bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of factors related to prolonged midazolam action: A multicenter, case-control study
Authors: Yano Takaaki , Watanabe Shinichi , Mori Yuto , Yamashita Noboru , Sakamoto Yuya , Oda Shinji , Hidaka Noriaki , Otsuka Takashi , Tanaka Mamoru 
Published: May 2024

Abstract

Background
Benzodiazepine midazolam is characterized by a rapid onset of action and a short half-life and is used for deep sedation in critically ill patients; however, hepatic and renal dysfunction, obesity, and prolonged use of midazolam are reported to prolong midazolam action. A few studies have investigated the association between midazolam use and hypoalbuminemia in critically ill patients. Therefore, this study aimed to investigate the effects of patient background on the prolonged action of midazolam by focusing on previously reported factors and albumin levels.
Methods
A total of 196 patients aged ≥ 18 years who were admitted to the University Hospital and Matsuyama Shimin Hospital intensive care unit between January 2015 and May 2022 and were administered midazolam continuously for ≥ 24 h were enrolled. Patient data, such as background, laboratory test values, and status of sedative drug use, including midazolam, were obtained from medical records. The primary outcome was the time required for improvement of the Richmond Agitation–Sedation Scale score after midazolam administration. Factors related to the prolongation of midazolam action were analyzed using the Mann–Whitney U test and logistic regression analysis. Statistical analyses were performed using EZR (version 1.61). Statistical significance was set at P < 0.05.
Result
In total, 68 patients were included in this study. The time required for Richmond Agitation–Sedation Scale score improvement after discontinuation of midazolam was < 48 h in 52 patients (76.4%) and > 48 h in 16 patients (23.5%).The factors related to prolonged midazolam action were age (P < 0.05), renal function (P < 0.01), risk factors reported in previous studies, and albumin levels (P < 0.01). The multivariate logistic regression analysis revealed that only albumin influenced the prolongation of midazolam activity (odds ratio, 0.61; 95% confidence interval, 0.44–0.85; P < 0.05).
Conclusions
Renal function, body mass index, age, and duration of midazolam administration are established factors that enhance and prolong the action of midazolam. In this study, the serum albumin level was identified as a new factor of relevance. Therefore, sedation in patients with low albumin levels should be carefully performed to avoid the prolongation and potentiation of midazolam action.
Prevalence, Anatomic-pathologic Findings, and Associated Factors of Nontraumatic Ileal Perforations Among Patients with Gut Perforation: A Multicenter Cross-sectional Study
Authors: Waziri Musa Abbas , Vivian Akello , Raymond Atwine , Lauben Amagara Kyomukama , Joel Wandabwa , Edwin Musinguzi , Peter Awio John , Godfroid Nyenge Basara , Sonye Kiyaka , Molle Fabrice , Sikakulya Franck Katembo , Muhumuza Joshua , Vahwere Bienfait Mumbere 
Published: May 2024

Abstract

Background: Nontraumatic ileal perforation is a cause of obscure peritonitis characterized by severe toxicity and high mortality. This burden is disproportionately greater in LMICs due to poor hygiene practices, burden of HIV infection, and other comorbidities.
This study aimed to determine the prevalence, anatomic-pathologic findings, and associated factors of nontraumatic ileal perforation at 3 selected hospitals in Uganda.
Methodology: This was a cross-sectional study of 149 consecutive sample participants that used a structured checklist. We conducted bivariate and multivariate analyses using SPSS v21.0 (IBM), for which p<0.02 and 0.05, respectively, were considered to indicate statistical significance.
Results: Nontraumatic ileal perforation was more prevalent among males (20.1%; 149) and peasants/farmers (41.6%; 149) of rural residence (22.1%; 149). The majority of the study participants had typhoid perforations (79.1%; 149). Most ileal perforations occurred 20-39 cm from the ileocecal junction (76.4%; 149), a perforation size/diameter of 0.5-1 cm was more common (58.1%; 149), and a single isolated perforation was more common (74.4%; 149). However, all perforations mainly occurred at the ante mesenteric border. Being an HIV-positive person was associated with greater odds of developing NTIP than was being a non-HIV-positive person. AOR 8.344, p = 0.015 (p<0.05). Additionally, patients treated with open and closed pit latrines were more likely to develop nontraumatic perforation than were those treated with water flash latrines. AOR 12.971, p = 0.004 (p < 0.05).
Conclusion
This study established that nontraumatic ileal perforation is more prevalent among male peasants living in rural areas and with typhoid fever. Being HIV positive or using a closed pit or open type of latrine was associated with high odds of nontraumatic ileal perforation.
The Predictive Capability of Some Anthropometric Indices to Identify the Risk of Metabolic Syndrome and Its Components among Industrial Workers
Authors: Konstantinova Ekaterina D. , Maslakova Tatiana A. , Ogorodnikova Svetlana Yu. 
Published: May 2024

