bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lactobacillus yogurts display antidepressant-like effects in CUMS mice via inhibition of NF-κB pathway, activating CREB-BDNF pathway and regulating gut-brain axis
Authors: Sun Yang , Li Xiujuan , Li Xiulian , Liu Lun , Wei Song 
Published: November 2024

Abstract

In this work, we compared the effects of probiotics (Lactobacillus reuteri and Lactobacillus bulgaricus) fermented yogurt on chronic unpredictable mild stress (CUMS)-induced anxious and depressive-like symptoms in mice as well as discussed potential mechanism. The behavioral test results showed that L. reuteri and L. bulgaricus fermented yogurt significantly improved anxious- and depressive-like symptoms. We also found that Lactobacillus fermented yogurt presented an overall neuroprotective effect on hippocampus as well as maintained the cerebral activity. L. reuteri and L. bulgaricus fermented yogurts also were observed to ameliorate the levels of monoamine neurotransmitters and inflammatory cytokines via inhibiting the activation of NF-κB pathway accompanying with elevating the CREB-BDNF pathway. The Our findings suggested that L. reuteri and L. bulgaricus fermented yogurts may be involved in modulating gut microbiota and metabolite composition, and thereby performing neuroprotective effects and ameliorating depressive behaviors in mice by at least partially microbiota-gut-brain axis.
A Defect Detection Algorithm for Steel Wire Ropes Based on Dual-residual Fast Convolution and Channel Feature Selection Mechanism
Authors: Liu Qunpo , Wang Hui , BU Xuhui , Hanajima Naohiko , Ding Weiping 
Published: November 2024

Abstract

To address the challenges of feature extraction redundancy and insufficient feature layer fusion present in the original RTDETR algorithm?both of which contribute to an increase in parameters and a loss of target semantic information ultimately leading to blueuced accuracy?this paper proposes a novel RTDETR object detection algorithm. This enhanced version employs a multi-scale fusion network that utilizes dual-residual fast convolution and channel feature selection to improve performance. Firstly, we integrate the proposed dual-residual fast convolution module into the backbone network of the RTDETR to extract effectively spatial features through partial convolution operations on the extracted features, thereby reducing computational redundancy and memory access. In addition, we designed a multi-scale feature fusion network based on channel feature selection. This network employs a channel feature selection module to extract key information and utilizes the semantic information from high-level feature maps as weights to guide the selection and fusion of low-level features, thereby enhancing the capability for feature information integration among multi-scale features. The final step is the introduction of the Wiou loss function, which addresses the issue of data class imbalance for defect types through weight adjustment, thereby improving the detection through the network. The experimental results show that, on the steel wire rope dataset, the improved MRD model achieves an mAP\_0.5 of 89.6\%, which represents a 1.4\% increase in mAP\_0.5 detection acquisition. Additionally, the overall number of parameters is slashed by 27.2\%, and the detection speed reaches 70.6 FPS. The improved MRD model exhibits greater robustness and superior performance in recognition of the steel wire rope, meeting the requirements for real-time industrial inspection.
Hyperinflammatory status associated with COVID-19: clinical and histopathology features of a pediatric series
Authors: Leite Douglas Squizatto , Cortes Lucas Silva , Domingues Maria Aparecida Maria Aparecida Custódio , Magalhaes Claudia Saad , Fernandes Taciana de Albuquerque Pedrosa 
Published: November 2024

