bluuebunny/crossref_metadata_2025_split huggingface dataset:
Childhood-Onset Ocular Mucous Membrane Pemphigoid Presenting with Peripheral Ulcerative Keratitis: A Case Report and Review of the Literature
Authors: Ramos-Dávila Eugenia M. , Ruiz-Lozano Raul E. , Rodriguez-Garcia Alejandro , Alvarez-Guzman Carlos 
Published: June 2024

Abstract

Purpose
The purpose of this study was to describe the case of a pediatric patient diagnosed with mucous membrane pemphigoid (MMP) with exclusive ocular involvement presenting at diagnosis with peripheral ulcerative keratitis and provide a review of the literature.
Methods
A 12-year-old girl presented with cicatricial conjunctivitis and peripheral ulcerative keratitis (PUK). A conjunctival biopsy and direct immunofluorescence revealed linear deposits of IgG, IgM, and C3 at the basement membrane zone, confirming a diagnosis of ocular MMP.
Results
The patient was initially treated with dapsone 25 mg/day and prednisone 40 mg/day along with topical treatment including cyclosporine 0.05%, loteprednol etabonate 0.05%, and sodium hyaluronate 0.15% and trehalose 3%. Inflammation persisted as an increase in the extension of symblepharon was documented. Subsequently, dapsone was switched to oral methotrexate 15 mg/week and prednisone was successfully tapered to 5 mg/day. After three years of follow-up, disease activity remained quiescent.
Conclusions
Pediatric mucous membrane pemphigoid with ocular involvement is a rare condition of which few reports have been published, resulting in scarce information regarding its clinical course and response to treatment. We report the first case observed in a Hispanic patient, opening with peripheral ulcerative keratitis, and responding successfully to methotrexate.
Modeling and investigation on dynamic behaviors of ball screw feed system with bolt looseness
Authors: Liu Zhendong , Li Changyou , wang gongdong , xu mengtao , zhang hongzhuang , Li zhenyuan , Miao Hui , Wang Chen 
Published: June 2024

Abstract

In this study, a more comprehensive multi-degree-of-freedom nonlinear dynamic model of ball screw feed system is presented. The relationship between bolt preload and contact force of the interface force is established. A new pedestal force model considering bolt looseness and inclination of contact surface is established. Based on the spatial position between pedestal and foundation, the modeling method of contact force of interface is proposed. The influence of bolt preload and bolt looseness on the dynamics of the feed system are investigated. A series of experiments are conducted to validated the proposed modeling method. The fractal parameters are obtained by the measurement of surface morphology. The results show that the increased preload have impacts on the vibration response and reduce the positioning accuracy of the system in specific frequency. Moreover, the proposed model is compared with traditional method proposed by previous study.
A multi-centric, single blinded, randomized, parallel group study to evaluate the effectiveness of nasoalveolar moulding treatment in non-syndromic patients with complete unilateral cleft lip, alveolus, and palate (NAMUC study). A study protocol for a randomized controlled trial.
Authors: Thiruvenkatachari Badri , Bonanthaya Krishnamurthy , Kuijpers-Jagtman Anne Marie , Sandler Jonathan , Powar Rajesh Shankar , Hussain Syed Altaf , B Subramanian , Bhola Nitin , Bhat Hari Kishore , Ramachandra Varun , Jayakumar Sylvia , Batra Puneet , Chakkaravarthi Subhiksha , V Thailavathy , Prathap Manoj , Elumalai Thulasiram , Nambiar Karthika , Vijayakumar Charanya , Mahajan Ravi Kumar , Sood Sundereshwer Chander , Kahlon SukhdeepSingh , Bijapur Shruti , Kamble Ranjit Haridas , M Keluskar K , Nigalkar Amit , Khan Faizan Ahmed , Das Devika , Srid Swetha , Buch Adrija , Kumar Shuba , Mohanraj Rani , Listl Stefan , Chopra Samiksha , Jadhav Vikranth , Arora Anika , Valiya Chintan , Pattamata Madhuri 
Published: June 2024

