bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transferable polychromatic optical encoder for neural networks
Authors: Majumdar Arka , Choi Minho , Xiang Jinlin , Wirth-Singh Anna , Baek Seung-Hwan , Shlizerman Eli 
Published: January 2025

Abstract

Artificial neural networks (ANNs) have fundamentally transformed the field of computer vision, providing unprecedented performance. However, these ANNs for image processing demand substantial computational resources, often hindering real-time operation. In this paper, we demonstrate an optical encoder that can perform convolution simultaneously in three color channels during the image capture, effectively implementing several initial convolutional layers of a ANN. Such an optical encoding results in ~24,000 times reduction in computational operations, with a state-of-the art classification accuracy (~ 73.2%) in free-space optical system. In addition, our analog optical encoder, trained for CIFAR-10 data, can be transferred to the ImageNet subset, High-10, without any modifications, and still exhibits moderate accuracy. Our results evidence the potential of hybrid optical/digital computer vision system in which the optical frontend can pre-process an ambient scene to reduce the energy and latency of the whole computer vision system.
A High-Precision Machine Learning-Based Prediction Model for Delayed Graft functon(DGF) in Chinese Kidney Transplant Patients: A Multicenter Study
Authors: Cheng Ying , sun he , sun ping , ding zheng , wang xi , he long , ma ke xin , wang gang , li jing yun , Wang Kangchun , yu zitong , zhang weichen , gu tianxiang 
Published: January 2025

Abstract

Delayed graft function (DGF) is a severe complication following kidney transplantation, and currently, there is a lack of accurate prediction tools tailored for the Chinese population. This study integrates data from 1,093 kidney transplant cases across four medical centers in China (2016–2024) to develop and validate a machine learning-based model for DGF prediction. By comparing nine machine learning algorithms, we found that the LightGBM model performed best in external validation (AUC = 0.80, accuracy = 0.73). SHAP analysis identified donor GFR, donor hemoglobin, and recipient plasma BNP levels as the primary predictive factors, while also highlighting novel predictors such as donor microscopic hematuria and APTT. Cox regression analysis showed that preoperative dialysis duration in recipients (HR = 1.006, 95% CI: 1.001–1.012) was an independent predictor of DGF recovery. In the follow-up study, we observed that while the DGF mortality group exhibited the most significant kidney function impairment (serum creatinine β = 200.57, eGFR β = -39.91), the prognosis of the DGF survival group was comparable to that of the non-DGF survival group. Additionally, the duration of DGF (16.66 ± 13.73 vs. 15.44 ± 14.62 days) and the number of dialysis treatments (8.13 ± 7.39 vs. 7.78 ± 7.22 sessions) were not significantly associated with prognosis. Based on these findings, we developed an online prediction platform (www.kidney-dgf-match.cn) to support clinical decision-making. This study not only establishes the first high-precision DGF prediction model for the Chinese population but also reveals the potential for favorable outcomes in DGF patients with proper management, offering new insights for optimizing post-transplant management strategies.
Amino acid pathways are central for defense in Arabidopsis revealed by time-resolved, integrated multi-omics analysis
Authors: Sasse Joelle , Joller Charlotte , Schlaeppi Klaus 
Published: January 2025

Abstract

Plants respond to biotic stress by altering transcription and metabolism. While the temporal dynamic of transcriptional changes in immune-stimulated plants is established, little is known about spatio-temporal metabolic changes. Here, we investigate immune-stimulated Arabidopsis thaliana shoot, root, and root exudate metabolite profiles in a time-resolved manner. Roots and shoots exhibited comparable metabolite changes upon immune stimulation, with various metabolites increasing. First metabolite changes occurred after 1.5 hours and persisted for 3 days. Exudate responses occurred within 4 hours and diminished for pulse-treated but persisted for continuously treated plants. Many chemical classes responded to immune-stimulation: defense compounds (phenylpropanoids) increased within hours, and amino acids preceded this increase at 1.5 h in shoots, roots, and exudates. Transcriptome analysis at 4 h and 1 d and integrated, multi-omic analysis of transcription and metabolome supported the role of aromatic and aliphatic amino acids as central players preceding defense responses.
How do machines learn? Evaluating the AIcon2abs method
Authors: Queiroz Rubens Lacerda , Lima Cabral , Sampaio Fábio Ferrentini , Lima Priscila Machado Vieira 
Published: January 2025

