Hasil untuk "Biology (General)"

Xiaofang Li, Chunli Lei, Xiang Bai et al.

Condition monitoring of rotating machinery is critical for ensuring industrial safety and operational reliability. As a core component of intelligent diagnostic systems, domain adaptation methods have achieved notable progress in mechanical fault diagnosis. However, most existing approaches presume a fully shared label space between source and target domains, limiting their effectiveness under partial domain adaptation scenarios commonly encountered in industrial practice. In addition, they often struggle with classification uncertainty near decision boundaries. To address these challenges, this paper proposes a Selective Adversarial Augmentation Network (SAAN) for cross-domain rolling bearing fault diagnosis with partial label space alignment. The proposed framework designs a multi-level feature extraction module to enhance transferable feature representation and a Balanced Augmentation Selective Adversarial Module (BASAM) to dynamically balance class distributions and selectively filter irrelevant source classes, thereby mitigating negative transfer and achieving fine-grained class alignment. Furthermore, an uncertainty suppression mechanism is put forth to reinforce classifier boundaries by minimizing the impact of ambiguous samples. Comprehensive experiments conducted on public and proprietary bearing datasets demonstrate that SAAN consistently surpasses state-of-the-art benchmarks in diagnostic accuracy and robustness, providing an effective solution for practical applications under class-imbalanced and variable operating conditions.

Giuseppe Altieri, Sabina Laveglia, Mahdi Rashvand et al.

This study aims to evaluate and classify the ripening stages of yellow-fleshed kiwifruit by integrating spectral and physicochemical data collected from the pre-harvest phase through 60 days of storage. A portable near-infrared (NIR) spectrometer (900–1700 nm) was used to develop predictive models for soluble solids content (SSC) and firmness (FF), testing multiple preprocessing methods within a Partial Least Squares Regression (PLSR) framework. SNV preprocessing achieved the best predictions for FF (R²P = 0.74, RMSEP = 12.342 ± 0.274 N), while the Raw-PLS model showed optimal performance for SSC (R²P = 0.93, RMSEP = 1.142 ± 0.022°Brix). SSC was more robustly predicted than FF, as reflected by RPD values of 2.6 and 1.7, respectively. For ripening stage classification, an Artificial Neural Network (ANN) outperformed other models, correctly classifying 97.8% of samples (R² = 0.95, RMSE = 0.08, MAE = 0.03). These results demonstrate the potential of combining NIR spectroscopy with AI techniques for non-destructive quality assessment and accurate ripeness discrimination. The integration of regression and classification models further supports the development of intelligent decision-support systems to optimize harvest timing and postharvest handling.

Hameed Byju, Hegde Maitreyi, Raveendran Natarajan et al.

Background Wetlands, globally, face significant threats from human activities, and waterbirds, as key indicators of wetland health, are essential to maintaining ecological balance. Any long-term conservation measures should prioritize coordinated habitat preservation, wetland restoration, and sustainable management practices involving local communities. Monitoring and analyzing waterbird population trends are critical for understanding restoration, conservation, and management practices. Methods The present study was carried out in five bird sanctuaries Chitrangudi, Kanjirankulam (Ramsar sites), Therthangal, Sakkarakottai, and Mel-Kel Selvanoor of Tamil Nadu, Southeast coast of India, over one year (April 2022 to March 2023). Monthly surveys using direct and block methods, with additional fortnightly visits during the breeding season, were conducted from vantage points to record species diversity, nesting activity, and conservation threats. Assessments of the residential status, national status (SOIB), and Convention for Migratory species (CMS) status were done along with the alpha and beta biodiversity profiles, principal component analysis, Pearson correlation and other statistical methods performed to assess breeding waterbirds community structure. Threats to the breeding waterbirds were categorised into high, medium, and low impacts based on degree of severity and irreversibility. Results The avifaunal checklist revealed a diversity of waterbird species utilizing the sanctuaries for breeding. Notable findings include two Near-Threatened species like, Asian Woolly-necked Stork Ciconia episcopus, and Spot-billed Pelican Pelecanus philippensis, where Asian Woolly-necked Stork recorded only in Therthangal Bird Sanctuary. Avifauna of each sanctuary with breeding waterbirds in parenthesis is as follows: Chitragundi 122 (13); Mel-Kel Selvanoor 117 (19); Therthangal 96 (23); Sakkarakottai 116 (17) and Kanjirankulam 123 (14). The breeding activity (incubation in nests) was from November to February except for Glossy Ibis and Oriental Darter whose breeding started in December; Spot-billed Duck and Knob-billed Duck breed only during January and February. Among the 131 species recorded from all the sanctuaries, 78% were resident birds; 27% were breeding waterbirds, and 21% were Winter visitors. The SOIB and CMS statuses underscore the necessity of implementing effective conservation measures to protect breeding habitats amid anthropogenic pressures. Water unavailability and nest tree unavailability in the sanctuaries are found to be the high degree threats to breeding waterbirds than others. This research provides critical baseline data for the forest department’s future wetland management plans.

