bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and Characterization of Ammonia Removal Moving Bed Biofilms for Landfill Leachate Treatment
Authors: Petrilli Rossana , Fabbretti Attilio , Pucci Kathleen , Pagliaretta Graziella , Napolioni Valerio , Falconi Maurizio
Published: September 2024

Urbanization growth has intensified the challenge of managing and treating increasing amounts of municipal solid waste (MSW). Landfills are commonly utilized for MSW disposal because of their low construction and operation costs. However, this practice produces huge volumes of landfill leachate, a highly polluting liquid rich in ammoniacal nitrogen (NH3-N), organic compounds and various heavy metals, making it difficult to treat in conventional municipal wastewater treatment plants (WWTPs). In recent years, research has shown that microbial biofilms, developed on carriers of different materials and called “Moving Bed Biofilm Reactors” (MBBRs), may offer promising solutions for bioremediation. This study explored the biofilm development and the nitrification process of moving bed biofilms (MBBs) obtained from high am-monia-selected microbial communities. Using Crystal Violet Staining and Confocal Laser-Scanning Microscopy, we followed the biofilm formation stages correlating nitrogen removal to metagenomic analyses. Our results indicate that MBBs unveiled a 10-fold more enhanced nitrification rate than the dispersed microbial community pre-sent in the native sludge of the Porto Sant’Elpidio (Italy) WWTP. Four bacterial families, Chitinophagaceae, Comamonadaceae, Sphingomonadaceae, and Nitrosomona-daceae accumulate in structured biofilms and significantly contribute to the high ammonium removal rate of 80% in 24 hours as estimated in leachate-containing wastewaters.
The Effects of the Modern Architecture Style on the Evolution of Mosques: A Case Study of Contemporary Mosques in Sulaymaniyah Governorate
Authors: Ahmed Ahmed Qadir , Fethi Ihsan
Published: September 2024

Following the economic and political transformations after 1991, including the autonomy of the Kurdistan Region and the establishment of Iraq's new federal government in 2003, extensive construction, including mosques, has reshaped the region. This requires examinations of evolving architectural features in new mosques and questioning their alignment with religious and aesthetic design objectives. This research focuses on the transformative impact of modern architectural styles on mosque evolution in Sulaymaniyah Governorate. Acknowledging the interplay of cultural evolution, technology, and artistic innovation, the study employs an in-depth case study approach to analyze selected mosques in Sulaymaniyah Governorate that blend traditional Islamic architecture with modern design principles. This synthesis of traditional and modern elements raises questions about religious legitimacy, historical symbolism, and architecture's role in reflecting and shaping religious values. Using quantitative methods including indicator-based impact assessment, the study identifies modern architectural indicators, determines religious objectives of mosque design through Islamic legitimacy references, and analyzes the case study data. By employing person coefficient correlation, the research aims to identify the causal relationship between modern architectural indicators and achieved design objectives. The results reveal that the overall influence of the modern architecture style tends to be more negative on the evol¬ution of mosques.
Forecasting Mortality Trends: Advanced Techniques and the Impact of COVID-19
Authors: Nalmpatian Asmik , Heumann Christian , Pilz Stefan
Published: September 2024

The objective of this research is to evaluate four distinct models for multi-population mortality projection in order to ascertain the most effective approach for forecasting the impact of COVID-19 pandemic on mortality. Utilising data from the Human Mortality Database for five countries Finland, Germany, Italy, the Netherlands, and the United States, the study identifies the generalized additive model (GAM) within the age-period-cohort (APC) analytical framework as the most promising for precise mortality forecasts. Consequently, this model serves as the basis for projecting the impact of the COVID-19 pandemic on future mortality rates. By examining various pandemic scenarios, ranging from mild to severe, the study concludes that projections assuming a diminishing impact of the pandemic over time are most consistent, especially for middle-aged and elderly populations. Projections derived from the superior GAM-APC model offer guidance for strategic planning and decision-making within sectors facing the challenges posed by extreme historical mortality events and the uncertain future mortality trajectories.
Development of a Rapid Detection Method for Ethylene Glycol and Glycolic Acid in Feline Samples: A Response to Increasing Antifreeze Poisoning Incidents in Korea
Authors: Chae HyunYoung , Byun Jae Won , Shin Go-Eun , Lee Kyunghyun , Kim Ah-Young , Ku Bok-Kyung , Hossain Md Akil , Kim Tae-Wan , Kang JeongWoo
Published: September 2024

Recently, cases of antifreeze poisoning in companion animals, particularly cats, have surged in the Republic of Korea. Ethylene glycol (EG), the toxic primary component of antifreeze, is metabolized into glycolic acid (GA), leading to severe conditions such as metabolic acidosis and acute renal failure. Traditional detection methods, although effective, are often time-consuming owing to complex sample preparation. This study involved a novel analytical method utilizing GC-MS for EG and LC-MS/MS for GA detection, which streamlined the detection process by eliminating the need for derivatization. The method was validated for accuracy and reliability, enabling the rapid and precise identification of EG and GA in biological samples. The study also included the successful application of this method in a case where initial exposure to antifreeze was not apparent, which highlighted the effectiveness of this method in diagnosing poisoning even in cases where clinical history is unclear. The development of this rapid diagnostic approach addresses the urgent need for the efficient detection of antifreeze poisoning, improving animal welfare and supporting forensic investigations.
Antioxidant Effects of Aromatic Plant Extracts in Neurodegenerative Diseases: A Review
Authors: Zhu Youyang , Tian Miao , Qin Yuliang , Zhao Ting , Li Zhaofu , Qin Dongdong
Published: September 2024