Abstract

This study is an expansion of a previous work aiming to evaluate the AIcon2abs method (AI from Concrete to Abstract: Demystifying Artificial Intelligence to the general public), an innovative method aimed at increasing the public (including children) understanding of machine learning (ML). The approach employs the WiSARD algorithm, a weightless neural network known for its simplicity, and user accessibility. WiSARD does not require Internet, making it ideal for non-technical users and resource-limited environments. This method enables participants to intuitively visualize and interact with ML processes through engaging, hands-on activities, as if they were the algorithms themselves. The method allows users to intuitively visualize and understand the internal processes of training and classification through practical activities. Once WiSARD's functionality does not require an Internet connection, it can learn effectively from a minimal dataset, even from a single example. This feature enables users to observe how the machine improves its accuracy incrementally as it receives more data. Moreover, WiSARD generates mental images representing what it has learned, highlighting essential features of the classified data. AIcon2abs was tested through a six-hour remote course with 34 Brazilian participants, including 5 children (8–11 yo), 5 adolescents (12–17 yo), and 24 adults (21–72 yo). Data analysis was conducted from two perspectives: a mixed-method pre-experiment (including hypothesis testing), and a qualitative phenomenological analysis. Nearly 100% of participants rated AIcon2abs positively, with the results demonstrating a high degree of satisfaction in achieving the intended outcomes. This research was approved by the CEP/HUCFF/UFRJ Research Ethics Committee.
A one-pot method for universal Dengue virus detection by combining RT-RPA amplification and CRISPR/Cas12a assay
Authors: Zhang Yunkai , Xiang Yan , Hou Dengyong , Fang Liben , Cai Shuqi , Zhang Jianping , Wang Yujia , Jiang Yuyu , Liu Bin , Bai Jie , Ding Yue , Fang Jingjing , Chen Shuanghong , Liu Xingguang , Ren Xiaomeng 
Published: January 2025

Abstract

Dengue Virus (DENV) is a severe life-threatening virus to human, which is the major cause for dengue fever. However, the efficiency of traditional detection methods unable to meet the additional requirements in clinic practice, including the virus isolation method, ELISA, RT-PCR and qRT-PCR and so on. Therefore, a rapid, simple, and accurate diagnostic for DENV is highly desired. In the current study, we developed a novel method for universal DENV detection via introducing recombinase polymerase amplification (RPA) assay and Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) and associated (Cas) protein 12a (CRISPR/Cas12a) system in one-pot, achieving the extremely sensitivity and specificity for DENV. The whole detection assay can be finished within 40 min without the requirement for sophisticated equipment. The limit of detection (LoD) was 91.7 copies per test. All the recombinant plasmid of these four serotypes of DENV (I to IV) were successfully identified by using present one-pot DENV universal RT-RPA CRISPR/Cas12a detection system. As for specificity, a total of 22 DENV positive samples were successfully identified, and no-cross reactions were observed in 4 other interferes nuclear acid samples. Moreover, we also established the universal DENV RT-RPA-CRISPR/Cas12a- lateral flow dipstick (LFD) platform and all the four serotypes of DENV (I to IV) were successfully identified, reaching the sensitivity of about 250 copies/test. Together, our present method not only provided an alternative approach for universal DENV detection but also gained a novel insight for other virus identification.
The Prophylactic Effect of Ficus carica Nanoparticles on C57BL/6 Female Mice Infected with Schistosoma mansoni
Authors: El-Attar Naira Adel , El-Sawi Mamdouh Rashad , El-Shabasy Eman Ahmed 
Published: January 2025

