bluuebunny/crossref_metadata_2025_split huggingface dataset:
Changes in the healthfulness of food and beverage purchases from 2006 to 2022 in formal, mixed, and informal outlets in Mexico
Authors: Domínguez-Barreto Ana Paula , Farah Irene , López-Olmedo Nancy , Perez-Ferrer Carolina , Ramírez-Toscano Yenisei , Langellier Brent A , Colchero M Arantxa , Rivera-Dommarco Juan A , Barrientos-Gutiérrez Tonatiuh , Stern Dalia 
Published: November 2024

Abstract

Background
To better inform retail food environment policies in the global south, it is necessary to further understand the healthfulness of food and beverages purchased by type of food outlet over time.
Methods
Using repeated cross-sectional data from the National Income and Expenditure Survey (ENIGH) in Mexico (2006 to 2022), we categorized food outlets as formal (supermarkets, chain convenience stores), informal (street markets, street vendors, acquaintances), fiscally mixed (public markets, small neighborhood stores, specialty stores), and others. We estimated the proportion of total purchases in each food outlet and the percentage of the types of foods purchased by outlet for the overall sample and stratified by education level and urbanicity.
Results
In 2006, the food outlets with the largest proportions of ultra-processed foods purchases were chain convenience stores (49%), small neighborhood stores (37%) and supermarkets (35%). In contrast, the outlets with the highest proportions of minimally processed food purchases were street markets (83%), public markets (81%), and specialty stores (75%). Over time, households improved the proportion of expenditure in minimally processed foods in supermarkets and slightly in small neighborhood stores (49 to 54% and 46 to 47%, respectively). Conversely, the proportion of expenditures in minimally processed foods decreased from 70 to 62% in street vendors. Households without formal education and residing in rural localities increased their minimally processed food purchases in specialty stores, but decreased in street vendors, acquaintances and public markets. Households with higher education and residing in more urbanized areas increased their purchases of minimally processed foods in supermarkets and small neighborhood stores and decreased in street vendors. These households also increased in ultra-processed foods in chain convenience stores.
Conclusions
Over time, purchases from informal outlets were healthier compared to purchases from the formal and mixed sectors, but no outlet sold only healthy or unhealthy foods. To ensure access to healthy foods, food policies should consider where the largest proportion of food purchases is being made, where the healthiest and unhealthiest purchases are, and why some purchases from certain food outlets are becoming healthier, while in others they are becoming less healthy.
Complete genome sequence of a novel iflavirus from wheat sawfly (Dolerus tritici)
Authors: Guo Jiashu , Liu Wenwen , Chen Chen , Francis Frederic , Wang Xifeng 
Published: November 2024

Abstract

Little is known about the commensal viruses in wheat sawfly, Dolerus tritici, which is an important agricultural insect feeding on wheat leaves. Here, we identified a novel single positive-strand RNA virus from the larvae of wheat sawfly collected in northern China through RNA sequencing, and then determined its complete genome sequence by rapid amplification of cDNA ends. The complete genome consists of 9,594 bp in size including a poly A tail at 3′ terminus, which is predicted encoding a 326.3 kD polyprotein. The phylogenetic tree analysis of deduced polyprotein revealed that this RNA virus was clustered in the clade with deformed wing virus in genus Iflavirus, family Iflaviridae. The full genome of this RNA virus shows 38.9-50.0% sequence identities with other iflaviruses. Sequence identity at the amino acid level of coat proteins shows this RNA virus has highest identity with slow bee paralysis virus at 33.6%, which no more than 90% suggesting that it is a new member in the genus Ifavirus. Thus, we tentatively designated as “Dolerus tritici iflavirus 1” (DtIV1). According to our knowledge, this is the first report of the commensal virus in wheat sawfly.
Rapid Detection of Soybean Nutrient Deficiencies Using YOLOv8s: Advancing Precision Agriculture
Authors: Jeong Minsoo , Park Sihyun , Kwon Sook-Min , Lim KyeongMo , Jung Da-Ryung , Lee Hong-Seok , Kim Hei Jung , Shin Jae-Ho 
Published: November 2024

