bluuebunny/crossref_metadata_2025_split huggingface dataset:
SM-CycleGAN: crop image data enhancement method based on self-attention mechanism CycleGAN
Authors: Liu Dian , Cao Yang , Yang Jing , Wei Jianyu , Zhang Jili , Rao Chenglin , Wu Banghong , Zhang Dabin 
Published: April 2024

AbstractCrop disease detection and crop baking stage judgement require large image data to improve accuracy. However, the existing crop disease image datasets have high asymmetry, and the poor baking environment leads to image acquisition difficulties and colour distortion. Therefore, we explore the potential of the self-attention mechanism on crop image datasets and propose an innovative crop image data-enhancement method for recurrent generative adversarial networks (GANs) fused with the self-attention mechanism to significantly enhance the perception and information capture capabilities of recurrent GANs. By introducing the self-attention mechanism module, the cycle-consistent GAN (CycleGAN) is more adept at capturing the internal correlations and dependencies of image data, thus more effectively capturing the critical information among image data. Furthermore, we propose a new enhanced loss function for crop image data to optimise the model performance and meet specific task requirements. We further investigate crop image data enhancement in different contexts to validate the performance and stability of the model. The experimental results show that, the peak signal-to-noise ratio of the SM-CycleGAN for tobacco images and tea leaf disease images are improved by 2.13% and 3.55%, and the structural similarity index measure is improved by 1.16% and 2.48% compared to CycleGAN, respectively.
Bacterial diversity dominates variable macrophage responses of tuberculosis patients in Tanzania
Authors: Hiza Hellen , Zwyer Michaela , Hella Jerry , Arbués Ainhoa , Sasamalo Mohamed , Borrell Sonia , Xu Zhi Ming , Ross Amanda , Brites Daniela , Fellay Jacques , Reither Klaus , Gagneux Sébastien , Portevin Damien 
Published: April 2024

AbstractThe Mycobacterium tuberculosis complex (MTBC) comprises nine human-adapted lineages that differ in their geographical distribution. Local adaptation of specific MTBC genotypes to the respective human host population has been invoked in this context. We aimed to assess if bacterial genetics governs MTBC pathogenesis or if local co-adaptation translates into differential susceptibility of human macrophages to infection by different MTBC genotypes. We generated macrophages from cryopreserved blood mononuclear cells of Tanzanian tuberculosis patients, from which the infecting MTBC strains had previously been phylogenetically characterized. We infected these macrophages ex vivo with a phylogenetically similar MTBC strain (“matched infection”) or with strains representative of other MTBC lineages (“mismatched infection”). We found that L1 infections resulted in a significantly lower bacterial burden and that the intra-cellular replication rate of L2 strains was significantly higher compared the other MTBC lineages, irrespective of the MTBC lineage originally infecting the patients. Moreover, L4-infected macrophages released significantly greater amounts of TNF-α, IL-6, IL-10, MIP-1β, and IL-1β compared to macrophages infected by all other strains. While our results revealed no measurable effect of local adaptation, they further highlight the strong impact of MTBC phylogenetic diversity on the variable outcome of the host–pathogen interaction in human tuberculosis.
Colored cotton crop wastes valorization through pyrolysis: a study of energetic characterization and analytical Py-GC/MS
Authors: Silva Janduir E. , Deus Junior Joemil O. , Calixto Guilherme Q. , Melo Dulce M. A. , Melo Marcus A. F. , Júnior Vital C. B. , Chagas Bruna M. E. , Medeiros Everaldo P. , Braga Renata M. 
Published: April 2024