Neurodegenerative diseases (NDDs) are a class of cognitive and motor disorders that include Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), and others. They are caused by lesions in cells and tissues of the central nervous system, resulting in corresponding dysfunctions and consequent decline in cognitive and motor functions. Neural tissues are extremely vulnerable to oxidative stress, which plays critical biological roles in NDDs. Aromatic compounds are found extensively in natural plants and have substantial effects of anti-oxidative stress damage, which not only have a wide range of research applications in cosmetics, foods, etc., but are also frequently utilized in the treatment of various central nervous system diseases. This review summarizes the relevant oxidative stress mechanisms in NDDs (AD, PD, HD, and ALS) and reviews aromatic compounds such as polyphenols, terpenoids, and flavonoids that can be used in the management of neurodegenerative diseases, as well as their specific mechanisms of antioxidant action. This review will serve as a reference for future experimental studies on neurodegenerative illnesses while also offering fresh insights into clinical therapy.
Procedimiento - Modalidad de suficiencia profesional para obtención de título profesional
Authors:   Universidad Científica del Sur
Published: September 2024

Procedimiento - Modalidad de trabajo de suficiencia profesional para obtención de título profesional. Versión 1.0 (2024). Vigente.
Protein Set Transformer: A protein-based genome language model to power high diversity viromics
Authors: Anantharaman Karthik , Martin Cody , Gitter Anthony
Published: September 2024

Exponential increases in microbial and viral genomic data demand transformational advances in scalable, generalizable frameworks for their interpretation. Standard homology-based functional analyses are hindered by the rapid divergence of microbial and especially viral genomes and proteins that significantly decreases the volume of usable data. Here, we present Protein Set Transformer (PST), a protein-based genome language model that models genomes as sets of proteins without considering sparsely available functional labels. Trained on >100k viruses, PST outperformed other homology- and language model-based approaches for relating viral genomes based on shared protein content. Further, PST demonstrated protein structural and functional awareness by clustering capsid-fold-containing proteins with known capsid proteins and uniquely clustering late gene proteins within related viruses. Our data establish PST as a valuable method for diverse viral genomics, ecology, and evolutionary applications. We posit that the PST framework can be a foundation model for microbial genomics when trained on suitable data.
In-Situ Microstructural Evolution and Mechanical Performance of Nickel-Containing Steels During High-Temperature Heat Treatment: Precipitation Behavior and Its Impact on Material Properties
Authors: Sun Guojin , Wang Qi
Published: September 2024

This study investigates the microstructural evolution and mechanical properties of steel subjected to high-temperature heat treatment, with a focus on the formation and effects of second phase precipitates. High Temperature Confocal Laser Scanning Microscopy (HTCLSM) was employed to observe the in-situ changes in microstructure as the steel was heated from room temperature to 900°C. The observations revealed that second phase precipitates, identified as chromium carbides (Cr7C3), began forming at approximately 820°C and increased in quantity and size up to 900°C. Scanning Electron Microscopy (SEM) and Energy-Dispersive X-ray Spectroscopy (EDX) confirmed that these precipitates significantly enhance the material's hardness, with microhardness values of 320 HV for the precipitates compared to 270 HV for the matrix. Tensile tests showed that the tensile strength of the steel increases with soaking time at 900°C, reaching a maximum after 3 minutes due to the strengthening effect of the precipitates. Beyond this point, strength decreases due to grain coarsening.
Intelligent Energy Optimization in Wind-PV-Battery Microgrids Using AI
Authors: Pandey Amit Kumar , Tiwari P. , Nishad D. K. , Khalid Saifullah
Published: September 2024

This research presents a novel swarm intelligence-based energy management framework for autonomous microgrids integrating wind, photovoltaic, and battery storage resources. Krill Herd, Moth-Flame, Particle Swarm, and Whale Optimization algorithms are employed for adaptive tuning of control parameters, maximizing renewable energy utilization, ensuring power balance, and maintaining voltage/frequency stability under dynamic conditions. A MATLAB/Simulink model of the wind-PV-battery microgrid is developed to evaluate the performance of the proposed AI-driven control approach. Simulations validate the superior performance of swarm-optimized controllers compared to conventional methods, demonstrating improved efficiency, renewable energy harvesting, power quality, and dynamic response. The AI-based energy management significantly enhances the reliability, sustainability, and economic viability of hybrid renewable microgrids. This work presents a significant advancement in optimizing energy flow and enabling intelligent, resilient operation of microgrids under variable conditions, paving the way for wider adoption of sustainable energy systems.
Cargo carrying model of high-speed railway express considering transportation capacity sharing and carbon trading
Authors: Yang Jingshuai , Yan Jiechan , Yang Yu’e
Published: September 2024