Abstract

Schistosomiasis has re-spread again lately in Africa including Egypt according to World Health Organization in 2023. Bilharziasis is an endemic disease that causes damage to the lungs, gastrointestinal, and liver. Praziquantel (PZQ) is the most effective commercial treatment for all Schistosoma species, although it cannot cause total death after infection besides being ineffective against larvae and eggs. The thesis aimed to study the prophylactic effect of Ficus carica leaves extract nanoparticles (F. carica-NPCs), silver nanoparticles (Ag-NPCs), and in combination (F. carica-Ag NPCs) against Schistosoma mansoni infected mice. Schistosomiasis could cause hepatic injury which showed decrease in GSH, SOD and CAT (antioxidants) and an increase in oxidative stress marker MDA in comparison with the negative control group. It caused increase in inflammatory markers such as CRP, IL-6, VCAM-1 and ICAM-1 in comparison to healthy control group. It elevated P53, Bax, cytochrome C, caspase 9, 3 otherwise Bcl-2 as apoptotic & anti-apoptotic markers in comparison with negative control group. Comet tail length and tail DNA showed significant DNA damage in infected mice compared to healthy control. Finally, hepatic cell membrane leak out occurred leading to increase in serum ALT, AST, ALP, ɤ-GT, and bilirubin unlike albumin as liver function parameters compared with the negative control group. The F. carica-NPCs, Ag-NPCs, and F. carica-Ag NPCs recorded significant amelioration in previous markers compared with the infected-untreated group. The F. carica-NPCs, Ag-NPCs, and F. carica-Ag NPCs had anti-schistosomal and hepatoprotective effects in comparison with the positive control group. The F. carica-Ag NPCs observed a better prophylactic effect than other groups.
Short-term nutrient addition improves soil organic carbon accumulation in tropical forest
Authors: Su Tian-yan , Jiang Ya-min , Chen Hua-ying , Wang Ying , Yang Qiu , Li Jia-ling , Lu Jing-li , Ran Hong-yu , Yang Huai , Liu Wenjie , Fang Meng-yang , Huang Liang-hong 
Published: January 2025

Abstract

Background and Aims: Highly weathered tropical forests are widely recognized as nitrogen (N)-rich and phosphorus (P)-poor, and the input of nutrienteffects soil carbon (C) cycling and storage in these ecosystems. In topsoil, short-term nutrient additionmay not only effect soil organic C (SOC) pools directly, but also impact soil C cycling and conversion process indirectly through altering soil microbial C use efficiency (CUE). However, the effects of short-term nutrient addition on soil C accumulation mechanisms remain unclear. The aim of this study was to clarify the mechanisms of SOC responding to short-term nutrient addition.
Methods: This study conducted a one-year N and P additions experiment in the tropical forest of Hainan, China. The SOC, soil C fractions (POC and MAOC), microbial biomass, enzyme activities, and physicochemical properties at depths of 0–10 cm, 10–20 cm and 20–40 cm were measured.
Results: The results showed that short-term nutrient addition increased SOC (8.91–20.03%), POC (6.65–24.90%), and MAOC (8.74–19.89%) in the topsoil (0–10 cm and 10–20 cm), whereas no significant changes occurred in the subsoil (20–40 cm). The results of Pearson’s correlation analysis revealed that litter biomass and CUE were significantly positively correlated with SOC. The partial least squares-path model showed that short-term nutrient addition influences the SOC by altering physicochemical properties and microbial characteristics.
Conclusions:These results suggested that the short-term nutrient addition increased SOC through increased soil properties and decreased microbial activities. Such information could provide insight to understand the effects of nutrient addition on soil C pool in tropical forest.
Automated Email Spam Classifier Application Using Python Flask, Machine Learning and Selenium Tool
Authors: Eppakayala Sathvik , Ankula Shiva Kumar Goud 
Published: January 2025

Abstract

We have created an email spam classifier using Naïve Bayes in machine learning and designed a user interface using Python Flask. Recently, we got the idea to prepare a model that automatically classifies spam emails. To achieve this, we used the Selenium tool to grab our emails from the mail folder, test them with our Flask application, and then classify them into spam and ham. Remember, this whole process is automated. Initially, we created the pickle model using Naïve Bayes and deployed it into a Python Flask application. Then, we created a Selenium automated algorithm that works continuously. However, each part of our project will be defined step-by-step in detail. We have also created an algorithm, which is attached in this article. Finally, we have achieved the desired results and are still researching ways to improve the model.
Understanding Community Perceptions, Preparedness, and Expectations of Preconception Care: A Formative Research Approach
Authors: Misra Swati , Mahajan Kamlesh , Gawai Mohini , Raut Abhishek V. , Varma Poonam , Paradkar R. J. , Jain Shuchi , Gupta Subodh S. , Garg B. S. 
Published: January 2025