Eva Caly-Simbou, Marie Veronique Nomenjanahary, Stéphanie Javegny et al.

Abstract Objectives The Ralstonia solanacearum species complex (RSSC) encompasses phytopathogenic bacteria responsible for bacterial wilt, a devastating disease affecting a wide range of agriculturally important crops. In the South-West Indian Ocean, lineage I-18 of R. pseudosolanacearum has emerged as a particularly destructive pathogen, posing a serious threat to regional food security. In this context, we report the complete genome sequence of isolate RUN2161, collected in Mayotte. This first genome from this island provides a valuable resource for unraveling the evolutionary and epidemiological mechanisms driving the emergence and spread of highly epidemic strains in agriculture.. Data description The genome of strain RUN2161 from Mayotte was sequenced using Illumina short reads and Nanopore long reads. A hybrid assembly was performed resulting in a complete genome of 5,989,529 bp with a G + C content of 66.7%. Functional annotation identified 5,268 CDS, 12 rRNAs, 61 tRNA genes, and 4 ncRNAs, assembled into one chromosome, one megaplasmid and one plasmid. Accessory plasmids are uncommon in RSSC. The RUN2161 plasmid contains Type IV secretion system genes, commonly found on conjugative plasmids, but less commonly, it also carries Type II secretion system genes involved in secretion of toxins and degradative enzymes, which could contribute to epidemiological success.

Julien Martinelli

Physics-Informed Machine Learning (PIML) has successfully integrated mechanistic understanding into machine learning, particularly in domains governed by well-known physical laws. This success has motivated efforts to apply PIML to biology, a field rich in dynamical systems but shaped by different constraints. Biological modeling, however, presents unique challenges: multi-faceted and uncertain prior knowledge, heterogeneous and noisy data, partial observability, and complex, high-dimensional networks. In this position paper, we argue that these challenges should not be seen as obstacles to PIML, but as catalysts for its evolution. We propose Biology-Informed Machine Learning (BIML): a principled extension of PIML that retains its structural grounding while adapting to the practical realities of biology. Rather than replacing PIML, BIML retools its methods to operate under softer, probabilistic forms of prior knowledge. We outline four foundational pillars as a roadmap for this transition: uncertainty quantification, contextualization, constrained latent structure inference, and scalability. Foundation Models and Large Language Models will be key enablers, bridging human expertise with computational modeling. We conclude with concrete recommendations to build the BIML ecosystem and channel PIML-inspired innovation toward challenges of high scientific and societal relevance.

Zihao Li, Zhichen Zeng, Xiao Lin et al.

Over the past decade, advances in generative modeling, such as generative adversarial networks, masked autoencoders, and diffusion models, have significantly transformed biological research and discovery, enabling breakthroughs in molecule design, protein generation, catalysis discovery, drug discovery, and beyond. At the same time, biological applications have served as valuable testbeds for evaluating the capabilities of generative models. Recently, flow matching has emerged as a powerful and efficient alternative to diffusion-based generative modeling, with growing interest in its application to problems in biology and life sciences. This paper presents the first comprehensive survey of recent developments in flow matching and its applications in biological domains. We begin by systematically reviewing the foundations and variants of flow matching, and then categorize its applications into three major areas: biological sequence modeling, molecule generation and design, and peptide and protein generation. For each, we provide an in-depth review of recent progress. We also summarize commonly used datasets and software tools, and conclude with a discussion of potential future directions. The corresponding curated resources are available at https://github.com/Violet24K/Awesome-Flow-Matching-Meets-Biology.

Marcos G. Alberti, Alejandro Enfedaque, Duarte M. V. Faria et al.