Abstract

Objective: Explore clinical, demographic and histopathologic features of pediatric hyperinflammatory manifestations associated to SARS-CoV-2, observed during the COVID-19 pandemic, and the relationship of Multisystemic Inflammatory Syndrome of Childhood (MIS-C) with other inflammatory and autoimmune manifestations, such as macrophage activation syndrome, vasculitis and vasculopathy.
Methods: A protocol with detailed socio-demographic and clinical features, SARS-CoV-2 exposure and morbidity was conducted in a public tertiary hospital as part of a multicentric international protocol. Cases were selected and enrolled in a single centre from 2020 to 2022, recording all the organ and systems manifestations, standard treatment and outcome.
Results: Of the 23 suspicious cases, 21 met the inclusion criteria of MIS-C. Gastrointestinal manifestations were frequent, and three out of 21 had acute abdomen, one with documented histiocytic necrotizing lymphadenopathy (HNL), 3 had macrophage activation syndrome (MAS), and one case, with previous enthesitis related arthritis evolved into type V Takayasu arteritis and malignant hypertension. All patients were treated with either intravenous immunoglobulin (IVIG), high dose glucocorticoids or both, five were under intensive care treatment with respiratory and cardio-circulatory support. All had full recovery during acute phase. Description the HNL histopathology showed proliferation of small lymphocytes and macrophage infiltrates with microthrombi and lymph nodes germinal centers necrosis.
Conclusion: Post-infectious hyperinflammatory states associated with COVID manifestations may cause not only to transient inflammatory features, but also autoimmunity, vasculitis and vasculopathy manifestations that require prompt treatment.
Enhanced Single Image Super-Resolution using Modified Very DeepSuper Resolution Network - Gaussian Mixture Models
Authors: Gunen Mehmet Akif 
Published: November 2024

Abstract

Single Image Super-Resolution (SISR) aims to enhance the quality of low-resolution images by reconstructing their high-resolution counterparts. This paper proposes a hybrid method, termed mVDSR-GMM, which leverages the strengths of both Gaussian Mixture Models (GMM) and a modified Very Deep Super-Resolution (mVDSR) network. The mVDSR-GMM method utilizes GMM to model the statistical properties of high-resolution images, enabling accurate reconstruction of high-frequency details. The enhanced mVDSR network, with increased depth and Leaky ReLU activation functions, further boosts the model's learning capability and robustness. Through extensive evaluations using satellite imagery datasets and metrics such as PSNR, SSIM, BRISQUE, and MSE, mVDSR-GMM consistently outperformed existing techniques, demonstrating its effectiveness in improving spatial resolution. Notably, the hybrid method showed superior classification performance in land use/cover analysis compared to the traditional Bicubic method. The proposed mVDSR-GMM emerges as a promising tool for advancing satellite imagery resolution, with potential applications in remote sensing and geospatial analysis.
Automatic detection of thermal fusion joints defects of high-density polyethylene gas pipes using ultrasonic total focusing method and deep learning
Authors: Chen Tianliang , Wang Qiang , Xiao Quanjing , Wang Hong , Liu Yanlei 
Published: November 2024

Abstract

Inspection of thermal fusion joints is essential for in-service high-density polyethylene (HDPE) gas pipe operating safety. A directivity-compensated circular coherence factor weighted total focusing method (D-CCF-TFM) algorithm is presented to solve the problem of low imaging quality of phased array ultrasonic testing during inspecting thermal fusion joints of HDPE pipes. The D-CCF-TFM leverages the circular coherence factor (CCF) to reduce noise interference during calculating the phase of defect and employs a directivity function to compensate sound field intensities in different directions, leading to obvious average signal-to-noise ratio (SNR) improvement compared to TFM, as confirmed through experiments on thermal fusion joint and test block. To automate defect detection in D-CCF-TFM images, an improved YOLOX algorithm is proposed, incorporating a convolutional block attention module (CBAM) and adopting the complete intersection over union (CIoU) as the regression loss. Evaluation of this improved YOLOX algorithm on a dataset of 2504 images yielded a mean average precision (mAP) of 99.15%, demonstrating its effect in detecting small defects. Thus, it provides theoretical and technical support for quality detection of thermal fusion joint welding.
Community Wellbeing Mediates Drought Adaptation in South African Rangelands
Authors: Clark Matt , Gallizioli Iacopo Tito , Crowe Olivia , Pienkowski Thomas , de Wet Ruan , Haw Anna Jean , Mills Morena 
Published: November 2024

