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Sharon Street’s influential Darwinian Dilemma argues that moral realism is incompatible with moral knowledge. In this paper I argue that Street’s argument cannot give us reason to reject moral realism. This is because the debunker’s own arguments imply that our evidence for the claim that we have moral knowledge underdetermines its truth. Furthermore, the final part of the Street’s argument, where she infers that moral realism must be false because we have moral knowledge, commits her to the view that underdetermining evidence cannot justify belief. This implies that the debunker is not justified in believing that we have moral knowledge. As a result, Street’s debunking argument does not give us reason to reject realism (or accept anti-realism), even if we grant that they successfully establish the incompatibility of moral realism with our having moral knowledge. [ABSTRACT FROM AUTHOR]

As the business world shifts to the web and tremendous amounts of data become available on multilingual mobile applications, new business and research challenges and opportunities have been explored. This research aims to intensify the usage of data analytics, machine learning, and sentiment analysis of textual data to classify customers' reviews, feedback, and ratings of businesses in Jordan's food and restaurant industry. The main methods used in this research were sentiment polarity (to address the challenges posed by businesses to automatically apply text analysis) and bio-metric techniques (to systematically identify users' emotional states, so reviews can be thoroughly understood). The research was extended to deal with reviews in Arabic, dialectic Arabic, and English, with the main focus on the Arabic language, as the application examined (Talabat) is based in Jordan. Arabic and English reviews were collected from the application, and a new model was proposed to sentimentally analyze reviews. The proposed model has four main stages: data collection, data preparation, model building, and model evaluation. The main purpose of this research is to study the problem expressed above using a model of ordinal regression to overcome issues related to misclassification. Additionally, an automatic multi-language prediction approach for online restaurant reviews was proposed by combining the eXtreme gradient boosting (XGBoost) and particle swarm optimization (PSO) techniques for the ordinal regression of these reviews. The proposed PSO-XGB algorithm showed superior results when compared to support vector machine (SVM) and other optimization methods in terms of root mean square error (RMSE) for the English and Arabic datasets. Specifically, for the Arabic dataset, PSO-XGB achieved an RMSE value of 0.7722, whereas PSO-SVM achieved an RSME value of 0.9988. [ABSTRACT FROM AUTHOR]

Metaheuristics are commonly used in various fields, including real-life problem-solving and engineering applications. The present work introduces a novel metaheuristic algorithm named the Artificial Circulatory System Algorithm (ACSA). The control of the circulatory system inspires it and mimics the behavior of hormonal and neural regulators involved in this process. The work initially evaluates the effectiveness of the suggested approach on 16 two-dimensional test functions, identified as classical benchmark functions. The method was subsequently examined by application to 12 CEC 2022 benchmark problems of different complexities. Furthermore, the paper evaluates ACSA in comparison to 64 metaheuristic methods that are derived from different approaches, including evolutionary, human, physics, and swarm-based. Subsequently, a sequence of statistical tests was undertaken to examine the superiority of the suggested algorithm in comparison to the 7 most widely used algorithms in the existing literature. The results show that the ACSA strategy can quickly reach the global optimum, avoid getting trapped in local optima, and effectively maintain a balance between exploration and exploitation. ACSA outperformed 42 algorithms statistically, according to post-hoc tests. It also outperformed 9 algorithms quantitatively. The study concludes that ACSA offers competitive solutions in comparison to popüler methods. [ABSTRACT FROM AUTHOR]

This work focusses on identifying the optimal stacking sequence for composite tubes in mountain bike frames using a data-driven model combined with evolutionary algorithms. The objective is to find a frame that is sufficiently stiff while meeting the requirements of weight, strength, and minimum tube wall thickness. The decision variables are the ply winding angles and the ply thicknesses of each tube. The study performs designs for two load cases – Starting and Uphill – and explores two types of winding: the gradual winding of individual layers (1ply) and the winding of layers between predefined inner and outer layers with variable thicknesses (TW). Additionally, the design process is applied to frames made of isotropic materials, such as steel, aluminium, and titanium, using the same methodology to allow for comparison of results. The article demonstrates the successful application of this methodology to common sports equipment, suggesting its potential for beneficial use in other common composite frame structures. [ABSTRACT FROM AUTHOR]

IHNV troubled the salmon breeding industry in China for years, and it often causes large-scale deaths. To study the disease characteristics of IHNV and its epidemiology in China, this study isolated and sequenced the Whole genome of an IHNV strain (IHNV-SCCD) (GenBank No: OQ801357) from farmed diseased rainbow trout in Chengdu and compared 99 IHNV strains from China by mega.11. The IHNV-SCCD strain was isolated by using EPC cells. The complete genome sequence was determined and deposited in the NCBI database. Phylogenetic analysis showed that IHNV-SCCD belongs to the typical J gene group, recently with Sichuan strains. Except for BjLL strain and LN12-17 strain, the remaining 98 strains followed a single evolutionary path. Note that IHNV in Liaoning province is the fastest evolutionary. In addition to the geographical differences, the Xinjiang strains were closely related to the Yunnan strains, and some strains from Beijing were closely related to some strains from Sichuan. There were two evolutionary branches in Gansu and Qinghai; QH17, isolated from Qinghai, was most closely related to SX1704 from Shaanxi. These results suggest that the prevalence of IHNV in China was extremely wide, and the evolution rate was fast. It is necessary to strengthen the monitoring and prevention methods. [ABSTRACT FROM AUTHOR]

Abstract The DHHC domain genes are crucial for protein lipid modification, a key post-translational modification influencing membrane targeting, subcellular trafficking, and protein function. Despite their significance, the DHHC gene family in Saccharinae remains understudied. Here, we identified 32 (110 alleles), 28, 53, and 48 DHHC genes in Saccharum spontaneum Np-X, Erianthus rufipilus, Miscanthus sinensis, and Miscanthus lutarioriparius, respectively. Collinearity analysis uncovered the loss of two M. lutarioriparius genes, homologues of EruDHHC1C and EruDHHC3A. Phylogenetic and classification analyses categorized DHHC family members into six subgroups (A-F). Ka/Ks ratio analysis indicated that gene duplication in these species was primarily driven by whole-genome duplication (WGD) and dispersed duplication (DSD), with DHHC genes evolving under strong purifying selection. Gene expression and trait correlation analysis revealed a significant negative correlation between SspDHHC28A expression in S. spontaneum and sucrose content, suggesting a role in photosynthesis product transport during rapid growth. This study deepens our understanding of the DHHC gene family’s functional dynamics and evolutionary path in Saccharinae, laying a foundation for future research.

