bluuebunny/crossref_metadata_2025_split huggingface dataset:
Soil environment effects on the occurrence of black sesame spot and clubroot disease in Chinese Cabbage
Authors: Chi Xiuli , Yang Kun , Li Chengran , Chu Dong 
Published: November 2024

Abstract

Chinese cabbage is a popular leafy vegetable widely consumed in Asian cuisine, particularly in China. However, it is susceptible to various diseases, including clubroot and black sesame spot, which can significantly impact yield and quality. The soil environment plays a crucial role in developing these two diseases. In our experiment, we measured eight soil indicators-soil pH, organic matter, alkali-hydrolyzable nitrogen, available phosphorus, rapidly available potassium, total salinity, total nitrogen, and slowly available potassium-across 38 cabbage-growing locations in Jiaozhou City, China. We compared the soil environments of disease-infested and non-infested sites. Our results indicated that the soil environment did not influence the occurrence of clubroot disease. However, black sesame spot was more prevalent in acidic soils with low phosphorus levels, demonstrating a significant correlation between soil conditions and the incidence of black sesame spot. Overall, our study provides a comprehensive understanding of how the soil environment affects the occurrence of clubroot and black sesame spot, offering valuable insights for the integrated management of these challenging cabbage diseases.
DiMorph: A Morphological Analyzer for Arabic Dialects with a Focus on the Moroccan Dialect
Authors: Khlif Nadia , Mazroui Azzeddine , Nahli Ouafae 
Published: November 2024

Abstract

Given the limited availability of resources for Arabic dialects, establishing corpora , linguistic resources, and tools presents a considerable challenge. To address the need for processing dialectal text, we developed a morphological analyzer called DiMorph (Dialectal Morphological Analyzer), specifically designed to process the Moroccan dialect. We adopted the AraMorph morphological engine, originally designed for processing Modern Standard Arabic texts. Subsequently, we created specific linguistic resources and preprocessing and postprocessing components to better handle dialectal texts’ morphological and linguistic intricacies. This article details the methodology and steps in constructing DiMorph and annotated corpora and lexical resources based on a Moroccan corpus.
Malware Detection Method Based on Feature Fusion
Authors: Yan Hao , Zhang Jian , Tang Zhangguo , Long Hancheng , Zhu Min , Zhang Tianyue , Luo Linglong , Li Huanzhou 
Published: November 2024

Abstract

In recent years, as cyberattacks continue to escalate, malware has become increasingly diverse and complex, posing significant security threats to enterprises, government agencies, and individual users. Malware developers often employ techniques such as feature obfuscation and behavior hiding, rendering traditional detection methods less effective. To address this challenge, this study proposes a malware detection method based on feature fusion and a multi-feature detection framework. The method extracts frequency features and semantic information from opcodes and readable characters, and byte transition probabilities from byte sequences, thereby constructing a comprehensive feature vector. A two-layer detection framework that combines deep learning with traditional machine learning is designed, effectively integrating different feature types and overcoming the limitations of single-feature approaches. Experimental results demonstrate that the proposed method significantly outperforms traditional algorithms in terms of detection accuracy and generalization capability, greatly enhancing the detection of complex malware families. Notably, it excels in handling packed code, obfuscation techniques, and imbalanced data, offering an efficient solution for malware detection.
Improving mental health, self-efficacy and social support in older people through a community intervention based on mindfulness
Authors: Juraga Denis , Rukavina Tomislav , Glavić Mihaela Marinović , Roviš Darko , Bilajac Lovorka , Antonić Maša , Raat Hein , Vasiljev Vanja 
Published: November 2024