AbstractThe present work aimed to study different parts of colored cotton waste through energetic characterization and analytical flash pyrolysis. Stalks and bolls of BRS cotton cultivars from Sementes do Brasil (Green, Ruby, Topaz and Jade) were studied, using white cotton (BRS 286) as a comparison. The energetic potential of biomass was evaluated by bulk density, High Heating Value (HHV), proximate and ultimate analysis, compositional and thermogravimetric analysis (TGA). Pyrolysis was performed in a micro-pyrolyzer and the products were identified by gas chromatography and mass spectroscopy (Py-GC/MS). The results indicated a significant energetic potential, suggesting that can be used as an alternative energy source for thermochemical processes. The results of conventional pyrolysis indicated the presence of oxygenated compounds of different organic groups: aldehydes, ketones, phenols, furans and ethers, characteristic of the decomposition of lignocellulosic materials. Light organic acids in the C1-C4 range stood out the most, followed by phenols that appeared in a considerable proportion. Finally, it is concluded that the energy potential and pyrolysis products of the different parts (stalks and bolls) of colored cotton waste can be used to generate bioenergy and various chemical compounds of plant origin from green chemistry.
Machine-learning prediction of a novel diagnostic model using mitochondria-related genes for patients with bladder cancer
Authors: Li Jian , Wang Zhiyong , Wang Tianen 
Published: April 2024

AbstractBladder cancer (BC) is the ninth most-common cancer worldwide and it is associated with high morbidity and mortality. Mitochondrial Dysfunction is involved in the progression of BC. This study aimed to developed a novel diagnostic model based on mitochondria-related genes (MRGs) for BC patients using Machine Learning. In this study, we analyzed GSE13507 datasets and identified 752 DE-MRGs in BC specimens. Functional enrichment analysis uncovered the significant roles of 752 DE-MRGs in key processes such as cellular and organ development, as well as gene regulation. The analysis revealed the crucial functions of these genes in transcriptional regulation and protein-DNA interactions. Then, we performed LASSO and SVM-RFE, and identified four critical diagnostic genes including GLRX2, NMT1, OXSM and TRAF3IP3. Based on the above four genes, we developed a novel diagnostic model whose diagnostic value was confirmed in GSE13507, GSE3167 and GSE37816 datasets. Moreover, we reported the expressing pattern of GLRX2, NMT1, OXSM and TRAF3IP3 in BC samples. Immune cell infiltration analysis revealed that the four genes were associated with several immune cells. Finally, we performed RT-PCR and confirmed NMT1 was highly expressed in BC cells. Functional experiments revealed that knockdown of NMT1 suppressed the proliferation of BC cells. Overall, we have formulated a diagnostic potential that offered a comprehensive framework for delving into the underlying mechanisms of BC. Before proceeding with clinical implementation, it is essential to undertake further investigative efforts to validate its diagnostic effectiveness in BC patients.
Dual action effects of ethyl-p-methoxycinnamate against dengue virus infection and inflammation via NF-κB pathway suppression
Authors: Tarasuk Mayuri , Songprakhon Pucharee , Muhamad Phunuch , Panya Aussara , Sattayawat Pachara , Yenchitsomanus Pa-thai 
Published: April 2024

AbstractDengue virus (DENV) infection can lead to severe outcomes through a virus-induced cytokine storm, resulting in vascular leakage and inflammation. An effective treatment strategy should target both virus replication and cytokine storm. This study identified Kaempferia galanga L. (KG) extract as exhibiting anti-DENV activity. The major bioactive compound, ethyl-p-methoxycinnamate (EPMC), significantly reduced DENV-2 infection, virion production, and viral protein synthesis in HepG2 and A549 cells, with half-maximal effective concentration (EC50) values of 22.58 µM and 6.17 µM, and impressive selectivity indexes (SIs) of 32.40 and 173.44, respectively. EPMC demonstrated efficacy against all four DENV serotypes, targeting the replication phase of the virus life cycle. Importantly, EPMC reduced DENV-2-induced cytokines (IL-6 and TNF-α) and chemokines (RANTES and IP-10), as confirmed by immunofluorescence and immunoblot analyses, indicating inhibition of NF-κB activation. EPMC's role in preventing excessive inflammatory responses suggests it as a potential candidate for dengue treatment. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) and drug-likeness for EPMC were predicted using SwissADME and ProTox II servers, showing good drug-like properties without toxicity. These findings highlight KG extract and EPMC as promising candidates for future anti-dengue therapeutics, offering a dual-action approach by inhibiting virus replication and mitigating inflammatory reactions.
Comparative genomics of sirenians reveals evolution of filaggrin and caspase-14 upon adaptation of the epidermis to aquatic life
Authors: Steinbinder Julia , Sachslehner Attila Placido , Holthaus Karin Brigit , Eckhart Leopold 
Published: April 2024

