bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and Research of an Online Diagnosis Platform for Tomato Seedling Facilities Production Diseases
Authors: Jin Xin , Zhu Xiaowu , Ji Jiangtao , Li Mingyong , Xie Xiaolin , Zhao Bo 
Published: July 2023

Abstract
The facility-based production method is an important stage in the development of modern agriculture, lifting natural light and temperature restrictions and helping to improve agricultural production efficiency. To address the problems of difficulty and low accuracy in detecting pests and diseases in the dense production environment of tomato facilities, an online diagnosis platform for tomato plant diseases based on deep learning and cluster fusion was proposed by collecting images of eight major prevalent pests and diseases during the growing period of tomatoes in a facility-based environment. The diagnostic platform consists of three main parts: pest and disease information detection, clustering and decision making of detection results, and platform diagnostic display. Firstly, based on the YOLOv5 algorithm, the key information of the disease was extracted by adding attention module (CBAM), multi-scale feature fusion was performed using weighted bi-directional feature pyramid network (BiFPN), and the overall construction was designed to be compressed and lightweight; Secondly, a K-means clustering algorithm is used to fuse with the deep learning results to output pest identification decision values to further improve the accuracy of identification applications; Finally, a web-side pest detection platform was designed and developed using Python, including the front-end, back-end, and database of the system to realize online diagnosis and interaction of tomato plant diseases and pests. The experiment shows that the algorithm detects tomato plant diseases and insect pests with mAP of 92.7% (mAP@0.5), weights of 12.8M, inference time of 33.6ms. Compared with the current mainstream single-stage detection series algorithms, the improved algorithm model has achieved better performance; The accuracy rate of the platform diagnosis output disease information of tomato images is 91.2%, and the accuracy rate of video disease information is 95.2%.
Therapeutic Effects of Gingival Mesenchymal Stem Cells and Their Exosomes in a Chimeric Model of Rheumatoid Arthritis
Authors: Bruckner Shane , Capria Vittoria M , Zeno Braden , Leblebicioglu Binnaz , Goyal Kanu , Vasileff William K , Awan Hisham , Willis William L , Ganesan Latha P , Jarjour Wael N 
Published: July 2023

Abstract
Background
Rheumatoid arthritis is a chronic systemic autoimmune disease that involves transformation of the lining of synovial joints into an invasive and destructive tissue. Synovial fibroblasts become transformed, invading and destroying bone and cartilage of the affected joint(s). Due to the significant role these cells play in the progression of the disease process, developing a therapeutic strategy to target and inhibit their invasive destructive nature could help patients who are afflicted with this debilitating disease. Gingival-derived mesenchymal stem cells are known to possess immunomodulatory properties and have been studied extensively as potential cell-based therapeutics for several autoimmune disorders.
Methods
A chimeric human/mouse model of synovitis was created by surgically implanting SCID mice with a piece of human articular cartilage surrounded by RASF. Mice were injected once with either GMSC or GMSCExo at 5–7 days post-implantation. Histology and IHC were used to assess RASF invasion of the cartilage. Flow cytometry was used to understand the homing ability of GMSC in vivo and the incidence of apoptosis of RASF in vitro.​
Results
We demonstrate that both GMSC and GMSCExo are potent inhibitors of the deleterious effects of RASF. Both treatments were effective in inhibiting the invasive destructive properties of RASF as well as the potential of these cells to migrate to secondary locations and attack the cartilage. GMSC home to the site of the implant and induce programmed cell death of the RASF.​
Conclusions
Our results indicate that both GMSC and GMSCExo can block the pathological effects of RASF in this chimeric model of RA. A single dose of either GMSC or GMSCExo can inhibit the deleterious effects of RASF. These treatments can also block the invasive migration of the RASF, suggesting that they can inhibit the spread of RA to other joints. Because the gingival tissue is harvested with little difficulty, relatively small amounts of tissue are required to expand the cells, the simple in vitro expansion process, and the increasing technological advances in the production of therapeutic exosomes, we believe that GMSCExo are excellent candidates as a potential therapeutic for RA.
Design and Characterization of a Membrane Dielectric-Barrier Discharge Reactor for Ammonia Synthesis
Authors: Veng Visal , Tabu Benard , Simasiku Ephraim , Landis Joshua , Mack John Hunter , Carreon Maria , Trelles Juan Pablo 
Published: July 2023

