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.

The development of modern genomic tools has sped up the breeding program of food crops. More recently, genomic resources are being developed for tropical forages and will be key resources for developing climate resilient high yielding forage varieties. In this study, we present a genome-wide association study for biomass yield and feed quality traits in buffel grass (Cenchrus ciliaris L. aka Pennisetum ciliare L.,). Genome-wide markers generated using the DArTSeq platform and mapped onto the reference genome of Setaria italica were used for the genome-wide association study. The results revealed several markers associated with biomass yield and feed quality traits. A total of 78 marker trait associations were identified with R2 values ranging from 0.138 to 0.236. The marker trait associations were distributed across different chromosomes. Of these associations, the most marker trait associations (23) were observed on Chr9, followed by Chr5 with 12. The fewest number of marker trait associations were observed on Chr4 with 2. In terms of traits, 17 markers were associated with biomass yield, 24 with crude protein, 26 with TDN, 14 with ADF, 10 with NDF and six with DMI. Twenty of the identified markers were associated with at least two traits. The identified marker trait associations provide a useful genomic resource for future improvement and breeding of buffel grass.

To determine the fracture rate of ceramic crowns and causes of ceramic crown failure, this study used keywords—namely “endocrown,” “veneered fixed dental prosthesis,” “monolithic lithium disilicate (LS2),” and “all-ceramic single crown”—to search for articles published in English from 2005 to 2023 in the PubMed electronic database. Rather than using the Boolean logic algorithm between MESH terms and keywords, we accurately calculated the numbers of final clinically tracked cases with crown fractures from the contents of articles. The titles and abstracts of many related articles focused on implant or abutment fracture, while crown fracture was investigated and mentioned only in the main texts of the articles. Our studies included those crowns as well as having more complete data collection. Our search yielded 228, 93, 404, and 358 articles for the keywords “endocrown,” “veneered fixed dental prosthesis,” “monolithic lithium disilicate (LS2),” and “all-ceramic single crown,” respectively. We used the Newcastle–Ottawa Scale (NOS) to assess article quality, and our inclusion criteria were randomized controlled trials (RCT) and cohort study articles involving more than 3 years of follow-up and more than 20 cases. After reviewing, 16 high-quality articles were selected for analysis. The 4.4% crown fracture rate recommended on the basis of most clinical results was achieved in only 6 of the 16 articles. In these 6 articles, the researchers concluded the following reasons that may cause the crown fractures: the thickness of the veneer ceramic material; the connector dimensions; pontic span of the fixed prosthesis; the type of cement; the treatment of the ceramic surface before luting. Other articles inferred that the computer-aided design libraries that were insufficient for the creation of appropriate anatomically supported frameworks for prostheses with ceramic veneers; the thermal expansion coefficient and fracture toughness of the framework material did not match those of the veneer ceramic, resulting in an insufficient area supporting the ceramic veneer then leads to premature crown failure after a long period chewing. The future prospective for material developing could focus on solving those problems and have better clinical results.

The two-scale method (TSM) is an effective approach to simulate electromagnetic (EM) scattering from rough sea surface, to interpret physical interaction of EM wave with rough sea surfaces. The sea surface roughness spectrum and the cutoff wavenumber are two key factors affecting the accuracy of TSM simulation. This paper takes the geophysical model functions (GMFs) of different band as reference, and quantitatively studies the two factors based on the numerical simulation of different polarization backscattering coefficients. The numerical simulation demonstrates that Apel spectrum is more suitable for the backscattering simulation in C/X/Ku-band, and the optimal cutoff wavenumbers are also derived for TSM simulation of EM scattering in C/X/Ku-band. Then an empirical model function of optimal cutoff wavenumbers with respect to frequency, incident angle and wind speed are obtained with regression method. Finally, the simulation results with the new model function of cutoff wavenumber are compared with the GMF and measured data in different bands and they are all consistent. Moreover, a physical explanation for the optimal cutoff wavenumber is also given.

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.

Large-scale farms are pivotal sites for the development of the agricultural industry, and the quality of the ecological environment is a significant factor affecting the growth of cereal crops. Consequently, assessing the ecological quality of large-scale farms is of great importance. This paper leverages the advantages of remote sensing imagery for long-term, quantitative, and dynamic monitoring of ecological quality over extensive areas. It develops an ecological assessment procedure suitable for agricultural regions based on an Improved Remote Sensing Ecological Index (IRSEI), which considers the coupling of ecosystem component elements. This procedure introduces a Pan-Salinity Index (PSI) tailored to the characteristics of soil salinization in farming areas and incorporates an ecological greenness index based on the Normalized Difference Vegetation Index (NDVI), an ecological humidity index derived from the K-T transform (WET), an ecological dryness index synthesized from the bare soil index and the built-up index (NDBSI), and an ecological heat index represented by the Land Surface Temperature (LST) calculated from atmospheric parameter models. These five indices are integrated into the ecological assessment system. The experimental results visually demonstrate the development and changes of ecological impact factors in the farm research area over the past decade, as well as the spatiotemporal variations in the quality of the farm's ecological environment. The findings indicate that between 2010 and 2019, the overall trend of IRSEI first declined, then rose, and subsequently experienced a slight decrease. Through differential analysis, regions and areas with declining ecological quality were identified, providing a data reference for the formulation and implementation of future ecological protection and management measures for the farm. The proposed IRSEI method offers a rapid and effective new monitoring approach for agricultural planting areas with a tendency towards soil salinization.

Colletotrichum lini is a flax fungal pathogen, comprising differently virulent strains. In this work, we sequenced the genomes of three C. lini strains of different virulence: high virulent #390-1, medium virulent #757, and low virulent #771. We obtained more than 100× genome coverage with Oxford Nanopore Technologies reads and more than 50× genome coverage with Illumina data. To construct high-quality genomes, several assembly strategies were tested. The final assemblies were obtained using the Canu – Racon ×2 – Medaka – Polca scheme and were 54.0-55.3 Mb in length, contained 26-32 contigs, had an N50 > 5 Mb and the BUSCO completeness > 96%. Comparative analysis of the constructed genomes showed high similarity between mitochondrial and nuclear genomes. However, a rearrangement event and the loss of a 0.9 Mb contig were revealed. The candidate effectors were predicted in sets of proteins received after genome annotation. The obtained genome sequences of C. lini strains extend the knowledge on the genetic diversity of Colletotrichum species and are the basis for establishing molecular mechanisms of pathogenicity of the flax pathogen and effective control of flax anthracnose.

One of the current challenges in Higher Education is the development of students’ emotional competencies, and consequently, how these competencies can be trained. Moreover, this must be addressed within the UN framework of inclusive, equitable, quality education (United Nations Agenda 2030) (SDG 4). To address this challenge, the present study set the following objectives: (1) to analyze pre-service teachers’ level of interest in EI and their perceived level of general EI knowledge, (2) to examine their self-perception of certain variables of emotional knowledge, according to their degree program and year of studies, (3) to analyze the relationship between these emotional knowledge variables and perceived emotional intelligence (EI); and (4) to study the predictive capacity of the study variables on future teachers' emotional knowledge variables. The study sample contained a total of 434 university students from three degree programs at two universities in Spain, of which 82.70% were women, and the mean age was 20.91 years. Two instruments were used: an ad hoc questionnaire, which assessed perceived emotional knowledge according to three variables (General knowledge of EI, where level of training in EI is considered; Intrapersonal knowledge of EI; and Theoretical-practical knowledge related to teaching), and the Trait Meta-Mood Scale (TMMS-24), which assesses metaknowledge of emotional states across three variables (Attention, Clarity, and Repair). Results of the study suggest that there are differences in perceived EI knowledge according to students' year of studies and according to their degree, and indicate that students present high interest, while their perceived level of knowledge is low. In addition, emotional clarity is the EI variable that was identified as being important in the emotional knowledge of future teachers. This study shows evidence of the importance of social-emotional competencies in initial teacher training.

In the rapidly evolving landscape of genetic engineering, the advent of CRISPR-Cas technologies has catalyzed a paradigm shift, empowering scientists to manipulate the genetic code with unprece-dented accuracy and efficiency. Despite the remarkable capabilities inherent to CRISPR-Cas sys-tems, recent advancements have witnessed the integration of small molecule to augment their functionality, introducing new dimensions to the precision and versatility of gene editing applica-tions. This review delves into the synergy between CRISPR-Cas technologies and small molecule drugs, elucidating the pivotal role of chemicals in optimizing target specificity and editing efficiency. By examining a diverse array of applications, ranging from therapeutic interventions to agricultural advancements, we explore how the judicious use of chemicals enhances the precision of CRISPR-Cas-mediated genetic modifications. In this review we emphasize the significance of small molecule drugs in fine-tuning the CRISPR-Cas machinery, which allows researchers to exert meticulous con-trol over the editing process. We delve into the mechanisms through which these chemicals bolster target specificity, mitigate off-target effects, and contribute to the overall refinement of gene edit-ing outcomes. Additionally, we discuss the potential of chemical integration in expanding the scope of CRISPR-Cas technologies, enabling tailored solutions for diverse genetic manipulation challenges. As CRISPR-Cas technologies continue to evolve, the integration of small molecule drugs emerges as a crucial avenue for advancing the precision and applicability of gene editing techniques. This re-view not only synthesizes current knowledge but also highlights future prospects, paving the way for a deeper understanding of the synergistic interplay between CRISPR-Cas systems and chemical modulators in the pursuit of more controlled and efficient genetic modifications.

Abstract: CRISPR/Cas systems are used for genome editing, both in basic science and in bio-technology. At the same time, CRISPR/Cas editors have several limitations, including insufficient specificity leading to "off-targets" and the dependence of activity on chromatin state. A number of highly specific Cas9 variants have been obtained now, but most of them are characterized by reduced activity on eukaryotic chromatin. We identified a spatial cluster of amino acid residues in the PAM-recognizing domain of Streptococcus pyogenes Cas9, whose mutations restore the activity of one of the highly specific forms of SpyCas9 without reducing its activity in Saccharomyces cere-visiae. In addition, one of these new mutations also increases the efficiency of SpyCas9-mediated editing of a site localized on the stable nucleosome. The improved Cas9 variants we obtained, which are capable of editing hard-to-reach regions of the yeast genome, may help in both basic research and yeast biotechnological applications.

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.

СrAss-like phages play an important role in maintaining ecological balance in the human intestine microbiome. However, their lifestyle and genetic diversity are still insufficiently studied. In this study, a novel CrAssE-Sib phage genome belonging to the epsilon сrAss-like phage genomes was found. Detailed analysis indicated that CrAssE-Sib encodes unusual proteins – DNA primase, virion RNA polymerase, prophage antirepressor, and transcriptional repressor, as well as reverse transcriptase (RT) and receptor binding protein (RBP) that are part of diversity-generating retroelement (DGR). Comparative analysis showed that all epsilon сrAss-like phages are divided into two putative genera, which were proposed to name Epsilonunovirus and Epsilonduovirus; CrAssE-Sib belongs to the first of them. RT from CrAssE-Sib and several Epsilonunoviruses contains a specific motif in its fourth domain that was not previously found in RTs from phage and bacterial DGRs. In addition, RBP from CrAssE-Sib and all Epsilonunoviruses has a unique structure. The presence of the conservative prophage repressor and anti–repressors that belong to the lysogenic-to-lytic cycle switches indicate that CrAssE-Sib and other Epsilonunoviruses could be temperate. Epsilon сrAss-like phage substantially differ from other crAss-like phages, including zeta сrAss-like phages. This fact indicates the need to isolate these phages into a separate family.

