bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Impact of Agricultural Science and Technology Innovation on Global Food Supply Chain —An Empirical Analysis Based on Panel Data from 68 Food Producing Countries
Authors: Li Shengzhu , Yang Dan 
Published: November 2024

Abstract

With the frequent occurrence of geopolitical, economic and military conflicts in the world, the supply chain security of the global food industry chain is facing serious challenges. In this paper, global food supply chain security(FSCS) is divided into two dimensions: food supply chain dependence and food supply chain concentration, based on cross-country panel data of 68 food-producing countries around the world from 2001 to 2021, firstly, to analyze the global food security situation, and then, based on constructing indexes to measure the agricultural scientific and technological innovation, to empirically estimate empirical estimation of the agricultural scientific and technological innovation(ASTI) capacity impact on global food supply chain security. The results of the study show that agricultural science and technology innovation capacity has a negative impact on both food supply chain concentration and food supply chain dependence; on the whole, the improvement of agricultural science and technology innovation capacity can bring about a decrease in global food supply chain concentration and dependence.
Portable In-Field DNA Sequencing for Rapid Detection of Pathogens and Antimicrobial Resistance: A Proof-of-Concept Study
Authors: Pillay Stephanie , Calderón-Franco David , Abeel Thomas 
Published: November 2024

Abstract

Purpose
Infectious diseases represent a major global health threat due to the rapid spread of pathogens, leading to widespread outbreaks. Concurrently, antimicrobial resistance (AMR) is increasing, making standard treatments less effective and complicating infection management. Effective surveillance systems are essential to address these challenges. Methods: We conducted a proof-ofconcept study to evaluate a portable in-field microbial lab against a traditional molecular lab for DNA isolation, sequencing, microbial detection, antibiotic resistance gene identification, and plasmid classification. Samples from lake water, wastewater treatment plant sludge, and retail meat were selected to reflect relevant surveillance vectors. This approach provides valuable data for environmental monitoring, public health, and food safety, aiding in outbreak preparedness. We compared results using five metrics: DNA yield and purity, read N50, taxonomic classification, antibiotic resistance gene identification (ARGs), and plasmid classification. Results: Our study found that metagenomic bacterial DNA isolation from environmental and food sources is feasible with portable lab technology, producing ≥ 800ng of DNA, suitable for Nanopore sequencing. DNA from retail meat, lake, and sludge samples resulted in similar read numbers and read N50 values. Taxonomic classification was achieved at the genus and species levels. A Jaccard similarity of over 50% was observed in the top 20 most abundant species between chicken samples, and lake samples. ESKAPE pathogens were detected in chicken and lake samples. ARGs and plasmids were also identified in both retail meat and lake samples. Conclusion: This study demonstrates that in-field DNA isolation and sequencing are feasible with minimal equipment, yielding results comparable to traditional lab methods.
Proteome-wide assessment of 10,000 plasma proteins with age-related diseases and multi-morbidity in a Chinese population
Authors: Bennett Derrick , Wright Neil , Yao Pang , Iona Andri , Clarke Jonathan , Wang Baihan , Mazidi Mohsen , Chan Kahung (Peter) , Clarke Charlotte , Im Pek Kei (Becky) , Kakkoura Maria , Kartsonaki Christiana , Rahmati Maryam , Hill Michael , Millwood Iona Y , Fry Hannah , Du Huaidong , Yang Ling , Chen Yiping , Avery Daniel , Yu Canqing , Lv Jun , Sun Dianjianyi , Li Liming , Clarke Robert , Chen Zhengming 
Published: November 2024

Abstract

Blood-based proteomics can help improve risk prediction and elucidate biological pathways underlying the development of age-related diseases and multi-morbidity. We assessed the associations of ~10,000 plasma proteins, assayed using Olink and SomaScan platforms, with all-cause mortality, 14 incident diseases and multi-morbidity among 2026 Chinese adults. Cox regression yielded hazard ratios for disease risks associated with specific proteins, after adjusting for confounders and multiple testing. Overall, 984 and 761 proteins were significantly associated with all-cause mortality and multi-morbidity respectively, with top proteins mostly involved in regulating immune responses, inflammation, and cell survival. For all-cause mortality, protein-based risk prediction models outperformed conventional risk factors (C-statistics: 0.825 [0.796-0.853] vs 0.806 [0.774-0.838]) and adding proteins to conventional risk factors improved net reclassification index by 32% (17-47%). Our results illustrate that, regardless of specific proteomic assay platform used, plasma proteins could be used to improve risk prediction and inform prevention and treatment of age-related diseases.
Genome-wide identification and characterization of Calcium-Dependent Protein Kinase (CDPK) gene family in autotetraploid cultivated alfalfa (Medicago sativa subsp. sativa) and expression analysis under abiotic stresses
Authors: Han Bingcheng , Dong Xueming , Shi Congcong , Wang Zhaoming , Chen Jiwei , Li Pengzhen , Yan Wei , Zhou Qiang , Liu Zhipeng , Yan Longfeng 
Published: November 2024

