unexpected “length’ added to the ‘width’ of a graviton wave just prior to specifying the creation of ‘gravitons’, while using Karen Freeze’s criteria as to the breakup of primordial black holes to give radiation era contributions to GW generation. The GW generation will be when there is sufficient early universe density so as to break apart Relic Black holes of the order of Planck mass (10^15 grams) which isabout when the mass of relic black holes is created, 10^-27 or so seconds after expansion starts. Need to state a key result will be in the initial potential V calculated, in terms of other input variables

We reduplicate the Book “Dark Energy” by M. Li, X-D. Li, and Y. Wang, zero-point energy calculation with an unexpected “length’ added to the ‘width’ of a graviton wavefunction just prior to the entrance of ‘gravitons’ to a small region of space-time prior to a nonsingular start to the universe. We compare this to a solution worked out using Klauder Enhanced quantization, for the same given problem. The solution of the first Cosmological Constant problem relies upon the geometry of the multiverse generalization of CCC cosmology which is explained in this paper. The second solution, used involves Klauder enhanced quantization. We look at energy given by our methods and compare and contrast it with the negative energy of the Rosen model for a mini sub universe and estimate GW frequencies

Complex systems can be described as the network of interactions between their components. In directed networks, information, energy and matter flow in dominant directions. Undirected networks, on the other hand, cannot easily capture these asymmetries. The local flow of information depends on the node spin, which is a function of the number of incoming and outgoing links attached to it. And yet, how the heterogeneous association between in-degree and out-degree constraints global dynamics remains poorly understood. Here, we develop a new theoretical model to study the relationship between node directionality and global flow dynamics. Our computational analysis of random and scale-free directed networks indicates that structural diversity constrains the dimensionality of reachable dynamical space. These results suggest how local directionality might be an universal driver of global dynamics in many systems, from social networks, to technological systems to the connectome.

The hypothesis posed was whether participation in LaLiga Genuine Santander (competitive football) influenced the quality of life (QL) of the people who participated in it, since their perception of themselves is enhanced by all the aformentioned factors (self-determination, social inclusion, emotional well-being, physical well-being, material well-being, rights, personal development, interpersonal relationships). The objective was to evaluate the QL of people with Down's Syndrome (DS) using their self-perception (n=39) and the perception of the informants (family members, teachers) (n=39). The KidsLife-Down Scale, with a few modifications was used. In general, differences of opinion between the subgroups of participants with DS and informants showed that results were higher in terms of perception for participants in the DS subgroup. Scores for all variables were higher for those participants with DS who said they did engage in practicing competitive football. Despite the perception of informants provides a great deal of information regarding the QL of participants with DS, the latter should be involved in the evaluation process and their self perceptions taken into account. Our research shows that participation in the league modifies the perceptions of the participants with Down's Syndrome regarding their quality of life. However, these perceptions are not shared by the informants.

Nanoparticle (NP) transport is increasingly relevant to subsurface engineering applications such as aquifer characterization, fracture electromagnetic imaging and environmental remediation. An efficient field-scale simulation framework is critical for predicting NP performance and designing subsurface applications. In this work, for the first time, a streamline-based model is presented to simulate NP transport in field-scale subsurface systems. It considers a series of behaviors exhibited by engineered nanoparticles (NPs), including time-triggered encapsulation, retention, formation damage effects and variable nanofluid viscosity. The key methods employed by the algorithm are streamline-based simulation (SLS) and an operator-splitting (OS) technique for modeling NP transport. SLS has proven to be efficient for solving transport in large and heterogeneous systems, where the pressure and velocity fields are firstly solved on underlying grids using finite-difference (FD) methods. After tracing streamlines, one-dimensional (1D) NP transport is solved independently along each streamline. The adoption of OS enhances flexibility for the entire solution procedure by allowing different numerical schemes to solve different governing equations efficiently and accurately. For the NP transport model, an explicit FD scheme is used to solve the advection term, an implicit FD scheme is used for the diffusion term and an adaptive numerical integration is used to solve the retention terms. The model is implemented in an in-house streamline-based code, which is verified against analytical solutions, a commercial FD reservoir simulator (ECLIPSE) and an academic FD colloid transport code (MNMs). For a 1D homogeneous case, the effluent breakthrough curves (BTC) produced by the in-house simulator are in good agreement with the analytical solution and MNMs, respectively. For a two-dimensional (2D) heterogeneous case, the BTC and concentration pattern of the in-house simulator all match well with the solution produced by commercial simulator. Simulations on a synthetic three-dimensional (3D) nanocapsule application engineering design case, are performed to investigate the effect of fluid and NP properties on the displacement pattern of an existing subsurface fluid.