One of the ways to regulate the sensitivity of human cells to the influenza virus is to knock out genes of the innate immune response. Promising targets for the knockout are genes of the interferon-inducible transmembrane protein (IFITM) family, in particular the IFITM3 gene, whose product limits the entry of a virus into the cell by blocking the fusion of the viral and endosomal membranes. In this study, by means of genome-editing system CRISPR/Cas9, monoclonal cell lines with an IFITM3 knockout were obtained based on WI-38 VA13 cells (human origin). It was found that such cell lines are more sensitive to infection by influenza A viruses of various subtypes. Nonetheless, this feature is not accompanied by an increased titer of newly formed viral particles in a culture medium.

Streptococcus thermophilus is widely used as a starter culture in the dairy industry and has garnered attention as a beneficial bacterium owing to its health-promoting functionalities in humans. In this study, the probiotic potential of S. thermophilus MCC0200, isolated from a dairy product, was investigated through a combinatorial approach of in-vitro and in-silico studies. MCC0200 demonstrated the ability to survive harsh gastro-intestinal transit (GIT), adhere to intestinal mucosa and exert health-promoting traits in in-vitro studies. These findings were corroborated with in-silico evidence, wherein MCC0200 genome harboured genes associated with tolerance to GIT conditions, intestinal adhesion and colonization. Genome mapping also highlighted the ability of MCC0200 to produce compounds advantageous for host (folate, bacteriocins), to release enzymes that can reinforce the host ability (antioxidative enzymes), to metabolize food components that can be harmful to sensitive people (lactose). MCC0200 also demonstrated a positive effect on reducing cholesterol levels, proving to be a potential candidate for food and pharmaceutical applications. Absence of transmissible antibiotic resistance genes and virulence genes underscored the GRAS nature of MCC0200. This study explored the potential of Streptococcus thermophilus for its probable applications as a probiotic beyond the dairy industry.

The EU’s energy targets are to achieve at least 32% renewables in the energy mix by 2030. Part of the solution is strengthening consumer rights by empowering individuals to generate their own electricity. The study aimed to identify the most suitable energy system for electricity generation of up to 50 kW in the EU residential sector. The Multi-Criteria Decision Analysis was used to compare four systems: proton exchange membrane fuel cell with photovoltaic panels, photovoltaic panels, biomass powered Stirling engine, and solar powered Stirling engine. Based on the results, the most beneficial system for household electricity generation is the Biomass-fueled Stirling engine system due to its affordability, reliability, and low environmental impact. Governments and businesses can use these findings to improve information for the residential sector and enable the transition to renewable energy.

This study presents a method for the rapid and accurate generation of two-dimensional (2D) orthomosaic maps using selected image data collected by drone-captured video. The focus is on developing a real-time method capable of creating maps more quickly than image selection. The scale-invariant feature transform (SIFT) algorithm is applied to drone images to extract features in various scale regions. For feature point matching, a matching method based on the fast library for approximate nearest neighbors (FLANN) was adopted. A comparison of the computational speed of the FLANN with that of the k-nearest neighbors (KNN) and brute force matcher during the matching process revealed FLANN's superior capability for real-time data processing. The random sample consensus (RANSAC) algorithm was employed to enhance the accuracy of the matching by removing outliers, effectively identifying and eliminating mismatches, and reinforcing the reliability of feature point matching. The combination of SIFT, FLANN, and RANSAC algorithms demonstrates the capacity to process drone-captured image data in real time, facilitating the generation of precise 2D orthomosaic maps. The proposed method was assessed and validated using imagery obtained as the drone executed curvilinear and straight flight paths, confirming its accuracy and operational efficiency concurrently with the image capture process.

Posttraumatic stress disorder (PTSD) and/or specific PTSD symptoms may evoke disordered eating and unhealthy lifestyles, resulting in adverse cardiometabolic events (e.g., hypertension and obesity) in certain groups, which may implicate the treatment of this complex condition. The diagnostic criteria of PTSD have lately expanded beyond the three common symptoms (intrusion, avoidance, and hyperarousal). Simultaneously, four-, five-, and six-dimensional structures of the Impact of Event Scale-Revised (IES-R), a popular PTSD measure, seem to be more robust than the original three-dimension structure. Within the context of COVID-19, this instrumental study used a convenience sample of 58 dental healthcare workers (HCWs) from Russia (mean age = 44.1±12.2 years, 82.8% females) to examine the criterion and predictive validity of two IES-R structures: the IES-R3 and the IES-R6 (with the added symptoms of numbing, sleep disturbance, and irritability). The subscales of the two IES-R structures expressed good internal consistency, strong correlations with the PTSD Symptom Scale (PSS), hypertension diagnosis, and high body mass index (BMI). In receiver-operating characteristic (ROC) curve analysis, all IES-R models perfectly predicted the PSS (all area under the curve (AUC) >0.9, p values <0.001). The IES-R, both hyperarousal subscales, and the IES-R3 intrusion subscale significantly predicted high BMI. Both avoidance subscales and the IES-R3 intrusion subscale, not the IES-R, significantly predicted hypertension. In conclusion, both IES-R structures can reliably measure PTSD symptoms. The IES-R, hyperarousal, and intrusion may be credible criterion variables for predicting high BMI within PTSD while the intrusion and avoidance subscales may reflect the cardiovascular consequences associated with PTSD more reliably than the IES-R itself. The IES-R subscales may predict cardiometabolic adversities in PTSD, signifying a need for proper assessment of lifestyle and the application of dietary and exercise interventions in order to lower physical morbidity in PTSD. Replicating the study in larger samples, which comprise different physical and mental conditions from heterogenous cultural contexts is pivotal to validate the results (e.g., in specific groups such as those with confirmed traumatic exposure and comorbid mood dysfunction).

Sarcomas are a heterogenous group of tumours that commonly carry poor prognosis with limited therapeutic options. Adolescents and young adults (AYA) with sarcoma are a unique and under-studied patient population that have only achieved modest survival gains compared to other groups. We present our institutional experience of AYA with sarcoma who underwent comprehensive molecular profiling (CMP) using either large-panel targeted DNA sequencing or whole genome and transcriptome sequencing and evaluated the feasibility and clinical impact of this approach. Genomic variants detected were determined to be clinically relevant and actionable following the Molecular Tumour Board evaluation. Clinicians provided feedback regarding the utility of testing three months after reporting. Twenty-five patients who were recruited for CMP are included in this analysis. The median time from consent to final molecular report was 45 days (interquartile range 37-57). Potentially actionable variants were detected for 14 patients (56%) and new treatment recommendations were identified for 12 patients (48%). Pathogenic germline variants were identified in three patients (12%), and one patient had a change of diagnosis. Implementation for CMP for AYA with sarcoma is clinically valuable, feasible and should be increasingly integrated into routine clinical practice as technologies and turnaround times continue to improve.

The benefits of event-driven architecture (EDA) derive from how systems and components are loosely coupled, which can facilitate independent development and deployment of systems, improved scaling and fault tolerance, and integration with external systems, especially in comparison to monolithic architectures. With the advent of new technologies such as containers, and microservices, a new generation of distributed event streaming platforms are commonly used in event-driven architecture for efficient event-driven communication. However, the asynchronous and distributed nature of EDA poses several problems that include handling failures, the dependence of an end-to-end transaction on individual component stability, etc. In this paper, we describe a new approach to designing self-regulating distributed applications with autopoietic and cognitive workflow management. This approach is based on the new science of information processing structures derived from the General Theory of Information. Just as a genome enables self-organizing and self-regulating biological structures, a digital genome enables a specific software application with several components, the ability to use distributed resources and self-regulate the evolution of the system based on functional and non-functional requirements, and best-practice policies that maintain the stability, safety, and survival under non-deterministic fluctuations in the demand for resources. In addition, cognitive workflow management assures end-to-end transaction delivery.

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.

Plant protein phosphatase 2Cs (PP2Cs) serve as negative regulators of protein kinase cascades activated in different processes and play important roles in plant development and abiotic-stress-mediated signaling pathways. In this study, a genome-wide study was conducted on the CqPP2C gene family. A total of putative 117 CqPP2C genes were identified. Comprehensive analyses of physical and chemical feature, chromosome localization and subcellular localization were conducted. According to phylogenetic analysis, CqPP2Cs were divided into 13 subfamilies. CqPP2Cs in the same subfamily had similar gene structure, conserved motif and all the CqPP2C proteins had the type 2C phosphatase domains. Gene duplication revealed that segmental duplication was the major driving force for CqPP2Cs expansion and all duplicated CqPP2Cs evolved from purifying selection. The expression of CqPP2Cs in various tissues under different abiotic stresses was analyzed using RNA-seq data. The results revealed that CqPP2C genes were involved in regulating development and stress responses of quinoa. Real-time quantitative reverse transcription PCR (qRT-PCR) analysis of six CqPP2C genes in subfamily A revealed that they were up-regulated or down-regulated under salt and drought treatments. Furthermore, the results of yeast two-hybrid assays revealed that subfamily A CqPP2Cs interacted not only with subclass III CqSnRK2s, but also with subclass II CqSnRK2s. Subfamily A CqPP2Cs could interact with CqSnRK2s in different combinations and intensities to respond to various biological processes and stresses. Overall, our results will be useful for understanding the functions of CqPP2C in regulating ABA signals and responding to abiotic stress.

The infections caused by various bacterial pathogens both in clinical and community settings represent a significant threat to public healthcare worldwide. The growing resistance to antimicrobial drugs acquired by bacterial species causing healthcare-associated infections has already become a life-threatening danger noticed by the World Health Organization. Several groups or lineages of bacterial isolates usually called ‘the clones of high risk’ often drive the spread of resistance within particular species. Thus, it is vitally important to reveal and track the spread of such clones and the mechanisms by which they acquire antibiotic resistance and enhance their survival skills. Currently, the analysis of whole genome sequences for bacterial isolates of interest is increasingly used for these purposes, including epidemiological surveillance and developing of spread prevention measures. However, the availability and uniformity of the data derived from the genomic sequences often represents a bottleneck for such investigations. In this dataset, we present the results of a comprehensive genomic epidemiology analysis of 17,546 genomes of a dangerous bacterial pathogen Acinetobacter baumannii. Important typing information including multilocus sequence typing (MLST)-based sequence types (STs), intrinsic blaOXA-51-like gene variants, capsular (KL) and oligosaccharide (OCL) types, CRISPR-Cas systems, and cgMLST profiles are presented, as well as the assignment of particular isolates to nine known international clones of high risk. The presence of antimicrobial resistance genes within the genomes is also reported. These data will be useful for researchers in the field of A. baumannii genomic epidemiology, resistance analysis and prevention measure development.