AbstractThe mammalian epidermis has evolved to protect the body in a dry environment. Genes of the epidermal differentiation complex (EDC), such as FLG (filaggrin), are implicated in the barrier function of the epidermis. Here, we investigated the molecular evolution of the EDC in sirenians (manatees and dugong), which have adapted to fully aquatic life, in comparison to the EDC of terrestrial mammals and aquatic mammals of the clade Cetacea (whales and dolphins). We show that the main subtypes of EDC genes are conserved or even duplicated, like late cornified envelope (LCE) genes of the dugong, whereas specific EDC genes have undergone inactivating mutations in sirenians. FLG contains premature stop codons in the dugong, and the ortholog of human CASP14 (caspase-14), which proteolytically processes filaggrin, is pseudogenized in the same species. As FLG and CASP14 have also been lost in whales, these mutations represent convergent evolution of skin barrier genes in different lineages of aquatic mammals. In contrast to the dugong, the manatee has retained functional FLG and CASP14 genes. FLG2 (filaggrin 2) is truncated in both species of sirenians investigated. We conclude that the land-to-water transition of sirenians was associated with modifications of the epidermal barrier at the molecular level.
Potential therapeutic targets for COVID-19 complicated with pulmonary hypertension: a bioinformatics and early validation study
Authors: Hou Qingbin , Jiang Jinping , Na Kun , Zhang Xiaolin , Liu Dan , Jing Quanmin , Yan Chenghui , Han Yaling 
Published: April 2024

AbstractCoronavirus disease (COVID-19) and pulmonary hypertension (PH) are closely correlated. However, the mechanism is still poorly understood. In this article, we analyzed the molecular action network driving the emergence of this event. Two datasets (GSE113439 and GSE147507) from the GEO database were used for the identification of differentially expressed genes (DEGs).Common DEGs were selected by VennDiagram and their enrichment in biological pathways was analyzed. Candidate gene biomarkers were selected using three different machine-learning algorithms (SVM-RFE, LASSO, RF).The diagnostic efficacy of these foundational genes was validated using independent datasets. Eventually, we validated molecular docking and medication prediction. We found 62 common DEGs, including several ones that could be enriched for Immune Response and Inflammation. Two DEGs (SELE and CCL20) could be identified by machine-learning algorithms. They performed well in diagnostic tests on independent datasets. In particular, we observed an upregulation of functions associated with the adaptive immune response, the leukocyte-lymphocyte-driven immunological response, and the proinflammatory response. Moreover, by ssGSEA, natural killer T cells, activated dendritic cells, activated CD4 T cells, neutrophils, and plasmacytoid dendritic cells were correlated with COVID-19 and PH, with SELE and CCL20 showing the strongest correlation with dendritic cells. Potential therapeutic compounds like FENRETI-NIDE, AFLATOXIN B1 and 1-nitropyrene were predicted. Further molecular docking and molecular dynamics simulations showed that 1-nitropyrene had the most stable binding with SELE and CCL20.The findings indicated that SELE and CCL20 were identified as novel diagnostic biomarkers for COVID-19 complicated with PH, and the target of these two key genes, FENRETI-NIDE and 1-nitropyrene, was predicted to be a potential therapeutic target, thus providing new insights into the prediction and treatment of COVID-19 complicated with PH in clinical practice.
Interactions between Bacillus thuringiensis and selected plant extracts for sustainable management of Phthorimaea absoluta
Authors: Ochieng Terry A. , Akutse Komivi S. , Ajene Inusa J. , Kilalo Dora C. , Muiru Maina , Khamis Fathiya M. 
Published: April 2024