The deployment of distributed multi-controllers for Software-Defined Networking (SDN) architecture is an emerging solution to improve network scalability and management. However, the network control failure affects the dynamic resource allocation in distributed networks resulting in network disruption and low resilience. Thus, we consider the control plane fault tolerance for cost-effective and accurate controller location models during control plane failures. This fault-tolerance strategy has been applied to distributed SDN control architecture, which allows each switch to migrate to next controller to enhance network performance. In this paper, the Reliable and Dynamic Mapping-based Controller Placement (RDMCP) problem in distributed architecture is framed as an optimization problem to improve the system reliability, quality, and availability. By considering the bound constraints, a heuristic state-of-the-art Controller Placement Problem (CPP) algorithm is used to address the optimal assignment and reassignment of switches to nearby controllers other than their regular controllers. The algorithm identifies the optimal controller location, minimum number of controllers, and the expected assignment costs after failure at the lowest effective cost. A metaheuristic Particle Swarm Optimization (PSO) algorithm was combined with RDMCP to form a hybrid approach that improves objective function optimization in terms of reliability and cost-effectiveness. The effectiveness of our hybrid RDMCP-PSO was then evaluated using extensive experiments and compared with other baseline algorithms. The findings demonstrate that the proposed hybrid technique significantly increases the network performance regarding the controller number and load balancing of the standalone heuristic CPP algorithm.

Jaboticaba is a typical tropical plant that blossoms and bears fruit on the tree trunks and branches. The fruits resemble grapes in appearance and texture and are also known as "treegrapes". Currently, research on the genomics of jaboticaba is lacking. In this study, we constructed an integrated, telomere-to-telomere (T2T) gap-free reference genome and two nearly complete haploid genomes, thereby providing a high-quality genomic resource. Furthermore, we unveiled the evolutionary history of several species within the Myrtaceae family, highlighting significant expansions in metabolic pathways such as the citric acid cycle, glycolysis/gluconeogenesis, and phenylpropanoid biosynthesis throughout their evolutionary process. Transcriptome analysis of jaboticaba fruits of different colors revealed that the development of fruit skin color in jaboticaba is associated with the phenylpropanoid and flavonoid biosynthesis pathways, with the flavanone 3-hydroxylase (F3H) gene potentially regulating fruit skin color. Additionally, by constructing the regulatory pathway of the citric acid cycle, we found that low citric acid content is correlated with high expression levels of genes such as thiamin diphosphate (ThDP) and low expression of phosphoenolpyruvate carboxykinase (PEPCK), indicating that PEPCK positively regulates citric acid content. These T2T genomic resources will accelerate jaboticaba pepper genetic improvement and help to understand jaboticaba genome evolution. [ABSTRACT FROM AUTHOR]

Copyright of Tasarim+Kuram is the property of KARE Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Plant senescence is an integrated programme of plant development that aims to remobilize nutrients and energy from senescing tissues to developing organs under developmental and stress-induced conditions. Upstream in the regulatory network, a small family of single-stranded DNA/RNA-binding proteins known as WHIRLYs occupy a central node, acting at multiple regulatory levels and via trans-localization between the nucleus and organelles. In this review, we summarize the current progress on the role of WHIRLY members in plant development and stress-induced senescence. WHIRLY proteins can be traced back in evolution to green algae. WHIRLY proteins trade off the balance of plant developmental senescence and stress-induced senescence through maintaining organelle genome stability via R-loop homeostasis, repressing the transcription at a configuration condition, and recruiting RNA to impact organelle RNA editing and splicing, as evidenced in several species. WHIRLY proteins also act as retrograde signal transducers between organelles and the nucleus through protein modification and stromule or vesicle trafficking. In addition, WHIRLY proteins interact with hormones, reactive oxygen species and environmental signals to orchestrate cell fate in an age-dependent manner. Finally, prospects for further research and promotion to improve crop production under environmental constraints are highlighted. [ABSTRACT FROM AUTHOR]

We investigate the links between accumulation and socio-metabolic regimes by studying French capitalism from socio-economic and material perspectives since 1948. We characterize its social metabolism both in domestic and footprint approaches. The periodization of accumulation regimes in terms of Fordism and finance-led capitalism translates into material terms. The offshore materiality of finance-led capitalism partly substitutes for and partly complements the more domestic materiality inherited from Fordism. The transition phase between the two socio-metabolic regimes clearly corresponds to the emergence of the offshoring–financialization nexus of French capitalism, indicating the shift from Fordism to finance-led capitalism. We highlight strong inter-linkages between accumulation and material dynamics and discuss how materials may be instrumental in shaping accumulation regimes. We therefore introduce the concept of accumulation–metabolism nexus. This work illustrates the relevance of combining institutionalist macroeconomics with Material Flow Analysis. [ABSTRACT FROM AUTHOR]