A significant amount of data is available for bench-scale fire assessments. However, there is little surrounding large-scale tests and even less so for bench-to-large scale comparisons. Large-scale tests require more material, time and preparation, making them more expensive than bench-scale assessments. However, large-scale testing is an essential component to bench-scale fire testing. The bench-scale tests must be representative of both large-scale and real fire behaviour to provide an insight into how a material or product will behave in the event of a fire during its end use application. The few existing studies reviewed in this study show more guidance and data is needed, especially on a large-scale. Unfortunately, the data that is presented is done so in an inconsistent manner using various means of presentation, statistical analysis, and modelling that doesn’t show clear comparisons between bench and large scale. Currently, no bench-scale method shows good agreement with large-scale fire behaviour. Overall, there is a need for more large-scale testing and data for direct comparisons to be made.

Small-scale fisheries are significant sources of nutrition and livelihood globally. However, increasing anthropogenic activities in coastal areas of developing countries have threatened the sustainability of artisanal fisheries and species. Fisheries of Sardinella maderensis (Lowe, 1838), to which Nigeria contributes 9% of the global stock and is a significant livelihood source in the coastal communities of Ibeju-Lekki, Lagos, face sustainability threats. This research investigated the effects of anthropogenic activities on S. maderensis fishery in the coastal areas of Ibeju-Lekki, Lagos, Nigeria. The study adopted a mixed-method approach involving qualitative and quantitative research methods. These include species identification, water quality analysis, land use change analysis, field surveys, focus group discussions and interviews. Results show genetic analysis of the fish samples from six stations revealed that the species had a mean of 98% similarity to Sardinella maderensis in NCBI. Multiple linear regression indicates that anthropogenic variables explained approximately 4.62% of the variance in the fish catch (p &lt; .001, R2 = .05). Water samples showed heavy metal levels were above international limits, high total petroleum hydrocarbon (TPH) pollution in all stations (27.56 mg/L- 3985.40 mg/L). Physiochemical analysis of water samples indicated TDS higher than acceptable limits (Mean = 24971.1 mg/L) and inadequate chlorophyll-a level (Mean = 0.01 µg/L). Hence, urgent strategies are required to mitigate anthropogenic threats through inclusive coastal management policies supporting resilient artisanal fisheries and marine spatial planning.

The authors of the article analyze the existing methods and models of technological preparation of machine-building industries. The structure of a three-level simulation model with network-centric control, the structures of individual elements of the simulation model and the process of simulation modeling are described. The criteria for choosing a rational option for the processing technological route have been determined. During the research, a simulation program was implemented in C++. It allows you to select the optimal scenario for the operation of a production site based on two criteria: time and cost. The volume of implementation is about 2x103 lines of code. A diagram of the modeling algorithm for the implemented program, a description of the classes and their interactions are given in the article. The developed simulation model was tested at a machine-building enterprise using the example of the “Pusher” part, manufactured under single-unit production condi-tions. The technological equipment used for the manufacture of this part was formed in the form of input data of the simulation model. The results of simulation modeling for the selected part are described. For each variant of the technological processing route, the values of variable costs and the duration of the production cycle were determined.

Machine learning, including deep learning, reinforcement learning, and generative artificial intelligence are revolutionising every area of our lives when data is made available. With the help of these methods, we can decipher information from larger datasets while addressing the complex nature of biological systems in a more efficient way. Although machine learning methods have been introduced to human genetic epidemiological research as early as 2004, those were never used to their full capacity. In this review, we outline some of the main applications of machine learning to assigning human genetic loci to health outcomes. We summarise widely used methods and discuss their advantages and challenges. We also identify several tools, such as Combi, GenNet and GMSTool, specifically designed to integrate these methods for hypothesis-free analysis of genetic variation data. We elaborate on the additional value and limitations of these tools from a geneticist’s perspective. Finally, we discuss the fast-moving field of foundation models and large multi-modal omics biobank initiatives.

During the progression of cancer cells, the degree of genome instability increases leading to genome chaos in populations of malignant cells. While normally chaos is associated with er-godicity, i.e., the state when the time averages of relevant parameters is equal to their phase space averages, the situation with cancer propagation is more complex. Chromothripsis, a catastrophic massive genomic rearrangement, is observed in many types of cancer leading to increased mu-tation rates. We present an entropic model of genome chaos and ergodicity and experimental evidence that increasing the degree of chaos beyond the non-ergodic threshold may lead to the self-destruction of the tumor cells. We study time and population averages of chromothripsis frequency in cloned rhabdomyosarcoma from rat stem cells. Clones with frequency above 10% result in cell apoptosis possibly due to mutations in the BCL2 gene. Potentially this can be used for suppressing cancer cells by shifting them into a non-ergodic proliferation regime.

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 effects of rare earth Y content on the microstructure and high-temperature oxidation properties of 47Fe-36Ni-15Cr-1.5Mn alloy at 1000°C were investigated. The results show that 47Fe-36Ni-15Cr-1.5Mn alloy oxidizes at 1000°C under laboratory atmospheric pressure to form an oxide film layer dominated by Cr2O3 and (Fe, Ni, Mn) Cr2O4 spinel, and the oxidation curve of the alloy follows the parabolic law. After the addition of rare earth Y, rare earth phases precipitated along the grain boundaries in the alloy, and the more Y content, the more precipitated phases in the grain boundaries. The alloy with added rare earths was oxidized at a high temperature of 1000 °C for 2160 min, the oxidation law still followed the parabolic law, while the rare earth phase at the grain boundary reacted with the oxygen atoms infiltrated from the outside to generate a rare earth Y-rich oxide residing at the boundary between the grain boundary and the precipitated phase of the alloy. Add 0.5 wt.% rare earth Y 47Fe-36Ni-15Cr-1.5Mn-0.5Y alloy 1000 ° C high temperature oxidation of the formation of spinel oxide crystalline particles, dense and complete oxide film layer, the surface of the addition of a small amount of (0.5 wt.%) rare earth Y after the refinement of the oxide particles, and in the alloy grain boundaries in the form of oxides reside in the alloy to inhibit the cations in the matrix and the oxygen negative ions. and oxygen-negative ions in the alloy matrix, improving the antioxidant performance of the alloy. With the further increase of rare earth Y, during the oxidation of the alloy at high temperature, the precipitation phase at the grain boundary promotes the inward diffusion of oxygen, resulting in the deterioration of the antioxidant property of the alloy.

Airworthiness certification requires proof of structure strength, which is performed generally through building block approach. To achieve this, representative intermediate scale experiments generated by test benches are in general needed, additionally to material characterization at coupons scale and structure testing at large scale. The VERTEX test bench can generate combined loading of tension/compression-shear-pressure on structural elements and was modelled with Finite Elements to perform virtual testing representative of its intermediate-scale specificity. The numerous bolted joints of the bench were modelled and their behavior identified in previous tests, so the model could quantitatively estimate the transfer function of the bench, which is the relation between the displacements imposed by the jacks and the resulting loads on a given sample. The VERTEX model was identified to represent load shapes and amplitudes on a training set, and was later confronted to a validation set of tests of tension and shear. A model with ideal boundary conditions was also developed for comparison but it failed to predict some load shape specificities and did not give any indication of loading amplitude. Application cases of the developed model are shown to assess a range of virtual testing possibilities.

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.

Background and objectives: TSC1 is a crucial component of the mTOR pathway, impacting cell growth, proliferation, and autophagy, while TSC2 is a tumor suppressor gene that regulates cell growth and is associated with the mTOR signaling pathway. In the present study, we analyzed TSC1 and TSC2 mRNA expression levels in rectal cancer, and evaluated the clinicopathological and prognostic characteristics of TSC1 and TSC2. Materials and Methods: TSC1 and TSC2 mRNA expression was examined in various cancer types. We further evaluated survival to determine the prognostic significance of TSC1 and TSC2 mRNA in CRC using The Cancer Genome Atlas (TCGA) data. Results: The study focused on rectal cancer, as it exhibited the most promising results. The patients were split into two subgroups, each comprising 50% of the total, based on the TSC gene expression levels. This division was made to assess the clinical characteristics associated with the expression of TSC1 and TSC2 genes. In the study, lower TSC1 expression was linked to venous invasion in rectal cancer patients, and there was also a related trend with lymphatic invasion, although it didn't reach statistical significance. Lower TSC2 expression was observed in younger patients and had some associations with sex and M stage, but these correlations were not statistically significant. When it came to survival analysis, TSC1 expression did not significantly impact overall survival, while higher TSC2 expression was associated with a poorer prognosis in rectal cancer. To enhance our comprehension, additional research, especially in larger case studies, is needed to explore the molecular mechanisms and clinical characteristics of TSC genes in colorectal cancer.

Permeability is an important transport property of porous materials, and its accurate evaluation is relevant in studying applied tasks such as CO2 injection into reservoirs and investigating groundwater quality issues. This study examines the dependence of permeability on total and connected porosity, hydraulic tortuosity, specific surface area, and mean pore radius based on the data of 408 cubic sub-volumes extracted from heterogeneous and naturally fractured cylindrical carbonate samples before and after injection of HCl solutions into them. These parameters were computed using pore-scale modeling of fluid flow. It has been shown that permeability correlates well with porosity and mean pore radius with correlation coefficients of R2≈0.65-0.79 for heterogeneous samples. It was found that the presence of natural fractures significantly influenced the relationship between permeability and other parameters. The relationship between permeability k, tortuosity τ, and specific surface area S is described by power laws k~τ-α and k~S-β, with coefficients α and β substantially exceeding those in the Kozeny-Carman equation. It was also found that there is a parabolic relationship between connected and total porosities both before and after rock dissolution with R2≈0.96-0.99. This allowed for estimation of percolation threshold porosity that are in good agreement with the literature data.

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.

Objective: To identify and characterise genomic and phylogenetically isolated SARS-CoV-2 viral isolates in patients from Lambayeque, Peru. Methods: nasopharyngeal swabs were taken from patients from the Almanzor Aguinaga Asenjo Hospital, Chiclayo, Lambayeque, Peru, which have been considered mild, moderate and severe cases of COVID-19. Patients had to have tested positive for COVID-19, using a positive RT-PCR for SARS-CoV-2. Subsequently, the SARS-CoV-2 complete viral genome sequencing was carried out using Illumina MiSeq®. The sequences obtained from the sequence were analysed in Nextclade V1.10.0 to assign the corresponding clades, identify mutations in the SARS-CoV-2 genes and perform quality control of the sequences obtained. All sequences were aligned using MAFFT v7.471. The SARS-CoV-2 isolate Wuhan NC 045512.2 was used as a reference sequence to analyse mutations at the amino acid level. The construction of the phylogenetic tree model was achieved with IQ-TREE v1.6.12. Results: it was determined that during the period December 2020 and January 2021, the lineages s C.14, C.33, B.1.1.485, B.1.1, B.1.1.1, B.1.111 circulated, lineage C.14 the most predominant with 76.7% (n=23/30), these lineages were classified in clade 20D mainly and also within clade 20B and 20A. On the contrary, the variants found in the second batch of samples of the period September – October 2021 were Delta Variant (72.7%), Gamma (13.6%), Mu (4.6%), Lambda (9.1%), distributed between clades 20J, 21G, 21H, 21J and 21I. Conclusions: This study reveals updated information on the viral genomics of SARS-CoV-2 in the Lambayeque region, Peru, which is crucial to understanding the origins and dispersion of the virus and provides information on viral pathogenicity, transmission and epidemiology.