Abstract

Ammonia synthesis via non-thermal plasma presents advantages over the Haber-Bosch process, particularly for small-scale and distributed operations powered by intermittent electricity from renewable energy sources. We designed and characterized a membrane Dielectric-Barrier Discharge (mDBD) reactor for ammonia synthesis from nitrogen and hydrogen. The reactor used a porous alumina membrane as dielectric barrier and as distributor of H2. This arrangement enabled greater residence time for N2 decomposition together with greater H2 availability in the reaction zone, as assessed by a computational thermal-fluid model. We evaluated the reactor's operation with membranes of 0.1, 1.0, and 2.0 µm pore size and porosities between 25% and 51%, and also in conventional DBD mode using a non-porous dielectric. The experimental characterization of the reactor encompassed electrical, optical, and spectroscopic diagnostics, as well as Fourier-Transform Infrared Spectroscopy (FTIR) to analyze gas products, as function of driving voltage. The results show that both, ammonia production and power consumption, vary inversely with membrane pore size. The highest energy yield of 0.35 g-NH3/kWh was obtained with the 1.0 µm pore membrane, whereas the maximum yield under conventional DBD operation was three-times lower. Our findings demonstrate that the use of a membrane dielectric can enhance the performance of DBD-based ammonia synthesis.
Evolution and Comparison of Three Typical Permanent Magnet Machines for All-Electric Aircraft Propulsion
Authors: Long Dingbang , Wen Honghui , Shao Yulong , Shuai Zhikang 
Published: July 2023

Abstract
In this paper, three typical permanent magnet machines for All-Electric aircraft propulsion are designed, optimized and compared. Firstly, the necessary performances are determined based on the requirements of high power/torque density and an aircraft with a maximum takeoff weight of 1500 kg. The initial structures of interior permanent magnet synchronous (IPM) machine, vernier permanent magnet (VPM) machine and flux-switching permanent magnet (FSPM) machine are designed with identical stator radius and rotor shaft length. Then, parametric sensitivity analysis and multi-objective particle swarm are combined as an optimization methodology to optimize these machines. Based on the finite element analysis, the electromagnetic performances such as no-load airgap flux density harmonic spectrum, cogging torque, average output torque, losses, efficiency and power factor etc. are generally compared and analyzed. Subsequently, the discussions are carried out, where the strength and weakness of these three machines are concluded and the future prospects are suggested. Finally, it is concluded that if effective measures are implemented to reduce the permanent magnet eddy current loss and improve the power factor, the VPM machine would be the most suitable choice among these machines for All-Electric aircraft propulsion.
A smart and noble method to desulfurize sulfur-containing materials from fossil fuels: the effect of competitor molecules
Authors: Rostami Siroos , Pour Ali Nakhaei , Mohammadi Ali 
Published: July 2023

Abstract
In this paper, the desulfurization of sulfurous organic solution (SOS) was studied by the adsorptive method. The Ni ion-exchanged NaY zeolite was selected as the adsorbent, and characterized by X-Ray diffraction (XRD) and X-Ray fluorescence (XRF) techniques. The SOS components are based on 1,2 ethanedithiol with 11400 ppm concentration (as sulfur-containing material) and n-hexane (as inert solvent). The sulfur content of SOS after a desulfurization process without competitor molecules reached 10100 ppm. Also, ethyl amine, diethyl amine, and triethyl amine were selected as competitive compounds. The results showed that ethyl amine, diethyl amine, and triethyl amine competitor molecules promote the desulfurization capacity of Ni-NaY adsorbent. The results showed that not only do these competitor molecules haven’t a negative effect on the desulfurization process but also, they facilitate the desulfurization capacity of Ni-NaY. The sulfur content of desulfurized SOS with the appropriate amount of these competitors reaches 110 ppm (up to 99% desulfurization).
Social Health Insurance for Universal Health Coverage in LMICs: A Policy Analysis of the Attainments, Setbacks, and Equity Implications of Kenya’s National Health Insurance Fund
Authors: Nungo Susan E. , Filippon Jonathan , Russo Giuliano 
Published: July 2023