This paper introduces an evolutionary algorithm for objective functions defined over clouds of points of varying sizes. Such design variables are modeled as uniform discrete measures with finite support and the crossover and mutation operators of the algorithm are defined using the Wasserstein barycenter. We prove that the Wasserstein-based crossover has a contracting property in the sense that the support of the generated measure is included in the closed convex hull of the union of the two parents' supports. We introduce boundary mutations to counteract this contraction. Variants of evolutionary operators based on Wasserstein barycenters are studied. We compare the resulting algorithm to a more classical, sequence-based, evolutionary algorithm on a family of test functions that include a wind-farm layout problem. The results show that Wasserstein-based evolutionary operators better capture the underlying geometrical structures of the considered test functions and outperform a reference evolutionary algorithm in the vast majority of the cases. The tests indicate that the mutation operators play a major part in the performances of the algorithms. [ABSTRACT FROM AUTHOR]

IntroductionWall-associated kinases (WAKs) are pivotal in linking plant cell walls to intracellular signaling networks, thereby playing essential roles in plant growth, development, and stress responses. MethodsThe bioinformatics analysis was employed to identify WAK genes in tobacco. The expression levels of NtWAK genes were assessed by qRT-PCR. The subcellular localization of WAK proteins was observed in tobacco cells and Arabidopsis protoplasts. Kinase activity of the WAK proteins was evaluated through in vitro assays. ResultsWe conducted a comprehensive genome-wide identification and analysis of the WAK gene family in tobacco (Nicotiana tabacum). A total of 44 WAK genes were identified in the tobacco genome, which were further classified into three distinct groups. Phylogenetic analysis comparing tobacco WAKs (NtWAKs) with Arabidopsis WAKs (AtWAKs) revealed species-specific expansion of these genes. The WAK proteins within each group displayed similar gene structures and conserved motif distributions. Promoter region analysis indicated that cis-elements of NtWAK genes are primarily involved in regulating plant growth and development, phytohormone signaling, and stress responses. Expression profiling under NaCl, PEG, and ABA treatments suggested that certain NtWAK genes may play key roles in modulating responses to abiotic stress. Three-dimensional structural predictions and subcellular localization analysis showed that NtWAK proteins from the three subgroups exhibit high cytoplasmic similarity and are primarily located to the plasma membrane. Kinase activity assay confirmed that they possess phosphorylation activity. DiscussionThis study represents the first genome-wide analysis of the WAK gene family in N. tabacum, laying the groundwork for future functional investigations.

As the business world shifts to the web and tremendous amounts of data become available on multilingual mobile applications, new business and research challenges and opportunities have been explored. This research aims to intensify the usage of data analytics, machine learning, and sentiment analysis of textual data to classify customers’ reviews, feedback, and ratings of businesses in Jordan’s food and restaurant industry. The main methods used in this research were sentiment polarity (to address the challenges posed by businesses to automatically apply text analysis) and bio-metric techniques (to systematically identify users’ emotional states, so reviews can be thoroughly understood). The research was extended to deal with reviews in Arabic, dialectic Arabic, and English, with the main focus on the Arabic language, as the application examined (Talabat) is based in Jordan. Arabic and English reviews were collected from the application, and a new model was proposed to sentimentally analyze reviews. The proposed model has four main stages: data collection, data preparation, model building, and model evaluation. The main purpose of this research is to study the problem expressed above using a model of ordinal regression to overcome issues related to misclassification. Additionally, an automatic multi-language prediction approach for online restaurant reviews was proposed by combining the eXtreme gradient boosting (XGBoost) and particle swarm optimization (PSO) techniques for the ordinal regression of these reviews. The proposed PSO-XGB algorithm showed superior results when compared to support vector machine (SVM) and other optimization methods in terms of root mean square error (RMSE) for the English and Arabic datasets. Specifically, for the Arabic dataset, PSO-XGB achieved an RMSE value of 0.7722, whereas PSO-SVM achieved an RSME value of 0.9988.

El programa docente de Proyectos Arquitectónicos en la Escuela de Arquitectura de la Universidad Europea de Canarias está integrado desde 2º hasta 6º curso, y se estructura mediante una metodología progresiva que aborda la enseñanza del diseño arquitectónico desde una perspectiva integral. A lo largo de los cursos, los estudiantes exploran diversas escalas y tipologías arquitectónicas, comenzando con proyectos de pequeña escala en el segundo año, como refugios de montaña y viviendas unifamiliares, hasta intervenciones urbanas complejas y edificios institucionales en el sexto año. Esta evolución permite a los estudiantes adquirir un dominio exhaustivo de la disciplina, adaptándose a los diferentes contextos urbanos y programas arquitectónicos. El enfoque pedagógico se basa en cuatro condiciones fundamentales: la escala, la complejidad programática, la intensidad urbana y la tecnología. Los estudiantes desarrollan proyectos que integran estos aspectos, abordando la relación entre diseño arquitectónico y normativa urbanística. Se promueve el uso de herramientas digitales avanzadas y técnicas sostenibles, lo que fortalece sus competencias para enfrentar los desafíos profesionales. El resultado es una preparación sólida que asegura que los estudiantes comprendan profundamente la interacción entre arquitectura, entorno y sociedad. La metodología, aplicada con éxito en los cursos 2021-22 y 2022-23, ha mejorado notablemente la percepción estudiantil de su seguridad personal y la evaluación de proyectos finales. Esto demuestra que los egresados están capacitados para desempeñarse con eficacia en el ámbito profesional, gestionando proyectos de diversas escalas y complejidades con seguridad pre-profesional. Abstract Architectural Design teaching program at the School of Architecture of the European University of the Canary Islands is integrated from the 2nd to the 6th year and is structured through a progressive methodology that approaches the teaching of architectural design from a comprehensive perspective. Throughout the courses, students explore various architectural scales and typologies, starting with small-scale projects in the second year, such as mountain refuges and single-family homes, up to complex urban interventions and institutional buildings in the sixth year. This progression allows students to gain an in-depth understanding of the discipline, adapting to different urban contexts and architectural programs. Our pedagogical approach is based on four fundamental conditions: scale, programmatic complexity, urban intensity, and technology. Students develop projects that integrate these aspects, addressing the relationship between architectural design and urban planning regulations. The use of advanced digital tools and sustainable techniques is promoted, which strengthens their competencies to face professional challenges. The result is a solid preparation that ensures students deeply understand the interaction between architecture, environment, and society. The methodology, successfully applied during the 2021-22 and 2022-23 academic years, has significantly improved students' perception of their personal confidence and the evaluation of final projects. This demonstrates that graduates are well-equipped to perform effectively in the professional field, managing projects of various scales and complexities with pre-professional confidence.