Abstract

Background: Cleft lip and palate (CLP) are among the most common congenital anomaly that affects up to 33,000 newborns in India every year. Nasoalveolar moulding (NAM) is a non-surgical treatment performed between 0 and 6 months of age to reduce the cleft and improve the nasal aesthetics prior to lip surgery. The NAM treatment has been a controversial treatment option with 51% of the cleft teams in Europe, 37% of teams in the US and 25 of cleft teams in India adopting this methodology. This treatment adds to the already existing high burden of care for these patients. Furthermore, the supporting evidence for this technique is limited with no high-quality long term clinical trials available on the effectiveness of this treatment.
Method: The NAMUC study is an investigator initiated, multi-center, single blinded randomized controlled trial with a parallel group design. The study will compare the effectiveness of NAM treatment provided prior to lip surgery against no treatment control group in 274 patients with non syndromic unilateral complete cleft lip and palate. The primary endpoint of the trial is the nasolabial aesthetics measured using Asher McDade index at 5 years of age. The secondary outcomes include dentofacial development, speech, hearing, cost effectiveness, quality of life, patient perception, feeding and intangible benefits. Randomization will be carried out via central online system and stratified based on cleft width, birth weight and clinical trial site.
Discussion: We expect the results from this study on the effectiveness of treatment with NAM appliance in the long term along with the cost effectiveness evaluation can eliminate the dilemma and differences in clinical care across the globe.
Trial Registration number: CTRI/2022/11/047426 (Clinical Trials Registry India) CTR India does not pick up on Google search with just the trial number. The following steps have to be carried out to pick up. How to search: (https://ctri.nic.in/Clinicaltrials/advsearch.php - use the search boxes by entering the following details: Interventional trial>November 2022>NAMUC)
Exercise Enhances Cardiomyocytic Mitochondrial Homeostasis to Alleviate Left Ventricular Dysfunction in Pressure Overload-Induced Remodelling
Authors: Ma Zhichao , Cen Yanling , Xun Weiwei , Mou Caiying , Yu Junwen , Hu Yarui , Liu Chen , Sun Jun , Bi Rui , Qiu Yanli , Ding Mingchao , Jin Li 
Published: June 2024

Abstract

Background: This study aims to explore how exercise enhances mitochondrial regulation and mitigates pathological cardiac hypertrophy.
Methods: Rat groups were assigned as CN, sham, SC, and SE. A bioinformatics analysis was conducted to uncover the underlying mechanisms.H9C2 cells were divided into: CON, Ang II, sh-GFP+Ang II, sh-ndufb10+Ang II, Ad-GFP+Ang II, and Ad-ndufb10+Ang II. Mitochondrial function was measured. mRNA and protein expression were assessed by qPCR or western blot analysis respectively.
Results: In the SC group, a significant increase was observed in cardiomyocyte diameter, function, autophagy, and apoptosis. After 8 weeks of swimming exercise, there was a substantial reduction in cardiomyocyte diameter, an improvement in cardiac function, a mitigation of mitochondrial fission and autophagy, and cardiomyocyte. Ndufb10 was markedly enriched in oxidative phosphorylation and downregulated in the SC group, while it was upregulated in the SE group. In the sh-ndufb10 group, mitochondrial fusion was suppressed; fission and autophagy were further facilitated; mitochondrial membrane potential, mPTP, and ROS levels increased; and TUNEL and apoptosis-related proteins showed significant upregulation. Overexpression of ndufb10 reversed pathological hypertrophy, mitochondrial autophagy, mitochondrial dysfunction, and cardiomyocyte in vitro.
Conclusions: Swimming exercise improves mitochondrial abnormalities and reduces cardiomyocyte through regulation of the ndufb10 in left ventricular hypertrophy.
Post-traumatic stress symptoms in interpreters assisting in psychotherapy- one-year follow-up
Authors: Herold Monja Lucia , Müller Lauritz Rudolf Floribert , Unterhitzenberger Johanna , Rosner Rita 
Published: June 2024