Abstract

Background: Ageing is a complex process that involves various biological, psychological and social changes. At the same time, older people are more susceptible to lower self-efficacy and social support, as well as deteriorating mental health and increasing levels of loneliness. As the global population ages, there is a growing demand for evidence-based interventions tailored to address specific mental health problems, enhance social support and improve overall well-being. The aim of this study was to investigate the effectiveness of a seven-week mindfulness-based community intervention on mental health, self-efficacy and social support in older people.
Methods: The study included 257 participants who were divided into an intervention group and a control group. Assessments were conducted before the intervention began and 6 months after its completion.
Results: The results showed a significant reduction in depression in the intervention group (p<.001). Furthermore, the intervention led to a significant improvement in general self-efficacy, chronic disease self-management self-efficacy, physical activity and nutritional self-efficacy in the intervention group compared to the control group, in addition to a statistically significant improvement in social support in the intervention group.
Conclusions: Overall, the results demonstrate the effectiveness of mindfulness-based community interventions in improving mental health, self-efficacy and social support of older people in a community setting. The results of the present study show that this programme leads to immediate health benefits in terms of mental health and self-efficacy in older people, while contributing to the development of effective strategies for chronic disease self-management and has the potential to reduce loneliness and social isolation.
Study of the Boundary Layer Interaction With the Bow Shock at Supersonic Flow Around a Blunt Body
Authors: Lapushkina T. A. , Kolesnik E. V. , Monahov N. A. , Popov P. A. , Belov K. I. 
Published: November 2024

Abstract

The work studies the influence of a growing boundary layer on the process of the supersonic flow around an aerodynamic body. The task is to select and implement in an experiment the parameters of a supersonic flow and to study the flow pattern near the surface of an aerodynamic body at different viscosity values of the incoming flow. Visualization of the shock wave configuration in front of the body and to study the change in the pressure field in the flow region under these conditions is the main goal of the work. The experiment is carried out on an experimental stand created on the basis of a shock tube. The aerodynamic body under study (a semi-cylinder pointed along a circle or an ellipse) is placed in the supersonic nozzle. The model is clamped by lateral transparent walls, which are simultaneously a source of boundary layer growth and the viewed windows for visualizing the flow. For selected modes with Reynolds numbers from 8200 to 45000, schlieren flow patterns and pressure distribution fields near surface of the streamlined models and the plate of the growing boundary layer were obtained. Data show a complex unsteady flow pattern is realized near the model that is caused by the viscous-inviscid interaction of the boundary layer with the bow shock wave near the wall.
Human Papillomavirus (HPV) Detection and Genotype Correlation with Cervical Lesions at the University Teaching Hospital of Kigali, Rwanda
Authors: Mbabazi Evode , Munyemana Jean Bosco , Mukashema Julienne , Bazimaziki Emmanuel , Ndayisaba Marie Claire , Tope Adegboyega Taofeek , Rugwizangoga Belson 
Published: November 2024

Abstract

Background
Cervical cancer remains a major health issue, especially in low- and middle- income countries (LMICs), with Human papillomavirus (HPV) infection serving as the primary precursor. Despite global efforts to combat cervical cancer, including vaccination, a critical knowledge gap persists regarding HPV prevalence, genotype distribution, and their correlation with cervical lesions in women from poor resource areas. This study assessed the prevalence of HPV infection, identified the most common HPV genotypes, and evaluated their correlation with cervical lesions among women attending the University Teaching Hospital of Kigali (CHUK), Rwanda.
Methods
This cross-sectional retrospective study initially involved 473 women who were screened for HPV infection. Cervical lesions were further evaluated in 74 HPV-positive women. Clinical and demographic data, HPV genotypes, and cervical lesion information were collected and analyzed for these 74 HPV-positive women. Data were analysed using IBM SPSS Statistics version 29.0.2. and significance level was set at 0.05.
Results
HPV detection rate was 74/473 (15.6%), with a concentration among women aged 41–45 years (29.7%). Notably, 16/74 (21.6%) of HPV-positive women were also human immunodeficiency virys (HIV) positive. HPV genotypes 16 and 18 were the most prevalent with 14(8.3%) each. Cytological analysis revealed 5.2% precancerous lesions, while histological examination showed 33.3% precancerous lesions and 33.3% invasive carcinomas. Women with high risk HPV (HR-HPV) infections demonstrated a 2.5-fold increased risk of developing cancerous lesions compared to those with low risk HPV (LR-HPV) infections (95% CI: 1.637–4.56, p = 0.0028).
Conclusion
This study highlights the varied distribution of HPV genotypes among Rwandan women and a link between HR-HPV types and cervical lesions. The findings emphasize the need for tailored cervical cancer prevention strategies, including targeted surveillance, vaccination, and enhanced screening in Rwanda and similar resource-limited settings.
Clinical Trial Number: not applicable
Convolutional Autoencoder Recommendation System
Authors: Ghadami Amirhossein , Tran Thomas 
Published: November 2024