Legume plants enter symbiosis with soil nitrogen-fixing bacteria (rhizobia), thereby gaining access to the assimilable atmospheric nitrogen. This symbiosis is important for agriculture, thus, biofertilizers with effective strains of rhizobia are created for crop legumes to increase their yield and minimize the amounts of mineral fertilizers used. In this work, we sequenced and characterized the genome of Rhizobium leguminosarum bv. viciae strain RCAM1022, a component of the ‘Rhizotorfin’ biofertilizer produced in Russia and used for pea (Pisum sativum L.).

Several studies in computer vision have examined specular removal, which is crucial for object detection and recognition. This research has traditionally been divided into two tasks: specular highlight removal, which focuses on removing specular highlights on object surfaces, and reflection removal, which deals with specular reflections occurring on glass surfaces. In reality, however, both types of specular effects often coexist, making it a fundamental challenge that has not been adequately addressed. Recognizing the necessity of integrating specular components handled in both tasks, we constructed a Specular-Light (S-Light) DB for training single-image-based deep learning models. Moreover, considering the absence of benchmark datasets for quantitative evaluation, the Multi-Scale Normalized Cross Correlation (MS-NCC) metric, which considers the correlation between specular and diffuse components, was introduced to assess the learning outcomes.

In the evolving landscape of pharmaceutical manufacturing, a comprehensive continuous production process is being crafted for small-scale active pharmaceutical ingredient production. This study focuses on continuous crystallization with separate nucleation and crystal growth units, as well as continuous downstream processing, encompassing filtration, washing, and drying until the formation of free-flowing particles. We introduce a novel continuous nucleator designed based on solubility data and produced via 3D printing, enabling a fast and precise small-scale manufacturing of a nucleator meeting the requirements for nucleation and for the further growth processes. The nucleator was evaluated with regard to its suitability for continuous long-term operation across various coupled crystallizers. As a practical application example it is connected to a slug flow crystallizer to enable high-quality continuous crystallization. Additionally, the full integration of downstream processes using the continuous vacuum screw filter to achieve free-flowing product particles is realized. Even under non-optimized process conditions, with the help of in-situ generation of nuclei free-flowing product particles were successfully obtained. This is particularly useful during drug development when no material is available for seed addition and quickly obtain product for further characterization.

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

Diversity-generating retroelements (DGRs) are prokaryotic systems providing rapid modification and adaptation of target proteins. In phages, the main targets of DGRs are receptor-binding proteins that are usually parts of tail structures and the variability of such host-recognizing structures enables phage adaptation to changes on the bacterial host surface. Sometimes, more than one target gene containing a hypermutated variable repeat (VR) can be found in phage DGRs. The role of mutagenesis of two functionally different genes is unclear. In this study, several phage genomes that contain DGRs with two target genes were found in the gut virome of healthy volunteer. Bioinformatics analysis of these genes indicated that they encode proteins with different topology; however, both proteins contain the C-type lectin (C-lec) domain with a hypermutated beta-hairpin on its surface. One of the target proteins belongs to a new family of proteins with a specific topology: N-terminal C-lec domain followed by one or more immunoglobulin domains. Proteins from the new family were named tentaclins after TENTACLe+proteIN. The genes encoding such proteins were found in the genomes of prophages and phages from the gut metagenomes. We hypothesized that tentaclins are involved in binding either to bacterial receptors or intestinal/immune cells.

Anastomosing rivers are wetland systems with multiple channels, and there are many constraints limiting in-situ observations of their hydrodynamics. Therefore, there are few reports on the hydrodynamic data of such rivers. In order to obtain the hydrodynamic parameters of the river channels without hydrological observations in the anastomosing rivers, this study proposes an expression method namely expression of channel morphological parameters (ECMP) for hydrodynamic calculations. The calculation formula of the ECMP method based on the shape factor, scale factor, and gradient factor of the flow cross-section as independent variables. This method can be used to calculate the average velocity, discharge, specific stream power, gross stream power and other hydrodynamic parameters of the flow cross-section at different water levels, only requiring the measurement of morphological parameters such as the average depth, width-depth ratio, and gradient of the flow (channel) cross-section. The applicability of the ECMP method was verified using measured hydrological data. The results show that the ECMP method is a practical calculation method with high computational accuracy and convenient application for calculating river hydrodynamic parameters. It has great application value in study on fluvial geomorphology and hydrodynamics, as well as in the reconstruction of ancient river hydrology and hydrodynamics.

In this observational study, we compared continuous physiological signals during an active stand test in adults aged 50 years and over, characterized as frail by three different criteria, using data from The Irish Longitudinal Study on Ageing (TILDA). Four independent groups were identified: those characterized as frail only by one of the frailty tools used (the physical Frailty Phenotype (FP), the 32-item Frailty Index (FI), or the Clinical Frailty Scale (CFS) classification tree), and a fourth group where participants were not characterized as frail by any of these tools. Continuous non-invasive physiological signals were collected during an active stand test: systolic (sBP) and diastolic (dBP) blood pressure, as well as heart rate (HR), using digital artery photoplethysmography. Additionally, frontal lobe cerebral oxygenation (Oxy), deoxygenation (Deoxy), and tissue saturation index (TSI) were also non-invasively measured using near-infrared spectroscopy (NIRS). The signals were visualized across frailty groups and statistically compared using one-dimensional statistical parametric mapping (SPM). A total of 1,124 participants (mean age 63.5 years, 50.2% women) were included: 23 were characterized as frail only by FP, 97 by FI, 38 by CFS, and 966 by none of these criteria. SPM analyses revealed that only the group characterized as frail by FI had significantly different signals (p<0.05) compared to the non-frail group. Specifically, they exhibited a lesser increase in HR between 5-15 seconds post-stand and larger deficits in sBP and dBP between 15-40 seconds post-stand, and possibly a lower Delta TSI at 20 seconds post-stand. In this comparison, the FI proved more adept at capturing distinct physiological responses to standing, likely due to its direct inclusion of cardiovascular morbidities in its definition.

Here, we critically evaluate the communication and integrative mechanisms in ctenophores or comb jellies, the descendants of the earliest animal lineage. Ctenophores convergently evolved their neuro-muscular systems compared to other animals. Besides the canonical neural organization with distinct synapses, recent 3D electron microscopy reconstruction revealed unique syncytial-type connectivity in some neuronal populations, providing additional support for the independent origins of neurons in ctenophores. Furthermore, it was proposed that non-synaptic transmission is the distinct characteristic of ctenophores, in contrast to other metazoans and Cajal’s neuronal doctrine, highlighting Golgi’s reticular theory. However, the astonishing diversity and higher information capacity of classical synapses and volume transmission indicate that chemical signaling is the hallmark of neural and other integrative systems regardless of their origins.

Transposons are mobile DNA sequences that contribute large fractions of many plant genomes. They provide exclusive resources for tracking gene and genome evolution and for developing molecular tools for basic and applied research. Despite extensive efforts, it is still challenging to accurately annotate transposons, especially for the beginners as transposon prediction requires necessary expertise in both transposon biology and bioinformatics. Moreover, the complexity of plant genomes and the dynamic evolution of transposons also bring difficulties for genome-wide transposon discovery. This review summarizes the three major strategies for transposon detections including repeat-based, structure-based, and homology-based annotation, and introduces the transposon superfamilies identified in plants thus far, and some related bioinformatics resources for detecting plant transposons. Furthermore, it describes the transposon classification and explains why the terms of ‘autonomous’ and ‘non-autonomous’ cannot be used to classify the superfamilies of transposons. Last, this review also discusses how to identify misannotated transposons and improve the quality of transposon database. This review provides helpful information about plant transposons and a beginner’s guide on annotating these repetitive sequences.

In Poland, the mountainous and hilly regions until recently were territories with unbalanced and poor diet quality, especially in early spring. Wild edible plants were or still are influential in supplementing a human diet. One of the earliest wild edible plants to appear in the growing season, characteristic of a broad swath of Europe from Ukraine to Germany, remains wild (bear) garlic (Allium ursinum L.). This paper assesses the impact of the vegetation site and preservation methods on selected parameters of the chemical composition of bear garlic. In addition, the connection between its genome pattern and chemical composition was assessed. The plants were collected in three locations in the Carpathian foothills, and the reference sample was plants collected in the lowlands. The site from which the raw material was harvested has a statistically significant effect on the chemical composition of the preserved leaves of bear garlic. The profiles of the analysed components differed in the material from a different site. Bear garlic leaves from mountainous areas had more analyzed components than those obtained from the lowland sites. Moreover, the material from the lowlands had a different genetic pattern from the leaves from the mountainous areas..

In our article in Genome Biology Ecology six years ago, one complete plastid genome of Belian was assembled for comparative analyses of the plastomes in Lauraceae. However, Ariati et al. (2023) concluded that our sequenced Belian individual could be located in the clade of Myristicaceae instead of that of Lauraceae. Here, we performed re-analyses of additional two Belian plastomes, along with 42 plastomes from plants spanning ten families of the Magnoliids. The plastomes of the three Belian individuals range from 157,535 to 157,577 bp in length. Comparative genomic analysis revealed 170 mutation sites in their plastomes, which include 111 substitutions, 53 indels, and six microinversions. Phylogeny was reconstructed using maximum likelihood and Bayesian approaches for 44 magnoliids species indicated that our three Belian individuals are nested among the species in the family Lauraceae rather than Myristicaceae.

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.

Constraint-based metabolic modeling approaches have enhanced our knowledge and understanding of the metabolism of prokaryotes and eukaryotes. This approach highly depends on the reconstruction process of genome-scale metabolic models (Mmodels). M-models can guide effective experimental design and yield new insights into the function and control of biological systems. Despite the recent advances in the automated generation of draft metabolic network reconstructions, the manual curation of these networks remains a labor-intensive and challenging task. Thus, these ten quick tips for the manual curation process are essential for optimizing high-quality metabolic model generation in less time. This collection of tips describes in great detail the resources and methods to ensure successful reconstruction. Furthermore, it increases the scope of other protocols of metabolic modeling by including resources to reconstruct eukaryotic organisms. Thus, all tips are applicable to a wide range of eukaryotic organisms. We believe this manuscript will interest a broad audience and researchers from different disciplines, spanning from microbiology and systems biology to biotechnology.

Cancer is a complex and devastating disease that has engaged scientists and researchers for decades. Despite tremendous efforts, previous hypotheses about cancer development have not achieved significant breakthroughs. Evolutionary Cancer Cell Biology (ECCB) is a novel and emerging branch of oncological science that provides an evolutionary perspective on the origin of cancer. It reveals that the cancer genome evolved hundreds of millions of years ago, long before multicellular organisms such as metazoans and humans emerged. ECCB aims to unify all evolutionary insights, hypotheses, and theories into a cohesive framework. It investigates the intricate relationship between cancer genomics and ancient pre-metazoan genes that emerge when normal cells transform into cancer cells. It challenges the conventional wisdom of cancer research by suggesting that cancer could arise through intrinsic cellular mechanisms without genetic alterations and mutations. Furthermore, it postulates that somatic mutations are only secondary, downstream events in the process of oncogenesis.