Abstract

Background: Interpreters are an important support in psychotherapy with patients who do not speak the national language. In the primarily qualitative literature, post-traumatic stress symptoms (PTSS) in interpreters are frequently mentioned, especially when translating traumatic content in trauma-focused psychotherapy. Possible risk and protective factors identified in research are the measurement occasion an attitude supporting psychotherapy, knowledge about post-traumatic stress and trauma-focused therapy, the working experience of the interpreters in years, Involvement of Interpreters in Trauma-Therapy, own refugee experience and any kind of qualificationbefore the training.
Method: A total of 134 interpreters registered for a workshop on translation in the context of trauma-focused cognitive behavioral therapy. Questionnaires were completed via Qualtrics before and after the workshop, and at 6 and 12 months. The Post Traumatic Stress Disorder (PTSD) Checklist for DSM-5 (PCL-5) was used to assess the interpreters’ PTSS. Hierarchical linear models were calculated with the R package lme4 to examine the development of PTSS symptoms over time and possible influencing factors.
Results: The interpreters’ PTSS did not change significantly over the one-year period. Attitude and knowledge had a positive influence on PTSS, while participation in trauma therapy had a negative influence on PTSS.
Discussion: Results show that the interpreters’ PTSS remained stable over the course of one year. However, translating in psychotherapy during this period represents a risk factor for interpreters´ PTSS. Further research on possible risk and protective factors for interpreters’ PTSS is necessary. One of the limitations of the present study is that it is a convenient and uncontrolled sample.
The health care needs and associated factors of breast cancer patients in shanghai, china
Authors: Chen Minxing , Zhu Qing , Qin Qiujun , Song Wenhua , Li Ruijia , Song Jie , Jin Chunlin 
Published: June 2024

Abstract

Background: As the number of breast cancer survivors increases, fatigue, poor physical fitness, and sleep quality issues begin to emerge, and there is a broad range of unmet health care needs.
Objective: To accurately identify and measure the unmet health care needs of breast cancer patients, analyze the impact of sociodemographic factors, clinical characteristics, and other factors on the multiple needs of patients, and identify emerging needs and trends in care in order to provide better health care.
Methods: A cross-sectional study of 6,020 cancer patients in Shanghai, focusing on 2,525 female breast cancer patients, was conducted to investigate their socio-demographic information, financial toxicity grade, physical status, and health care needs, and to explore the relationship among socio-demographic factors, financial toxicity, physical status, and health care service needs through descriptive statistics and multiple linear regression analysis.
Results: The unmet needs of breast cancer patients were concentrated in the areas of health education and social support (1.70 ± 0.85), with the most common needs including information, comorbidity management, sleep guidance, and TCM rehabilitation. Bachelor's degree and above (β=8.06, P<0.001), limited self-care (β=16.29, P=0.01), and moderate financial toxicity (β=14.35, P<0.001) were associated with high levels of unmet medical needs, and tumor secondary/metastasis (β=1.52, P=0.01) was associated with unmet needs for primary medical care, health education, and social support.
Conclusion: The overall health care needs of breast cancer patients are at a low level, and new needs such as comorbidity management, sleep guidance, and Chinese medicine rehabilitation have emerged among patients. In the future, it is necessary to combine multidisciplinary and individual characteristics to provide appropriate health care services.
Development of a predictive classification model and extraction of signature wavelengths for the identification of spoilage in chicken breast fillets during storage using Near Infrared Spectroscopy
Authors: Siddique Aftab , Herron Charles B. , Wu Bet , Melendrez Katherine S.S. , Sabillon Luis J. G. , Garner Laura J. , Durstock Mary , Sanz-Saez Alvaro , Morey Amit 
Published: June 2024