Abstract

Background
Calcium-dependent protein kinases (CDPKs), play multiple roles in plant development, growth and response to bio- or abiotic stresses. Calmodulin-like domains typically contain four EF-hand motifs for Ca²⁺ binding. The CDPK gene family can be divided into four subgroups in Arabidopsis, and it has been identified in many plants, such as rice, tomato, but has not been investigated in alfalfa yet.
Results
In our study, 38 non-redundant MsCDPK genes were identified from the “XinJiangDaYe” alfalfa genome. They can be divided into four subgroups which is the same as in Arabidopsis and Medicago truncatula, and there were 15 MsCDPK proteins in CDPK I, 12 in CDPK II, 10 in CDPK III and only one MsCDPK in group IV. RNA-seq analysis revealed tissue-specificity of 38 MsCDPK genes. After researching the transcriptome data, we found these 38 MsCDPK members responsive to drought, salt, and cold stress treatments. Further analysis showed that the expression of almost all the MsCDPKs is regulated by abiotic stresses. In addition, we chose MsCDPK06, MsCDPK35, MsCDPK20 and MsCDPK07 for RT-qPCR validation which was from CDPK I-IV subgroups respectively. The result showed that the expression of these four genes were significantly induced by drought, salt and cold treatments. The subcellular location experiment showed that these four proteins were all located in nucleus.
Conclusion
In our study, we identified 38 distinct MsCDPK genes within the alfalfa genome, which were classified into four groups. We conducted a comprehensive analysis of various gene features, including physicochemical properties, phylogenetic relationships, exon-intron structures, conserved motifs, chromosomal locations, gene duplication events, cis-regulatory elements, 3D structures, and tissue-specific expression patterns, as well as responses to drought, salt, and cold stresses. These results also provide a solid foundation for further investigations into the functions of MsCDPKs aimed at improving drought tolerance in autotetraploid cultivated alfalfa through genetic engineering.
Low degree of domestication can be an indicator of high potential of biological invasion
Authors: Marciniak Brisa , Dechoum Michele S. , Levis Carolina , Lemes Gustavo , Peroni Nivaldo 
Published: November 2024

Abstract

The degree of domestication can influence the ability of introduced species to survive and reproduce. Species with higher degrees of domestication are highly dependent on humans for survival and reproduction. On the other hand, lower degrees may result in lower survival rates and reproduction output. However, the interrelationship between degrees of domestication and plant invasion remains underexplored. We focused our study on plant species native to the Americas with distinct degrees of domestication, with fruits used for human consumption, to test the hypothesis that plants with intermediate degrees of domestication show higher invasion potential than plants with lower or higher degrees of domestication. We calculated an invasion potential index as the ratio between the number of checklists where an introduced species was recorded as invasive and the total number of checklists where it was registered as introduced. Our results show a negative non-linear relationship between the degree of domestication and invasion potential. While species with intermediate degrees of domestication show higher invasion potential than those fully domesticated, species with the lowest degrees of domestication showed the highest invasion potential. These findings suggest that full domestication does not eliminate invasion risk, highlighting the complexity of the relationship between domestication and invasion. Our results provide valuable insights to support public policies, inform future studies on plant invasions, and the need for management strategies that consider different degrees of domestication.
Seismic Performance Assessment and Retrofitting Recommendations for a Historic Masonry Building: The Case of Amasya Çilehane Complex
Authors: Sözen Şahin 
Published: November 2024

Abstract

Cultural continuity can be ensured by protecting and strengthening historical buildings, part of the world's cultural heritage. Protection of these buildings from damage caused by destructive earthquakes can only be achieved by accurately predicting their structural behavior. Amasya Çilehane Complex, the focus of this study, has a unique place among the historical buildings, which are an essential component of the cultural heritage of the civilizations that have left their mark on history. This study evaluates the complex's seismic performance, consisting of a mosque, a special worship space (in Turkish tevhidhane), a tomb, a sheik’s room, and ordeal rooms. For this purpose, non-linear static, modal, and non-linear time history analyses were performed. The time history analysis reveals that the structure's lateral load capacity corresponds to 30% of its total weight. Considering the elastic design spectrum curve of the structure, it is seen that the structure can be subjected to an acceleration above 1.2g for the design earthquake with a 10% probability of exceedance in 50 years. Non-linear time history analyses showed that the structure would suffer severe damage and could wholly or partially collapse. This study also presents effective retrofitting methods for historic masonry structures, highlighting the necessity of retrofitting the Amasya Çilehane Complex using appropriate methods found in the literature.
The effect of glucose and lipid control on sperm parameters: An analysis of 7291 semen samples
Authors: Leybovitz-Haleluya Noa , Cohen Ram , Gutvirtz Gil , Har-Vardi Iris , Zeadna Atif , Steiner Naama 
Published: November 2024