When describing the tribological behaviour of technical surfaces, the need for full length scale microtopographic characterization often arises. The self-affine of surfaces and the characterization of self-affine by a fractal dimension and its implantation into tribological models are commonly used. The goal of our present work was to determine the frequency range of fractal behaviour of surfaces by analysing the microtopographic measurements of a brake plunger. We also wanted to know if the bifractal and multifractal behaviour can be detected in real machine parts. As a result, we developed a new methodology for determining the fractal range boundaries to separate the nano- and micro-roughness. In order to reach our goals, we used atomic force microscope (AFM) and stylus instrument to provide measurements in wide frequency range (19 nm - 3 mm). As a result of the power spectral density (PSD) based fractal evaluation, it was found that the examined surface could not be characterized by a single fractal dimension and that we developed a methodology for stopping the margin of validity of each fractal dimension, and we also developed a methodology for determining the limits of validity of certain fractal dimensions.

Background. Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous systemic syn-drome that often coexists with multiple comorbidities. In high-complex COPD patients the role of the Cumulative Illness Rating Scale (CIRS) as a risk predictor of COPD exacerbation is not known. Objective. To determine the effectiveness of the CIRS score in detecting the association of comorbidities and disease severity with the risk of acute exacerbations in COPD patients. Methods. 105 adults with COPD were included in this prospective study. All participants at baseline had at least 2 moderate exacerbations or 1 leading to hospitalization. The primary outcome was a composite of moderate or severe COPD exacerbation during 12-months follow-up. Results. CIRS indices (CIRS total score, Severity Index and Comorbidity Index) showed a positive correlation with mMRC, CAT and a negative correlation with FEV1, FVC, FEV1/FVC. The three CIRS indices were able to predict the 12-month rate of moderate or severe exacerbation (CIRS-Total Score: Hazard Ratio (HR) = 1.12 (95% CI: 1.08-1.21); CIRS-Severity Index: HR = 1.21 (95% CI: 1.12-1-31); CIRS-Comorbidity Index = 1.58 (95% CI: 1.33-1.89)). Conclusions. Among patients with COPD, comorbidity number and severity, assessed by the CIRS score, influence the risk in moderate to severe exacerbations. The CIRS score also correlates with the severity of respiratory symptoms and lung function

(1) Background: Thrombophilia is a tendency towards hypercoagulability, and it is increased by pregnancy, and peaking around delivery.; (2) Methods: 80 Eighty thrombophilia patients admitted for delivery between 1/10/2017 and 1/12/2021 were prospectively studied, together with 80 eighty age- and para-matched control patients. Patients were admitted for delivery at term by means of cesarean section. The inflammation indexes from the complete blood count values analysis, in during both the 24 hours before and the 24 hours after labor—, extracted from the hospital’s medical records—, were calculated, and then correlated with uterine involution.; (3) Results: In pregnant patients treated for thrombophilia patients, the patients who did not manage to have close their uterine cavity closed with in the first 24-48 hours had significantly higher SII and AISI inflammation indexes SII and AISI , than the onesthose who did manage to have their uterine cavity closed their uterine cavity. In pregnant patients treated for thrombophilia patients, MLR is higher in patients without the Rh factor than in those with the Rh factor. In non-thrombophilia patients, PLR was significantly higher as compared to treated thrombophilia patients. In non-thrombophilia patients, MCVL increased with age and, before labor, while SII and AISI increased with age, postpartum. ; (4) Conclusions: There may be an underlying inflammation state that persisted despite treatment in some pregnant thrombophilia pregnant patients.

Cable-supported façades represent a novel approach in the design and technology of double skin façades (DSF). This type of systems not only offer flexibility in terms of exterior finishes, but also regulates the access of solar radiation, thereby transforming the appearance of the building in response to varying daylight conditions. However, the structural performance of these façades under wind, impact and seismic loads remains an active area of research. The study is a groundbreaking work that experimentally evaluates the wind and seismic behaviour of these type of façades. The methodology used for the evaluation of flexible masonry facades includes laboratory tests analysing the individual capacity of the connections and materials of the system under standardized and non-standardized procedures. A full-scale experimental sub-assembly specimen of a representative module of the façade is also subjected to uniformly distributed pressures of wind load tests as well as hard body and soft body impact tests. The setup considered the border conditions, tension loads, and actual materials. Furthermore, the earthquake assessment includes tests of full-scale specimens subjected to these demands. Research findings allowed the refinement and redesign of the system's components granting the validation of the DSF used as a case study.

A novel approach was developed that combined LP-based row generation with optimization-based sorting to tackle computational challenges posed by budget allocation problems with combinatorial constraints. The proposed approach dynamically generated constraints using row generation and prioritized them using optimization-based sorting to ensure a high-quality solution. Computational experiments and case studies revealed that as the problem size increased, the proposed approach outperformed simplex solutions in terms of solution search time. Specifically, for a problem with 50 projects (N = 50) and 2,251,799,813,685,250 constraints, the proposed approach found a solution in just 1.4 seconds, while LP failed due to the problem size. The proposed approach demonstrated enhanced computational efficiency and solution quality compared to traditional LP methods.

MADS-box genes play a crucial role in fruit ripening, yet limited research has been conducted on mango. Based on the conserved domains of this gene family, 84 MADS-box genes were identified in the mango genome, including 22 type I and 62 type II MADS-box genes. Gene duplication analysis revealed that both tandem duplication and segmental replication significantly contributed to the expansion of MADS-box genes in the mango genome, with purifying selection playing a vital role in the segmental duplication events within the MiMADS gene family. Cis-acting element analysis demonstrated that most MiMADS genes were hormonally regulated and participated in the growth, development, and stress resistance of mango fruit. Moreover, through expression pattern analysis and phylogenetic tree construction, we identified six MiMADS genes belonging to the SEP1 subfamily and two belonging to the AG subfamily as potential candidates involved in mango ripening regulation. Notably, Mi08g17750 and Mi04g18430 from the SEP1 subfamily were identified as key regulators inhibiting mango fruit maturation; their interaction network was also analyzed. These findings provide a foundation for further investigation into the regulatory mechanisms underlying mango ripening.

With 500+ papers and 20+ books spanning many scientific disciplines, Mark Burgin has left an indelible mark and legacy for future explorers of human thought and information technology professionals. In this paper, I discuss his contribution to the evolution of machine intelligence using his general theory of information (GTI) based on my discussions with him and various papers I co-authored during the past eight years. His construction of a new class of digital automata to overcome the barrier posed by the Church-Turing Thesis, and his contribution to Super-Symbolic Computing with Knowledge Structures, Cognizing Oracles, and Structural Machines are leading to practical applications changing the future landscape of information systems. GTI provides a model for the operational knowledge of biological systems to build, operate, and manage life processes using 30+ trillion cells capable of replication and metabolism. The schema, and associated operations derived from GTI are also used to model a digital genome specifying the operational knowledge of algorithms executing the software life processes with specific purposes using replication and metabolism. The result is a digital software system with a super-symbolic computing structure exhibiting autopoietic and cognitive behaviors that biological systems also exhibit. We discuss here one of these applications.

Leeches are well-known annelids due to their obligate blood-feeding habits. Some leech species secrete various biologically active substances which have important medical and pharmaceutical value in antithrombotic treatments. In this study, we provide a high quality genome of the Asian buffalo leech (Hirudinaria manillensis), based on which we performed a systematic identification of potential antithrombotic genes and their corresponding proteins. Combining automatic and manual prediction, we identified 21 antithrombotic gene families including fourteen coagulation inhibitors, three platelet aggregation inhibitors, three fibrinolysis enhancers, and one tissue penetration enhancer. A total of 72 antithrombotic genes, including two pseudogenes, were identified and most of their corresponding proteins forming three or more disulfide bonds. Three protein families (LDTI, antistasin, and granulin) have internal tandem repeats containing 6, 10, and 12 conserved cysteines, respectively. We also measured the anticoagulant activities of the five identified hirudins (hirudin_Hman1 ~ hirudin_Hman5). The results showed that three (hirudin_Hman1, hirudin_Hman2, and hirudin_Hman5), but not the remaining two, exhibited anticoagulant activities. Our study provides the most comprehensive collection of antithrombotic biomacromolecules from a leech to date. These results will greatly facilitate the research and application of leech derivatives for medical and pharmaceutical purposes of thrombosis.

Research on Cas9 nucleases from different organisms holds great promise for advancing genome engineering and gene therapy tools as it could provide novel structural insights into CRISPR editing mechanisms, expanding its application area in biology and medicine. The current study focuses on generating a construct to express a compact Cas9 nuclease (AnoCas9) from the thermophilic microorganism Anoxybacillus flavithermus. Next, distinctive AnoCas9 properties are investigated. AnoCas9 gene is expressed in E.coli producing a polypeptide fused with the maltose-binding protein (MBP-AnoCas9). His-Tag in its structure enables purification using metal-chelate chromatography followed by the cleavage of the polypeptide by TEV protease. Bioinformatical analysis of the CRISPR array found in the genome of an Anoxybacillus flavithermus strain helps predict a functional PAM sequence for AnoCas9, which is supported by in vitro experiments. The purified protein demonstrates nuclease activity in the presence of crRNA:tracrRNA duplex in the 37-60 °С range, with maximum activity observed at 45-55 °С. The analysis of FAM-labeled dsDNA substrate cleavage has allowed us to determine the functional AnoCas9 PAM motif as 5’-NNNNCDAA-3’. Thus, AnoCas9 adds to the repertoire of thermophilic Cas9 effectors and its properties suggest application in areas requiring the presence of thermostable CRISPR/Cas systems.

Elongate loach (Leptobotia elongata) is an endemic fish in China. Previous studies have provided some insights into the mitochondrial genome composition, and the phylogenetic relationships of L. elongata inferred using protein-coding genes (PCGs). However, the detailed information about is limited. Therefore, in this study, we sequenced the complete mitochondrial genome of L. elongata and analyzed its structural characteristics. The PCGs and mitochondrial genome were used for selective stress analysis and genomic comparative analysis respectively. The complete mitochondrial genome of the L. elongata, together with those of 36 Cyprinidae species, was used to infer the phylogenetic relationships of the Cobitidae family through maximum likelihood (ML) reconstruction. The results showed that the genome sequence has a full length of 16,591 bp, which includes 13 PCGs, 22 transfer RNA genes (tRNA), two ribosomal RNA genes (rRNA), and two non-coding regions (CR D-loop and light chain sub-chain replication origin OL). Overall, L. elongata shared the same gene arrangement and composition of the mitochondrial genes with other teleost fishes. The Ka/Ks ratios of all mitochondrial PCGs were less than 1, indicating that all the PCGs were evolving under purifying selection. Genome comparison analyses showed a significant sequence homology of species of Leptobotia. A significant identity between L. elongata and the other 5 Leptobotia species was observed in the visualization result, except for L. mantschurica, which lacked the tRNA-Arg gene and had a shorter tRNA-Asp gene. The phylogenetic tree revealed that the Cobitidae species examined here can be grouped into two clades, with L. elongata forming a sister relationship with L. microphthalma. This study could provide additional inferences for a better understanding of the phylogenetic relationships among Cobititdae species.