Abstract

Early detection of nutrient deficiencies is crucial for optimizing crop yields and ensuring sustainable agricultural practices. This study presents a novel application of the YOLOv8s object detection model for identifying nitrogen, phosphorus, and potassium deficiencies in soybean plants. Employing a unique dataset from a long-term nutrient-deficient field maintained for over 40 years, we trained and evaluated the model on 6,020 red, green, and blue images of soybean leaves exhibiting nutrient stress conditions. The YOLOv8s model achieved exceptional performance, with a mean average precision (mAP@0.5) of 99.18% during training and 98.51% for validation. Precision rates for individual nutrient deficiencies ranged from 90.03–96.54%, with highly accurate potassium deficiency detection. The model demonstrated robust generalization across diverse field conditions, processing images in 3.46 ms each, making it suitable for real-time applications. This research significantly advances the field of precision agriculture by providing a fast, accurate, and scalable method for detecting early nutrient deficiency in soybean crops, potentially revolutionizing fertilizer management practices and contributing to more sustainable farming systems.
FocusNet: Multi-Scale Parallel CNN Model with an Attention-Based Feature-Fusion Technique
Authors: Mehta Akash , Paul Rahul , Setua Sanjit Kumar 
Published: November 2024

Abstract

FocusNet is a new Multi-Scale Parallel CNN model. The model is a parallel backbone architecture with a self-attention mechanism. The attention-based feature-fusion technique averages out the parallel backbone's feature maps. This model introduces the desirable properties of ViT into the CNN architecture. We validate the working of FocusNet by conducting extensive experiments on the CIFAR-10 Dataset. We display that the induction of self-attention in the model's backbone and our attention-based feature-fusion technique dramatically improve the model's accuracy.
TNMD in pan-cancer analysis: Exploring its impact on immune modulation and uncovering functional insights in colorectal cancer
Authors: Chen Jingfeng , Hu Qin , Zhang Cong , Guan Bihua , Wang YiFan , Zhang Min , Li Xia , Chen Biao , Zeng Lulu , Chen Minjiang , Wu Bing , Wang Jianping , Yang Yang , Ji Jiansong 
Published: November 2024

Abstract

Background
Tendomodulin (TNMD) is pivotal in various malignancies, including colorectal cancer (CRC). However, its comprehensive impact across cancers, particularly its immunomodulatory function in CRC, remains underexplored. This study explored the role of TNMD in CRC by focusing on its immunomodulatory functions through comprehensive molecular and clinical analyses.
Methods
Multiple bioinformatics databases and analytical tools were utilized for the TNMD in pan-cancer analysis. To validate the role of TNMD in CRC, we performed experiments, including immunofluorescence (IF), immunohistochemistry (IHC), real-time quantitative reverse transcription PCR (qPCR), Western blotting, and cell migration assays.
Results
TNMD expression and gene mutation vary across cancers and offer high diagnostic value. Survival analysis has found that TNMD is associated with prognosis in multiple cancers. Notably, in patients with high microsatellite instability (MSI-H) CRC, TNMD expression correlated positively with various immune cells, particularly natural killer (NK) cells, whereas it was inversely correlated with regulatory T cells (Tregs). Crucially, in patients with microsatellite stability (MSS) CRC, high TNMD expression was associated with better immunotherapy outcomes, indicating its potential as a biomarker for patient stratification and tailored treatment approaches. Furthermore, single-cell sequencing data revealed stronger interactions between TNMD-positive tumor cells and fibroblasts or macrophages in the tumor microenvironment. Finally, TNMD was overexpressed in CRC tumor tissues and cell lines, thereby promoting invasion and metastasis.
Conclusions
Our findings reveal a critical immunomodulatory role of TNMD in CRC, particularly in influencing tumor–immune interactions. Beyond its potential diagnostic and prognostic biomarker, TNMD promotes CRC metastasis and invasion, thus emerging as a promising therapeutic target. These findings highlight TNMD's significance in CRC and potentially other malignancies.
Factors on Affecting Engagement of Physical Activity: Anderson Behaviour Model
Authors: Badarali Mishbahuddin , Rungsihirunrat Kanchana 
Published: November 2024