Abstract

In today's online business environment, recommendation systems are essential for increasing companies' revenue by guiding customers to spend time or money on products. However, the challenge of creating an effective recommendation system has always been a concern for both companies and scientists.Researchers have explored various methods to understand the complex interaction between users and item features, aiming for more precise and accurate recommendations. This paper introduces a new recommendation system based on deep learning. Our approach (CAERS) employs a Convolutional Autoencoder to capture meaningful interaction between users and items.Furthermore, we enhance our system by extracting additional content information, offering a comprehensive overview of each item. This process enables the model to understand better and process individual items. Additionally, our method uniquely addresses the cold start problem by depending exclusively on content information. This approach improves our system's capability to provide recommendations even in situations with limited user or item interaction data. Our model is designed to be versatile and capable of functioning across various domains. However, we utilize movie datasets to showcase the model's ability and performance for our experimental purposes. Our experience demonstrates that our proposed method effectively captures interactions between users and items, successfully overcoming the cold start problem and outperforming existing approaches.
Infestation symptoms as indicators of a sustained bark beetle outbreak in conserved and managed Norway spruce forests in south-eastern Finland
Authors: Simon Diana-Cristina , Lyytikäinen-Saarenmaa Päivi , Pelto-Arvo Mikko , Tuviala Johanna , Kosunen Maiju , Honkavaara Eija , Näsi Roope , Tikkanen Olli-Pekka , Kilpeläinen Antti , Peltola Heli 
Published: November 2024

Abstract

European spruce bark beetle (Ips typographus L., SBB) infestations are extending in northern Europe due to increases in temperature and drought, which increase the risk of outbreaks in Norway spruce (Picea abies L.) forests. The severity of SBB damage may be decreased by timely detection and management measures. In this study, we analysed the SBB infestation levels of trees, the overall SBB damage at the stand level, the relationship between SBB damage and stand characteristics, and the effect of an outbreak over time on the volume and basal area in managed and conserved areas. We visually observed SBB symptoms at the stem level (entrance-exit holes, resinous flows, bark damage) and crown level (defoliation, discoloration) in 60 sampling plots in south-eastern Finland. These plots were established in an SBB outbreak area triggered by a severe wind disturbance in August 2010. Data were collected in 2014–2017 in conserved areas and in 2019–2021 in both conserved and managed areas. The results showed that in conserved areas, 70% of the trees were already highly infested in 2015, reaching 90% in 2017. During 2019–2021, the conserved areas were significantly more damaged than the managed ones. The volume of the stands decreased over time on average by 80% in conserved areas and 40% in managed areas, with the highest decrease occurring six to seven years after the initial SBB colonization. The damage estimated based on resinous flows and entrance-exit holes was similar regardless of the year or treatment. Our detection method may be used to support timely risk assessment and management of SBB outbreaks and decrease damage at the landscape level.
Are LLMs Good for Low-resource Vietnamese and Other Translations?
Authors: Nguyen Van-Vinh , Nguyen-Tien Ha , Nguyen-Ngoc Phuc , Hoang Minh-Cong Nguyen , Nguyen-Tat Dat 
Published: November 2024