The semantic segmentation of high-resolution remote sensing images (HR-RSI) is crucial for a wide range of applications, such as precision agriculture, urban planning, natural resource assessment, and ecological monitoring. However, accurately classifying pixels in HR-RSI faces challenges due to densely distributed small objects and scale variations. Existing techniques, including Convolutional Neural Networks (CNNs) and other methods for hierarchical feature extraction and fusion of remote sensing image, often do not achieve the desired accuracy. In this paper, we propose a novel approach called the Hierarchical Rich-scale Fusion Network (HRFNet) to address these challenges. HRFNet utilizes advanced information rating and image partition techniques to extract rich-scale features within image layers. This allows for the adaptive exploration of both local and global contextual information. Moreover, we introduce a structured intra-layer to inter-layer feature aggregation module, which enables the adaptive extraction of fine-grained details and high-level semantic information from multi-layer feature maps in a highly flexible manner. Extensive experimentation has been conducted to validate the effectiveness of our proposed method. Our results demonstrate that HRFNet outperforms existing techniques, achieving state-of-the-art (SOTA) results on benchmark datasets, specifically the ISPRS Potsdam and Vaihingen datasets.

To conduct a precise impact assessment of marine diesel engines, a 200t floating impact platform was utilized to simulate realistic testing conditions. The testing generated the acceleration time curve and the impact response spectrum for the diesel engine. According to the applicable standards, the spectral velocity was chosen as the evaluation index, and an evaluation of the longitudinal, transverse, and vertical impact environment of the diesel engine was conducted. The shock factor interpolation method was corrected using the confidence interval based on normal distribution, and the interpolated confidence interval of the shock factor was determined. The findings reveal that: The 200t-class floating shock platform is capable of providing a reliable shock environment for diesel engine tests. The shock wave serves as the primary external force during the experiment, and the impact of bubble pulsation can be disregarded when assessing using the floating shock platform. To more accurately describe the experimental shock intensity when presented with dispersed data, the confidence interval can be utilized, and the resulting prediction formula provides a higher level of impact safety. The obtained conclusions can serve as a reference for predicting the shock environment of large shipboard equipment using the shock platform.

The Quantum-Cosmos Nexus Theory delves into the intricate web of relationships that tie together fundamental constants, cosmological properties, and the boundaries of our comprehension in the realm of physics. It unveils a profound interconnection between the gravitational constant (G), the speed of light (c), and the parameters of the observable universe. It introduces a unification equation that hints at a connection between the fundamental constants. It also introduces a new constant, , which is similar to the Planck constant but, on a large scale, signifies the ultimate unit of action or energy on a cosmic scale. With this new constant, new units similar to Planck units have been introduced. They are the equivalence of Planck units in the sense that they represent the limits of our current understanding of physics on the largest scale. The theory also shows that most of the fundamental constants of nature, including the gravitational constant (G), the speed of light (c), vacuum permittivity (ε₀) vacuum permeability (u₀), the Boltzmann constant (K_B), and the fine-structure constant (α), can be derived from these new units and Planck units. The first derived equation suggests a potential weakening of the gravitational constant over time, assuming the density remains relatively constant. Although this is a matter of speculation, it has the potential to explain observations related to dark matter. The theory also makes use of the Planck force, defining it as the maximum force on the quantum and cosmic scales. It also emphasizes that the Planck scale is not the ultimate limit and reveals our observational constraints, offering a unique perspective on the universe's fundamental workings. The Quantum-Cosmos Nexus Theory reveals how fundamental constants, cosmic dynamics, and the limits of our understanding converge, opening the door to fresh perspectives on the underlying principles of the universe.

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.

Image segmentation is the process of partitioning an image into multiple segments where the goal is to simplify the representation of the image and make the image more meaningful and easier to analyze. In particular, semantic segmentation is an approach of detecting the classes of objects, based on each pixel. In the past, most semantic segmentation models were for only one single style, such as urban street views, medical images, or even Manga. In this paper, we proposed a semantic segmentation model called Dual-Pyramid Wide Residual Network (DPWRN) to solve the segmentation for cross-style datasets, which is suitable for diverse segmentation applications. The DPWRN integrated the Pyramid of Kernel paralleled with Dilation (PKD) and Multi-Feature Fusion (MFF) to improve the accuracy of segmentation. To evaluate the generalization of the DPWRN and its superiority over most state-of-the-art models, three datasets with completely different styles are tested in the experiments. Finally, the DPWRN verified its generalization and also showed its superiority over most state-of-the-art models.

Multidrug resistance (MDR) among gram-negative bacteria is a global public health threat because it has exhausted all standard therapeutic options. This has necessitated clinicians to reconsider colistin, an “old sort” antibiotic which was deemed toxic for clinical use. Unfortunately, swift resistance towards colistin by K. pneumoniae has been reported in different parts of the world. The study aimed at investigating the genetic determinants of colistin resistance in K. pneumoniae isolated from patients admitted in a tertiary care hospital in Kampala, Uganda. 31 archived multidrug resistant K. pneumoniae isolates obtained from rectal swabs of patients admitted to the Mulago Hospital ICU were retrieved. From this collection, we selected 7 colistin resistant K. pneumoniae isolates for whole genome sequencing and molecular profile analysis. In silico sequence data analyses were performed using established web-based bioinformatics tools. The sequence analysis of the genes involved in colistin resistance revealed several non-synonymous mutations in nucleotide sequences of pmrA, pmrB, phoP, phoQ and mgrB genes. Insertion transposase genes for the insertion sequences IS1 and IS5 which are highly implicated in colistin resistance via modification or inactivation of mgrB gene were identified in all isolates and were located in the chromosomal DNA at different genomic positions. No plasmid-borne mcr genes were detected. More so, the strains harbored numerous multidrug resistant genes. This study underscores the need of genomic surveillance of K. pneumoniae strains to limit further spread of colistin resistance genes to avert the potential risk of pandrug resistance. And high throughput sequencing is imperative.

Gibberella ear rot (GER) caused by Fusarium graminearum (teleomorph Gibberella zeae) is one of the most destructive diseases in maize that severely reduces grain yield and contaminates several potential mycotoxins. However, few efforts had been devoted to dissect the genetic basis of maize GER resistance. In the present study, a genome-wide association study (GWAS) was conducted in a maize association panel consisting of 303 diverse inbred lines. The phenotypes of GER severity were evaluated using kernel bioassay across multiple time points in the laboratory. Then, three models including fixed and random model circulating probability unification model (FarmCPU), general linear model (GLM) and mixed linear model (MLM), were conducted simultaneously in GWAS to identify single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance. A total of four individual significant association SNPs with the phenotypic variation explained (PVE) ranging from 3.51 to 6.42% were obtained. Interestingly, the peak SNP (PUT-163a-71443302-3341) with the greatest PVE value, was co-localized in all models. Subsequently, 12 putative genes were captured from the peak SNP that several of these genes were directly or indirectly involved in disease resistance. Overall, these findings contribute to understand the complex plant-pathogen interactions in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the kernel bioassay that can be used for evaluating and selecting elite germplasm resources with GER resistance in maize.

By the end of 2023, biowaste must be completely separated or recycled at source based on the EU legislation. Separate biowaste collection and valorisation towards biofuels could play an essential role in the biobased circular economy. In this context, the principal goal of this paper was to demonstrate in pilot scale the technological solution of bioethanol production via the utilisation of urban source-separated biowaste within the city context of Athens, Greece. More specifically, the main aim was the demonstration of a pilot system in continuous operation (over 10 operating cycles) with real feedstock – wet separately collected biowaste. From the 11 pilot trials performed with wet feedstock, the mean starch and cellulose degradation of the pilot trials amounted up to 80.69±16.27% and 79.41±10.37% respectively, while the bioethanol yield was 74.05±6.82%. The latter was comparable to that of more intensive pretreatment methods. Homogenization and shredding that was applied in this study, stand as promising and cost-effective pretreatment methods for bioethanol production from wet feedstock. Further research is needed to optimize conditions and evaluate scalability. Nevertheless, pilot scale testing is a crucial step in the development and deployment of this technology since it serves as a bridge between laboratory research and full-scale implementation, offering a practical and controlled environment to validate and optimize the technology while minimizing risks and uncertainties.

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.

This paper deals with the analysis of the cognitive functions of the cerebral cortex or cortex in the evolutionary context. The triune brain model is presented given its notorious popularity in fields that are not strictly neuroscientific, and its limitations and inaccuracies are also shown. Although it is an outdated theory, this one represented the passage to a new era, because it really was the model of the movement towards understanding the brain in evolutionary terms. Next, the paper illustrates the different areas of the cortex and their functions, as well as the evolution of the brain and the cortex in vertebrates. To date, the expansion of the cortex with the amniotes was placed 300 million years ago, although recent studies place it in the lampreys more than 500 million years ago. Evolutionary changes in mammalian brain and cortex size are discussed, showing the evolution from three to six cell layers and trends in different groups of mammals. Finally, the most recent contributions in the field of research are illustrated, such as the role of neurogenesis and the evolution of the connectivity of the cortex.

In recent decades, porous scaffolds for bone tissue engineering (BTE) have gained significant attention. Considerable research efforts have been dedicated to investigating the impact of scaffold pore size on a diverse array of biological processes, including cell-scaffold interactions, substance transportation, and vascularization. However, the multi-scale hierarchical porosity, a key structural characteristic of natural bone, has rarely been replicated in BTE scaffolds due to the challenges of controlling the scaffold structure across multiple length scales. With the advancement of manufacturing technology, there has been increasing research on biomimetic multi-scale hierarchical materials, which are also gaining favor in the field of BTE. Therefore, there is an urgent need to review multi-scale hierarchical porous BTE scaffolds. This paper aims to review the role and fabrication methods of multi-scale porous BTE scaffolds at different length scales, the design and manufacturing of new BTE scaffolds for bone regeneration.

: Medial temporal lobe atrophy (MTA) remains an important imaging biomarker in brain magnetic resonance imaging (MRI) for diagnosing and evaluating Alzheimer's disease (AD). We compared the detection performance for determining significant MTA and the correlation with Scheltens' scale between two automatic volumetry software, NeuroQuant® and Aqua®, in non-AD and AD groups. Overall, 127 (non-AD, 54; AD, 73) individuals who underwent three-dimensional T1-weighted volumetric MRI in our hospital between January and August 2011 were enrolled and retrospectively analyzed using NeuroQuant® and Aqua®. The accuracy, sensitivity, and specificity for detecting significant MTA and the correlation for Scheltens' scale with the mean hippocampal volume of each software were evaluated. The study sample’s mean age was 78 (range, 59–97) years. Regarding accuracy and specificity, Aqua® was non-inferior to NeuroQuant®. Aqua® had significantly higher overall specificity than NeuroQuant® for detecting significant MTA. Additionally, the calculated mean hippocampal volume of Aqua® was more correlated with Scheltens' scale (Kendall's τ, - 0.48) than that of NeuroQuant® (Kendall's τ, - 0.20). The accuracy and specificity of Aqua® in detecting MTA are not inferior to those of NeuroQuant®. Additionally, Aqua® has a stronger correlation of mean hippocampal volume with Scheltens' scale than NeuroQuant®.

Ornamental kale (Brassica oleracea var. acephala) is an attractive ornamental plant with a range of leaf colors and shapes. Breeding new varieties of ornamental kale has proven challenging due to its lengthy breeding cycle and the limited availability of genetic markers. Microspore culture is an effective approach to generate new materials and genetic maps are a prerequisite for quantitative trait loci analysis, MAS, fine gene mapping, and genome sequence assembly. In this study, a F1DH ornamental kale population comprising 300 DH lines was constructed using microspore culture. A high-density genetic map was developed by conducting whole-genome sequencing on 150 individuals from the F1DH population. The genetic map contained 1,696 bin-markers with 982,642 single-nucleotide polymorphisms (SNPs) spanning a total distance of 775.81 cM on all nine chromosomes with an average distance between markers of 0.46 cM. The ornamental kale genetic map contained substantially more SNP markers compared with published genetic maps for other B. oleracea crops. The F1DH progenies provide an excellent resource for germplasm innovation and breeding new varieties of ornamental kale. The high-density genetic map provides crucial insights for gene mapping and unraveling the molecular mechanisms behind important agronomic traits in ornamental kale.