Abstract

Objective: The study explores community perceptions, preparedness, and expectations regarding preconception care (PCC). It evaluates the acceptance of nurses delivering PCC services, the efficiency of a community-based PCC package, and community readiness for village-level PCC services, aiming to co-develop a tailored PCC package.
Methods: This formative research employed a qualitative approach, including focus group discussions (FGDs), in-depth interviews (IDIs), and free listing and ranking exercises. Conducted in 96 villages across four Primary Health Centres in rural Maharashtra, the study involved diverse participants, including eligible couples, village representatives, and community health workers. Data were analyzed using thematic content analysis, employing both deductive and inductive methods to identify themes related to perceptions, contributions, and expectations for PCC.
Results: The study revealed gaps in community awareness of PCC, including genetic screening and early detection. Despite this, members emphasized PCC’s benefits, such as improved maternal health and safer deliveries, showing strong support for accessible clinics with local involvement. Unique priorities like health screening, family wellbeing, and lifestyle modifications enriched PCC, reflecting a holistic approach.
Conclusion: The findings highlight the community's readiness to adopt PCC services, provided they are affordable, accessible, and tailored to local needs. The study underscores the importance of culturally sensitive approaches and leveraging community networks to promote PCC. Integrating locally prioritized areas into PCC frameworks can enhance maternal and child health outcomes and ensure effective implementation in resource-limited settings.
Risk Factors, Prevention and Control Programs, and Prevalence of Diabetes in Indoniesia – District Association
Authors: Machfutra Eka Denis , Wahidin Mugi , Wardani Yurika Fauzia , Kusuma Dian , Riyadina Woro , Sitorus Nikson , Letelay Alfons Maryono 
Published: January 2025

Abstract

Aims: The study aimed to examine the relationship between several risk factors as well as prevention and control programs with Diabetes prevalence at district level in Indonesia.
Methods: This study used a cross-sectional study design and performing descriptive, Pearson Correlation, and multivariate linear regression analysis. Secondary data was collected from the Ministry of Health and National Insurance Body involving 241 districts aggregate data. The risk factors included in the study were overweight, obesity, central obesity, sweet food consumption, sweet beverage consumption, fatty food consumption, lack of fruit and vegetable consumption, lack of physical activity, smoking, and hypertension. The prevention and control programs included NCD Post (Posbindu), village running Posbindu, examination of Posbindu, Pandu PHC, chronic disease program (Prolanis), routine checking blood glucose, Minimum standard service (SPM) of Diabetes services and adult screening.
Results: There was a difference in the prevalence of Diabetes between districts and cities (p-value <0.001) and difference across seven regions in Indonesia (p-value <0.001). There were 15 variables associated with Diabetes prevalence (R2 0.606), 5 of which had significant association, namely central obesity (p 0,018; Beta 0.027), fatty food consumption (p 0.015; Beta 0.006), smoking (p 0.002; Beta -0.034), Prolanis (p 0.001; Beta 0.899), and routine of blood glucose checking (p 0,000; Beta 0.279).
Conclusions: Several risk factors and programs associated with Diabetes prevalence at district level in Indonesia.
The Role of Natural Resource Wealth and National-Level Economic Forces in Energy Poverty Intensity in African Economies
Authors: Aladejare Samson Adeniyi 
Published: January 2025