Abstract

Metabolic syndrome (MetS) is closely associated with adverse cardiometabolic outcomes. The objective of this study is to search for practical methods that would enable effective identification of MetS based on anthropometric indicators. 347 male workers employed in hazardous working conditions were investigated. The presence of MetS was established in according to the guidelines of the International Diabetes Federation (IDF). Simple linear regression was used to determine the relationship between anthropometric indices and MetS components. Logistic regression provided MetS odds ratios (OR) in relation to increases in anthropometric measures. ROC-curves were calculated to compare the ability of each anthropometric index to predict MetS as well as to determine the diagnostic thresholds of the indicators considered. According to the IDF criteria, 36.3% of the workers had MetS. A direct relationship was found between the individual components of MetS and the anthropometric indices studied. The highest OR was shown by the Body Roundness Index (BRI) 2.235, 95% CI: 1.796-2.781. For different age quartiles, the optimal cut-off values predicting MetS were: for BRI, 4.1-4.4 r.u.; for a body shape index (ABSI), 0.080-0.083 m11/6∙kg-2/3; and for the lipid accumulation product (LAP), 49.7-70.5 cm∙mmol/l. The most significant associations with MetS were observed where the values were higher than these cut-off points (Se = 97.4%).
DAS Detection Technology for Gangue Slurry Pipeline Conveying Blockage
Authors: Zhu Lei , Qiu Fengqi , Liu Chengyong , Gu Wenzhe , Ma Chenyang , Song Tianqi , Pan Hao , Zhang Peng 
Published: May 2024

Abstract

The pipeline conveying system as the gangue slurry filling technology "lifeline". The occurrence of pipeline blockage will lead to the paralysis of the entire filling system; timely detection of pipeline blockage and early warning are needed to ensure the safe, stable, and efficient operation of the core elements of the coal gangue slurry filling system. Based on this, this paper summarizes and analyzes the classification of pipeline blockage and summarizes the current pipeline conveying blockage detection technologies. It elaborates in detail on the principles and advantages and disadvantages of existing pipeline blockage detection technologies, and points out that distributed fiber optic acoustic sensing technology (DAS), as an emerging fiber optic detection technology in recent years, can achieve high-precision, large-scale, real-time dynamic and distributed acoustic detection, Compared with traditional monitoring for pipeline blockage, it is more suitable for detecting blockage in coal gangue slurry pipeline conveying; then from the sensing principle of distributed fiber optic acoustic wave sensing technology, it discusses the current status of DAS technology application, analyzes the pipeline blockage DAS detection mechanism, and verifies the feasibility of pipeline conveying blockage detection based on the distributed fiber optic acoustic wave sensing technology by building a pipeline blockage DAS detection simulation experiment system; finally, it puts forward the feasibility of distributed fiber optic acoustic wave sensing technology; finally, it puts forward the feasibility of distributed fiber optic wave sensing technology detection. Finally, a pipeline blockage DAS detection and identification system is proposed, the function of each subsystem is introduced, and the core key technology involved in the pipeline blockage DAS detection and identification system is analyzed in detail, and the future development direction of gangue slurry pipeline conveying blockage DAS detection technology is also pointed out in order to provide reference for the development of the subsequent gangue slurry pipeline blockage and other pipeline conveying blockage DAS detection technology.
NRSC-KG: Noise-Robust Speech Comprehension Based on Knowledge Graph for HRI
Authors: Gun Liu-Hai , Deng Yan-Fang , Xie Ming-Shan 
Published: May 2024