Abstract

Introduction: The prevalence of diabetes mellitus (DM) continue to increase. DM is known to have adverse effects on male sexual function. We studied the impact of DM on seminal fluid and sperm parameters.
Methods: A retrospective, case-control study including semen samples from patients 18 – 65 years of age. Patients with azoospermia, those undergoing hormonal treatment or post-chemotherapy or radiotherapy were excluded. All samples were analysed using Makler counting chamber for the parameters: sperm concentration, semen volume, , motile sperm and morphology according to World Health Organization (WHO) guidelines. Diagnoses of DM and impaired fasting glucose (IFG), body mass index (BMI) and the level of high density lipoproteins (HDL) were retrieved from patients’ computerized medical records. Multivariate modelling for oligozoospermia and asthenozoospermia was undertaken using generalized linear mixed models (GLMMs) with adjusted for age, BMI and smoking.
Results: A total of 7,291 semen samples: 336 from DM patients, 276 from men with IFG and 6,679 from patients with normal glycemia. Using the WHO cutoff parameters, we found that men with DM have statistically significant higher rates of low seminal fluid volume (hypospermia), asthenozoospermia and teratozoospermia as compared to men with IFG or normal glucose levels. Using a multivariate model, we DM was an independent risk factor for hypospermia and teratozoospermia (aOR 1.57, 95% CI 1.18-2.10, p=0.002 and aOR 1.68, 95% CI 1.23-2.27, p=0.001, respectively).
Conclusion: DM adversely affect sperm parameters. Men should be advised on the harmful effects of abnormal glucose levels as it may impact their compliance
Confronting the Economic Burden of Diabetes: Can TCM DRG Payment Reform in China Offer a Viable Solution? Insights from Empirical Research in Western China
Authors: Chen Mengen , Yu Jing , Xia Shiji , Wang Yuhan , Wang Yan , Yuan Youshu , Zhang Xiaoxi , Sun Henong , Jia Xuan , Wu Guoping , Wang Jiayi , Cong Tianzhen , Kong Fanxin , Hou Haojia , Yang Jingyu , Wang Zhiwei 
Published: November 2024

Abstract

Background
Diabetes poses a major global public health challenge, carrying significant economic implications worldwide. In China, the ongoing implementation of Diagnosis Related Groups (DRG) payment reforms, especially within Traditional Chinese Medicine (TCM) contexts, is critical in improving diabetes patient care and alleviating associated economic burdens.
Methods
We examined 2,804 hospitalized diabetes patients at Qingyang City Hospital of Chinese Medicine in Gansu Province from 2017 to 2022. Using univariate and interrupted time-series (ITS) analyses, we compared patient visit data, healthcare-related costs, and length of stay pre- and post-DRG reform.
Results
Following DRG reform at Qingyang City Hospital of Chinese Medicine, significant differences were noted in patients’ gender, age, visit times, type of diabetes, complications and comorbidities, use of Chinese medicine diagnostic and therapeutic equipment, and surgeries and operations, compared with the pre-reform period (P < 0.05). Post-reform, there was a noteworthy decrease in hospitalization cost and Western medicine cost, and TCM treatment cost (P < 0.05), while Chinese medicine cost remained stable but the overall cost level increased (P > 0.05). Additionally, there was a slight reduction in length of stay after the reform, although this change did not reach statistical significance (P > 0.05).
Conclusions
DRG reform significantly reduces hospitalization cost, TCM treatment cost, and Western medicine cost for diabetes patients in TCM hospitals. However, its impact on Chinese medicine cost and length of stay is limited. Future reforms should capitalize on the unique strengths of TCM treatment, enhance cost management strategies, and focus on minimizing length of stay and medical expenses while ensuring effective patient care.
ESW-YOLO: A lightweight YOLO model for defect detection in bottled liquor
Authors: Wang Xuyang , Lan Xuerui , Liu Lijun 
Published: November 2024