The monochromatic hyperbolic neutron density wave is conceived as a Rayleigh-like wave with mixed transverse and longitudinal components. It is proved for the first time that the absolute ratio of the longitudinal to transverse interfering components, varies, with increasing the frequency of this wave, from zero to 1. Such a limited variation is to be coined as vibrational enhancement of evolutionary one-speed neutron transport.

This paper builds on prior work by the author on cost share-induced technological change. The theoretical model views selection of candidate innovations as a capital budgeting exercise. In this paper it treats the case in which firms target an incremental rate of profit, which introduces a nonzero threshold into a "selection frontier". This presents analytical challenges, which are resolved in this paper by assuming that the probability distribution of potential increases in productivity among the set of fit innovations is normal. That permits an explicit derivation of a micro-level model of cost share-induced technological change that can be taken as a candidate functional form for an aggregate model. The model is calibrated against historical data for India, China, and the United States, three large continental economies at different levels of per capita GDP. The model is able to fit the data with reasonable fidelity, and the fitted model parameters can be given a reasonable interpretation. The paper further shows that combining cost share-induced technological change with price-setting behavior produces theoretically interesting results. [ABSTRACT FROM AUTHOR]

The recent concurrent emergence of H5N1, H5N6, and H5N8 avian influenza viruses (AIVs) has led to significant avian mortality globally. Since 2020, frequent human-animal interactions have been documented. To gain insight into the novel H5 subtype AIVs (i.e., H5N1, H5N6 and H5N8), we collected 6102 samples from various regions of China between January 2021 and September 2022, and identified 41 H5Nx strains. Comparative analyses on the evolution and biological properties of these isolates were conducted. Phylogenetic analysis revealed that the 41 H5Nx strains belonged to clade 2.3.4.4b, with 13 related to H5N1, 19 to H5N6, and 9 to H5N8. Analysis based on global 2.3.4.4b viruses showed that all the viruses described in this study were likely originated from H5N8, exhibiting a heterogeneous evolutionary history between H5N1 and H5N6 during 2015-2022 worldwide. H5N1 showed a higher rate of evolution in 2021-2022 and more sites under positive selection pressure in 2015-2022. The antigenic profiles of the novel H5N1 and H5N6 exhibited notable variations. Further hemagglutination inhibition assay suggested that some A(H5N1) viruses may be antigenically distinct from the circulating H5N6 and H5N8 strains. Mammalian challenge assays demonstrated that the H5N8 virus (21GD001_H5N8) displayed the highest pathogenicity in mice, followed by the H5N1 virus (B1557_H5N1) and then the H5N6 virus (220086_H5N6), suggesting a heterogeneous virulence profile of H5 AIVs in the mammalian hosts. Based on the above results, we speculate that A(H5N1) viruses have a higher risk of emergence in the future. Collectively, these findings unveil a new landscape of different evolutionary history and biological characteristics of novel H5 AIVs in clade 2.3.4.4b, contributing to a better understanding of designing more effective strategies for the prevention and control of novel H5 AIVs. [ABSTRACT FROM AUTHOR]

Abstract Background KNOTTED1-like homeobox (KNOX) genes, plant-specific homologous box transcription factors (TFs), play a central role in regulating plant growth, development, organ formation, and response to biotic and abiotic stresses. However, a comprehensive genome-wide identification of the KNOX genes in Moso bamboo (Phyllostachys edulis), the fastest growing plant, has not yet been conducted, and the specific biological functions of this family remain unknown. Results The expression profiles of 24 KNOX genes, divided into two subfamilies, were determined by integrating Moso bamboo genome and its transcriptional data. The KNOX gene promoters were found to contain several light and stress-related cis-acting elements. Synteny analysis revealed stronger similarity with rice KNOX genes than with Arabidopsis KNOX genes. Additionally, several conserved structural domains and motifs were identified in the KNOX proteins. The expansion of the KNOX gene family was primarily regulated by tandem duplications. Furthermore, the KNOX genes were responsive to naphthaleneacetic acid (NAA) and gibberellin (GA) hormones, exhibiting distinct temporal expression patterns in four different organs of Moso bamboo. Short Time-series Expression Miner (STEM) analysis and quantitative real-time PCR (qRT-PCR) assays demonstrated that PeKNOX genes may play a role in promoting rapid shoot growth. Additionally, Gene Ontology (GO) and Protein–Protein Interaction (PPI) network enrichment analyses revealed several functional annotations for PeKNOXs. By regulating downstream target genes, PeKNOXs are involved in the synthesis of AUX /IAA, ultimately affecting cell division and elongation. Conclusions In the present study, we identified and characterized a total of 24 KNOX genes in Moso bamboo and investigated their physiological properties and conserved structural domains. To understand their functional roles, we conducted an analysis of gene expression profiles using STEM and RNA-seq data. This analysis successfully revealed regulatory networks of the KNOX genes, involving both upstream and downstream genes. Furthermore, the KNOX genes are involved in the AUX/IAA metabolic pathway, which accelerates shoot growth by influencing downstream target genes. These results provide a theoretical foundation for studying the molecular mechanisms underlying the rapid growth and establish the groundwork for future research into the functions and transcriptional regulatory networks of the KNOX gene family.