Abstract

Despite the overwhelming natural resource endowments and economic progression of Africa, the continent happens to be the world’s poorest energy source in terms of availability, affordability, and accessibility of energy for basic human needs. Consequently, this paper examined the contributions of natural resource rents and homogenous economic factors to energy poverty intensity in 26 African countries between 1990 and 2023. Methodologically, the method of moments quantile regression approach was employed in deriving the study’s main inferences. Also, the dynamic common correlated estimation technique was applied for robustness. Empirically, the paper demonstrated that in African economies with relatively high levels of energy poverty intensity, resource endowments have a weak effect in propelling the former. However, natural resource rents are more important to exacerbate energy poverty in African countries with relatively more moderate energy poverty severity than those with low intensity. As a national-level economic factor, while income has an insignificant effect irrespective of energy poverty intensity in the African economies, public outlay substantially aggravates across all energy poverty intensity classifications by the same magnitude. However, infrastructure development reduced energy poverty more in economies with relatively low energy poverty severity, followed by moderate and high-intensity nations. Also, population growth’s adverse impact was most dominant in the low-energy-poverty-intense countries, followed by the medium- and high-energy-poverty-severe economies. Applicable policy measures were proposed by the study.
JEL Classification: O13, O55, Q43.
A Study on Clinical Outcomes of Septic Shock Patients Receiving Intravenous Vitamin C
Authors: Fareedullah Mohammed , Panga Shanmuka Nagaraju , Ahmed Mohammed Haseeb , Arif Afaaf , Razzak Mohammed Munaf Ur , Haq Mohammed Misbah Ul , Almas Juveria 
Published: January 2025

Abstract

Background
Sepsis is a severe condition resulting from a dysregulated immune response to infection, often leading to organ failure and high mortality rates. Septic shock, the most severe form, has a mortality rate of 25–40% despite standard treatments.
Aim
To evaluate the impact of intravenous vitamin C on improving clinical outcomes in septic shock patients. This study aims to assess the effectiveness of high-dose intravenous vitamin C as a supplementary therapy in patients with septic shock.
Methods
A prospective, interventional study was conducted on 50 septic shock patients in the critical care unit (CCU) of a multispecialty hospital in Hyderabad, India. Patients were randomly assigned to two groups: the test group received intravenous vitamin C, while the control group received standard care. Data collected included demographics, comorbidities, infection source, blood culture results, vasopressor use, length of CCU stay, and MAP levels. SOFA and APACHE II scores were calculated before and after treatment. Data analysis was done using Microsoft Excel and SPSS version 26.
Results
The test group showed improvement in clinical outcomes, including reduced 30-day mortality, better APACHE II and SOFA scores, shorter ICU stays, and decreased vasopressor duration compared to the control group.
Conclusion
Intravenous vitamin C may help resolve septic shock more rapidly. However, due to the study’s small sample size and short duration, further research is needed to confirm the benefits of vitamin C in managing septic shock.
Population Changes and Healthcare Delivery in Ebonyi State, Nigeria
Authors: Arochukwu Agatha , Ike Felix , Adewoyin Adelowo Adefisayo , Eludoyin Adebayo 
Published: January 2025

Abstract

This study investigates the population dynamics of healthcare delivery in Ebonyi State, Nigeria, emphasising gender disparities, spatial distribution, and the accessibility of basic health facilities, employing Geographic Information Systems (GIS) for analysis. The research reveals that Izzi, Onicha, Ikwo, and Ohaukwu Local Government Areas (LGAs) collectively account for over 40% of the state's population. Demographic data indicates a 2.8% annual population growth across the 13 LGAs from 2006 to 2022, with Ivo LGA, the least populated, representing approximately 4.6% of the state's population. The GIS analysis indicates that 81.1% of the population resides within 60 minutes of a primary healthcare centre (PHC), though accessibility varies significantly, especially in rural areas. The gender distribution shows an overall balance with 49% males and 51% females; however, LGAs such as Izzi and Ikwo exhibit a higher proportion of females than males. These findings underscore the necessity for targeted healthcare interventions, including equitable resource allocation, enhancement of PHC facilities, and the provision of gender-sensitive services such as maternity and pediatric care. The GIS-based accessibility mapping highlights the importance of incorporating spatial analysis into healthcare planning to identify underserved areas and optimise resource allocation. This study provides essential data for developing population-centered, spatially aware, and sustainable healthcare policies in Ebonyi State, thus serving as a valuable resource for international health researchers and policymakers.