Abstract

Indonesia's national policy on non-communicable diseases focuses on modifying health behaviours. The implementation of this policy faces significant challenges, particularly in promoting physical activity. This study aims to examine factors influencing physical activity engagement, using three factors of the Anderson Behavioural Model as independent variables, while the dependent variable is engagement in the recommended 150 minutes of physical activity per week. Key factors associated with physical activity included age, awareness, and motivation to engage in physical activity. Lower engagement was observed in males, and Muslims. Enabling factors such as flexible work schedules, availability of public sports facilities, and community empowerment for communal physical activity also significantly influenced physical activity engagement. Need factors, including BMI and regular health check-ups, were not significantly associated. Strengthening the national NCD policy requires raising awareness of healthy living initiatives, providing accessible venues for physical activity, and empowering communities to engage in group activities.
Dual Clinical Practice (DCP) policy to improve the Retention of Human Resources for Health in Rwanda: A mid-term review using a cross-sectional and retrospective study design
Authors: Kayumba Kizito , Ntihabose Corneille , Musange Sabine , Ngabo Bernard , Irakiza Piero , Rubuga Felix K. , Umutoni Nathalie , Kalisa Ina Rukundo , Birindabagabo Pascal , Rwamasirabo Emile , Kayibanda Emmanuel , Mukundirukuri Patience , Absolomon Gashaija , Dhanani Sumana , Condo Jeanine 
Published: November 2024

Abstract

Background
Despite the high demand for public services globally, ensuring the quality of services provided by public health facilities is challenging. Poor remuneration from public sector health care providers (HCPs) drives their migration to private health facilities. The Dual Clinical Practice (DCP) Policy in Rwanda represents a strategic initiative aimed at retaining healthcare professionals in public health facilities, allowing them to engage in private practice concurrently. This study assesses the implementation challenges and identifies opportunities for potential reformulation of DCP schemes.
Methods
This study employed a mixed methods approach, incorporating both cross-sectional and retrospective designs across six Rwandan public hospitals. Quantitative and qualitative data were collected through key informant interviews (KIIs) and joint interviews (JIs), as well as through the analysis of health facility records obtained from the Health Management Information System (HMIS) and the Electronic Medical Record (EMR). Qualitative data were analyzed using Atlas.ti software, while quantitative data were analyzed using Microsoft Excel.
Results
The study involved participants from six Rwandan hospitals, including 20 healthcare providers and 32 patients. Qualitative results revealed that a substantial majority of health care providers supported the DCP policy, with a high patient satisfaction rate of 81% regarding DCP services. However, challenges emerged, including limited awareness of the policy and difficulties in tracking DCP engagements. Quantitative data from the HMIS and EMR indicated an increase in patient enrollment across most facilities, with DCP outpatient visits accounting for a significant percentage of total visits in some hospitals. While the DCP contributed positively to hospital revenues, concerns about the sustainability of the scheme and the adequacy of health care remuneration were highlighted, calling for a review of DCP policy involving stakeholders beyond the Ministry of Health.
Conclusion
This paper underscores the need for a multifaceted approach involving tax authorities, hospital administrations and health insurance companies to address the challenges identified. Ultimately, there is a pressing need for collaborative efforts to revise policies and enhance physical infrastructure, balancing healthcare quality with provider retention. This study provides valuable insights applicable to addressing similar global healthcare challenges.
Throughput enhancement of High-Bandwidth Wireless Network using Deep Double Q-Network Algorithm
Authors: Wang Chengman , Aljohani Abeer , Khan Fazlullah 
Published: November 2024

Abstract

In high-bandwidth network environments, multiple users and devices frequently share similar high-frequency bands, but signal propagation limitations lead to unstable network links. These can affect the throughput of high-bandwidth wireless networks, reducing the continuity and efficiency of data transmission. Therefore, this paper constructs a high-bandwidth wireless network throughput performance enhancement model based on the Double Deep Q-Network algorithm (Double DQN). This method designs a mathematical model for high-bandwidth wireless networks, visually presents node connections using undirected graphs, and constructs a throughput performance enhancement model based on channel allocation and link scheduling by combining interference model analysis. In addition, this method introduces the Double DQN algorithm, integrates the reinforcement learning framework, and realizes dynamic adjustment of optimal channel allocation and link scheduling strategies through continuous interaction and learning between the agent and the environment. Experimental results confirm that this model significantly improves the throughput of high-bandwidth wireless networks to above 2500kb/s and reduces the call drop rate of voice and video network services to 0.01–0.02%, meeting the demand for high data continuous transmission.
TaIncBC: Topic-aware In-context Prompt with Bias Calibration for Event Causality Identification
Authors: Xiang Wei , Zhan Chuanhong , Du Xu , Wang Bang 
Published: November 2024