Copyright of ABE: Advances in Building Education is the property of Departamento de Tecnologia de la Edificacion, Universidad Politecnica de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Equisetum is one of the oldest extant group vascular plants and is considered to be the key to understanding vascular plant evolution. Equisetum is distributed almost all over the world and has a high degree of adaptability to different environments. Despite the fossil record of horsetails (Equisetum, Equisetaceae) dating back to the Carboniferous, the phylogenetic relationship of this genus is not well, and the chloroplast evolution in Equisetum remains poorly understood. In order to fill this gap, we sequenced, assembled, and annotated the chloroplast genomes of 12 species of Equisetum, and compared them to 13 previously published vascular plants chloroplast genomes to deeply examine the plastome evolutionary dynamics of Equisetum. The chloroplast genomes have a highly conserved quadripartite structure across the genus, but these chloroplast genomes have a lower GC content than other ferns. The size of Equisetum plastomes ranges from 130,773 bp to 133,684 bp and they encode 130 genes. Contraction/expansion of IR regions and the number of simple sequences repeat regions underlie large genomic variations in size among them. Comparative analysis revealed we also identified 13 divergence hotspot regions. Additionally, the genes accD and ycf1 can be used as potential DNA barcodes for the identification and phylogeny of the genus Equisetum. Twelve photosynthesisrelated genes were specifically selected in Equisetum. Comparative genomic analyses implied divergent evolutionary patterns between Equisetum and other ferns. Phylogenomic analyses and molecular dating revealed a relatively distant phylogenetic relationship between Equisetum and other ferns, supporting the division of pteridophyte into Lycophytes, Equisetaceae and ferns. The results show that the chloroplast genome can be used to solve phylogenetic problems within or between Equisetum species, and also provide genomic resources for the study of Equisetum systematics and evolution. [ABSTRACT FROM AUTHOR]

Within western social psychology and neuroscience, compassion is described as being conditioned by costbenefit appraisals, such as the attribution of responsibility for the causes of suffering. Buddhist traditions maintain the possibility of cultivating and embodying unconditioned and universal forms of compassion. Whereas a growing body of empirical literature suggests that Buddhist-inspired compassion-based programs foster prosociality and well-being in healthy and clinical populations, there is no evidence that such compassionate disposition toward others can become unconditioned from moral judgment. To address this question, we collected and integrated self-report and behavioral data from expert Buddhist practitioners and trained novices using a previously validated within-subject experiment that manipulates contextual information to influence moral judgment toward suffering others and a newly designed approach-avoidance task. We found that context manipulation impacted responsibility and blame attribution in both groups and that experts' reported willingness to help was higher and less influenced by context, compared to novices. Partial correlation networks highlighted a negative relationship between blame attribution and willingness to help in novices, but not in expert practitioners. Self-reported willingness to help was correlated to reaction times when approaching suffering stimuli. Approach behavior was modulated by context in novice, but not in experts. This study provides initial evidence of a dissociation between moral attributions and prosocial attitude in expert Buddhist practitioners and challenges established evolutionary accounts of compassion in western psychology. [ABSTRACT FROM AUTHOR]

Genetic Algorithm is an optimization technique inspired by nature. The technique has been used by scientists and engineers for real-life search and optimization problems. This work makes use of the genetic algorithm for the solution of the traveling salesman problem. This work focuses on real-time problems; the algorithm is used to find the optimum path for sales travelers inside the Khyber Pakhtunkhwa Province of Pakistan. The solution provides the shortest distance between the cities to be traveled and gives the optimal route. The coding is done in Python-3 and software is developed for the traveling salesmen, where the salesmen can select the cities, they want to travel, and the software will provide the optimal path and the distance. [ABSTRACT FROM AUTHOR]

Background: KNOTTED1-like homeobox (KNOX) genes, plant-specific homologous box transcription factors (TFs), play a central role in regulating plant growth, development, organ formation, and response to biotic and abiotic stresses. However, a comprehensive genome-wide identification of the KNOX genes in Moso bamboo (Phyllostachys edulis), the fastest growing plant, has not yet been conducted, and the specific biological functions of this family remain unknown. Results: The expression profiles of 24 KNOX genes, divided into two subfamilies, were determined by integrating Moso bamboo genome and its transcriptional data. The KNOX gene promoters were found to contain several light and stress-related cis-acting elements. Synteny analysis revealed stronger similarity with rice KNOX genes than with Arabidopsis KNOX genes. Additionally, several conserved structural domains and motifs were identified in the KNOX proteins. The expansion of the KNOX gene family was primarily regulated by tandem duplications. Furthermore, the KNOX genes were responsive to naphthaleneacetic acid (NAA) and gibberellin (GA) hormones, exhibiting distinct temporal expression patterns in four different organs of Moso bamboo. Short Time-series Expression Miner (STEM) analysis and quantitative real-time PCR (qRT-PCR) assays demonstrated that PeKNOX genes may play a role in promoting rapid shoot growth. Additionally, Gene Ontology (GO) and Protein–Protein Interaction (PPI) network enrichment analyses revealed several functional annotations for PeKNOXs. By regulating downstream target genes, PeKNOXs are involved in the synthesis of AUX /IAA, ultimately affecting cell division and elongation. Conclusions: In the present study, we identified and characterized a total of 24 KNOX genes in Moso bamboo and investigated their physiological properties and conserved structural domains. To understand their functional roles, we conducted an analysis of gene expression profiles using STEM and RNA-seq data. This analysis successfully revealed regulatory networks of the KNOX genes, involving both upstream and downstream genes. Furthermore, the KNOX genes are involved in the AUX/IAA metabolic pathway, which accelerates shoot growth by influencing downstream target genes. These results provide a theoretical foundation for studying the molecular mechanisms underlying the rapid growth and establish the groundwork for future research into the functions and transcriptional regulatory networks of the KNOX gene family. [ABSTRACT FROM AUTHOR]