AbstractPhthorimaea absoluta is a global constraint to tomato production and can cause up to 100% yield loss. Farmers heavily rely on synthetic pesticides to manage this pest. However, these pesticides are detrimental to human, animal, and environmental health. Therefore, exploring eco-friendly, sustainable Integrated Pest Management approaches, including biopesticides as potential alternatives, is of paramount importance. In this context, the present study (i) evaluated the efficacy of 10 Bacillus thuringiensis isolates, neem, garlic, and fenugreek; (ii) assessed the interactions between the most potent plant extracts and B. thuringiensis isolates, and (iii) evaluated the gut microbial diversity due to the treatments for the development of novel formulations against P. absoluta. Neem recorded the highest mortality of 93.79 ± 3.12% with an LT50 value of 1.21 ± 0.24 days, Bt HD263 induced 91.3 ± 3.68% mortality with LT50 of 2.63 ± 0.11 days, compared to both Bt 43 and fenugreek that caused < 50% mortality. Larval mortality was further enhanced to 99 ± 1.04% when Bt HD263 and neem were combined. Furthermore, the microbiome analyses showed that Klebsiella, Escherichia and Enterobacter had the highest abundance in all treatments with Klebsiella being the most abundant. In addition, a shift in the abundance of the bacterial genera due to the treatments was observed. Our findings showed that neem, garlic, and Bt HD263 could effectively control P. absoluta and be integrated into IPM programs after validation by field efficacy trials.
Wideband low-RCS and gain-enhanced antenna using frequency selective absorber based on patterned graphene
Authors: Wang Fuwei , Wang Yi , Zhang Xiaoyu , Liu Lu , Li Ke , Ren Yuhui 
Published: April 2024

AbstractIn this paper, a double-layer patterned graphene-based frequency-selective absorber (DGFSA) is proposed as a means of reducing an antenna’s radar cross-section (RCS) while simultaneously increasing its gain. The antenna consists of a patch antenna with Multi-Graphene Frequency Selective Absorber (MGFSA) mounted on top. The DGFSA consists of double-layer patterned graphene and a band-pass frequency selective surface (FSS). Two patterned graphene lossy layers with different square resistances are used, which broaden the electromagnetic (EM) wave absorption bandwidth of the DGFSA, thus greatly reducing the out-band monostatic RCSs of the patch antenna. Meanwhile, due to the quasi-Fabry-Perot (F-P) effect, the gain of the proposed antenna is enhanced by 2.4 dB. Additionally, the low-RCS antenna reduces the monostatic RCS from 1.32 to 17 GHz under y-polarization and from 1.4 to 16.8 GHz under x-polarization, respectively. Furthermore, a decrease in the bistatic RCS is accomplished. Results from simulations and measurements match up nicely, which means the antenna we proposed has a good application on the stealth platform.
Experimental evidence on the role of shared protocols as coordination device on clinical best practices
Authors: Finocchiaro Castro Massimo , Lisi Domenico , Romeo Domenica 
Published: April 2024

AbstractOur experiment assesses the level of coordination on clinical best practice among physicians and investigates whether the release of guidelines helps in supporting coordination. Based on three clinical vignettes using current national guidelines, physicians evaluate the appropriateness of each of the proposed courses of action. Afterwards, physicians are allowed to ask which action corresponds to national guidelines and change their ratings, if desired. On average, slightly more than half of the sample coordinated on appropriateness evaluations. Empirical analysis indicates that several organizational and individual variables influence the level of coordination. Additionally, the release of national guidelines improved both the level of conformity and coordination. Our findings suggest changes in implementation practices to increase the impact of these shared protocols in the health field.
The natural history of neurolymphomatosis
Authors: Xu Elizabeth , Ho Quan , Liu Ashley , Gautam Shiva , Wong Eric T. 
Published: April 2024

Abstract
Background
Neurolymphomatosis is a lymphoid malignancy of the peripheral nervous system and its natural history is poorly understood.

Methods
We performed PubMed search and extracted clinical data for Kaplan-Meier statistics to determine outcome parameters over time. Kruskal-Wallis test was performed to compare prognostic factors.

Results
Our search identified 559 patients and their median age was 61 years. Median overall survival (OS) was 12.0 (range 10.0–15.0) months. Diffuse large B-cell lymphoma was the most frequent histology, involving the brachial plexus, cranial nerves, and sciatic nerve. None had molecular profiling. There was a progressive lengthening of OS in successive decades, from 0.5 (95% CI 0.0–0.8) to 26.4 (95% CI 18.0–34.8) months between 1951 and 2022 (r2 = 0.0528, p < 0.00001). Time from first treatment (treatment 1) to progression increased from 2.0 to 36.0 (95% CI 6.5–50.7) months (r2 = 0.0961, p = 0.00236). Time from symptom onset to diagnosis remained unchanged (r2 = 0.0000556, p = 0.939). Patients were most frequently treated with methotrexate, rituximab, and/or radiation either alone or in combination. Primary neurolymphomatosis had a better prognosis than secondary neurolymphomatosis. No OS difference was noted between B- and T-cell disease, but low-grade B-cell performed better than Burkitt’s lymphoma.