Material optimization was one of the challenges for achieving cost-competitive solutions when concrete was introduced in construction, leading to new structural shapes for both civil works and buildings. As concrete construction became dominant, saving material was given less significance, and the selection of the structural typology was mostly influenced by construction or architectural considerations. Simple and non-time-consuming methods for building thus arose as the dominant criteria for design, and this led to the construction of less efficient structures. Currently, the awareness of the environmental footprint in concrete construction has brought the focus again to the topic of structural efficiency and material optimization. In addition, knowledge of material technology is pushing the use of cements and binders with lower environmental impact. Within this framework, Fiber-Reinforced Concrete (FRC) has been identified as a promising evolution of ordinary concrete construction. In this paper, a discussion is presented on the structural properties required for efficient design, focusing on the toughness and deformation capacity of the material. By means of several examples, the benefits and potential application of limit analysis to design at the Ultimate Limit State with FRC are shown. On this basis, the environmental impact of a tailored mix design and structural typology is investigated for the case of slabs in buildings, showing the significant impact that might be expected (potentially reducing CO₂-eq emissions to half or even less in slabs when compared to ordinary solutions).

Bareqa Salah, Diana Shahin, Momen Sarhan et al.

Michael Gorczyca, Justice Sefas

Studies in circadian biology often use trigonometric regression to model phenomena over time. Ideally, protocols in these studies would collect samples at evenly distributed and equally spaced time points over a 24 hour period. This sample collection protocol is known as an equispaced design, which is considered the optimal experimental design for trigonometric regression under multiple statistical criteria. However, implementing equispaced designs in studies involving individuals is logistically challenging, and failure to employ an equispaced design could cause a loss of statistical power when performing hypothesis tests with an estimated model. This paper is motivated by the potential loss of statistical power during hypothesis testing, and considers a weighted trigonometric regression as a remedy. Specifically, the weights for this regression are the normalized reciprocals of estimates derived from a kernel density estimator for sample collection time, which inflates the weight of samples collected at underrepresented time points. A search procedure is also introduced to identify the concentration hyperparameter for kernel density estimation that maximizes the Hessian of weighted squared loss, which relates to both maximizing the $D$-optimality criterion from experimental design literature and minimizing the generalized variance. Simulation studies consistently demonstrate that this weighted regression mitigates variability in inferences produced by an estimated model. Illustrations with three real circadian biology data sets further indicate that this weighted regression consistently yields larger test statistics than its unweighted counterpart for first-order trigonometric regression, or cosinor regression, which is prevalent in circadian biology studies.

Jae Young Lee, Y. Minami, B. Choi et al.

The first edition of the guidelines for the use of ultrasound contrast agents was published in 2004, dealing with liver applications. The second edition of the guidelines in 2008 reflected changes in the available contrast agents and updated the guidelines for the liver, as well as implementing some nonliver applications. The third edition of the contrast-enhanced ultrasound (CEUS) guidelines was the joint World Federation for Ultrasound in Medicine and Biology-European Federation of Societies for Ultrasound in Medicine and Biology (WFUMB-EFSUMB) venture in conjunction with other regional US societies such as Asian Federation of Societies for Ultrasound in Medicine and Biology, resulting in a simultaneous duplicate on liver CEUS in the official journals of both WFUMB and EFSUMB in 2013. However, no guidelines were described mainly for Sonazoid due to limited clinical experience only in Japan and Korea. The new proposed consensus statements and recommendations provide general advice on the use of Sonazoid and are intended to create standard protocols for the use and administration of Sonazoid in hepatic and pancreatobiliary applications in Asian patients and to improve patient management.

J. Burdick, G. Vunjak‐Novakovic

Claudia S. Priglinger, Günter Rudolph, Irene Schmid et al.