Abstract

Climate change is triggering a diverse set of adaptive responses from communities across environmental and socioeconomic contexts. In African rangelands, selling livestock is critical for responding to changes in local environmental conditions. As these decisions further affect environmental and community wellbeing, identifying where, when, and how livestock sales are expected to respond to particular climatic shifts is important for delineating the total impact of climate change and responding accordingly. Scattered evidence suggests that socioeconomic wellbeing mediates how communities use cattle sales in response to precipitation. However, this has not been quantified as a generalizable trend across local to regional scales or within and between years. This study examines the relationship between socioeconomic wellbeing (measured through a standard deprivation index), precipitation, and monthly cattle slaughtering across South Africa from 2015 to 2022. We find that in better-off provinces (-1 standard deviation of deprivation), expected cattle slaughtering declined from 73,296 (90% CI: 38,430–130,709) under the highest observed precipitation, to 57,897 (90% CI: 30,431–103,378) in response to the lowest observed precipitation. In contrast, in worse-off provinces (+ 1 standard deviation), expected cattle slaughtering increased from 10,306 (90% CI: 5,916–19,753) under high precipitation, to 19,966 (90% CI: 11,437–38,245) in response to low precipitation. We further investigate this dynamic using a novel disaggregation regression statistical procedure, showing similar standardized effects sizes at a 16-km spatial resolution for the year 2020 and producing high-resolution estimates of where slaughtering was most likely given socioeconomic and environmental conditions. Our findings show that poorer communities are more prone to selling cattle in response to precipitation shortages, a practice that can erode long-term resilience and deepen inequalities. This general trend suggests that interventions encouraging strategic destocking during favorable conditions and maintaining herd health during droughts can build resilience in disadvantaged pastoral areas. Identifying such archetypal patterns can guide more deliberate implementation of interventions to support climate adaptation across many social-ecological settings.
Simulation-based process optimization of full-scale advanced wastewater treatment systems using powdered activated carbon
Authors: Atallah Al-asad Hana , Alex Jens , Parniske Janna , Morck Tobias 
Published: November 2024

ABSTRACT
This study extends a previously developed competitive modeling approach for predicting the adsorption of organic micropollutants (OMPs) on powdered activated carbon (PAC) in full-scale advanced wastewater treatment. The approach incorporates adsorption analysis for organic matter fractionation, assumes pseudo-first order kinetics and differentiates between fresh and partially loaded PAC through fraction segregation. Validation through full-scale measurement campaigns reveals successful model predictions of OMP removal, underestimating, however, diclofenac removals by 15–20%. Based on model testing, the impact of excess PAC return to the biological stage enhanced OMP removal, reaching up to 15% improvement for benzotriazole, carbamazepine and metoprolol, but no evident improvement of diclofenac removal. Intermittent PAC dosing revealed rapid process response, where organic matter concentration increased within 2 h after PAC cut-off. The simulation-based study demonstrated that during rain events, the overall OMP removal efficiency in the entire wastewater treatment plant was reduced by approximately 50% due to a shift of OMP concentration and a shortened hydraulic retention time in the biological and adsorption stages. Testing of various PAC dosing strategies revealed potential PAC savings of 10–15% compared to inflow-proportional dosing by using predefined OMP removal grades or maximum allowable effluent OMP concentrations as criteria for PAC dosing.
Anti-inflammatory and Anti-proliferative Role of Essential Oil of Leaves of Cleistocalyx operculatus (Roxb.) Merr. & Perry
Authors: Pandey Vivek , Khanal Sumnath , Shahi Nerina , Parajuli Rupak , Adhikari Achyut , Pokharel Yuba Raj 
Published: November 2024

Background:
Phytochemicals have long remained an essential component of the traditional medicine
system worldwide. Advancement of research in phytochemicals has led to the identification of novel constituents
and metabolites from phytochemicals, performing various vital functions ranging from antimicrobial properties to
anticarcinogenic roles. This plant is traditionally used by local people to manage inflammation. In this study, we
aim to extract and chemically profile the essential oil from the leaves of Cleistocalyx operculatus (Roxb.) Merr.
& Perry and study of the anti-inflammatory and anti-proliferative role of essential oil.

Methods:
The hydro distillation method was used for the extraction of essential oil, and the GC-MS was applied
for the chemical profiling. The percentage of cell viability was calculated using a crystal violet assay, colony
formation assay was performed using Semiquantitative PCR, Propodium iodite staining was used for cell death
assay, and Western blotting was used to determine antibodies and proteins. Schrodinger 2015 software was used
for molecular docking.