Discussion
Better outcome for patients with neurolymphomatosis is noted over time. But timely diagnosis remains a major problem that needs improvement.
A new virtual consensus‐based wide area differential protection
Authors: Koloushani Sayed Mahdi , Taher Seyed Abbas 
Published: April 2024

AbstractThis paper introduces a virtual consensus‐based wide area differential protection method through cooperative control concepts and graph theory. Using multi‐agent systems eliminates the need for a direct telecommunication connection between the protective relays to implement the proposed differential protection. In addition, applying telecommunication subgraphs facilitates the establishment of numerous differential protection areas. Collaboration between protected areas is facilitated by common agents, establishing a wide‐area cooperative protection network. The capability of the network operator to define various protection areas and the collaboration between these areas ensure the versatility of the proposed method for various protection purposes. The present paper primarily represents the application of the proposed protection system as a wide‐area supervisor protection for distance relays. Performance evaluations on an IEEE 39‐bus test system illustrate the method's effectiveness in various scenarios. The results show enhanced power system stability and resilience, particularly when traditional methods struggle to detect power swings with high impedance variation rates.
Spatio‐temporal attention modules in orientation‐magnitude‐response guided multi‐stream CNNs for human action recognition
Authors: Khezerlou Fatemeh , Baradarani Aryaz , Balafar Mohammad Ali , Maev Roman Gr. 
Published: April 2024

AbstractThis paper introduces a new descriptor called orientation‐magnitude response maps as a single 2D image to effectively explore motion patterns. Moreover, boosted multi‐stream CNN‐based model with various attention modules is designed for human action recognition. The model incorporates a convolutional self‐attention autoencoder to represent compressed and high‐level motion features. Sequential convolutional self‐attention modules are used to exploit the implicit relationships within motion patterns. Furthermore, 2D discrete wavelet transform is employed to decompose RGB frames into discriminative coefficients, providing supplementary spatial information related to the actors actions. A spatial attention block, implemented through the weighted inception module in a CNN‐based structure, is designed to weigh the multi‐scale neighbours of various image patches. Moreover, local and global body pose features are combined by extracting informative joints based on geometry features and joint trajectories in 3D space. To provide the importance of specific channels in pose descriptors, a multi‐scale channel attention module is proposed. For each data modality, a boosted CNN‐based model is designed, and the action predictions from different streams are seamlessly integrated. The effectiveness of the proposed model is evaluated across multiple datasets, including HMDB51, UTD‐MHAD, and MSR‐daily activity, showcasing its potential in the field of action recognition.
Predicting travel mode choice with a robust neural network and Shapley additive explanations analysis
Authors: Tang Li , Tang Chuanli , Fu Qi , Ma Changxi 
Published: April 2024

AbstractPredicting and understanding travellers’ mode choices is crucial to developing urban transportation systems and formulating traffic demand management strategies. Machine learning (ML) methods have been widely used as promising alternatives to traditional discrete choice models owing to their high prediction accuracy. However, a significant body of ML methods, especially the branch of neural networks, is constrained by overfitting and a lack of model interpretability. This study employs a neural network with feature selection for predicting travel mode choices and Shapley additive explanations (SHAP) analysis for model interpretation. A dataset collected in Chengdu, China was used for experimentation. The results reveal that the neural network achieves commendable prediction performance, with a 12% improvement over the traditional multinomial logit model. Also, feature selection using a combined result from two embedded methods can alleviate the overfitting tendency of the neural network, while establishing a more robust model against redundant or unnecessary variables. Additionally, the SHAP analysis identifies factors such as travel expenditure, age, driving experience, number of cars owned, individual monthly income, and trip purpose as significant features in our dataset. The heterogeneity of mode choice behaviour is significant among demographic groups, including different age, car ownership, and income levels.