Abstract

Large language models (LLMs) such as ChatGPT4, Gemini and LLaMA have seen widespread applications due to their strong instruction-following abilities, including machine translation (MT). LLMs have revolutionized machine translation for well-resourced languages. However, this paper studies their limitations in translating languages with small parallel text data (low-resource languages), especially, Vietnamese and other pairs. To address this problem, we propose a systematic study for examining the theoretical underpinnings of LLMs and their adaptation to low-resource settings carefully. We also present a new method for training the vanilla transformer model from scratch to create the most effective translation model for resource-poor language pairs like Vietnamese-Lao. Experiment results with the low-resource language pair Vietnamese-Lao show that the vanilla transformer model (seq2seq is only used for machine translation tasks) is better than MT with large language models, especially open source models (Llama2,3) both quality and speed time. This research is very meaningful as Vietnam has 54 different ethnic groups who speak more than 100 different languages [1], most of which have few bilingual resources. This study also shows the selection of a model to specifically optimize the translation problem with few resources between Vietnamese (the official language) and other languages.
Neuroprotective activities of sertraline, tiagabine, and bicifadine with autophagy-inducing potentials in a 6-hydroxidopamine-treated Parkinson’s disease cell model
Authors: Lee Chaemi , Kim Seong Soon , Bae Myung Ae , Kim Seong Hwan 
Published: November 2024

Abstract

Parkinson’s disease (PD) is a prevalent neurodegenerative disease characterized by the progressive loss of dopaminergic neurons in the substantia nigra. The development of effective neuroprotective therapies is crucial for mitigating the devastating effects of PD, and autophagy induction has recently emerged as a promising neuroprotective strategy. This study aimed to identify autophagy-inducing compounds and evaluate their neuroprotective activity in the chemical library. Among 3,200 chemicals consisting of FDA-approved drugs or are being evaluated in clinical trials, 547 chemicals indicating CNS diseases were filtered in, and 3 compounds (sertraline, tiagabine and bicifadine) were finally identified to exhibit the autophagy-inducing activity and the neuroprotective activity in 6-hydroxydopamine (6-OHDA)-induced PC12 neuronal damaged PD model. Furthermore, Neurochemical profiling also revealed that 3 chemicals alleviated 6-OHDA-induced neurochemical pathway disruptions in PC12 cells. In conclusion, sertraline, tiagabine, and bicifadine, not only exhibited autophagy-inducing potential but also demonstrated significant neuroprotective activity with the change of neurochemical profiles against 6-OHDA-induced neurotoxicity in PD model, suggesting that 3 autophagy-inducing chemicals could be repositioned for PD to protect the neuronal cells.
Liver-X receptor β-selective agonist CE9A215 regulates Alzheimer’s disease- associated pathology in a 3xTg-AD mouse model
Authors: Ban So Young , Nam Yunkwon , Do Thi Thuong , Kim Byeong-Hyeon , Shin Soo Jung , Nguyen My Tuyen Thi , Kim Jaehan , Moon Minho , Park Jong-Tae 
Published: November 2024

Abstract

Background
In Alzheimer's disease (AD), tau pathology is more closely associated with disease progression. Therefore, the development of agents that alleviate tau pathology is essential. Liver-X receptor (LXR), a nuclear receptor with α and β subunits, has garnered interest for the prevention and treatment of neurodegenerative diseases, especially AD. Inotodiol (CE9A215) is an oxysterol isolated from Chaga mushroom, known for its anti-inflammatory, hepatoprotective effects, and efficacy in diabetes. However, its mechanism of action (MOA), how it regulates genes, and its potential effects on Alzheimer's disease (AD) remain unclear.
Methods
Molecular docking simulation and LXR FRET assay were performed for CE9A215. Gene expression of CE9A215 was confirmed using LXR a K/O mice and LXR b K/O mice. Y-maze analysis was conducted using 3xTg mice to assess AD-associated behaviors, and immunohistochemistry (IHC) was performed to examine amyloid-b, phosphorylated tau, and neuroinflammation. Transcriptome analysis of the brain was performed following oral administration of CE9A215.
Results
Molecular docking studies and TR-FRET binding assays demonstrated that CE9A215 preferentially binds to LXRβ (EC50 <10 nM), with no significant interaction observed with LXRα at concentrations up to 1,000 nM. Moreover, CE9A215 affected the expression of ABCA1, APOE, SREBP-1c and AQP4, in brain of wild-type and LXR α/β knockout mice in LXRβ-dependent manner. The treatment efficacy of CE9A215 on AD-related pathologies was evaluated using 3xTg-AD mice. CE9A215 exerted both prophylactic and therapeutic effects on AD-associated behaviors and pathologies, including reductions in amyloid-β, phosphorylated tau, and neuroinflammation in the hippocampus. Transcriptomic analysis revealed that CE9A215 induced significant changes in genes associated with tau pathology, particularly in pathways related to protein phosphorylation and PI3K/AKT signaling.
Conclusions
Our findings suggest that CE9A215 could be a promising therapeutic candidate for AD, particularly in mitigating tau hyperphosphorylation and related AD pathologies.
mRNA-based AXL-targeting chimeric antigen receptor-T cells against solid tumors
Authors: Zou Bo , Bai Shimeng , Wang Mengge , Li Ning , Fan Zhongyi , Peng Yuanzheng , Han Mingshu , Zeng Chen , Lu Hongzhou , Qi Lin , Zhang Xing-Ding , Tan Xiaohua , Liao Qibin 
Published: November 2024