Results:
Myrcene, a monoterpene, constitutes 56% of the oil and could be attributed to its anti-inflammatory
potential. Treatment of LPS-challenged mouse macrophages RAW264.7 cells with essential oil resulted in a
decline in the inflammatory markers, such as IL-1β, TNFα, iNOS, COX-2, and NFκB. Further, essential oil inhibited
cancer PC-3, A431, A549, and MCF-7 cell lines at concentrations lower than normal PNT2 and HEK-293
cell lines. This decline in proliferative potential can be attributed to a decline in anti-apoptotic proteins, such as
procaspase 3 and PARP, an increase in CKIs, such as p21, and a decline in the Akt signaling responsible for
survival.

Conclusion:
The essential oil of the plant Cleistocalyx operculatus may be a potential lead for anti-inflammatory
and anti-proliferative function.
Uncovering Specific Navigation Patterns by Assessing User Engagement of People With Dementia and Family Caregivers With an Advance Care Planning Website: Quantitative Analysis of Web Log Data
Authors: Dupont Charlèss , Smets Tinne , Potts Courtney , Monnet Fanny , Pivodic Lara , De Vleminck Aline , Van Audenhove Chantal , Mulvenna Maurice , Van den Block Lieve 
Published: November 2024

Abstract

Background
Web-based tools have gained popularity to inform and empower individuals in advance care planning. We have developed an interactive website tailored to the unique needs of people with dementia and their families to support advance care planning. This website aims to break away from the rigid pathways shown in other tools that support advance care planning, in which advance care planning is shown as a linear process from information to reflection, communication, and documentation.

Objective
This study aimed to assess the website’s usage by people with dementia and their family caregivers, identify distinct user engagement patterns, and visualize how users navigated the website.

Methods
We analyzed the website’s log data obtained from an 8-week evaluation study of the site. Interactions with the website were collected in log data files and included visited web pages or clicked-on hyperlinks. Distinct user engagement patterns were identified using K-means clustering process mining, a technique that extracts insights from log data to model and visualize workflows, was applied to visualize user pathways through the website.

Results
A total of 52 participants, 21 individuals with dementia and their family caregivers as dyads and 10 family caregivers were included in the study. Throughout the 8-week study, users spent an average of 35.3 (SD 82.9) minutes over 5.5 (SD 3.4) unique days on the website. Family caregivers mostly used the website (alone or with a person with dementia) throughout the 8-week study. Only 3 people with dementia used it on their own. In total, 3 distinct engagement patterns emerged: low, moderate, and high. Low-engagement participants spent less time on the website during the 8 weeks, following a linear path from information to communication to documentation. Moderate- and high-engagement users showed more dynamic patterns, frequently navigating between information pages and communication tools to facilitate exploration of aspects related to advance care planning.

Conclusions
The diverse engagement patterns underscore the need for personalized support in advance care planning and challenge the conventional linear advance care planning representations found in other web-based tools.
Pasar Kerja dan Migran Kembali di Kabupaten Perbatasan Kalimantan Barat-Sarawak
Authors: Djafar Fariastuti 
Published: November 2024