Abstract

Technologies for rapid identification and prediction of food spoilage can be crucial in minimizing food waste and losses, although their efficiency requires further improvement. This study aimed to pinpoint specific near-infrared (NIR) wavelengths that could indicate spoilage in raw chicken breast fillets. In this study, commercial tray-packs of boneless, skinless chicken breast fillets stored in a walk-in cooler at 4˚C were periodically tested every other day until they reached the spoilage state (identified by > 7 log CFU/ml). A portable Hyper spectral spectroscopy device (Field Spec Hi-Res4), with a range of wavelengths of 350–2500 nm, was used to measure reflectance. In addition to hyper-spectral analysis, aerobic plate counts were conducted on the fillets. The data from these counts were then used to train a Back Propagation Neural Network (B.P.N.N.) with specific parameters (250,000 steps, a learning rate of 0.02, and 5 hidden layers) and Linear-Support Vector machines (SVM-Linear) with ten-fold cross-validation technique to categorize spoilage into three stages: baseline microbial count (up to 3 log CFU/ml) (Initiation), propagation (between 3 and 6.9 log CFU/ml), and spoiled (> 7 log CFU/ml). The feature extraction process successfully identified the most representative six signature wavelengths from the whole hyper-spectral profile, which facilitated the classification of different phases of spoilage. The BPNN model demonstrated a high classification accuracy, with 93.7% for baseline counts, 95.2% for the propagation phase, and 98% for the spoiled category. These signature hyperspectral wavelengths hold the potential for developing cost-effective and rapid food spoilage detection systems, particularly for perishable items.
pH modulation for high capacity and long cycle life of aqueous zinc-ion batteries with β-MnO2 /3D graphene-carbon nanotube hybrids as cathode
Authors: Jin Duolong , Dong Xiaoping , Liu Jiankai , Pang Qianran , Xin Shenghai , Yang Liying , Wang Cuibiao 
Published: June 2024

Abstract

With the continuous development of new energy application technology, there is an increasingly urgent need for the safety and affordability of new energy storage products. In recent years, aqueous zinc-ion batteries based on mild aqueous electrolytes have garnered widespread attention as a potential replacement for traditional lithium-ion batteries. However, the limited capacity and low operating voltage of aqueous zinc-ion batteries restrict their widespread application. For this reason, sulfuric acid was added to the electrolyte, which effectively promotes the two-electron conversion of MnO2/Mn2+ during the discharge process. This enhancement results in the high-voltage segment of the batteries' discharge phase offering a higher reversible specific capacity. The results showed that the batteries with 0.1 M H2SO4 added to the electrolyte had a reversible discharge specific capacity of up to 536.07 mAh·g-1 at a current density of 100 mA·g-1. The activated batteries exhibited a reversible specific capacity of 85.11 mAh·g-1 even at a high current density of 1 A·g-1. Furthermore, the capacity retention rate after 1,000 cycles was 88.3%. Moreover, the activation rate of the batteries was faster with the addition of H2SO4, and the average operating potential increased compared to the batteries without H2SO4 in the electrolyte. This provides an effective solution for the practical application of aqueous zinc-ion batteries in power grids.
Political Expression of Academics on Social Media
Authors: Garg Prashant , Fetzer Thiemo 
Published: June 2024

Abstract

Academics have traditionally played a vital role in both the generation and dissemination of knowledge, ideas and narratives. Social media, relative to traditional media, provides for new and more direct ways of science communication. Yet, since not all academics may engage with social media, the sample that does so may have an outsize influence on shaping public perceptions of academia more broadly through at least two channels: the set topics they engage with and through the particular style and tone of communication. This paper describes patterns in academics' expression online found in a newly constructed global dataset covering over 100,000 scholars linking their social media content to academic record. We document large and systematic variation in politically salient academic expression concerning climate action, cultural, and economic concepts. We show that these appear to often diverge from general public opinion in both topic focus and style.
Deep Learning-based Visual Risk Warning System for Autonomous Driving
Authors: Qiu Chengqun , Tang Hao , Xu Xixi , Peng Yu , Ji Jie , Ji Xinchen , Lin Shengqiang 
Published: June 2024