In order to make full use of high-speed railway (HSR) transportation capacity and facilitate the low-carbon development of transportation infrastructure, this paper examines the cargo carrying method in the context of transportation capacity sharing of HSR. With carbon trading incorporated into the profit of HSR express, a cargo carrying decision-making model with consideration of carbon trading is developed, considering constraints such as loading capacity of HSR and work ability of stations. Using genetic algorithm as the framework, a multi-loading rules genetic algorithm is designed to solve the model, considering the effect of cargo service types, origin-destination (OD) pairs, and loading priority of HSR trains. The numerical case of Xi'an-Chengdu HSR line is implemented to validate the proposed model by Gurobi solver, and the performance of different algorithm is compared. The results show that the three loading rules proposed are reasonable and the multi-loading rule genetic algorithm outperforms them. From the sensitivity analysis, it was determined that enhancing station work ability and considering train transfer can increase total profit.
Anomalous US-wide prevalence of reversion mutants in the emergence of Omicron BA.1
Authors: Kakeya Hideki
Published: September 2024

Surface glycoprotein sequences of the Omicron BA.1 lineage that included only reverse mutations were searched for in NCBI GenBank, where the dates and locations of collection were retrieved for each mutant. Data from BA.1.x lineages that emerged during the same period of time were used as a control, and the early spread of these mutants was compared. The number of states where the first 20 samples were found was compared between the group of reversion mutants and the control group. The result reveals that the reversion mutants were widespread from the early days of their emergence, showing statistically significant differences compared to the control group. Whether the origin of the reversion mutants is natural infection from abroad, domestic natural mutation, or leakage from a laboratory, it is usually possible to make a rough estimation of the epicenter by tracing its spread. The wide prevalence of reversion mutants of BA.1 from the beginning of their emergence is highly anomalous, which cannot be explained by any theories of molecular biology, virology, or infectiology currently known.
A classroom behavior recognition method based on Temporal Attention Mechanism and Fragment-based Mechanism
Authors: Lai Xiang , Fu Ruijie , Jiang Hongbo , Peng Yue , Tang Qiang , Yao Jinghua , Liu Tao
Published: September 2024

Classroom behavior detection aims to enhance classroom efficiency by collecting information on students' behavior and developing strategies for improved teaching methods. However, existing models suffer from low efficiency, subjectivity, and recognition accuracy. To address these issues, we propose a classroom behavior recognition model utilizing a dataset from monitoring devices, based on the Temporal Attention Mechanism (TAM) and Fragment-based mechanism of a 3D convolutional neural network. Our TAM applies attention distribution in the time dimension, combined with 3D CAM, as the Channel and temporal attention module (CTAM), resulting in a 10\% accuracy improvement. We integrate 3D-CAM and 3D-SAM with TAM, validating the portability and universality of our time attention mechanism. Furthermore, we introduce the Fragment-based mechanism, synthesizing feature outputs of different time scales for improved classification. By incorporating this mechanism, the model achieves a 30\% accuracy improvement on the classroom behavior dataset. Evaluation on a public dataset demonstrates significant improvements compared to the original model.
Perception of Undergraduate Medical Students and Examiners Towards Grand Objective Structured Clinical Examination
Authors: Hawezy Dawan J. , Barzinjy Saman Tahir , Saadadin Govand , Hawezy Gasheen Abdilwahid , Bakir Waleed
Published: September 2024

Background
The assessment of undergraduate medical students consists of a written component and an advanced clinical competency test that evaluates the students' skills. The Objective Structured Clinical Examinations (OSCE) was only implemented in most medical schools in the last ten years, similar in many developing countries. It was first used with other clinical assessment methods
This study was designed to investigate how medical students in the fourth and sixth grades and examiners perceived the unique format, features, and quality of the GRAND OSCE, a novel method for assessing students. The aim was to understand how this innovative method, distinct from traditional assessment methods, prepares students for real-world scenarios where they encounter different specialty cases.
Additionally, the study aimed to understand the significant role and challenges faced by the Faculty of General Medicine at Koya University in implementing this type of OSCE and to identify potential improvements to enhance the quality of the assessment process.
Method
Following the administration of two distinctGRAND OSCE examinations for the fourth and sixth stages, feedback forms were created using Google Forms and distributed to both students and examiners. The feedback forms covered all aspects of the examination process. The responses were then rigorously analyzed using the scientific tool SPSS, allowing for a comparison between students from both stages and the faculty and external examiners.
Results
In the survey of 104 undergraduate students (78% of attendants), the majority (84n,80%) rated the fairness of the assessment as good, which is the primary goal of this version of OSCE. A large percentage (89n,85.6%) agreed that the examination covered a wide range of clinical skills. Eighty students (76.85%) believed the patients cooperated and found the findings precise; on the other hand, The obtained responses from 24 out of 33 faculty staff members (75%) and 29 out of 35 external examiners (82%) strongly agreed that the examination adequately covered a wide variety of clinical abilities. Only two of 68 examiners (2.9%) believed the examination needed more to provide a learning opportunity.
Conclusion
With the insightful suggestions for improvement provided by the participants, this version of OSCE has a promising potential to evolve into a fair, objective clinical tool for assessing medical students, instilling a sense of optimism for its future development.
Novel Approaches to Reducing Gastric Cancer Risk through Electromagnetic Signal Treatment of Pork Meat and Its Effects on MAPK Pathway Modulation
Authors: Justine Elsa Easter , Samad Abdus , Dhandapani Sanjeevram , Lee Dongbin , Kim Yeon-Ju
Published: September 2024