Abnormal behaviors degrade overall system efficiency and may lead to system suspension. Extensive academic research has focused on anomaly detection across various sectors, including industrial, information security, and artificial intelligence. In this study, we propose a NeuroEvolution AutoEncoder (NEAE) for classifying and predicting abnormalities in internet-based applications. The NEAE is genetically programmed to process dataset features that encompass abnormal behaviors in internet activities. Our approach targets multivariate anomalies using parallel dimension processing, aiming for synchronized intelligence. Genetic programming is central to our technique, enhancing optimization. We evaluate our proposed technique using a substantial internet-based dataset, specifically network traffic. Simulation results demonstrate the effectiveness of the NEAE in detecting abnormalities based on performance metrics. Given its relevance and integration with diverse industries such as the Internet of Things, wireless communication, network traffic, and the web, we choose an Internet-based application dataset to validate the NEAE's performance. [ABSTRACT FROM AUTHOR]

H4 avian influenza viruses (AIVs) have been widely detected in live poultry markets in China. However, the potential public health impact of H4 AIVs remains largely uncertain. Here, we fully analyzed the distribution and phylogenetic relationship of H4 AIVs in China. We obtained 31 isolates of H4 viruses in China during 2009–2022 through surveillance in poultry-associated environments, such as live poultry markets and poultry farms. Genomic sequence analysis together with publicly available data revealed that frequent reassortment and introduction of H4 AIV from wild birds to poultry may have occurred. We identified 62 genotypes among 127 whole genome sequences of H4 viruses in China, indicating that H4 AIVs had great genetic diversity in China. We also investigated molecular markers and found that drug resistance mutations frequently occurred in the M2 protein and a few mutations related to receptor binding and the host signature in H4 AIVs. Our study demonstrates the cross-species transmission potential of H4 AIVs in China and provides some reference significance for its risk assessment. [ABSTRACT FROM AUTHOR]

Fuzzing is a technique that was used to detect potential vulnerabilities and errors in software or systems by generating random, abnormal, or invalid test cases.When applying fuzzing to the kernel, more complex and challenging obstacles were encountered compared to user-space applications.The kernel, being a highly intricate software system, consists of numerous interconnected modules, subsystems, and device drivers, which presented challenges such as a massive codebase, complex interfaces, and runtime uncertainty.Traditional fuzzing methods could only generate inputs that simply satisfied interface specifications and explicit call dependencies, making it difficult to thoroughly explore the kernel.In contrast, evolutionary kernel fuzzing employed heuristic evolutionary strategies to dynamically adjust the generation and selection of test cases, guided by feedback mechanisms.This iterative process aimed to generate higher-quality test cases.Existing work on evolutionary kernel fuzzing was examined.The concept of evolutionary kernel fuzzing was explained, and its general framework was summarized.The existing work on evolutionary kernel fuzzing was classified and compared based on the type of feedback mechanism utilized.The principles of how feedback mechanisms guided evolution were analyzed from the perspectives of collecting, analyzing, and utilizing runtime information.Additionally, the development direction of evolutionary kernel fuzzing was discussed.

This paper introduces an evolutionary algorithm for objective functions defined over clouds of points of varying sizes. Such design variables are modeled as uniform discrete measures with finite support and the crossover and mutation operators of the algorithm are defined using the Wasserstein barycenter. We prove that the Wasserstein-based crossover has a contracting property in the sense that the support of the generated measure is included in the closed convex hull of the union of the two parents’ supports. We introduce boundary mutations to counteract this contraction. Variants of evolutionary operators based on Wasserstein barycenters are studied. We compare the resulting algorithm to a more classical, sequence-based, evolutionary algorithm on a family of test functions that include a wind-farm layout problem. The results show that Wasserstein-based evolutionary operators better capture the underlying geometrical structures of the considered test functions and outperform a reference evolutionary algorithm in the vast majority of the cases. The tests indicate that the mutation operators play a major part in the performances of the algorithms.

Abstract Background The Begonia species are common shade plants that are mostly found in southwest China. They have not been well studied despite their medicinal and decorative uses because gene penetration, decreased adaptability, and restricted availability are all caused by frequent interspecific hybridization. Result To understand the patterns of mutation in the chloroplast genomes of different species of Begonia, as well as their evolutionary relationships, we collected seven Begonia species in China and sequenced their chloroplast genomes. Begonia species exhibit a quadripartite structure of chloroplast genomes (157,634 − 169,694 bp), consisting of two pairs of inverted repeats (IR: 26,529 − 37,674 bp), a large single copy (LSC: 75,477 − 86,500 bp), and a small single copy (SSC: 17,861 − 18,367 bp). 128–143 genes (comprising 82–93 protein-coding genes, 8 ribosomal RNAs, and 36–43 transfer RNAs) are found in the chloroplast genomes. Based on comparative analyses, this taxon has a relatively similar genome structure. A total of six substantially divergent DNA regions (trnT-UGU-trnL-UAA, atpF-atpH, ycf4-cemA, psbC-trnS-UGA, rpl32-trnL-UAG, and ccsA-ndhD) are found in the seventeen chloroplast genomes. These regions are suitable for species identification and phylogeographic analysis. Phylogenetic analysis shows that Begonia species that were suited to comparable environments grouped in a small clade and that all Begonia species formed one big clade in the phylogenetic tree, supporting the genus’ monophyly. In addition, positive selection sites were discovered in eight genes (rpoC1, rpoB, psbE, psbK, petA, rps12, rpl2, and rpl22), the majority of which are involved in protein production and photosynthesis. Conclusion Using these genome resources, we can resolve deep-level phylogenetic relationships between Begonia species and their families, leading to a better understanding of evolutionary processes. In addition to enhancing species identification and phylogenetic resolution, these results demonstrate the utility of complete chloroplast genomes in phylogenetically and taxonomically challenging plant groupings.

