bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of ICU Admission Thresholds on Outcomes in Rapid Response System Activations: A Multicenter Study in Japan
Authors: Ono Shohei , Uchino Shigehiko , Tokito Miho , Saito Taishi , Sasabuchi Yusuke , Sanui Masamitsu 
Published: June 2024

Abstract

Background
The variability in ICU admission rates for patients activated by the Rapid Response System (RRS) is substantial and differs significantly across institutions. This study explores the disparities in ICU admission thresholds and their impact on patient outcomes.
Methods
A multicenter retrospective observational study was conducted using a Japanese in-hospital emergency registry, focusing on patients for whom the RRS was activated from 2018 to 2022. We calculated the ICU admission rate (ratio of ICU admissions to RRS activations) and the Standardized ICU Admission Ratio (SIAR: ratio of actual to predicted ICU admissions) for each institution (N = 35). The relationship between SIAR and patient outcomes, specifically death or Cerebral Performance Category (CPC) at 30 days, was analyzed using multivariable analysis with the Generalized Estimating Equation (GEE) model.
Results
The study included 8,794 patients, with 26.9% admitted to the ICU. The median ICU admission rate was 0.33 (1st quantile: 0.21, 3rd quantile: 0.47), and the median SIAR was 0.98 (1st quantile: 0.75, 3rd quantile: 1.17). Univariable analysis indicated that a higher SIAR significantly correlated with a lower incidence of CPC ≥ 3 or death at 30 days (P = 0.037) and showed a trend towards lower mortality at 30 days (P = 0.059). The GEE model revealed that the odds ratio of SIAR for death at 30 days was 0.89 (95% CI = 0.72 to 1.09; P = 0.30), and for CPC ≥ 3 or death at 30 days was 0.78 (95% CI = 0.64 to 0.95; P = 0.015).
Conclusions
This study demonstrates a significant association between higher SIAR and improved patient outcomes, suggesting that lower ICU admission thresholds during RRS activations may enhance patient prognosis.
Arsenic Contamination of Drinking Water: A Study of the Exposure to Residents From the Passagem De Mariana, A Historical Gold Mining Town in the Quadrilátero Ferrifero, Brazil
Authors: Mendes Louise Aparecida , de Lena Jorge Carvalho , Abreu Adriana Trópia , Soares Liliane Catone , Silva Emanueli do Nascimento da , Froes Roberta Eliane Santos , Palmieri Helena Eugênia Leonhardt , Costa Adivane Terezinha 
Published: June 2024

Abstract

Human biomonitoring is one of the important tools for assessing exposure to toxic chemicals. A history of arsenic contamination via drinking water from gold mines in the Passagem district of Mariana, Brazil, is a way of incorporating this element into the body. This study aimed to evaluate water quality consumed by residents of Passagem de Mariana and to analyze biological samples, and investigate the magnitude of the exposure to arsenic. The results showed the presence of this trace element in higher concentrations than the maximum value permitted by the law. In two samples, concentrations were above 10 µg L− 1, regardless of the season, for two years. As for biological samples, arsenic concentrations in hair samples (0.048 to 0.925 µg g− 1) were lower than the normal level (< 1µg g− 1). Arsenic was quantified in urine, both in individuals in the exposed (9.80 to 211 µg L− 1) and in the reference group (8.20 to 55.7 µg L− 1), whose content is capable of affecting a degree of medium and high toxicological risk (> 15 µg L− 1). This group was affected by other sources contributing to arsenic exposure, making it necessary to study other environmental matrices as well as foods. After confirming the exposure, continued biomonitoring was recommended since the adverse effects caused by arsenic can be manifested in the long term.
Comparison of the efficacy and safety of immunotherapy combined with lenvatinib at different time points in unresectable hepatocellular carcinoma: a single-center retrospective study
Authors: Yu Zeyu , Leng Bin , You Ran , Wang Chendong , Diao Lingfeng , Xu Qingyu , Yin Guowen 
Published: June 2024