The consumption of red meat, such as pork, beef, and lamb, has been associated with an incidence of gastric cancer (GC) due to certain processing and preparation methods. However, electromagnetic signal (EMS) exposure has demonstrated beneficial effects on food preparation, potentially improving food quality and reducing risk factors associated with GC. In our study, pork meat was treated with EMS, and this meat was investigated for its potential to reduce GC risk viain vitroand transcriptomic approaches. 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide and quantitative reverse transcription polymerase chain reaction assays were used to explore the cytotoxic and apoptotic effects of EMS-treated (EMS-T) and untreated (EMS-UT) pork meat extract on GC cells (KATO-III and S1M). The results indicated that KATO-III and S1M cells exhibited the highest inhibitory effect, with 32.8% and 24.53% inhibition, respectively, following treatment with 500 μg/mLEMS-T pork meat extract as compared to the EMS-UT meat extract treatment. Additionally, the apoptotic markers,CASP3andCASP9, and theBAX/BCL2ratio suggested that apoptosis was initiated upon treatment with EMS-T pork meat extract. Transcriptomic analysis further revealed that EMS-T pork treatment led to 217 uniquely differentially expressed genes in KATO-III cells, with 135 suppressed genes and 82 stimulated genes. Notably, the mitogen-activated protein kinase (MAPK) pathway emerged as a notably interconnected signaling pathway, with key genes, such asDUSP5, MAP4K2, TGFB3, CACNA2D2, CD14, CACNA1H, andEREG, showing significant interactions. Specifically, EMS-T pork meat extract treatment resulted in the suppression ofMAP4K2, TGFB3, andCD14, whileDUSP5andCACNA2D2were stimulated in KATO-III cells, contrasting with the gene expression profiles observed in cancer patients compared to healthy individuals according to The Cancer Genome Atlas data. Overall, these findings suggest that EMS-T meat may offer a novel approach for reducing GC risk by modulating apoptosis and the MAPK signaling pathway
CV Content Recognition and Organization Framework based onYOLOv8 and Tesseract-OCR Deep Learning Models
Authors: Sarhan Amany M. , Ali Hesham A. , Wagdi Mariam , Ali Bassant , Adel Aliaa , Osama Rahf
Published: September 2024

The growing number and variety of resumes in the job market makes it necessary to have better systems for sorting them efficiently. The task of finding suitable candidates for an open job position would be a repetitive and time-consuming task, especially from a large pool of candidates. The same task could be an actual fair screening and shortlisting though. Indeed, it is not acceptable to lose the chance to employ top skilled candidates because of the tardiness of the whole census or the poor selection caused by human fault. In order to help automating this cycle, this study introduces a new CV recognition system that combines advanced technologies: You Only Look Once (YOLO) for detecting important sections in the CV files, Tesseract-OCR for extracting text in each section, and an efficient post processing steps for correcting possible faults in recognized text. We also propose to automatically organize the data within the CV into a database to facilitate performing any data analytics or searching processes. To evaluate the system, we used a dataset of 1,300 resumes in JPEG, PNG, and JPG formats from various sources, showcasing different formats, languages, and quality levels. Preprocessing steps were taken to ensure the data is high quality and consistent. This approach saves time and improves the efficiency and accuracy of sorting resumes, helping HR teams focus on more strategic tasks and making the hiring process easier and less stressful. Results support the validity of the proposed system through the experiments with this diverse dataset. The system’s effectiveness was confirmed through experiments with this diverse dataset, achieving a mean Average Precision (mAP) of 92.1%, a precision rate of 92.2%, and a recall rate of 86.0%.
Methods for verifying the relationship between weak uranium information and uranium-rich geological bodies in the covered areas of Erlian Basin, Inner Mongolia
Authors: Shi Liancheng , Li Huaiyuan , Wang Nanping , Han Penghui , Shen Zhengxin , Yu Cong , ZHANG Xiang , Meng Xiangbao
Published: September 2024

The Erlian Basin, being an inportant base for sandstone-type uranium deposit exploration in Chin, is affected by overburden layers, resulting in indistinct characteristics of uranium anomalies in airborne gamma-ray spectrometry(AGS). To harness the potential of AGS, it is imperative to develop effective verification methods that can identify the spatial relationship between weak uranium information and deep uranium-rich geological bodies. This study presents a comprehensive investigation of geophysical and geochemical measurements conducted in four distinct areas. There is a significant positive correlation between the ground gamma spectrometry equivalent uranium(eUGGS) content, soil radon concentration(CRn), geoelectrochemical uranium(UGEC) and metal activity state uranium(UMAS) content directly above and at the edges of the uranium-rich geological bodies. When the buried depth of the uranium-rich geological body is more than 100 m, the eUGGS content and CRn above it mainly show locally weak increases with low values, while sharp anomalies and high-value zones are more likely to appear at its edges. Meanwhile, UGEC and UMAS content show sawtooth-like uranium peak anomalies on the profile. The verification methods and corresponding interpretation indicators, namely GGS, CRn, GEC or MAS measurements, can quickly reveal the spatial relationship and provide reliable basis for concealed uranium deposits exploration.
Exploration of the causal relationship between obesity and sepsis and investigation of the mechanism of anoikis in sepsis
Authors: Zhou Wenyan , Feng kai , Zhang Xusheng , Zhang Xiaoya , Chen Bendong
Published: September 2024