The Oropouche virus is an important arthropod-borne virus in the Peribunyaviridae family that can cause febrile illnesses, and it is widely distributed in tropical regions such as Central and South America. Since the virus was first identified, a large number of related cases are reported every year. No deaths have been reported to date, however, the virus can cause systemic infections, including the nervous and blood systems, leading to serious complications. The transmission of Oropouche virus occurs through both urban and sylvatic cycles, with the anthropophilic biting midge Culicoides paraensis serving as the primary vector in urban areas. Direct human-to-human transmission of Oropouche virus has not been observed. Oropouche virus consists of three segments, and the proteins encoded by the different segments enables the virus to replicate efficiently in the host and to resist the host's immune response. Phylogenetic analyses showed that Oropouche virus sequences are geographically distinct and have closer homologies with Iquitos virus and Perdoes virus, which belong to the family Peribunyaviridae. Despite the enormous threat it poses to public health, there are currently no licensed vaccines or specific antiviral treatments for the disease it causes. Recent studies have utilised imJatobal virusmunoinformatics approaches to develop epitope-based peptide vaccines, which have laid the groundwork for the clinical use of vaccines. The present review focuses on the structure, epidemiology, immunity and phylogeny of Oropouche virus, as well as the progress of vaccine development, thereby attracting wider attention and research, particularly with regard to potential vaccine programs.

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A 57-year-old female cadaver donated for research contained an accidental bilateral presence of the psoas minor (PMn) muscle. Bilateral PMn is a rare finding but it may be associated with other anatomical variations or abnormalities in the abdomen or pelvis. In some cases, the muscle may be involved in the development of certain medical conditions or may compress nearby structures, leading to symptoms such as pain or discomfort. Overall, bilateral PMn is a relatively uncommon anatomical variation that may be of interest to anatomists or medical professionals. A thorough understanding of this muscle is essential, particularly when making a clinical diagnosis and carrying out procedures in the iliac area. In this case report, we tried to discuss the clinical, embryological, and evolutionary significance of PMn muscle. [ABSTRACT FROM AUTHOR]

A methodology of optimising composite frame structures has been applied to three selected geometries. A cyclic process driven by predefined objectives achieved the most desirable parameters through adjustments in winding angles and tube ply thicknesses. A geometry resembling a crane structure underwent initial analyses, allowing for the determination of appropriate settings for the surrogate model's training phase, considering accuracy and computational time. Its final design was influenced by prevalent bending and tension loads, resulting in near-zero winding angles and a range of thicknesses that met displacement, strength, and weight requirements. A second geometry with further restrictions was also considered. Finally, for a third geometry, winding angles were tailored to accommodate torsion forces. The presented optimisation process resulted in volume reduction while maintaining displacement and strength parameters. These findings highlight the effectiveness and transferability of the optimisation approach across different geometries. [ABSTRACT FROM AUTHOR]

Phylogenetic comparative methods use random processes, such as the Brownian Motion, to model the evolution of continuous traits on phylogenetic trees. Growing evidence for non-gradual evolution motivated the development of complex models, often based on Lévy processes. However, their statistical inference is computationally intensive and currently relies on approximations, high-dimensional sampling, or numerical integration. We consider here the Cauchy Process (CP), a particular pure-jump Lévy process in which the trait increment along each branch follows a centered Cauchy distribution with a dispersion proportional to its length. In this work, we derive an exact algorithm to compute both the joint probability density of the tip trait values of a phylogeny under a CP and the ancestral trait values and branch increments posterior densities in quadratic time. A simulation study shows that the CP generates patterns in comparative data that are distinct from any Gaussian process, and that restricted maximum likelihood parameter estimates and root trait reconstruction are unbiased and accurate for trees with 200 tips or less. The CP has only two parameters but is rich enough to capture complex-pulsed evolution. It can reconstruct posterior ancestral trait distributions that are multimodal, reflecting the uncertainty associated with the inference of the evolutionary history of a trait from extant taxa only. Applied on empirical datasets taken from the Evolutionary Ecology and Virology literature, the CP suggests nuanced scenarios for the body size evolution of Greater Antilles Lizards and for the geographical spread of the West Nile Virus epidemics in North America, both consistent with previous studies using more complex models. The method is efficiently implemented in C with an R interface in package cauphy, which is open source and freely available online. [ABSTRACT FROM AUTHOR]

Remaining useful life (RUL) predictions are a key enabler for predictive maintenance. Data-driven approaches, typically based on deep neural networks (DNNs), have shown success in RUL prediction. However, DNNs are usually handcrafted via a labor-intensive design process. To overcome this issue, we propose a neural architecture search (NAS) technique based on a surrogate-assisted genetic algorithm that automatically discovers the optimal architectures of Transformers. To our knowledge, this is the first work to optimize the architecture of Transformers for RUL predictions using evolutionary computation. We evaluate the performance of the proposed method (in terms of RMSE and s -score) on the well-known CMAPSS benchmark dataset. Compared with the state-of-the-art, the Transformers obtained by our NAS method outperform other recent handcrafted DNNs in terms of RMSE and are comparable regarding the s -score. Our results demonstrate that the proposed method provides better prediction accuracy with less human effort compared to other data-driven approaches. [ABSTRACT FROM AUTHOR]

This paper focuses on the use of truss topology optimization using an evolutionary approach to find optimized, additively manufactured components through a multi-objective formulation, keeping in mind application areas like 3D printing. Additive manufacturing plays a key role here, as the inherent complexity of most optimized truss structures would not allow for any different manufacturing techniques. The multi-optimization formulation consists of optimizing two conflicting objectives: minimization of structural compliance and minimization of heat flowing from the structure to its supports. A background on truss topology optimization, including a literature overview and the motivation behind the problem, is presented. The physical models and the optimization algorithms are explained and afterward, an example problem is solved and analyzed. [ABSTRACT FROM AUTHOR]