Abstract

Speech comprehension is the key to Human-Robot Interaction (HRI), however, noise energetic masking can greatly reduce the performance of speech comprehension. Simply using Speech Enhancement (SE) methods can easily lead to suboptimal solutions. To alleviate these issues, this paper proposes a Noise-Robust Speech Comprehension system based on Knowledge Graph (NRSC-KG), which designs robust methods in Automatic Speech Recognition (ASR) and ASR error correction. In ASR, we propose a Self-adaptive Speech Feature Fusion Network (SSFF-Net) to dynamically fuse enhanced speech features with the original speech features. In ASR error correction, we propose a divergent apperceive error correction method based on domain-specific Knowledge Graph (KG). The experiment on AISHELL-1 speech corpus shows that compared to the traditional joint training of SE and ASR, our method achieves a relative Character Error Rate (CER) reduction of 12.7%. We validated the KG based error correction method on our customized Herbal Cuisine ordering Dialogue speech dataset (HCDialogue), and the results showed that our method achieved a relative CER reduction of 5.0% and 2.1%, respectively, compared to the language model based and end-to-end neural network based methods. It’s indicated that the KG based method has great potential in improving speech comprehension performance.
Measuring and optimizing the spatial accessibility of primary health care in remote and rural areas: a case study of Liannan Yao Autonomous County in China
Authors: Liu Lulu , Chen Yaowen , Xiang Haiqing , Zhong Jiawei , Xiao Yu , Zhou Peng , Wang Lan , Sun Ying 
Published: May 2024

Abstract

The need for equitable access to primary healthcare services in the current global context has attracted widespread attention, prompting nations to continuously enhance their grassroots medical service levels. In response, China launched the "Healthy China" initiative, which prioritizes the enhancement of national health as a core goal of the healthcare system and uses this opportunity to deepen reforms aimed at strengthening primary care. However, in remote and rural areas, the optimization of medical resource allocation and the achievement of balanced service development remain critical challenges owing to limited resources. This study selected Liannan Yao Autonomous County, which is situated in the northwestern corner of Guangdong Province, as a case study due to its remote mountainous location, underdeveloped economy, and minority region characteristics. Through field research and interviews, this study thoroughly explored the needs of both supply and demand, factoring in elements such as the service capability of medical facilities and residents' travel thresholds to enhance the two-step floating catchment area model, thus making it more applicable to remote villages. By integrating electric vehicles and cars, which are the primary means of transportation in rural areas, this study conducted a thorough analysis and comparison of the accessibility of medical services in Liannan Yao Autonomous County. The results reveal significant disparities in healthcare accessibility, an uneven distribution of medical resources, and varying impacts of transportation conditions and facility service capabilities on accessibility. Notably, the study revealed that improving transportation conditions alone has limited effects in rural areas; the key lies in balancing medical service capabilities and the rationality of overall layouts. From the perspectives of equity and efficiency, this study employs the equitable coverage model and the efficiency-driven model to construct two scenarios, comparing accessibility changes in Liannan under both conditions and proposing strategies to improve the spatial layout of local medical facilities. This research not only deepens the understanding of healthcare service accessibility in rural areas but also provides a scientific basis for optimizing resource allocation and enhancing primary medical services, offering valuable guidance and reference for Liannan and other similar rural regions.
A Dual Track Feature Fusion Network for ASD Detection using Swin Transformers and Convolutional Neural Network
Authors: Radhakrishnan Menaka , Ramamurthy Karthik , Shanmugam Saranya , Prabhu Aneesh Jayan , Sivaraman Balamadhan , Janarthanam Aishwar Haris 
Published: May 2024