Objective To explore the causal relationship between common obesity indicators (body mass index, hip circumference, waist circumference) and sepsis based on Mendelian randomization analysis. Furthermore, the mechanism of the role of anoikis in sepsis was explored based on the bioinformatics mining. Methods In the first part, SNPs strongly associated with body mass index, Hip circumference, and Waist circumference were downloaded from the genome-wide association study(GWAS) database and screened as instrumental variables, and sepsis was used as an outcome variable. IVW was used as the primary analysis method to assess causal associations, with Weighted median and Mr-Egger as complementary methods. Heterogeneity among genetic variants was detected using Cochran's Q test and funnel plot analysis, horizontal pleiotropy was detected using Mr-Egger-intercept, and sensitivity analyses were performed using the "leave-one-out" method. In the second part, the biological functions and mechanisms of anoikis in sepsis were investigated based on R-analysis downloaded from the GEO database. Resuts The body mass index(BMI), hip circumference(HC), and waist circumference (WC) were risk factors for sepsis. The core ARDEGs SERPINB1, MERTK and CEACAM8 were significantly up-regulated in sepsis and showed good diagnostic efficacy. The risk model based on ARDEGs showed good potential for clinical application. SERPINB1 may be involved in the regulation of inflammatory responses in sepsis through the NLRC4/CASP1-inflammatory effects signaling pathway. Conclusion There is a causal association between obesity and sepsis and obesity is a risk factor for sepsis. The anoikis genes SERPINB1, MERTK and CEACAM8 are potential diagnostic targets for sepsis. And SERPINB1 may be involved in the regulation of inflammatory effects in sepsis through the NLRC4/CASP1- inflammatory effects signaling pathway.
Integrative taxonomy of Janirella (Isopoda: Asellota: Janirellidae), with descriptions of two new species and an amended classification of the genus
Authors: Ohta Mizuki , Kakui Keiichi , Kojima Shigeaki , Shimomura Michitaka
Published: September 2024

We describe two new Janirella species, Janirella scutum sp. nov. and Janirella spinoscutum sp. nov., collected at depths of 2893–3176 m on the landward slope of the Japan Trench, northwestern Pacific. These species differ from congeners in having an ovoid body with dorsal spines on each pereonite; the pleotelson with two pairs of short and one pair of long lateral projections; and the posterior projection on the pleotelson shorter than pleotelson length. They differ from one another in the number and size of dorsal spines on the pereonites. We determined partial sequences for the cytochrome c oxidase subunit I (COI) gene for the two new species and seven other Janirella species and constructed a COI-based maximum-likelihood tree of Janirella. In the tree, the subgenus Parjanirella was monophyletic but embedded within a paraphyletic group of species in the subgenus Janirella. Based on this result, we propose the elimination of subgenus ranks in Janirella.
Structural Perceptual Local Feature Pattern
Authors: Xu Jie , Deng Yizhi , Chen Jianping
Published: September 2024

This paper introduces a novel feature extraction technique, named Structural Perceptual Local Feature Pattern (SPLFP). The SPLFP method integrates Fechner's law into a compact encoding scheme, aiming to mimic the human perception of external stimuli and extract features from images that conform to human visual habits. At the same time, under the framework of the famous Petersen graph, SPLFP extracts spatial structure information from four different directions within the 5×5 neighborhood of each pixel. The effectiveness of SPLFP and its single-scale methods, SPLFPv and SPLFPh, were rigorously evaluated on several face data sets. The results demonstrated that SPLFP and its single-scale methods exhibit remarkable performance, consistency, and stability across all tested datasets. This indicates that SPLFP enables the extraction of highly discriminative features, positioning it as a strong candidate for face classification tasks.
A developmental classification system for the comparison of Puya raimondii giant Andean rosettes
Authors: Suni Mery , Vadillo Giovana , Prado Gerson , Tumi Liscely , Ramsay Paul Michael
Published: September 2024