Abstract

With the growing adoption of deep learning in AI, flaw detection in bottled liquor production has become crucial to ensure product quality and consumer satisfaction. However, existing flaw detection models often face issues of low efficiency, particularly in multi-category and multi-target scenarios, and struggle with integration into resource-constrained devices. To solve these challenges, this study proposes ESW-YOLO, a lightweight model optimized to detect diverse flaws in bottled liquor production. This model is designed as follows: firstly, the Efficient Multi-Branch \& Scale FPN (EMBSFPN) is developed to reduce model size while increasing the detection accuracy of small flaws. Secondly, the SE attention mechanism is incorporated to emphasize critical features, which strengthens the model’s robustness in complex scenarios. Thirdly, the Wise-IoU loss function is used to optimize localization accuracy, particularly for irregular defects. Finally, a lightweight shared convolutional detection head (ESCD) is proposed to further decrease model size and improve detection efficiency. Experimental results on a bottled liquor flaw detection dataset demonstrate that ESW-YOLO achieves a mean average precision (mAP) of 94.7% and a recall of 91.8%. Additionally, the proposed model reduces computational cost by 30.8%, decreases parameter count by 45.1%, and maintains a compact model size of only 3.6 M. This method can provide a reference for the development of defect detection methods in bottled liquor.
Dynamic stability of high-efficiency quantum dot light-emitting diodes
Authors: Li Hongbo , Liu Xiaonan , Gao Yan , Li Bo , Yue Yansong , Wei Jing , Wu Zhenhui , Liu Fangze , Shen Huaibin 
Published: November 2024

Abstract

Quantum dot light-emitting diodes (QD-LEDs) hold great potential for enabling ultra-clear and ultra-bright displays technologies. Although the operational lifetime of QD-LEDs under static conditions has reached commercial standard, their dynamic stability, i.e., performance consistency while being switched on and off, remains largely behind that of state-of-the-art III-V LEDs. In this work, we studied the degradation mechanism of red QD-LEDs with high external quantum efficiency (EQE) and long static operational lifetime and found that the accelerated EQE decline is mainly due to the fast-increasing electron leakage into the organic hole transport layer (HTL) under continuous voltage scans. To improve the dynamic stability of QD-LEDs, we refined the structure of CdZnSe/ZnSe QDs by introducing a ZnSeS/ZnS outer shell, where the ZnS shell improves the electron confinement and the ZnSeS mitigates the lattice mismatch between ZnSe and ZnS. Consequently, the electron leakage into the HTL is significantly inhibited, leading to QD-LEDs with minimal EQE drop of less than 4% after more than 5,000 voltage cycles within the range between 0 V and 4.5 V, while the devices still possess excellent static stability for maintaining 95% of its initial luminance (T95) at 1,000 cd m-2 for over 61,000 h.
Taguchi Method Analysis of Layer Thickness, Printing Orientation, and Heat Treatment Effects on FDM Printed PLA Impact Strength
Authors: A.S. Shagul , E Poovannan 
Published: November 2024

Abstract

Optimizing process parameters to enhance the impact strength of polylactic acid (PLA) products remains a hard task in fused deposition modeling (FDM), a widely used 3D printing technology. The objective of this study is to identify the most effective process parameters for achieving the highest impact strength of PLA components produced by FDM printing. This study employed the Taguchi L9 orthogonal array approach to improve the process parameters for PLA produced using FDM. We utilized the Izod impact test to quantify the impact strength. We methodically altered and evaluated various factors such as layer thickness, printing orientation, and heat treatment. The theory posited that specific combinations of printing settings would yield increased impact strength. Based on the results, the best conditions for getting the highest impact strength of 534.8571 J/m were a layer thickness of 0.08 mm, the material being upright, being heated to 80°C, and being bent 65 degrees. These conditions resulted in little deformation. Conversely, even with a layer thickness of 0.08 mm and a heat treatment at 100°C, a vertical alignment resulted in inadequate impact resistance. The study emphasizes the critical role of printing orientation in achieving greater impact strength in 3D-printed PLA. It shows that orientation has a more significant impact than layer thickness and temperature. This discovery is essential for maximizing material performance efficiency in real-world applications.
Development of a Distributed and Scalable Testbed for UAVs using Reinforcement Learning
Authors: Mahmood Jawad , Raja Muhammad Adil , Loane John , Caffery Fergal Mc 
Published: November 2024

Abstract

The aim of this project is to develop a Testbed for designing and training Multi-agent Reinforcement Learning (RL) algorithms for cooperative and self-organizing Unmanned Aerial Vehicles (UAVs). The main purpose of the development of a scalable and distributed testbed based on Multi-agent RL algorithms is to enable UAVs to make decisions using real-time data and perform tasks autonomously. In this project, a novel testbed is developed that allows the integration of different Multi-agent RL algorithms with a flight simulator. This testbed supports UAVs that learn to fly and coordinate together in the simulated environment to accomplish the objective of target tracking. It employs novel techniques that enable faster learning and higher performance as compared to conventional Multi-agent RL methods. FlightGear is the flight simulator used in this project. This testbed can be used to train control models for a wide variety of use cases. As a proof of concept, a problem is formulated regarding target tracking of UAVs. The tracking aircraft follows the path of the target aircraft. Both tracking and target aircraft are controlled by different Multi-agent RL models and fly on a common flight simulator. This testbed can also scale up the number of tracking aircraft and can be distributed to several systems.