The duality is one of the most interesting properties of the Laplace and Fourier transforms associated to the integer order derivative. Here, we will generalize it for fractional derivatives and extend the results to the Mellin, Z and discrete-time Fourier transforms. The scale and nabla derivatives are used.

The aim of this work is the study of genome organization and metabolic potential of Streptomyces carpaticus strain SCPM-O-B-9993, promising plant-protecting and plant-stimulating strain isolated from brown semi-desert soils with a very high degree of salinity. The genome of the strain contains of a linear chromosome of 5,968,715 bp and has no plasmids. Gene clusters of production of secondary metabolites with antimicrobial properties (ohmyungsamycin, pellasoren, naringenin, ansamycin) were identified in the genome. The strain SCPM-O-B-9993 has antiviral activity against cucumber mosaic virus on tomatoes under laboratory conditions.

COVID-19 has rapidly spread worldwide since December 2019. During the pandemic, SARS-CoV-2 repeatedly mutated from Alpha to Omicron. The severity and mortality are related to age, sex, and underlying diseases (respiratory, cerebrovascular, cardiovascular, metabolic, cancer, and immune diseases). We retrospectively studied 44 hospitalized stroke patients infected with the SARS-CoV-2 Omicron variant. The mortality rate of hospitalized stroke patients with COVID-19 was 6 (13.6%). The cause of death was coagulopathy in 3 cases of ischemic stroke. High modified Rankin Scale score（mRS）of stroke patient was correlated with severity of COVID-19. The timing of vaccination is inversely correlated with COVID-19 severity. In conclusion, stroke patients with COVID-19 have high mortality rates attributed to coagulopathy. Stroke patients with high mRS scores are more likely to develop severe COVID-19. In high mRS scores, therapy for severe COVID-19 should be administered.

While it is well known that 98-99% of the human genome do not encode proteins, but are nevertheless transcriptionally active and give rise to a broad spectrum of noncoding RNAs (ncRNAs) with complex regulatory and structural functions, specific functions have so far been assigned to only a tiny fraction of all known transcripts. On the other hand, the striking observation of an overwhelmingly growing fraction of ncRNAs, in contrast to an only modest increase in the number of protein-coding genes, during evolution from simple organisms to humans, strongly suggests critical but so far essentially unexplored roles of the noncoding genome for human health and disease pathogenesis. Research into the vast realm of the noncoding genome during the past decades thus lead to a profoundly enhanced appreciation of the multi-level complexity of the human genome. Here, we address a few of the many huge remaining knowledge gaps and consider some newly emerging questions and concepts of research. We attempt to provide an up-to-date assessment of recent insights obtained by molecular and cell biological methods, and by the application of systems biology approaches. Specifically, we discuss current data regarding two questions: (1) By which mechanisms could evolutionary recent ncRNAs with critical regulatory functions in a broad spectrum of cell types (neural, immune, cardiovascular) constitute novel thera-peutic targets in human diseases ? (2) Since noncoding genome evolution is causally linked to brain evolution, and given the pro-found interactions between brain and immune system, could human-specific brain-expressed ncRNAs play a direct or indirect (immune-mediated) role in human diseases? Synergistic with the remarkable recent progress regarding delivery, efficacy, and safety of nu-cleic acid-based therapies, the ongoing large-scale exploration of the noncoding genome for human-specific therapeutic targets is encouraging to proceed with the development and clinical evaluation of novel therapeutic pathways suggested by these research fields.

Underwater robotics equipped with visual detection systems have the function of detecting un-derwater artifacts, which is of great significance to deep-sea archaeology. Underwater artifacts are located in complex environments with poor imaging conditions, and the targets have chal-lenging problems such as breakage, stacking, and sediment burial, which causes the marine cul-tural target detection failures. To solve these problems, this paper proposes an underwater cul-tural target detection algorithm based on the deformable deep aggregation network model for underwater robotics exploration. To fully extract the target feature information of underwater targets in complex environments, this paper designs a multi-scale deep aggregation network with deformable convolutional layers. Besides, the BAM attention module is designed for fea-ture optimization, which enhances the potential feature information of the target while weak-ening the background interference information. Finally, the target prediction is achieved through feature fusion at different scales. The proposed algorithm has been extensively validat-ed and analyzed on the collected underwater artifact datasets, and the precision, recall, and mAP of the algorithm have reached 93.1%, 91.4%, and 92.8%, respectively. In addition, the present al-gorithm has been practically deployed on the underwater robotics. In the deep-sea tests, the ar-tifact detection frame rate reaches up to 19 fps, which satisfies the real-time target detection。

Several genetic tools have been developed for Clostridium acetobutylicum utilizing 5-fluorouracil (5FU) or 5-fluorocytosine (5FC) resistance as a selection method. A method based on the integration, by single crossing-over, of a suicide plasmid (pCat-upp) followed by selection for the second crossing-over using a counter-selectable marker (the upp gene and 5FU resistance) was recently developed for genome editing in C. acetobutylicum. This method allows the modification of the genome without any marker or scar left in a strain of C. acetobutylicum that is ∆upp. Unfortunately, 5FU has strong mutagenic properties inducing mutations in the strain’s genome. After numerous applications of the pCat-upp/5FU system for genome modification in C. acetobutylicum, the bacteria became completely resistant to 5FU in the presence of the upp gene, resulting in failure in the selection for the second crossing-over. It was found that the potential repressor of the pyrimidine operon, PyrR, was mutated at position A115, leading to the 5FU resistance of the strain. We developed two plasmids, one overexpressing the native pyrR gene and a suicide plasmid carrying a non-mutated and optimized pyrR gene (pyrR*) and upp, which allowed us to restore the 5FU sensitivity of the strain. We also improved the pCat-upp/5FU system by reducing the concentration of 5FU from 1mM to 5 µM using a define synthetic medium.

Small-scale facilities play a significant role in the landscape of nuclear physics research in Europe. They address a wide range of fundamental questions and are essential for teaching and training personnel in accelerator technology and science, providing them with diverse skill sets, complementary to large projects. The current status and perspectives of nuclear physics research at small-scale facilities in Europe will be given.

Women's empowerment represents a process in which they are recognized as subjects of rights. Despite advances in women's rights, inequalities persist in various areas. This study aims to validate a psychometric scale of 31 items in seven factors: Participatory Empowerment, Temerity, External Influences, Independence, Social Satisfaction and Equality. The objective is to measure the empowerment of women in the university context. The research was carried out in a transversal and non-experimental manner, with the participants' voluntary collaboration, including the participation of 1,478 university students from four Higher Education Institutions in Zone 4 of Ecuador. The data was analyzed through inferential statistics, including exploratory and confirmatory factor analysis. The results indicated that the instrument for measuring empowerment can be made up of 24 items grouped into six factors, and this model showed a good fit.

The grinding process by friction at the micro-scale in a mill with stones is considered a variable combination of contacts: with two-body (the asperities of lower millstone in direct contact with the asperities of upper millstone) and the three-body (micro-particles of ground seeds trapped between the asperities of lower and the upper stones of the mill). Three elements are described: (1) the mechanic contact of the asperities of the lower and upper millstone, to predict pressures on asperities, by modeling; (2) tests on a millstone sample covered with grinding particles, and (3) tests on a wafer sample formed by the millstones with the grinding particles between them. The paper highlights the combined effects of the micro-scale friction by individual measurements and to sum these effects an analytical model was used, and to validate the model, several experiments were performed. A suitable grind by friction assumes the grain’s movement and the interaction between the seeds and solid surfaces and is highlighted through theoretical and experimental studies. Topography analysis of the surface of the millstones revealed the model of microscopic frictional force. Endpoint measurements (the traces of the surface topography evolution), enable model verification in the grinding process.

Background: Patients with allergic rhinitis (AR) have bothersome symptoms that may assess using the visual analog scale (VAS). Asthma frequently is associated with AR. The present study investigated the role of VAS in children with newly-diagnosed AR. Methods: Parameters were VAS for nasal and asthma symptoms, and doctor’s perception of these diseases, medication use, and asthma comorbidity. Results: 67% of AR children had asthma. Severity of perceived nasal symptoms was associated with more intense asthma symptoms and doctor’s perception of disease severity (p<0.001 and p=0.02, re-spectively. Conclusions: Allergic rhinitis frequently is associated with asthma in child-hood. Symptom perception assessment using VAS is a simple tool for assessing their intensity. Moreover, the severity of nasal symptoms is associated with asthma symptom severity. Therefore, asthma should be carefully considered in AR children and require appropriate symptom perception assessment.

Simple weir irrigation was recently introduced in rural areas of Zambia. This irrigation technique is based on gravity diversion of the river flow using simple weirs. This study was conducted between November 2022 to January 2023 in 3 northern region provinces (Luapula, Copperbelt, and North-western) of Zambia to perform a diagnostic assessment on simple weirs during the dry and the wet seasons. In this study, 15 single-line simple weirs were selected. The objective of the study is to assess the physical status, identify problems and extent, and estimate water diversion potential by each single-line weir. The findings of this study showed that 67% of weirs were in excellent status (recently maintained and repaired), and 26% of the weirs were partially damaged (leakages, decayed thatch grass). The study revealed that single-line weirs were able to raise a flood height of 0.1m at low flow and 0.5m at medium flow. It was found that single-line weirs in excellent condition diverted more than 90% of the river flow while poorly maintained weirs diverted below 45% of the river discharge. Based on the findings, Single-line weirs have the potential to assist small-scale farmers in accessing river water for irrigation purposes through diversion.

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.

Keywords: bariatric surgery, sleeve gastrectomy, Roux-en-y gastric bypass, obesity, microbiota, gut-brain axis, beck scale, depression, diet, probiotics

Rapid advances in the screening, diagnosis, and treatment of genetic disorders has increased the number of conditions that could be detected through universal newborn screening (NBS). However, addition of conditions to the Recommended Uniform Screening Panel (RUSP) and implementation of nationwide screening has been a slow process taking several years to accomplish for individual conditions. Here we describe web-based tools and resources developed and implemented by the newborn screening translational research network (NBSTRN) to advance newborn screening research and support NBS stakeholders. NBSTRN’s tools include the Longitudinal Pediatric Data Resource (LPDR), the NBS Condition Resource (NBS-CR), the NBS Virtual Repository (NBS-VR), and the Ethical, Legal, and Social Issues (ELSI) Advantage. Research programs including the Inborn Errors of Metabolism Information System (IBEM-IS), BabySeq, EarlyCheck, and Family Narratives Use Cases have utilized NBSTRN’s tools, and in turn contributed research data to further expand and refine these this resource. Additionally, we discuss ongoing tool development to facilitate expansion of genetic disease screening in increasingly diverse populations. In conclusion, NBSTRN’s tools and resources provide a trusted platform to enable NBS stakeholders to advance NBS research and improve clinical care for patients and their families.