Puya raimondii Harms, an endangered giant bromeliad, has great ecological and cultural significance in the Central Andes. To help studies of population size structure in this species, this study aims to develop a rapid classification system based on plant developmental stages instead of using absolute size measurements, and applies it to three areas in or near Huascarán National Park, Peru. Plant height, stem height, total and photosynthetically-active rosette diameter and height to the base of the rosette were measured, to illustrate how the developmental stages compare, along with estimates of vegetation, rocks, and bare ground. Five plant developmental stages were identified in the study: juvenile, subadult, adult, reproductive adult, and senescent reproductive adult. The juvenile stage could, in future, be further divided into smaller, vulnerable plants and more established juveniles, but this requires more detailed study to determine appropriate distinguishing developmental criteria. Comparing locations, Puya plants in Queshque, were smaller than in the other locations, across all developmental stages. However, the environmental variables recorded in this study could not explain this difference, indicating the importance of other, unknown factors. This study provides an efficient and informative classification system for P. raimondii giant rosettes, using well-defined developmental stages, that can reveal important differences between populations and prompt the generation of new hypotheses about the ecology of these important plants. The classification system could be applied in populations across the species’ distributional range in the Central Andes to explore how age, size and environmental factors affect growth and development in this species.
Elucidating the binding specificity of interactive compounds targeting ATP binding cassette subfamily G member 2 (ABCG2)
Authors: Ray Pawan , Kumari Indu , Prasad Rajendra , Ray Shashikant , Banerjee Atanu , Prakash Amresh
Published: September 2024

The ATP-binding cassette (ABC) transporter superfamily plays a pivotal role in cellular detoxification and drug efflux. ATP binding cassette subfamily G member 2 (ABCG2) referred to as the Breast cancer resistance protein (BCRP) has emerged as a key member involved in multidrug resistance displayed by cancer cells. Understanding the molecular basis of substrate and inhibitor recognition, and binding within the transmembrane domain of ABCG2 is crucial for the development of effective therapeutic strategies. Herein, utilizing state-of-the-art molecular docking algorithms and molecular dynamic (MD) simulations, substrates and inhibitors molecular binding with ABCG2 are defined, distinctly. We performed extensive virtual screening of Drugbank to identify the potential candidates, and MD simulations of docked complexes were carried out in POPC lipid bound membrane. Further, the binding affinities of compounds were estimated by free binding energy employing MM-GBSA. Docking results show three compounds, Docetaxel > Tariquidar > Tezacaftor having highest binding affinities (> 12.00 Kcal/mol) for ABCG2. Remarkably, MM-GBSA results suggest the most stable binding of Tariquidar with ABCG2 as compared to the other inhibitors. These results provide valuable insights into the key residues that may govern substrate/inhibitor recognition, shedding light on the molecular determinants influencing substrate specificity, transport kinetics and ABCG2-mediated drug efflux. Hence, Tariquidar could serve as a potential candidate for the design of highly efficient inhibitors targeting ABCG2 in breast cancer therapy.
Experimental Study on the Effects of Water Retaining Agents in Ecological Substrates on Soil Properties
Authors: Yang Xuanyu , Wang Yong
Published: September 2024

With the deepening of sustainable development concepts, vegetation protection has become the primary method for highway slope protection and has seen widespread application. Among these, the type and properties of substrate materials significantly affect the protective effectiveness, making it a core issue in vegetation protection. In arid regions, where rainfall is scarce and evaporation rates are high, water retention becomes a key focus in the study of ecological substrates. This study, focusing on the semi-arid regions of the Northern Hemisphere, investigates the effects of varying water-retaining agent content on soil water retention and mechanical behavior through laboratory evaporation tests and triaxial compression tests. By examining crack development during the evaporation process, the study reveals the micro-mechanisms by which water-retaining agents influence soil properties. The findings are as follows: (1) Water-retaining agents can effectively reduce the evaporation rate, with higher contents leading to slower evaporation and stronger soil water retention capacity; (2) The agents have little effect on the overall strength of the soil but primarily alter the soil’s deformation behavior, reducing cohesion while having minimal impact on the internal friction angle; (3) The hydrological properties of soils containing water-retaining agents are unstable and prone to cracking under dry conditions. Therefore, the content of water-retaining agents should be carefully calibrated according to the geotechnical properties of the protective slope, and in the early stages of ecological protection, surface evaporation prevention measures should be implemented to avoid surface cracking.
Genome wide association analysis revealed novel candidate genes for body measurement traits in indigenous Gudali and crossbred Simgud in Cameroon
Authors: Matenchi Youchahou Poutougnigni , Hegarty Matthew , Baștanlar Evren Koban
Published: September 2024

Background: The genetics of Central African cattle have not been well-explored in terms of their potential for improved productivity. We therefore performed a genome wide association analysis (GWAS) on a total of 856 animals genotyped with the GGP Bovine 100K array, to identify genes or genomic regions of importance in body measurements in a local zebu (Gudali) and its crossbreed with the European Simmental (Simgud), using mixed linear model (MLM).
Results: SNP-based heritability of the four body traits under study varied between 0.23 ± 0.12 for the height at wither (HAW) to 0.44 ± 0.11 for the sacrum height (SH). The genetic correlation ranged from 0.19 ± 0.14 between HAW and ear length (EL), to 0.81 ± 0.06 between HAW and SH. For the phenotypic correlation, the ranges were 0.58 ± 0.00 between body length (BL) and EL to 0.90 ± 0.06 between HAW and BL. The maximum LD was 0.465 for Gudali and decreased by half (0.23) at a distance of 50,708 bp, while for the Simgud population the maximum LD was 0.47 and decreased to half (0.23) at 99,201 bp. Interestingly, we observed long ranges of LD throughout the Gudali and Simgud genome up to more than 1 mbp distant. These features are of great potential interest in association analysis and genetic improvement initiatives. We identified 59 SNPs associated to body traits. These SNPs were mapped within or near some 189 genes throughout the genome, with the CDCA2, EBF2, ADGRD1, NDUFAF1, DPPA4 and DPPA2 genes showing a pleiotropic effect since they were found associated with 2 or more traits.
Conclusions: This study identified a number of novel genes/loci associated with pathways influencing growth and body traits, disease resistance and immunity, reproduction and milk production. Overall, the identified genes could be considered as candidate genes in any attempt to improve growth, disease resistance and production in tropical cattle managed under extensive conditions. These genes or genomic regions should be targeted for any future cattle breeding in Cameroon.
Identifying Key Predictive Variables in Medical Records Using a Large Language Model (LLM)
Authors: Veigulis Zachary P. , Ware Anna D. , Hoover Peter J. , Blumke Terri L. , Pillai Malvika , Yu Li , Osborne Thomas F.
Published: September 2024