Abstract

Event Causality Identification (ECI) is to determine whether there exists a causal relation between two event mentions. Recently, the prompt learning paradigm has been applied in the ECI task to leverage a large-scale pre-trained language model through carefully designed prompts, yet their contexts do not describe causal relations. In this paper, we propose to include some topic-aware demonstration samples with their ground-truth labels into the query prompt to form an in-context input prompt, so as to facilitate PLM’s understanding and comprehending of universal causal relations. Although including demo samples into prompts may enrich in-context causality information, care must be taken for potential bias that could also be introduced into the event prediction model by such demo samples. To address this challenge, we further design a nearest neighbour-based bias calibration to help alleviating demonstration deviations for our topic-aware in-context prompt learning. Our model, called TaIncBC, is experimented on the widely used EventStoryLine and Causal-TimeBank corpus and results validate our design objective in terms of significantly performance improvements over the state-of-the-art algorithms.
Vacuum Electrospray Deposition for Face-on Orientation and Interface Preservation in Organic Photovoltaics
Authors: Lee Younjoo , Jeong Junkyeong , Jung Kwanwook , Lee Jeihyun , Youn Yungsik , Park Soohyung , Lee Hyunbok , Yi Yeonjin 
Published: November 2024

Abstract

Despite recent advancements in organic photovoltaics (OPVs), further improvements in power conversion efficiency (PCE) and device lifetime are necessary for commercial viability. Strategies such as optimizing the molecular orientation and minimizing the charge traps of organic films are particularly effective in enhancing photovoltaic performance. In this study, we successfully utilized vacuum electrospray deposition (VESD) to achieve favorable face-on stacking geometries while preserving the integrity of the interfaces in poly(3-hexylthiophene-2,5-diyl) (P3HT):[6,6]-phenyl-C61-butyric acid methyl ester (PCBM) bulk heterojunction (BHJ) films. Unlike conventional spin-coated (SC) P3HT:PCBM BHJ films, which predominantly exhibit an edge-on orientation, VESD facilitates a beneficial face-on orientation, improving vertical charge transport through enhanced π-π stacking interactions. Furthermore, VESD effectively eliminates residual solvents during film formation, ensuring well-defined interfaces between the layers in the OPV devices. As a result, the VESD OPVs demonstrated enhanced PCE and extended operational lifetimes compared to their SC counterparts. Impedance spectroscopy analysis confirmed that the VESD OPVs possessed significantly higher electron mobility and longer electron lifetimes, indicating reduced charge traps and improved charge dynamics. These results highlight the potential of VESD as a versatile technique for controlling molecular orientation in solution-processable organic semiconductors, enabling the development of highly efficient devices with fewer charge traps without relying on synthetic or epitaxial methods.
Global Optimization for Road Traffic Accident
Authors: Kussia Bulbula Kumeda , ALWAN Ghanim , HUSSAIN Sadiq , ASSEFA Maregu , BORA Pranjal Kumar 
Published: November 2024

Abstract

The exponential growth in road traffic accidents worldwide is resulting in severe difficulties in every scene of human life. The paper builds a reliable optimization frame to find the global minimum injury severity versus 20 attributes. A new method to find optimal values for the nonlinear frame of road traffic accidents was implemented here. To design and construct a reliable simulated model to improve the quality of the road traffic accident optimization process by using an advanced optimization technique. Even though the solving problems of non-linear optimization configuration were solved in some cases. The programming for solving optimization problems for 20 attributes is complicated; especially for integer constraints. Advanced work will be needed to achieve this task. Optimization aims to discover the values of a model's variables that produce the best value for the objective function, subject to any limiting conditions placed on the variables. The complexity of integer programming was solved based on good formulating of the integrated optimization model and the selection of a suitable matrix of constraints to avoid sharp changes for optimal results. Our experimental results show that Impactype (X8) and Invtype (X9) are still effective and sensitive attributes for injury severity.
Opportunities and Constraints for Urban Broiler Production in Harare, Zimbabwe
Authors: Mafigu Takudzwa , Charambira Takudzwa , Hodzi Pride 
Published: November 2024