Abstract
Background
Growing evidence suggests that healthcare financing is one of the key factors for the attainment of Universal Health Coverage (UHC) in low- and middle-income countries (LMICs). Social Health Insurance (SHI) has recently earned global recognition as a possible financing mechanism to enable affordable and equitable healthcare services in resource-scarce settings. However, the path to establishing such schemes is known to be ridden with structural and political contextual challenges.
Methods
This work aimed to identify the enabling factors for the implementation of SHI as a financing tool for UHC in LMICs, using Kenya's National Health Insurance Fund (NHIF) experience as a case study. We used health policy lenses to analyse how actors' behaviours interplayed with other dimensions of policymaking to shape the development of Kenya’s NHIF and interpret their perceptions of policy outcomes. Drawing from 21 semi-structured interviews and an analysis of published and grey literature, we gathered qualitative as well as quantitative evidence to perform a retrospective case analysis of the NHIF experience in Kenya.
Results
One of our key findings is that only 17% of Kenya’s population are covered by SHI. Despite the predominance of the informal labour market in Kenya (83%), only 27% are covered by the NHIF, implying very low uptake and/or retention rates. There was little stakeholder engagement in the policy implementation process and minimum adoption of expert advice. Health financing policies were heavily influenced by political affiliations and positions of power. In addition, the purchasing and payment of healthcare was flawed, with inefficiencies including slow bureaucratic reimbursement procedures, little knowhow by rural hospital clerks, misappropriation, and a preference for private healthcare providers. The group-based parallel schemes run alongside the national scheme and the penalty payments for defaulted premiums increased the equity gap of the NHIF’s benefits for Kenya’s population.
Conclusion
Although the SHI system was perceived to increase the coverage and quality of Kenya’s health services, substantial structural and contextual challenges appear to have hindered its potential to finance the attainment of UHC, which should be a stepping-stone towards comprehensive healthcare attainment. Based on Kenya’s experience, we identify informal sector participation, efficiency of purchasing and payment of healthcare, and political engagement as key bottlenecks for the implementation of SHI schemes in LMICs.
Alzheimer’s Disease MRI Identification, Recognition, &amp; Evaluation - Deep Learning
Authors: Muniagurria Tomás Premoli , Rowlands Sareh 
Published: July 2023

Abstract

In this study, we investigate the impact of various Convolutional Neural Network (CNN) architectures on the accuracy of diagnosing Alzheimer’s Disease (AD) using patient MRI scans. Alzheimer’s Disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s Disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.
Remote learning during COVID-19 and transformative learning theory: tendency towards Quadruple Helix Model for future post-secondary education in Indigenous contexts
Authors: Hossain Amzad , Kong Ying , Malik Amjad 
Published: July 2023

Abstract
This paper aims to examine UCN (University College of the North) students’ remote learning experience during the COVID-19 pandemic to provide reference for future remote education in Indigenous contexts. Survey data are used for empirical analysis of the five themes: socio-demographic contexts; social activities, stress, and well-being; academic performance; course delivery; and student support services. Transformative learning theory and Quadruple Helix Model are used as a framework to explore the breadth and depth of such five themes. As the descriptive study shows, the majority of UCN students are over 25 years old and study in their first and second year with major challenges such as Internet connectivity, private space, and interruption. Mean values reveal that the remote learning performance is determined by concerns about COVID-19 infection, mental and physical health, isolation and lack of socio-cultural activities, students’ self-preparedness and motivation, and support services. The regression analysis shows that students’ concerns about COVID-19 infection interference with course completion are directly affected by their worries about themselves or someone in their families who could be exposed to COVID-19, their mental health, and blended course delivery. Therefore, students’ remote learning performance and their well-being will be enhanced if we take into consideration improving social distancing, educational technology, and course delivery with community-university culturally responsive collaboration. The research findings and the reviewed literature attest that transformative learning theory fits UCN’s remote learning practices to meet educational goals through the university-community collaboration, which is supported by the Quadruple Helix model. As a result, such remote learning practices engage students, particularly Indigenous students, and the practices will help upgrade universities with similar attributes globally into Mode 3 university, contributing to community economic development.
Effect of Women’s View Toward Their Rights on Receiving Better Antenatal Care in Bangladesh
Authors: Morshed Ramisa 
Published: July 2023

AbstractBackground:A woman or a prospective mother’s view of her husband beating her tells a lot about a country’s view, and a woman’s preferred age of marrying can also exhibit her attitude toward her rights and goals. In a country, many girls may forcefully be married off at an early age where there might be no hand in it of the girls. But the thought they carry throughout their lifetime can be resembled in their children’s lives too and can proclaim plenty of the country’s problems, especially receiving improved antenatal care (ANC). So the thought they have in mind about their rights are often more important than what actually their activities tell. However, limited research has focused on understanding women's perspectives on their rights and their relation with ANC quality in Bangladesh. The findings of this study will contribute to a deeper understanding of women's perspectives on their rights and the barriers they face in accessing quality ANC.Objective:This study aims to investigate the view of Bangladeshi women toward their own rights and the impact on their access to improved ANC.Method:To address this gap, a binary logistic regression model was employed by analyzing in IBM SPSS Statistics 25 using BDHS 2017-18 data. The study recruited a diverse sample of women from various social backgrounds, beliefs, and geographical locations in Bangladesh.Result:It was spotted that a small percentage (6.6%) of women in Bangladesh were under proper ANC coverage. The women who didn’t justify domestic violence were 1.231 times more likely to be under ANC coverage in Bangladesh than those who justify domestic violence. Moreover, women who were exposed to news media more often and women with a higher level of education were more likely to be under ANC coverage than those who were not. Unfortunately, almost one-fifth of all Bangladeshi women (19.6%) justify being beaten by their husbands. The preferred marriage age by these women didn’t come out significant in the adjusted probit model but came out significant in the adjusted model where women preferring a higher age for marriage were more likely to be under ANC coverage.Conclusion:Women’s entitlements enable them to actively engage in their own healthcare programs, leading to improved health outcomes for both mother and child. Through targeted awareness campaigns, educational initiatives, and policy advocacy, Bangladesh can create an environment where women are aware of their rights and have access to quality ANC services. By ensuring their rights are respected, a society that values reproductive health and the well-being of women and children can strive.
Reviewing Stimulus and System-Specific Differences in Expression Profiles of Methanogenesis Optimized Anaerobic Digestion Transcriptomes
Authors: MOHLOMI Nikwando , Nkuna Rosina , Permaul Kugenthiren , Puri Adarsh 
Published: July 2023