EHR systems are widely used, but leveraging their unstructured clinical notes for insights has been challenging. Large Language Models (LLMs) can offer scalable, precise extraction of pertinent information from clinical notes. This paper presents a novel framework for using LLMs to derive medical insights from EHRs, demonstrated through an assessment on female infertility within the Veterans Health Administration (VHA), combining unstructured and structured data for enhanced analysis.
Seasonal variations in net ecosystem exchange of CO 2 and conservation of water use efficiency of cotton in the Mississippi Delta
Authors: Anapali Saseendran , Bhandari Ammar B. , Adireddy Rajanna , Reddy Krishna N.
Published: September 2024

Accurately quantifying the net ecosystem exchange of CO2 (NEE) is a critical prerequisite for developing alternative farm management strategies to enhance carbon sequestration in biological systems and reduce greenhouse gas emissions. A two-year study quantified the NEE of CO2 from cotton (Gossypium hirsutum L.) on silty clay in farm-scale fields using an eddy covariance approach (EC). On a seasonal scale, NEE and evapotranspiration (ET) were 8,836 kg CO2 ha− 1 and 367 mm, respectively, in 2017, and 10,759 kg CO2 ha− 1 and 430 mm, respectively, in 2018. Harvested cotton lint yields were 1,269 and 1,569 kg ha− 1 in 2017 and 2018, respectively. The water use efficiency (WUE) for lint production (WUElint) and ecosystem level WUE for NEE (WUENEE) across the two seasons was nearly constant. WUElint were 3.5 kg lint ha− 1 mm− 1 and 3.6 kg lint ha− 1 mm− 1, respectively, in 2017 and 2018, and WUENEE were 24 kg CO2 ha− 1 mm− 1 and 25 kg CO2 ha− 1 mm− 1. The NEE and WUE measured in this study can be used as a benchmark for comparing carbon sequestration potential in cotton production. However, further research is needed to understand NEE responses to long-term climate variability and to develop climate-smart crop-soil management strategies.
Assessment of Knowledge, Attitude and Practice towards Obesity among Medical Students in Jalalabad City, Afghanistan
Authors: Sherzad Abdul Ghafar , Shinwari Muhibullah , Zahirzai Mohammad Sediqe , Jabarkhil Abdul Nasir , Azimee Mohammad Azim , Mulavizada Habibullah , Zeng Qingchun
Published: September 2024

Background
Obesity is a global public health concern affecting individuals of all ages, sexes, and socioeconomic groups. It is generally linked to a greater risk of disability. Therefore, the present study aimed to determine the knowledge, attitudes, and practices of medical students toward obesity in Jalalabad city, Afghanistan.
METHODS
This institution-based, cross-sectional survey was conducted with 463 public and private medical university students in Jalalabad city, Afghanistan, from June 2023 to September 2023. The study participants were chosen via a nonprobability convenience sampling technique, and data were collected through structured questionnaires completed by all participants.
RESULTS
In this study, a total of 463 participants were enrolled. A total of 86.2% of them were male, and 13.8% were female. The majority (98.9%) had heard of term obesity. Body mass index (BMI) is the technique most commonly used to identify obesity. Ninety-five percent of the respondents were aware that obesity leads to cardiovascular diseases and diabetes mellitus. The participants’ attitudes toward obesity were satisfactory. Obesity was viewed as a disease by 86.6% and weight loss as a necessity by 99.1% of the participants. Only 24.6% of the respondents believed that obesity was inherited and could not be reduced. Among the respondents, 23.8% walked every day, and 28% participated in sports. Over half (53.6%) of the participants had never attempted to lose weight, and 43.2% reported eating junk food on a daily basis.
CONCLUSION
Most participants were aware of obesity and agreed that obesity is a serious health problem; however, they had inadequate practices compared with their knowledge and attitudes.
MLLM4Rec : Multimodal Information Enhancing LLM for Sequential Recommendation
Authors: Yuxiang Wang , Xin Shi , Xueqing Zhao
Published: September 2024