Abstract Background Biallelic pathogenic variants in the neuroblastoma‐amplified sequence (NBAS) gene manifest in a broad spectrum of disorders, including, but not limited to recurrent acute liver failure, skeletal dysmorphism, susceptibility to infections, and SOPH syndrome with its cardinal symptoms of short stature, optic atrophy, and Pelger–Huët anomaly. We aimed to present clinical and genetic characteristics of two sisters (20 and 15 years old) who were diagnosed with optic atrophy and cone dystrophy in childhood. Genome sequencing revealed two novel variants in NBAS in compound heterozygous state in both sisters, namely a 1‐bp deletion predicted to result in a premature termination codon (c.5104del; p.(Met1702*)), and a non‐canonical splice site variant of unclear significance (c.886‐5T>A; p.?). Results Clinical examination and history revealed cone dystrophy, optic atrophy, and Pelger–Huët anomaly, but no short stature, recurrent acute liver failure, or susceptibility to infections. RNA analysis revealed that the c.886‐5T>A variant results in two aberrant transcripts that are predicted to lead to in frame amino acid changes in the β‐propeller region of the protein. Conclusion We hypothesize that the phenotype of our subjects, which appears to be at the end of the spectrum of NBAS‐related disorders, could be explained by residual protein function mediated by the non‐canonical splice site variant c.886‐5T>A. Our study contributes to the existing knowledge on the genotypic and phenotypic spectrum of NBAS‐related disorders.

Ubaldo Jorge Augusto de Filipe André, Ana Paula Sarmento do Santos, Onelis Portuondo Savón et al.

Context: Today, quite a few environmental problems require swift responses toward adjustment, mitigation, and sustainability. Accordingly, how could university students acquire effective environmental education so they can play their social roles in balance with environmental protection? Aim: To recommend methodological actions to contribute to student education at the Faculty of Natural Sciences, the University of Namibe, Angola. Methods: Consequently, this study took from qualitative methods of social research. Methods and techniques, such as analysis-synthesis, inductive-deductive, and documentary review for processing information about environmental education and climate change in university education. Results: Five methodological guidelines for environmental education were established. They were inserted in subject Physics II, in the first year of the Marine Biology Bachelor Degree, with six general actions that link theory and practice, through the teaching process in the degrees of Oceanography, Marine Biology, and Marine Resources. The study demonstrated the fulfillment of learning objectives related to Sustainable Development Goals No. 13 and 14, based on UNESCO (2017) guidelines. Conclusions: There is a potential for students to acquire environmental information through methodological actions by the staff, in terms of subject preparation at the Faculty of Natural Sciences, the University of Namibe.

Yulong Li, Andy Zeng, Shuran Song

Most successes in autonomous robotic assembly have been restricted to single target or category. We propose to investigate general part assembly, the task of creating novel target assemblies with unseen part shapes. As a fundamental step to a general part assembly system, we tackle the task of determining the precise poses of the parts in the target assembly, which we we term ``rearrangement planning''. We present General Part Assembly Transformer (GPAT), a transformer-based model architecture that accurately predicts part poses by inferring how each part shape corresponds to the target shape. Our experiments on both 3D CAD models and real-world scans demonstrate GPAT's generalization abilities to novel and diverse target and part shapes.

Gerald Stanhill

I teach Phy-Chem and AP Biology in an urban magnet high school. Phy-Chem is understood to be a freshmen general science class with an emphasis on physics and chemistry. AP Biology is a high school biology class that uses a college curriculum provided by the College Board. At my school AP Biology’s, like all AP classes, enrollment is an open-door policy wherein students can choose to take the class and do not have to meet any requirements to enter. The Phy-Chem curriculum is structured around 21 Next Generation Science Standards (NGSS). These standards are drawn from both the physical and environmental science standards as well as engineering standards.

J. Rupp, K. Sokoloski, Natasha N Gebhart et al.

Francisco Yanez-Lemus, Rubén Moraga, Carlos T. Smith et al.

Lactic acid bacteria (LAB), obtained from rainbow trout (<i>Oncorhynchus mykiss</i>) intestine, were cultured in MRS medium and probiotic candidates. Concurrently, producers of elemental selenium nanoparticles (Se⁰Nps) were selected. Probiotic candidates were subjected to morphological characterization and the following tests: antibacterial activity, antibiotic susceptibility, hemolytic activity, catalase, hydrophobicity, viability at low pH, and tolerance to bile salts. Two LAB strains (S4 and S14) satisfied the characteristics of potential probiotics, but only strain S14 reduced selenite to biosynthesize Se⁰Nps. S14 strain was identified, by 16S rDNA analysis, as <i>Lactiplantibacillus plantarum</i>. Electron microscopy showed Se⁰Nps on the surface of S14 cells. Rainbow trout diet was supplemented (10⁸ CFU g⁻¹ feed) with Se⁰Nps-enriched <i>L. plantarum</i> S14 (LABS14-Se⁰Nps) or <i>L. plantarum</i> S14 alone (LABS14) for 30 days. At days 0, 15, and 30, samples (blood, liver, and dorsal muscle) were obtained from both groups, plus controls lacking diet supplementation. Fish receiving LABS14-Se⁰Nps for 30 days improved respiratory burst and plasmatic lysozyme, (innate immune response) and glutathione peroxidase (GPX) (oxidative status) activities and productive parameters when compared to controls. The same parameters also improved when compared to fish receiving LABS14, but significant only for plasmatic and muscle GPX. Therefore, Se⁰Nps-enriched <i>L. plantarum</i> S14 may be a promising alternative for rainbow trout nutritional supplementation.