Abstract

Early diagnosis of Autism Spectrum Disorder (ASD) plays a crucial role in enriching a child's development, particularly in improving social communication, language development, and addressing behavioural challenges. Early signs of autism may be observable in childhood, but a formal diagnosis often occurs later in life. Behavioural-based assessments, such as the Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule-Revised (ADOS-R), are currently used for diagnosing ASD. These methods of diagnosis are time-consuming and require trained professionals. Due to these disadvantages of the traditional method of diagnosis, deep learning is used, where feature extraction is done automatically from Magnetic Resonance Imaging (MRI) data, eliminating the reliance on subjective pre-defined features. This advancement not only captures subtle information that may be missed by human-defined features but also enhances accuracy significantly. The dataset comprises of axial view of MRI images from ABIDE-I dataset from Autism Brain Imaging Data Exchange (ABIDE) database. This study proposes a dual-track feature fusion network architecture comprising Swin Transformer and customised Convolutional Neural Network (CNN) for precise classification. Swin Transformers excel in capturing long-range dependencies within images, facilitating a deeper understanding of interrelations among different image components. Concurrently, CNNs are adept at extracting local features, thus contributing to improved classification performance by considering both local and global features. The experimental outcomes highlight the efficacy of the proposed feature fusion network, showcasing an accuracy rate of 98.7%, precision of 98.12%, recall of 98.77%, and an F1-score of 98.65% upon evaluation using the ABIDE dataset.
The Role of Information Technology in Sustainable Urban Mobility Development
Authors: Petersen Daniel , Behr Ariel 
Published: May 2024

Abstract

The exponential growth of the population living in urban centers has contributed to intensifying problems related to various aspects of mobility. In this context, information technology has been widely used as an important resource for building solutions aimed at overcoming infrastructure and urbanism deficiencies, collecting information in its multiple contexts, and constructing tools for management, planning, and other resources necessary for the development of smarter forms of mobility. This qualitative article was conducted through research and bibliographic analysis where, through a systematic literature review (SLR), it investigated the different IT solutions applied in mitigating the consequences of urban mobility problems. 400 studies analyzing 72 distinct approaches to mobility were identified and classified into 16 application groups. The objective was to map the multiple aspects of sustainable urban mobility researched by the academic community in recent years. Additionally, the article highlights the Mobility as a Service (MaaS) approach.
Investigation on the mechanism of Ranunculus ternatus Thunb. against esophageal squamous cell carcinoma based on network pharmacology and experimental verification
Authors: Deng Michen , Deng Yanhong , Tang Zu-gui , Nie Wenqiang , Lu Yi , Wang Zhe , Wang Xicheng , Kong Yi 
Published: May 2024

Abstract

Purpose
This study was conducted to assess the pharmacological mechanisms of ethyl acetate extract of Ranunculus ternatus Thunb. (RTE) in combating esophageal squamous cell carcinoma (ESCC) through the integration of network pharmacology analysis and experimental validation.
Methods
Utilizing network pharmacology methodologies, potential targets of RTE and targets associated with ESCC were identified from public databases. Subsequently, protein-protein interaction (PPI) network analysis, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted to ascertain the key targets and pathways through which RTE may exert its effects against ESCC. Finally, the putative mechanisms of action of RTE on ESCC, as predicted by network pharmacology analysis, were validated through in vitro experiments.
Results
A total of 274 potential targets were retrieved by searching the intersection of RTE and ESCC targets. 14 key genes of RTE acting on ESCC were obtained combined Component-Target-Disease Pathway and PPI network analysis, including AKT1, HSP90AA1, EGFR, MAPK1, and TNF.GO biological process analysis mainly involved in regulation of inflammatory response, response to lipopolysaccharide, and regulation of apoptotic signaling pathway, etc. KEGG signaling pathway analysis mainly related to MAPK signaling pathway, Relaxin signaling pathway, and PI3K/Akt pathway, etc. Then, the results of in vitro experiment indicated that RTE could inhibit proliferation of EC-109 and TE-13 cells. The in vitro experiments validated that RTE exhibited its therapeutic effects on ESCC mainly though the regulation of cell proliferation via MAPK/ERK and PI3K/Akt signaling pathways.
Conclusion
This study demonstrated that it may offer a useful tool to clear the molecular mechanism of RTE on ESCC by combination of network pharmacology prediction with experimental validation.
Identification of novel PHGDH inhibitors based on computational investigation: an all-in-one combination strategy to develop potential anti-cancer candidates
Authors: Xu Yujing , Yang Zhe , Yang Jinrong , Gan Chunchun , Qin Nan , Wei Xiaopeng 
Published: May 2024