In recent years, With the advent of large language models (LLMs) such as GPT-4, LLaMA, and ChatGLM, leveraging multimodal information (e.g., images and audio) to enhance recommendation systems has become possible. To further enhance the performance of recommendation systems based on large language models (LLMs), we propose MLLM4Rec, a sequence recommendation framework grounded in LLMs. Specifically, our approach integrates multimodal information, with a focus on image data, into LLMs to improve recommendation accuracy. By employing a hybrid prompt learning mechanism combined with role-playing for model fine-tuning, MLLM4Rec effectively bridges the gap between textual and visual representations, enabling text-based LLMs to "read" and interpret images. Moreover, the fine-tuned LLM is utilized to rank retrieval candidates, thereby maintaining its generative capabilities while optimizing item ranking according to user preferences. Extensive experiments were conducted on three publicly available benchmark datasets to evaluate the proposed method. The results demonstrate that MLLM4Rec outperforms traditional sequence recommendation models and pre-trained multimodal models in terms of NDCG, MRR, and Recall metrics.
AutoML-based workflow for reliable DOE selection and reference studies for analyzing imprecise experimental data with machine learning
Authors: xu xukuan , li donghui , bi jinghou , Moeckel Michael
Published: September 2024

Design of experiments (DOE) is an established method to allocate resources for efficient parameter space exploration.Model-based active learning (AL) data sampling strategies have shown potential for further optimization. This paper introduces a workflow for conducting DOE comparative studies using automated machine learning. Based on a practical definition of model complexity in the context of ML, the interplay of systematic data generation and model performance is examined considering various sources of uncertainty: this includes uncertainties caused by stochastic sampling strategies, imprecise data, suboptimal modeling, and model evaluation. Results obtained from electrical circuit models with varying complexity show that not all AL sampling strategies outperform conventional DOE strategies, depending on the available data volume, the complexity of the dataset, and data uncertainties. Trade-offs in resource allocation strategies, in particular between identical replication of data points for statistical noise reduction and broad sampling for maximum parameter space exploration, and their impact on subsequent machine learning analysis are systematically investigated. Results indicate that replication-oriented strategiesshould not be dismissed but may prove advantageous for cases with non-negligible noise impact and intermediate resource availability.
A framework for integrating genomics, microbial traits, and ecosystem biogeochemistry
Authors: Riley William , Li Zhen , Marschmann Gianna , Karaoz Ulas , Shirley Ian , Wu Qiong , Bouskill Nicholas , Chang Kuangyu , Crill Patrick , Grant Robert , King Eric , Saleska Scott , Sullivan Matthew , Tang Jinyun , Varner Ruth , Woodcroft Ben , Wrighton Kelly , Brodie Eoin
Published: September 2024

Microbes drive the biogeochemical cycles of earth systems, yet the long-standing goal of linking emerging genomic information, microbial traits, mechanistic ecosystem models, and projections under climate change has remained elusive despite a wealth of emerging genomic information. Here we developed a general genome-to-ecosystem (G2E) framework for integrating genome-inferred microbial kinetic traits into mechanistic models of terrestrial ecosystems and applied it at a well-studied Arctic wetland by benchmarking predictions against observed greenhouse gas emissions. We found variation in genome-inferred microbial kinetic traits resulted in large differences in simulated annual methane emissions, quantitatively demonstrating that the genomically observable variations in microbial capacity are consequential for ecosystem functioning. Applying microbial community-aggregated traits via genome relative-abundance-weighting gave better methane emissions predictions (i.e., up to 54% decrease in bias) compared to ignoring the observed abundances, highlighting the value of combined trait inferences and abundances. This work provides the first example of integrating microbial functional trait-based genomics, mechanistic and pragmatic trait parameterizations of diverse microbial metabolisms, and mechanistic ecosystem modeling. The generalizable G2E framework will enable use of abundant microbial metagenomics data to improve predictions of microbial interactions in many complex systems, including oceanic microbiomes.
Interactive connections between the claustrum and lateral parabrachial nucleus participate in the regulation of nociceptive information and accompanying negative emotions
Authors: Li Yun-Qing , Qiu Xin-Tong , Ren Xiao , Zhou Lu-Xi , Ye Xiao-Ni , Gong Tao , Li Yi-Yao , Li Fei , Pan Lv-La , Xing Ke-Ke , Chen Tao , Li Hui , Huang Fensheng , Zhang Ming-Ming
Published: September 2024

The claustrum (CLA) is a widely connected brain area associated with pain sensation, but the underlying mechanism remains elusive. Here, we demonstrate that the activation of CLA vesicular glutamate transporter-2 (VGluT2) neurons promotes nociceptive and anxiety-like behaviors, whereas parvalbumin (PV) neurons in the core of the CLA inhibit the functional activity of VGluT2 neurons. Morphologically, the VGluT2 neurons in the shell of the CLA reciprocally communicate with the VGluT2 neurons in the lateral parabrachial nucleus (LPB). Manipulation of the LPBVGluT2–CLAVGluT2 pathway, LPBVGluT2–CLAPV pathway and CLA–LPB glutamatergic pathway results in bidirectional modulation of pain and emotions. Pharmacogenetic activation of the LPBVGluT2–CLAVGluT2–LPBVGluT2 circuit facilitates nociception and negative emotions, and vice versa, alleviates hyperalgesia and anxiety-like behaviors. These findings illuminate that the CLA plays a vital role in pain perception and emotional impacts and provide crucial insight to help researchers unveil the functions of the CLA.