Manufacturing long-chain branched polymers enhances the quality of products at the cost of production time, translating into high manufacturing costs. In this manuscript, we study the cost-versus-quality trade-off while optimizing the operating conditions for large-scale industrial production of Polyvinyl acetate (PVAc). PVAc polymerization is emulated using a large system of stiff differential equations resulting in time-expensive function evaluation. Thus, we aim to achieve the Pareto optimality using Multi-Objective Bayesian Optimization (MOBO) that introduces q-Expected Hyper-Volume Improvement (qEHVI) as the novel acquisition function. Comparison with Non-dominated Sorting Genetic Algorithm-II (NSGA-II), applied to the high-fidelity model, resulted in a similar Pareto front with only 1% of the high-fidelity calls required by NSGA-II. The results indicate the efficiency of MOBO for PVAc optimization and present a real-world application of a generic method that can be implemented to solve time-expensive multi-objective optimization in manufacturing processes [ABSTRACT FROM AUTHOR]

This paper presents a circular recycling system for end-of-life tires (ELTs) under extended producer responsibility (EPR) by integrating Individual Producer Responsibility (IPR) and Industrial Symbiosis (IS). The system aims for sustainability and circularity in the tire industry, avoiding the detrimental effects of landfilling. It focuses on emission-free recyclers to create IS for ensuring environmental sustainability. Additionally, the system uses a "dynamic pricing strategy" to take-back ELTs from consumers. This paper also presents a "multi-period scenario-based nonlinear mixed integer programming" model to investigate the economic sustainability of the proposed system under uncertainty. Three different evolutionary metaheuristic algorithms, "genetic algorithm (GA)-based simulated annealing", "GA" and a new variant of "particle swarm optimization" are used to obtain the solution of the model. Through a case study, it is found that the proposed system is economically sustainable and has the potential to aid in the successful implementation of EPR in the tire industry. [ABSTRACT FROM AUTHOR]

Evolutionary single- and bi-objective optimization of industrial problems, namely, naphtha cracking and styrene reactor are considered. Bi-objective optimization is solved using the HMODE-DLS algorithm, whereas an improved black hole optimizer (BHO) is employed for the single-objective optimization (SOO) problem. For the naphtha cracking process, ethylene selectivity (SE) and severity index (SI) are selected as objectives. Similarly, styrene selectivity (SST) and styrene flow rates (FST) are considered objectives for styrene reactor. Pareto ranking is carried out by using the net flow method (NFM) and the best solution is compared with the single- and multi-objective optimization results. In a single objective optimization study, the optimum solution corresponds to the lowest value of the SI (1.571) at the cost of the worst value of SE (0.269). Similarly, the highest values of FST (16.642 kmol/h) and SST (96.158%) are resulted in the SOO study of styrene reactor. [ABSTRACT FROM AUTHOR]

Background: The Begonia species are common shade plants that are mostly found in southwest China. They have not been well studied despite their medicinal and decorative uses because gene penetration, decreased adaptability, and restricted availability are all caused by frequent interspecific hybridization. Result: To understand the patterns of mutation in the chloroplast genomes of different species of Begonia, as well as their evolutionary relationships, we collected seven Begonia species in China and sequenced their chloroplast genomes. Begonia species exhibit a quadripartite structure of chloroplast genomes (157,634 − 169,694 bp), consisting of two pairs of inverted repeats (IR: 26,529 − 37,674 bp), a large single copy (LSC: 75,477 − 86,500 bp), and a small single copy (SSC: 17,861 − 18,367 bp). 128–143 genes (comprising 82–93 protein-coding genes, 8 ribosomal RNAs, and 36–43 transfer RNAs) are found in the chloroplast genomes. Based on comparative analyses, this taxon has a relatively similar genome structure. A total of six substantially divergent DNA regions (trnT-UGU-trnL-UAA, atpF-atpH, ycf4-cemA, psbC-trnS-UGA, rpl32-trnL-UAG, and ccsA-ndhD) are found in the seventeen chloroplast genomes. These regions are suitable for species identification and phylogeographic analysis. Phylogenetic analysis shows that Begonia species that were suited to comparable environments grouped in a small clade and that all Begonia species formed one big clade in the phylogenetic tree, supporting the genus' monophyly. In addition, positive selection sites were discovered in eight genes (rpoC1, rpoB, psbE, psbK, petA, rps12, rpl2, and rpl22), the majority of which are involved in protein production and photosynthesis. Conclusion: Using these genome resources, we can resolve deep-level phylogenetic relationships between Begonia species and their families, leading to a better understanding of evolutionary processes. In addition to enhancing species identification and phylogenetic resolution, these results demonstrate the utility of complete chloroplast genomes in phylogenetically and taxonomically challenging plant groupings. [ABSTRACT FROM AUTHOR]

Although socioeconomic conditions are crucial predictors of adult attachment, the relationships between attachment patterns and distinct dimensions of socioeconomic disadvantage, reflecting its structure as a multi-faceted social construct, remain largely unexplored. Moreover, the overwhelming majority of the previous studies utilized samples from Western, educated, industrialized, rich, and democratic (WEIRD) societies, so little is known about how these relationships unfold in underrepresented cultural contexts. To fill these gaps, we explored the relationships between attachment dimensions and multiple indicators of socioeconomic disadvantage in a large community sample of married couples (N = 2622) in Turkey. We expected that indicators of socioeconomic disadvantage would be positively related to both attachment anxiety and avoidance, particularly among women. In line with our expectations, we found that several indicators of socioeconomic disadvantage are related to both dimensions of insecure attachment. Furthermore, lower income levels emerged as a predictor for women's attachment avoidance. Results are discussed in light of gender, evolutionary, and cultural perspectives. [ABSTRACT FROM AUTHOR]