Abstract

Urban broiler production in Harare has the potential to grow and contribute largely to the growth of Zimbabwe’s poultry industry. However, the firm is not characterized. This research aimed to characterize broiler production in Harare and provide evidence-based recommendations for sustainable urban broiler production, considering its importance. A multi-stage sampling approach was used to get the respondents who produced broilers. The respondents were then interviewed using a semi-structured questionnaire. The results showed that women dominated (56.82%) urban broiler production. The average age of respondents was 36.21 years. Local authorities did not bother respondents, except for just 1% of respondents who encountered complaints from neighbors. Resources like day-old chicks (DOC), feeds, veterinary medicine, and vaccines were readily available from local companies and agents. Three-phase feeding was mostly preferred (72.73) to two-phase feeding (27.27%) systems. Broiler batch sizes differed significantly (p < 0.05) across the three residential suburbs included in the study. Spent bedding and chicken manure were used to fertilize the backyard gardens (51.14%), dumped as litter (40.91%), or sold (7.95%). About 92% of the respondents used Information Communication and Technology (ICT) tools to market broilers. Respondent's homes (54.12%), local shops (18.88%), restaurants (17.21%), schools (5.69%), and supermarkets (4.10%) were the market channels for broilers in Harare. Almost all respondents (99%) expressed interest in expanding their enterprises. The challenges reported were all related to a lack of financial and technical support. Supportive policies could unlock the potential of urban broiler production in Harare
Material discovery of secondary and natural cementitious precursors
Authors: Mahjoubi Soroush , Venugopal Vineeth , Manav Ipek , Azarijafari Hessam , Kirchain Randolph , Olivetti Elsa 
Published: November 2024

Abstract

Cement production contributes to over 6% of global greenhouse gas (GHG) emissions, driven by clinker’s energy-intensive production and limestone calcination. Substituting clinker with cementitious substitutes is an effective strategy for decarbonization. However, typical clinker substitutes---coal fly ash and ground granulated blast furnace slag---face current and future supply constraints. Here we systematically map reactivity variations and expand the repertoire of secondary and natural cementitious precursors. Large language models extract chemical compositions and material types of 14,000 materials from 88,000 academic papers. A multi-headed neural network predicts the degree of cementitious reactivity and pozzolanicity. Subject to performance constraints, current supply allows for substituting half of global cement production with construction and demolition wastes and municipal solid waste incineration ash, reducing the global GHG emissions by 3%---equating to removing 260 million vehicles from the roads in United States. Discovered natural cementitious precursors, including rhyolite, dacite, and gabbro, are distributed globally and show significant potential as raw substitutes for clinker.
Advanced Neural Analysis for Ransomware Detection Through Dynamic Network Signature Mapping
Authors: Dale Jeremy , Staehli Quentin , Goodspeed Elbert , Marchand Clifford , Koenig Stefan 
Published: November 2024

Abstract

Dynamic Network Signature Mapping (DNSM) is introduced as a novel and advanced approach for detecting ransomware threats through adaptive, real-time analysis of network traffic patterns. Utilizing an integrated framework of convolutional and recurrent neural networks, DNSM captures spatial and temporal dependencies within network data, enabling precise classification of ransomware activities even under encrypted or high-volume conditions. Unlike traditional, signature-based methods, DNSM constructs a dynamic and evolving threat profile that reduces the need for manual updates, thereby improving adaptability to emerging ransomware techniques. Empirical results from the study validate DNSM’s ability to maintain high detection accuracy and low false positive rates across a spectrum of network environments, while demonstrating efficient real-time performance critical for high-stakes operational contexts. The modularity of DNSM, coupled with its automated threat scoring and pattern recognition capabilities, establishes it as a resilient solution that addresses the demands of modern ransomware detection, offering a scalable, resource-effective alternative for proactive network security.