Therapeutic proteins are used to successfully treat hemophilia, Crohn’s Disease, diabetes, and cancer. Recent product recalls have occurred because of sub-visible particle formation resulting from the inherent instability of proteins. It has been suggested that particle formation is associated with late stage processing steps of filling, shipping, and delivery. Previous works demonstrated that cavitation might occur in therapeutic vials subjected to agitation or accidentally dropped, but that mitigation can be achieved with fluid property manipulation. The goal of this research was to (1) assess the risk of cavitation under common pharmaceutical manufacturing conditions (i.e., pipe contraction and pumps), (2) establish a simple threshold criterion for when particulate will form, and (3) suggest a series of mitigation techniques based on these thresholds. To accomplish these tasks, computational fluid dynamic simulations for a variety of pipe contraction and fluid properties were performed. The results of this research show that reducing the turbulence in a fluid system will reduce the likelihood of cavitation. Additionally, threshold bounds were created that establish a definitive transition at which cavitation will occur.

Risk assessment management have been a hot topic for the researchers since a very long time. Software risk management is an important part of project management as it contains the identification, analysis, estimation and monitoring of different risks present in the system. This helps developers in decision making while assessing the problems that could arise in the software systems. Risk management is very complex in large scale system as these systems have very complex development. The paper describes risk management techniques for large scale system. Furthermore we have provided a detailed comparative analysis of these techniques with commonly identified risks in software systems and have provided a systematic order for risk management process to ensure risk mitigation.

Photoelectrochemical systems have the potential to contribute to de-carbonation of the energy system because solar energy can be directly converted to hydrogen which can be burnt without the release of greenhouse gases. However, meaningful deployment of photoelectrochemical (PEC) technology in the global energy system, even when highly efficient scaled up devices become available, shall only be a reality when their safe and reliable operation can be guaranteed over serveral years of service life. The first part of the review discusses the importance of hermetic sealing of up scaled PEC device provided by the casing and sealing joints from a reliability and risk perspective. The second part of the review presents a survey of fully functional devices and early demonstrators and uses this to establish the extent to which the state of the art in PEC device design address the issue of hermetic sealing. The survey revealed that current material choices and sealing techniques are still unsuitable for scale –up and commercialization. Accordingly, we examined possible synergies with related photovoltaic and electrochemical devices that have been commericalised and derived therefrom, recommendations for future research routes that could accelerate the development of hermetic sealings of PEC devices.

The technique of Faraday tomography is a key tool for the study of magnetised plasmas in the new era of broadband radio polarisation observations. In particular, observations at metre-wavelengths provide significantly better Faraday depth accuracies compared to traditional cm-wavelength observations. However, the effect of Faraday depolarisation makes the polarised signal very challenging to detect at metre wavelengths (MHz frequencies). In this work, Faraday tomography is used to characterise the Faraday rotation properties of polarised sources found in data from the LOFAR Two-Metre Sky Survey (LoTSS). Of the 76 extragalactic polarised sources analysed here, we find that all host a radio-loud AGN. The majority of the sources (∼64%) are large FRII radio galaxies with a median projected linear size of 710 kpc and median radio luminosity at 144 MHz of 4 × 10^26 W/Hz. In several cases, both hotspots are detected in polarisation at an angular resolution of ∼20". One such case allowed a study of intergalactic magnetic fields on scales of 3.4 Mpc. Other detected source types include an FRI radio galaxy and at least 8 blazars. Most sources display simple Faraday spectra, however, we highlight one blazar that displays a complex Faraday spectrum, with two close peaks in the Faraday dispersion function.

Objective: The goal of this study was to analyse the attitudes and perceptions of emergency and mental health nurses through the validation of the SM-GIBED scale in specialised care in Spain on alcoholics and other drug-dependent patients. Design and Setting: This cross-sectional study was developed using the Spanish hospital version of the Seaman-Mannello scale to denominate the SM-GIBED scale. Participants: 170 Emergency and Mental Health Nursing from five Spanish Hospitals. Intervention: Self-administered questionnaire to analiyse the perceptions and attitudes about the drug addict and the alcoholic. Primary and Secondary Outcome Measures: A descriptive and inferential analysis of the study variables was carried out. A psychometric analysis was performed to validate the scale. Results: A total of 170 questionnaires were collected from 257 healthcare workers. Overall, 99.1% of the participants had contact with drug-dependent patients during their professional experience. Nearly 75% had difficulties in treating them. The psychometric analysis of the SM-GIBED scale in the Spanish context obtained values of KMO = 0.655 and Bartlett's test p < 0.000. Cronbach's alpha of 0.738 was obtained from the reliability analysis. A reliability analysis of each of the SM-GIBED questions found no case with an alpha lower than 0.71. In conclusion, positive aspects include an ingratiating attitude and subject-to-subject communication when nurses self-define as empathic and non-paternalistic. Among the negative aspects, there is a lack of communication skills and assertiveness with these patients. This highlights a certain degree of resignation and dissatisfaction when working with drug addicts.