In recent years, the high-frequency abnormal price fluctuations of small-scale agricultural products have been detrimental to market stability. The traditional method based on statistical data of production factors can no longer accurately predict abnormal price fluctuations. Taking scallions as a case, the paper identifies price influencing factors from massive network information, and analyzes the causes and changing characteristics of price fluctuations from four perspectives: market supply, economic environment and market sentiment, and attention. Initially, the study employs an LDA topic model to extract factors from online sentiment data over the past four years, including market supply and demand, economic conditions, related agricultural prices, and market attention. Subsequently, using the SO-PMI algorithm to expand domain-specific lexicons and employing semantic and sentiment analysis with syntactic parsing, the study aims to improve the accuracy of sentiment quantification in text analysis. Furthermore, cointegration and Granger causality tests validate the significant impact of these factors on scallion price fluctuations, mitigating spurious regression issues. Finally, by employing a TVP-VAR model, the study compares the impulse responses and shock magnitudes of various factors in different time and spatial dimensions. It also delves into the mechanisms of heterogeneous impacts and trends in scallion prices, considering the corresponding socio-economic context and public sentiment events within specific time windows, thereby providing valuable decision-making insights for the healthy development of agricultural markets.

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.

Digital Image Correlation (DIC) is an optical technique used to measure surface displacements and strains in materials and structures. This technique has demonstrated significant utility in structural examination and monitoring. This manuscript offers a comprehensive review of contemporary research and applications that have leveraged the DIC technique in laboratory-based structural tests. The reviewed works encompass a broad spectrum of structural components, such as concrete beams, columns, pillars, masonry walls, infills, composite materials, structural joints, steel beams, slabs, and other structural elements. These investigations have underscored the efficacy of DIC as a metrological instrument for precise quantification of surface deformation and strain in these structural components. Moreover, the constraints of the DIC technique have been highlighted, especially in scenarios involving extensive or complex test configurations. Notwithstanding these constraints, the DIC methodology has validated its effectiveness as a strain measurement instrument, offering numerous benefits such as non-invasive operation, full-field measurement capability, high precision, real-time surveillance, and compatibility with integration into other measurement instruments and methodologies.

Background: The potential impact of the pandemic on mental health should not be overlooked, especially among vulnerable populations such as women who gave birth during the COVID-19 pandemic. The aim of the study was to assess the mental health status of women who gave birth during a pandemic and to examine the possible links between the onset of depressive disorder symptoms in close proximity to the time of delivery and the socio-demographic conditions, health status and obstetric circumstances of the patients. Materials and Methods: The study is a cross-sectional survey conducted from 01.03.2020 to 01.03.2023, during the period of SARS-CoV-2 (COVID-19) pandemic, based on a retrospective evaluation of 860 postpartum women. The screening tool used to assess symptoms of postpartum depression was the Edinburgh Postnatal Depression Rating Scale (EPDS) questionnaire. The questionnaire was completed both in the Obstetrics and Gynaecology Clinical Sections I and II of the "Pius Brînzeu" County Emergency Hospital from Timisoara, Romania and online using Google Forms. Results: The highest severity of postpartum depression symptoms was observed during the COVID-19 pandemic. The results of the study conducted during the period of SARS-CoV-2 pandemic (COVID-19) showed that the prevalence of major postpartum depressive disorder (EPDS ≥ 13) was 54.2% (466 patients), while 15.6% (134) had minor depressive disorder (10 &lt; EPDS ≤ 12) in the first year after delivery. Comparing these results with those obtained in research conducted before the onset of the pandemic period shows an alarming increase in the prevalence of postpartum depression. Risk factors associated with postpartum depression included type of delivery, level of education, socio-economic conditions, health status, age, background, personal obstetric history (number of abortions on demand, parity). Conclusions: The effects of the pandemic on mental health are of particular concern for women in the first year after childbirth. Observing these challenges and developing effective measures to prepare our health system early can help and facilitate effective mental health screening for postpartum women, promoting maternal and child health.

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 advances in understanding the Planck scale have led to a new, straightforward method for quantizing the general theory of relativity. This results in a theory of gravity that predicts the same outcomes as general relativity with greater fundamental comprehension connected directly to the Planck scale.

Background: Ultrasonography (US) represents the gold standard imaging method for the assessment of testicular lesions (TL). The gray-scale (GSUS) and color-Doppler (CDUS) ultrasound examination allow sonographers to investigate size, margins, echotexture and vascular features of TL, with the effort to differentiate benign from malignant lesions. Recently, the use of contrast-enhanced US (CEUS) and sonoelastography (SE) led to further improvements in the differential diagnosis of TL. Although GSUS and CDUS are often sufficient to suggest the benign or malignant nature of TL, CEUS can be decisive in the differential diagnosis of unclear findings, while SE can help to strengthen the diagnosis. The contemporary combination of GSUS, CDUS, CEUS and SE led to a new diagnostic paradigm named multiparametric US (mp-US), able to provide a more detailed characterization of TL than the single techniques alone. This narrative and pictorial review is aimed to describe the mp-US appearance of several TL. Methods: An extensive Medline search was performed identifying studies in the English language focusing on mp-US evaluation of TL. Results: a practical mp-US “identity card” and iconographic characterization of several benign and malignant TL is provided herein. Conclusions: the mp-US characterization of TL reported herein can be useful in daily clinical practice.

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.

This paper presents a two-stage hierarchical neural network using image classification and object detection algorithms as key building blocks for a system that automatically detects a potential design right infringement. This neural network is trained to return the Top-N original design right records that highly resemble the input image of a counterfeit. Design rights specify the unique aesthetic characteristics of a product. Due to the rapid change of trends, new design rights are continuously generated. This work proposes an Ensemble Neural Network (ENN), an artificial neural network model that aims to deal with a large amount of counterfeit data and design right records that are frequently added and deleted. At first, we performed image classification and objection detection learning per design right using the existing models with a proven track record of high accuracy. The distributed models form the backbone of the ENN and yield intermediate results aggregated at a master neural network. This master neural network is a deep residual network paired with a fully connected network. This ensemble layer is trained to determine the sub-models that return the best result for a given input image of a product. In the final stage, the ENN model multiples the inferred similarity coefficients to the weighted input vectors produced by the individual sub-models to assess the similarity between the test input image and the existing product design rights to see any sign of violation. Given 84 design rights and the sample product images taken meticulously under various conditions, our ENN model achieved average Top-1 and Top-3 accuracies of 98.409% and 99.460%, respectively. Upon introducing new design rights data, a partial update of the inference model was done an order of magnitude faster than the single model. ENN maintained a high level of accuracy as it scaled out to handle more design rights. Therefore, the ENN model is expected to offer practical help to the inspectors in the field, such as the customs at the border that deal with a swarm of products.

Taiwan is highly susceptible to global warming, experiencing a 1.4°C increase in air temperatures from 1911-2005, which is twice the average for the Northern Hemisphere. This has led to higher rates of respiratory and cardiovascular mortality. Accurately predicting maximum temperatures during the summer season is crucial, but numerical weather models become less accurate and more uncertain beyond five days. To improve forecast reliability, statistical post-processing is needed to address systematic errors. In September 2020, NOAA NCEP implemented the Global Ensemble Forecast System version 12 (GEFSv12) to help manage climate risks. This study developed a Hybrid statistical post-processing method that combines Artificial Neural Networks (ANN) and Quantile mapping (QQ) approaches to predict daily maximum temperatures and extremes in Taiwan during the summer season. The Hybrid technique, utilizing deep learning techniques, was applied to the GEFSv12 reforecast data and evaluated against ERA5 reanalysis. The Hybrid technique was the most effective among the three techniques tested. It had the lowest bias, RMSE, and highest correlation coefficient. It successfully reduced the warm bias and overestimation of Tmax extreme days. This led to improved prediction skills for all forecast lead times. Compared to ANN and QQ, the Hybrid method was more effective in predicting summer daily Tmax and its extremes on an extended-range time scale deterministic and ensemble probabilistic forecasts over Taiwan.

Vancomisin resistant enterococcus(VRE), is a resistant microorganism which colonizates and causes infections in hospitalized patients. It was aimed to show the spread of vancomycin-resistant Enterococcus (fVREfm) step-by-step in all intensive care units, which started with the growth of vancomycin-resistant Enterococcus faecium (VREfm) on 02.12.2021 in the blood culture of a patient hospitalized in the anesthesia intensive care unit of our hospital and was found to have reached epidemic size in the surveys. Rectal swab samples were taken from all patients hospitalized in intensive care units, VRE colonization was determined and the VanA and VanB resistance genes associated with vancomycin resistance of VREfm isolates were determined by PCR method, and clonal association analysis was performed by Arbitrarily Primed-PCR (AP-PCR) and Pulsed-Field Gel Electrophoresis. In our study, VRE was detected in 61 of 2601 rectal swab samples. 54 (85.52%) of the VRE isolates were Enterococcus faecium, 3 (4.91%) was Enterococcus faecalis, 3 (4.91%) was Enterococcus gallinorum, 1 (1.63%) was Enterococcus casseliflavus. It was determined that all of the 54 VREfm isolates, which were the most detected among all VRE isolates, carried the vanA gene. In the clonal association analysis of the isolates by AP-PCR and PFGE methods, it was found that they had 12 different genotypes, 48 of them were included in any cluster, the clustering rate was 88.8%, and the largest cluster was genotype 1 cluster with 36 isolates. Of the 54 patients with VREfm isolated recently, 18.51 percent of the clinical samples were isolated before the survey, and 9.24% were isolated after the survey. It was determined that 100% of VREfm isolates were resistant to ampicillin, levofloxacin, ciprofloxacin, high-level gentamicin, trimethoprim-sulfamethoxazole, teicoplanin, 7.4% to tigecycline and 1.85% to linezolid. In our study, in the clonal association analysis performed by isolating VREfm in rectal swab samples, it was found that 88.8% of the samples were indistinguishably similar and the increase in the number of VREfm infections after the index case in our hospital was associated with the epidemic. VREfm infections cause long term hospitalization, costs and also deaths, which shows the seriousness of the event, and the importance of the combination of epidemiological and molecular analysis in epidemic research.

Listerias of the phylogenetic lineage II (PLII) are common in the European environment, and are hypovirulent. Despite this, they caused more than a third of sporadic cases of listeriosis, and multi-country foodborne outbreaks. L. monocytogenes ST37 is one of them. During the COVID-19 pandemic ST37 appeared in the clinical cases and ranked second in occurrence among food isolates in the Moscow region. The aim of this study was to describe the genomic features of ST37 isolates from different sources. All clinical cases of ST37 were in the cohort of male patients (age, 48-81 years) with meningitis-septicemia manifestation, and COVID-19 or Influenza in the anamnesis. The core genomes of the fish isolates were closely related. The clinical and meat isolates revealed a large diversity. Prophages (2-4/genome) were the source of the unique genes. Two clinical isolates displayed the pseudolysogeny, and excided prophages were A006-like. Absence of the plasmids, the assortment of virulence factors and resistance determinants in chromosome corresponded to the hypovirulent characteristics. However, all clinical isolates caused severe disease with deaths in four cases. Thus, these studies allow us to speculate that a previous viral infection increases a human susceptibility to listeriosis.

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.