Abstract

Background
Currently approved CAR-T cells primarily utilize retroviral or lentiviral vectors (LV), posing significant challenges due to their time-consuming and costly nature, and associated safety concerns, including insertional mutagenesis. Consequently, mRNA delivery holds promising prospects in CAR-T cell engineering. AXL represents an ideal target for LV-engineered CAR-T cells in the treatment of various malignancies, including breast, lung, and pancreatic cancer. However, the anti-tumor activity of mRNA-based AXL CAR-T cells remains to be fully elucidated.
Methods
We developed a novel CAR utilizing a fully humanized AXL-specific antibody. Subsequently, the mRNA encoding AXL-specific CAR was synthesized via in vitro transcription. This mRNA was then transfected into pre-activated T cells through electroporation. The expression levels of mRNA-based CAR were evaluated by flow cytometry. Furthermore, in vitro and in vivo assays were performed to evaluate the antigen-specific cytotoxicity and cytokine release capabilities of mRNA-based AXL CAR-T cells in various tumor cells and in a tumor-bearing mouse model.
Results
Electroporation of mRNA-encoding AXL CAR minimally affected T cell viability, resulting in high CAR expression over 90%, and this CAR expression persisted for at least three days following electroporation, consistent with observed cytotoxicity against the lung cancer cell line A549. mRNA-based AXL CAR-T cells exhibited dose-dependent cytotoxicity against both A549 and pancreatic cancer cell line Panc-1, achieving a killing rate exceeding 80% at an effector:target ratio of 4:1. Additionally, mRNA-based AXL CAR-T cells specifically secreted high level of cytokines IL-2 and IFN-γ upon interaction with target tumor cells. mRNA-based AXL CAR-T cells exhibited minimal impact on T cell subtypes while demonstrating robust cytotoxicity comparable to LV-engineered CAR-T cells. Additionally, mRNA-based AXL CAR-T cells demonstrated good anti-tumor activity in a subcutaneous lung cancer xenograft model.
Conclusions
mRNA-based AXL CAR-T cells transiently expressed high levels of CAR, enabling cost-effective large-scale production, and comparable functionality to LV-engineered CAR-T cells within a short time frame, which offers a safe alternative for clinical therapy utilizing LV-engineered CAR-T cells. mRNA-based AXL CAR-T cells have shown promising results in treating solid tumors, including lung cancer and pancreatic cancer, establishing an experimental basis for their potential clinical application in solid tumors.
Isolation and characterization of 35 SNP markers based on RAD sequencing in Vallisneria natans
Authors: Zhang Shengman , Tan Meng , He Peimin , Huang Xiangfeng , Li Chunyang 
Published: November 2024

Abstract

Vallisneria natans is widely distributed around the world. This species can adsorb suspended solids and solve the eutrophication of water bodies effectively, so it has become the focus of aquatic environment research. With the intensification of water pollution, the wild population of V. natans has declined rapidly during recent years, and insufficient molecular markers have limited the effective conservation of this species. In this research, 35 novel single nucleotide polymorphism (SNP) markers were developed in a cultivar of V. natans and 14 wild species of V. natans using restriction site-associated DNA sequencing (RAD-seq). A total of 778 alleles were detected, with an average value of 2.59 alleles per sample. The newly developed polymorphic SNPs of V. natans are of great significance for the genetic breeding of Vallisneria and conservation genetics research.