Given the cross-scale interactions of agricultural ecosystems, it is important to collect ecosystem service data at the multiple spatial scales they operate at. Mapping of ecosystem services helps to assess their spatial and temporal distribution and is a popular communication tool of their availability and value. For example, maps can be used to quantify distance between areas of available ecosystem services and their beneficiaries and how services fluctuate with changes in land use patterns over time, allowing identification of synergies and trade-offs. However, a lack of local context and too large a resolution can reduce the utility of these maps, whilst masking heterogeneities in access due to equity dynamics. This review identifies and summarizes eight main methods of ESS mapping found in the literature—remote sensing, biophysical modelling, agent based modelling, economic valuation, expert opinion, user preference, participatory mapping, and photo-elicitation. We consider what spatial scales these methods are utilized at and the transferability of data created by each method. The analysis concludes with a methodological framework for mapping ecosystem services, intended to help researchers identify appropriate methods for a multi-scale research design. The framework is exemplified with an overview of a research project in Ethiopia.

In previous researches, Job Crafting questionnaire to develop is consists of 3 factors which are Task Crafting, Cognitive Crafting, and Relationship Crafting with 12 to 17 items. The purpose of study is to develop JCQ for leisure sports instructor of Korean. 274 valid samples are used for analysis. Data collecting is purposeful sampling. At result, for Korean Sports Instructor Job Crafting Scale is constructed 3 factors with 12 items is constructed by 3 step procedure. KSIJCQ is confirmed on convergent discriminant validity evidence. In conclusion, KSIJCQ is a valid scale of the measuring and distributes Job Crafting of generalization in sports.

We evaluated the potential of using fish species and functional traits as indicators of land use impacts to fish assemblages. We used environmental data collected at multiple spatial scales (local, reach, and upstream catchment) for 19 tributary and main stem sites in the Nolichucky River watershed in Tennessee. Canonical correspondence analyses showed that temperature, elevation, specific conductivity, sediment yield, impervious surfaces, and row crop cover at the catchment scale were strongly associated with fish assemblage structure, as well as forest cover from all three spatial scales. Blocked indicator species analysis, with stream size as the block, showed that significantly strong indicators of the least-impacted riparian land use condition (≥60% forest cover) were Saffron Shiner (Notropis rubricroceus), Rainbow Trout (Oncorhyncus mykiss), Longnose Dace (Rhynichthys cataractae), Creek Chub (Semotilus atromaculatus), and Mottled Sculpin (Cottus bairdi). Traits indicative of the least-impacted sites were the herbivorous trophic guild, mean female age-at-maturity, longevity, rock-gravel spawners, montane geology and pelagic swimmers. Specific conductivity was strongly related to multiple catchment-scale land use variables, and was a strong local-scale influence on fish assemblage structure. Our results show promise for using a relatively common but endemic southern Appalachian fish species, the Saffron Shiner, as an indicator for land-use related impacts to these streams.

Tobamoviruses are a group of plant viruses posing a significant threat to agricultural crops worldwide. In this review, we focus on plant immunity against tobamoviruses, including pattern-triggered immunity (PTI), effector-triggered immunity (ETI), RNA-targeting pathway, hormones and reactive oxygen species (ROS). Further, we highlight genetic resources for resistance against tobamoviruses in plant breeding and discuss future directions on plant protection against tobamoviruses.

Genome-wide association studies (GWAS) have successfully revealed many disease-associated genetic variants. For a case-control study, the adequate power of an association test can be achieved with a large sample size, although genotyping large samples is expensive. A cost‐effective strategy to boost power is to integrate external control samples with publicly available genotyped data. However, the naïve integration of external controls may inflate the type I error rates if ignoring the systematic differences (batch effect) between studies, such as the differences in sequencing platforms, genotype calling procedures, population stratification, and so forth. To account for the batch effect, we propose an approach by integrating External Controls into the Association Test by Regression Calibration (iECAT-RC) in case-control association studies. Extensive simulation studies show that iECAT-RC not only can control type I error rates but also can boost statistical power in all models. We also apply iECAT-RC to the UK Biobank data for M72 Fibroblastic disorders by considering genotype calling as the batch effect. Four SNPs associated with Fibroblastic disorders have been detected by iECAT-RC and the other two comparison methods. However, our method has a higher probability of identifying these significant SNPs in the scenario of an unbalanced case-control association study.