Abstrak. Pengalaman sebagai migran seharusnya dapat membantu migran kembali untuk mendapatkan pekerjaan yang lebih baik guna mengurangi tekanan ekonomi. Tekanan ekonomi cenderung mendorong warga untuk menjadi migran berulang yang sebagian berstatus ilegal. Sementara itu, Kabupaten Sambas berbatasan darat dengan Sarawak, Malaysia, yang banyak menawarkan pekerjaan berketerampilan rendah dengan upah yang relatif tinggi. Penelitian ini bertujuan untuk mengelaborasi pasar kerja lokal dan menginvestigasi jenis pekerjaan migran kembali. Penelitian ini menggunakan data sekunder terutama yang bersumber dari BPS dan data primer yang dikumpulkan dengan melakukan wawancara terstruktur dan mendalam serta observasi nonpartisipasi. Hasil penelitian memberikan konfirmasi bahwa Sambas adalah sumber pekerja migran, di mana penawaran tenaga kerja perempuan usia muda lebih tinggi dari laki-laki. Penawaran tenaga kerja didominasi oleh tamatan sekolah menengah, sementara sebagian besar permintaan tenaga kerja adalah untuk tamatan SD atau lebih rendah. Permintaan tenaga kerja juga didominasi oleh sektor primer, buruh/karyawan bagi laki-laki serta pekerja tak dibayar bagi perempuan. Pasar kerja di Sambas telah menyebabkan pengalaman sebagai migran kurang berdampak terhadap jenis pekerjaan migran kembali. Sebagian besar pekerjaan responden saat kembali tidak jauh berbeda dengan pekerjaan saat migrasi. Tingkat upah yang lebih rendah di tempat asal pada akhirnya mendorong sebagian mantan migran kembali menjadi pekerja migran. Abstract. The migration experience should help returning migrants find better jobs in their place of origin, reducing their economic pressures and the likelihood of re-migrating to Malaysia and working illegally. Meanwhile, Sambas district shares a land border with Sarawak which offers many low-skilled jobs with relatively high wages. This research used secondary data mainly published by Statistics Indonesia and primary data collected by conducting structured and in-depth interviews and non-participatory observation. Findings in this research confirm that Sambas as a source of labour migrants. That is indicated by the higher female than male labour supply in the 15-19 age group. The labour supply is dominated by high school graduates, while labour demand is mostly for completed primary education or less. Labour demand is also dominated by the primary sector, male labourers/employees and unpaid female workers. The job market in Sambas has made migration experience have less impact on the employment of returning migrants, as they mostly work in occupations similar to or worse than those during their migration. The low wage level in their place of origin ultimately encourages some former migrants to re-migrate for work. Submitted: 2024-03-03 Revisions: 2024-04-26 Accepted: 2024-09-11 Published: 2024-09-25
Formulation and Validation of Herbosomes Loaded Herbal Topical Preparation for Eczema
Authors: Vidhale Gunjan S. , Waghulkar V.M. , Jadhao Dr. M.P. , Game Dr. M.D. , Jawarkar S.G. 
Published: November 2024

Eczema, a common inflammatory skin condition, presents significant challenges in management due to its multifactorial etiology and diverse clinical manifestations. Characterized by pruritus, erythema, and eczematous lesions, eczema negatively impacts patients' quality of life and requires comprehensive treatment approaches. Conventional treatments include topical corticosteroids, moisturizers, and immunomodulators, which provide symptomatic relief but may be associated with adverse effects and limited long- term efficacy. In recent years, there has been growing interest in alternative therapies, including herbal medicines, probiotics, and phototherapy, for eczema management.Herbal remedies, such as Berberis Aquifolium, have shown promise in eczema treatment due to their anti-inflammatory and antimicrobial properties. Novel drug delivery systems, such as Herbosomes, offer innovative approaches to enhance the bioavailability and efficacy of herbal constituents for eczema management. In the present study, the Berberis Aquifolium herbosomal lotion was formulated and used for an analytical method that is Ultraviolet spectroscopy (UV) which is developed and validated. In the method development solvent used is distilled water. The method is validated for linearity, range, limit of detection, limit of quantification, precision, and robustness. The developed analytical method was found to be simple, reliable, precise, and robust. The validated UV Spectroscopy method was successfully applied for quantification of Berberis Aquifolium loaded Herbosomal lotion.
Unlocking the Potential of Niosomes: A Comprehensive Review
Authors: Ritthe Punam V. , Fugate Dr. Ajay , Shafi Dr. Sameer , Rudrurkar Muktai N. , Kazi Anis J. , Patil Sneha R. , Sante Rohini U. , Shaikh. Imran 
Published: November 2024

Niosomes are vesicular systems that are similar to liposomes and are obtained by hydrating synthetic nonionic surfactants, with or without incorporating cholesterol or their lipids. They can be used as carriers for amphiphilic and lipophilic drugs and are biodegradable, biocompatible, non-immunogenic, and flexible in their structural characterization. Niosomes have been widely evaluated for controlled release and targeted delivery for the treatment of cancer, viral infections, and other microbial diseases. They can entrap both hydrophilic and lipophilic drugs and prolong the circulation of the entrapped drug in the body. By encapsulating drugs in a vesicular system, the existence of the drug in the systemic circulation can be extended, and penetration into target tissue can be enhanced, reducing toxicity if selective uptake can be achieved. This review article focuses on the advantages, disadvantages, types, preparation methods, factors affecting, characterizations and applications of niosomes.