Abstract

PHGDH has been identified as a promising drug target for the therapy/management of various cancers. 3D-QSAR pharmacophore model-based virtual screening, ADME/T prediction, molecular docking, lead optimization and molecular dynamics simulation were utilized to identify novel potential PHGDH inhibitors. A ligand-based 3D-QSAR pharmacophore model was developed using HypoGen algorithm methodology of Discovery Studio. The selected Hypo_2 pharmacophore model was further validated by test set validation, cost analysis, Fischer randomization validation and was then used as a 3D query to screen compound libraries with various chemical scaffolds. Estimated activity, drug-likeness, molecular docking, growing scaffold and molecular dynamics simulation were applied in combination in order to further narrow the number of virtual hits. Finally, an all-in-one combination was employed successfully to design and develop two potential anti-cancer candidates.
Shortest Characteristic Factors of a Deterministic Finite Automaton and Computing Its Positive Position Run by Pattern Set Matching
Authors: Janoušek Jan , Plachý Štěpán 
Published: May 2024

Abstract

Given a deterministic finite automaton (DFA) A, we present a simple algorithm for constructing deterministic finite automata that accept the shortest forbidden factors, the shortest forbidden prefixes, the shortest forbidden suffixes, the shortest forbidden words, the shortest allowed suffixes, and the shortest allowed words of the automaton A. We refer to these sets as the shortest characteristic factors of the automaton A. If the given automaton is local, and therefore the language it accepts is strictly locally testable, the sets of its shortest characteristic factors are finite, and these automata are acyclic. Otherwise, they accept infinite languages. This approach simplifies existing methods for the extraction of forbidden factors, allows the extraction of more types of characteristic factors, and also generalizes the extraction for all classes of DFAs. Furthermore, we demonstrate that this type of extraction can be used for a sublinear run of an automaton for certain inputs. We define a positive position run of a deterministic finite automaton, representing all positions in an input string where the automaton reaches a final state. Finally, we present an algorithm for computing the positive position run of the automaton, which utilizes pattern set matching of its shortest forbidden factors and its shortest forbidden or allowed suffixes, provided that the sets are finite. We showcase the computation of the positive position run of a local automaton using backward pattern set matching, which can achieve sublinear time.
Automatic Rehabilitation Exercise Task Assessment of Stroke Patients Based on Wearable Sensors with a Lightweight Multichannel 1D-CNN Model
Authors: Wang Jiping , Li Chengqi , Zhang Bochao , Zhang Yunpeng , Shi Lei , Wang Xiaojun , Zhou Linfu , Xiong Daxi 
Published: May 2024

Abstract

Approximately 75% of stroke survivors have movement dysfunction. Rehabilitation exercises are capable of improving physical coordination. They are mostly conducted in the home environment without guidance from therapists. It is impossible to provide timely feedback on exercises without suitable devices or therapists. Human action quality assessment in the home setting is a challenging topic for current research. In this paper, a low-cost HREA system in which wearable sensors are used to collect exercise data and a multichannel 1D-CNN framework is used to automatically assess action quality. The proposed 1D-CNN model is first pretrained on the UCI-HAR dataset, and it achieves a performance of 91.96%. Then, five typical actions were selected from the Fugl-Meyer Assessment Scale for the experiment, wearable sensors were used to collect the participants’ exercise data, and experienced therapists were employed to assess participants’ exercise at the same time. Following the above process, a dataset was built based on the Fugl-Meyer scale. Based on the 1D-CNN model, a multichannel 1D-CNN model was built, and the average accuracy of the model on the dataset was 97.23%. This shows that the HREA system can be used in the home environment and help patients receive timely assessment feedback.