Control of Tropical Theileriosis, a tick-borne disease with a strong impact on cattle breeding, can be facilitated by using marker-assisted selection in breeding programs. Genome-wide association studies (GWAS) using high-density arrays are extremely important for the ongoing process of identifying genomic variants associated with resistance to Theileria annulata infection. In this work, Single Nucleotide Polymorphisms (SNPs) were analyzed in the Portuguese autochthonous cattle breeds Alentejana and Mertolenga. In total, 14 SNPs suggestive of significance (p ≤ 10-4) were identified for Alentejana cattle and 20 SNPs for Mertolenga cattle. The genomic regions around these SNPs were further investigated for annotated genes and Quantitative trait loci (QTLs) previously described by other authors. Regarding the Alentejana breed, the MAP3K1, CMTM7, SSFA2, and ATG13 genes are located near suggestive SNPs and appear as candidate genes for resistance to Tropical Theileriosis, considering its action the immune response and resistance to other diseases. On the other hand, in the Mertolenga breed, the UOX gene is also a candidate gene due to its apparent link to the pathogenesis of the disease. These results may represent a first step towards the possibility of including genetic markers for resistance to Tropical Theileriosis in current breed selection programs.

Recent successes in the field of evolutionary cancer cell biology (ECCB) have brought to a head two of the most important controversies regarding cancer origin. The first concerns the question of whether carcinogenesis is initiated only by genetic alterations, mutations, and driver genes, as the mutational theory teaches. The ECCB, claims that a large number of polyploidy-related cancers (PGCC cancers) are not due to mutations, but rather to inadequate ancient repair mechanisms used by DNA-damaged stem cells for their repair. Somatic mutations are merely secondary. The second controversy, described in the previous article, concerns the non-mutational theory itself: Are non-mutational polyploid cancers an atavism - as previously thought - or rather the effect of an ancient gene regulatory network aGRN that controls genome reprogramming in precancerous DNA-damaged cells as well in the transformed cells. Finally, the unicellular gene module of cancer, of which the aGRN is a part, has evolved along with the multicellular genome during the last 1000 My of evolution. and non-mutated cancer cell systems are under the control of the aGRN. The atavistic theory relies on phylostratigraphic evidence to determine the age of cancer genes. It states that most cancer-like genes arose during the transition period from unicellularity to multicellularity, but also during the early metazoan era. In our opinion, the atavistic theory is flawed and suffers from many misunderstandings. It provides little insight into the origin and coevolution of the cancer cell system and its control by the ancient gene regulatory network aGRN.

The sharing of genome sequences in online data repositories, allows for large scale analyses of specific genes or gene families. This can result in the detection of novel gene subtypes as well as development of improved detection methods. Here we used publicly available WGS data to detect a novel Stx subtype, Stx2n in two clinical E. coli strains isolated in the USA. During this process, additional Stx2 subtypes were detected; six Stx2j one Stx2m strain and one Stx2o, all were analyzed for variability from the originally described subtypes [1,2]. Complete genome sequences were assembled from short or long read sequencing and analyzed for serotype, and ST types. The stx2n and Stx2o WGS were further analyzed for virulence genes pro-phage analysis and phage insertion sites. Nucleotide and amino acid maximum parsimony trees showed expected clustering of the previously described subtypes and a clear separation of the novel Stx2n subtype. WGS data was used to design OMNI PCR primers for the detection of all known Stx1 (283 bp amplicon), Stx2 (400 bp amplicon), eae (222bp amplicon) and Stx2f (438 bp amplicon) subtypes. These primers were tested in three different laboratories, using standard reference strains. Analysis of complete genome sequence showed variability in serogroup, virulence genes, ST type, and Stx2 pro-pages showed variability in size, gene composition, and phage insertion sites. The isolates with Stx2n and Stx2o in this study demonstrated toxicity for Vero cells. The Stx2n strain were induced when grown with sub-inhibitory concentrations of Cip, and toxicity was detected. Taken together, these data highlight the need to reinforce genomic surveillance to identify the emergence of potential new Stx2 or Stx1 variants. The importance of this surveillance has a paramount impact in public health. Per our description in this study, we suggest that 2017C-4317 be designated as the Stx2n type-strain.

Recent developments in artificial nucleic acid and drug delivery systems (DDS) present possibilities for the symbiotic engineering of oligonucleotide therapeutics, such as antisense oligonucleotides (ASOs), and small interfering RNA (siRNA). These technologies can also be applied for triplex-forming oligonucleotides (TFOs) to develop symbiotic genome-targeting tools and a new class of oligonucleotide drugs. Many reports have described the functionalization of TFOs and the enhancement of TFO activities. In particular, the tethering of crosslinking groups to TFOs enables irreversible triplex formation and is frequently exploited for antigene and genome-editing experiments. These crosslinkable TFOs have shown considerable potential for therapeutic application. In this review, we revisit these crosslinking techniques and explore the combination of these techniques with recent artificial oligonucleotide and DDS technologies.