Cristina Zivko, Kathrin Fuhrmann, Gregor Fuhrmann et al.

A method is developed to isolate and characterize extracellular vesicles (EVs) from human hepatic stellate cells and proteomics reveals that the matricellular protein SPARC may be used as an EV marker after lipid-based antifibrotic treatment.

Ruosha Liu, Dongmei Wang

Ecological stoichiometry is an effective tool for analyzing and explaining changes and connections between plants and the environment. However, the changes in ecological stoichiometry throughout the leaf-root-litter-soil continuum during different seasons in plantation ecosystems are not fully understood. In this study, the C, N and P contents of leaves, roots, litter and soil were measured in four plantations growing Larix principis-rupprechtii, Picea crassifolia, Betula platyphylla and Populus cathayana in spring, summer and autumn. The stoichiometric characteristics and seasonal dynamics along the continuum were analyzed to reveal nutrient limitations on the plantations and coupling relationships among the components. Our analysis revealed that the C and N contents and C:P and N:P ratios of leaves, the P content of litter, and the C:N ratio of roots were the highest among all components. The seasonal dynamics showed that the N and P contents of leaves and roots and the P content of soil and litter were the highest in spring on all plantations, while the C:N, C:P and N:P of leaves, the C:N and C:P of roots and soil, and the C:P and N:P of litter were the lowest in spring. In all plantations, the N contents of BP and PR in each component were higher, while the P content and C:P and N:P ratios in roots of LR in summer were lower. The N element between litter-soil-root-leaf had a strong coupling relationship, and the P element between leaf-litter-root had a strong coupling relationship. Our results demonstrated that plants and the environment in each season on the Loess Plateau were mainly coupled and regulated by the N element in litter-soil-root-leaf and by the P element in leaf-litter-root. The plants absorbed N mainly from the soil and P mainly from litter. Plantations were limited by N in spring and summer and by P in autumn; this information may help guide plantation restoration and management.

Yeasmin Akter Moonnee, Md Javed Foysal, Abu Hashem et al.

Abstract Background The leather industry generates huge volume of waste each year. Keratin is the principal constituents of this waste that is resistant to degradation. Some bacteria have the ability to degrade keratin through synthesis of a protease called keratinase that can be used as sources of animal feed and industrial production of biodiesel, biofertilizer, and bioplastic. Majority of the studies focused on keratin degradation using gram-positive bacteria. Not much of studies are currently available on production of keratinase from gram-negative bacteria and selection of best parameters for the maximum production of enzyme. The aim of this study was to isolate and characterize both groups of bacteria from soil for keratinase and optimize the production parameters. Results A total of 50 isolates were used for initial screening of enzyme production in skim milk, casein, and feather meal agar. Out of 50, five isolates showed significantly higher enzyme production in preliminary screening assays. Morphological and biochemical characterization revealed 60% of the isolates as gram-negative bacteria including two highest enzyme-producing isolates. The isolates were identified as Pseudomonas aeruginosa through sequencing of 16S rRNA gene. Maximum production of enzyme from P. aeruginosa YK17 was achieved with 2% chicken feather, beef extract, and ammonium nitrate as organic and inorganic nitrogen sources and glucose as a carbon source. Further analysis revealed that 3% inoculum, 40 °C growth temperature and 72-h incubation, resulted in maximum production of keratinase. Conclusion The overall results showed significant higher production of enzyme by the P. aeruginosa YK17 that can be used for the degradation of recalcitrant keratin waste and chemical dehairing in leather industries, thereby preventing environmental pollution.