Abstract
Anaerobic digestion is a crucial process in wastewater treatment, renowned for its sustainable biogas production capabilities and simultaneous reduction of environmental pollution. However, dysregulation of vital biological processes and pathways can lead to reduced efficiency and suboptimal biogas output. This study aimed to investigate gene expression patterns in anaerobic digestion and identify potential therapeutic targets using RNA sequencing data from NCBI's Sequence Read Archive (SRA) database. By creating a reference genome that was 86.4% complete we were able to assemble transcripts and follow expression patterns of the different sample groups that were in question. We identified pathways for homeostasis and cellular transport to be the most important in full scale anaerobic digesters and further elaborated on specific reactions and gene expression in this context. By analyzing the homolog signatures with regard to oxidative phosphorylation gene sets, we were able to characterize the heterogenic transcriptome to be absolutely prokaryotic. We discovered variants of highly conserved alleles for electron cycling by the heterodisulfide reductase complex, methylation and demethylation by methyl-transferases, and oxidation of active coenzyme A and B by methyl coenzyme reductase.
Potential Role of PPARα in Ameliorating Neuropathic Pain by Gut Microbiota Alteration
Authors: Zhao Yuying , Wu Zijun , Du Yue , Han Qingqing , Bai Yuanyuan , Liu Bin , Li Jing 
Published: July 2023

Abstract
Background
Neuropathic pain (NP) is a chronic disease state centred on neuroinflammation that severely affects the life and emotional state of patients. Peroxisome proliferator-activated receptor α (PPARα) has a bright future in NP management due to its promising anti-inflammatory properties. Emerging evidence suggests that the gut microbiome and its derived metabolites play a key role in NP. In this paper, we aimed to determine whether PPARα can influence the development and regression of NP by modulating gut microbes and serum nontarget metabolites.
Methods
A chronic constriction injury (CCI) pain model was established in C57BL/6J mice, and the PPARα agonist GW7647 (5 mg/kg) or PPARα inhibitor GW6471 (20 mg/kg) was injected intraperitoneally every other day to investigate whether PPARα could regulate NP through modulation of gut microbes. Pain behaviour tests were performed on mice, including the von Frey test and the hot plate test. Mice were sacrificed after 14 days and the corresponding tissues were collected in preparation for subsequent assays.
Results
The mice were divided into four groups: Sham + vehicle, CCI + vehicle, CCI + GW7647 and CCI + GW6471. 16S rDNA sequencing and liquid chromatography–mass spectrometry (LC-MS/MS) untargeted metabolomics analysis revealed significant changes in gut microbial and metabolite levels in CCI mice, and H&E staining revealed that the sciatic nerves of CCI mice showed significant inflammatory cell infiltration. Intraperitoneal injection of the PPARα agonist GW7647 (5 mg/kg) significantly attenuated mechanical allodynia and thermal hyperalgesia in CCI mice, whereas injection of the PPARα antagonist GW6471 (20 mg/kg) produced the opposite effect. Immunofluorescence showed a significant inhibitory effect of GW7647 on microglial activation. The distribution and abundance of intestinal microbial communities were significantly changed after the administration of GW7647 or GW6471 in CCI mice. Further serum LC‒MS/MS analysis revealed alterations in 258 potential serum metabolic biomarkers. The combined analysis showed that many alterations in serum metabolic biomarkers were closely associated with intestinal microorganisms.
Conclusion
This study demonstrates that PPARα can influence serum metabolite levels by modulating the abundance and community composition of gut microbes, which in turn modulates NP, providing a new idea for further research on the pathogenesis of NP.