Abstract

In autonomous driving, the identification and tracking of multiple vehicles on the road are critical tasks. This paper aims to develop a risk warning system using deep learning algorithms to address the heterogeneous, high-dynamic, and complex driving environments. To enhance the generalization capability and detection accuracy of small objects in road perception, we propose a novel VBFNet-YOLOv8 algorithm for real-time vehicle identification, tracking, distance measurement, and speed estimation. Specifically, we replace the Backbone of the original YOLOv8 network with the VanillaNet structure and upgrade the traditional PANet in the neck part to Bi-FPN. By integrating the optimized YOLOv8n algorithm with Deepsort and TTC algorithms, we achieve a comprehensive road risk assessment. The algorithm continuously tracks the targets, and the TTC algorithm intuitively assesses the risk. Finally, the system provides layered warnings by changing the color of the bounding boxes, offering drivers an integrated and real-time risk alert. Comparative experimental results show that the optimized algorithm improves Precision by 0.61%, mAP@0.5 by 0.63%, and mAP@0.5:0.95 by 0.70%. In the road tests on sections A and B, the detection frame rate of the risk warning system maintained a minimum of 37.1fps and a maximum of 56.4fps. The detection Confidence of various objects remained above 0.67, reaching up to 0.97.
AFCNet:An adaptive fusion of composite attention convolutional neuralnetwork for polyp image segmentation
Authors: Jin Bo jiao , Zhang Yi , Qi Lin , Qian Wei 
Published: June 2024

Abstract

Accurately locating and segmenting polyps from colon images is crucial for the treatment of rectal cancer. However, the environment of rectal polyps is characterized by high noise, diverse sizes, complex boundaries, and a high demand for detailed information, making the task challenging. The acquisition and processing of polyp features are central to the research on polyp segmentation methods. This paper introduces an Adaptive Fusion Of Composite Attention Convolutional Neural Network (AFCNet) for polyp image segmentation. First, this work combine depth-wise separable convolutions and convolutional attention mechanisms with a multi-branch structure to better supplement missing details and unearth potential critical features. Secondly, we employ a multi-scale cross structure and an adaptive multi-scale feature harmonization module to balance the contribution of features at different levels, thus fully integrating information across scales to maximize the utilization of previously acquired features. Lastly, we propose an upsampling feature retrospective module to filter detailed information and use the concept of gating units to filter out interfering information. Extensive experiments on five publicly available polyp segmentation datasets demonstrate the effectiveness of our AFCNet in enhancing the accuracy of polyp segmentation.The experimental results indicate that AFCNet significantly outperforms state-of-the-art models. AFCNet is an effective polyp segmentation network, and due to its excellent generalization ability, it can also be applied to other medical image segmentation tasks.
MRS-YOLO: A High-Precision Model for Efficient Waste Detection and Classification
Authors: Ren Yuanming , Li Yizhe , Gao XinYa 
Published: June 2024

Abstract

With the advancement in living standards, there has been a significant surge in the quantity and diversity of household waste. To safeguard the environment and optimize resource utilization, there is an urgent demand for effective and cost-efficient intelligent waste classification methodologies. This study presents MRS-YOLO (Multi-Resolution Strategy-YOLO), a waste detection and classification model. The paper introduces the SlideLoss_IOU technique for detecting small objects, integrates RepVit into the Transformer mechanism, and devises a novel feature extraction strategy by amalgamating multi-dimensional and dynamic convolution mechanisms. These enhancements not only elevate the detection accuracy and speed but also bolster the robustness of the current YOLO model. Validation conducted on a dataset comprising 18,219 samples across 10 categories, including recyclable metal and paper, reveals a 3.53% enhancement in mAP50% accuracy compared to YOLO v8, coupled with a 15.09% reduction in volume. Furthermore, the model demonstrates improved accuracy in detecting small targets and exhibits comprehensive detection capabilities across diverse scenarios.