Abstract

Background: The lenvatinib combined with immunotherapy therapies as first-line treatment are still controversial in unresectable hepatocellular carcinoma (uHCC). This research aimed to compare the efficacy and safety of lenvatinib monotherapy (L) and synchronous therapy (LI) and sequential therapy (L-LI) in uHCC patients.
Methods:181 uHCC patients were enrolled in this study. Patients were classified into three groups: (1) Lenvatinib monotherapy (L). (2) Synchronous therapy (LI) (lenvatinib plus immune checkpoint inhibitors (ICIs) at the same time). (3) Sequential therapy (L-LI) (patients were initially treated with lenvatinib monotherapy for 3 months, stable disease remained, followed by subsequent addition of ICIs). Overall survival (OS) and progression-free survival (PFS), baseline characteristics, safety were compared among these groups.
Results: The combination groups (LI, L-LI) had longer OS and PFSthan the L group, and there was no significant difference between the LI group and the L-LI group. However, in the subgroup of patients without distant metastases, the L-LI group exhibited longer PFS compared to the LI group. Conversely, in the subgroup of patients with distant metastases, the LI group showed longer PFS than the L-LI group. The ECOG PS and AFP were independent prognostic factors for survival. The frequency of grade ≥ 3 AEs was not significantly different.
Conclusions: Our study demonstrated that, in all patients, the combination groups (LI, L-LI) had longer OS and PFS than the L group, and there was no significant difference between the LI group and the L-LI group. However, synchronous therapy (LI) has better efficacy in patients with distant metastases, but worse efficacy in patients without distant metastases than sequential therapy (L-LI).
The effects of diabetes on gas transfer capacity, lung volumes, muscle strength and cardio- pulmonary responses during exercise
Authors: Ali Emir , Priel Eldar , Brister Danica , Diab Nermin , Freitag Andy , O’Byrne Paul M. , Gerstein Hertzel , Killian Kieran J. , Satia Imran 
Published: June 2024

Abstract

Background Diabetes is a risk factor for the development of vascular disease, chronic kidney disease, retinopathy and neuropathy. Diabetes is a co-morbid condition commonly present in patients with respiratory disorders but the extent to which it influences ventilatory capacity, gas exchange and functional capacity is not well known.Research question: Does the presence of diabetes contribute to impairment in spirometry, gas transfer, and exercise capacity?Methods Retrospective analysis of all subjects who performed incremental cardio-pulmonary exercise testing(CPET) between 1988–2012 at McMaster University Medical Centre. The impact of diabetes on physiological outcomes and maximum power output(MPO) was assessed using stepwise multiple additive linear regression models including age, height, weight, sex, muscle strength and previous myocardial infarct as co-variates, and was also stratified based on BMI categories.Results 40,776 subjects were included in the analysis; 1938(5%, 66% male) had diabetes. Diabetics were older(59 vs. 53 years), heavier(88.3 vs.78.0 kg), and had a higher BMI(31 vs. 27 kg/m2). The presence of diabetes was independently associated with a reduction in FEV1(-130ml), FVC(-220ml), DLCO(-1.52 ml/min/mmHg) and VA(-340ml) but not KCO. Patients with diabetes achieved a lower % predicted MPO[diabetic subjects 70% predicted(670 kpm/min ± 95% C.I. 284) vs. 80% in non-diabetics(786 kpm/min ± 342), p < 0.001]. With the exception of KCO, these differences persisted across BMI categories and after adjusting for MI.Conclusion The presence of diabetes is independently associated with weaker muscles, lower ventilatory and gas transfer capacity and translates to a lower exercise capacity. These differences are independent of age, height, weight, sex and previous MI.
Advancing the acceptability of game-based digital mental health interventions: A qualitative study on clinicians’ views
Authors: Lukka Lauri , Karhulahti Veli-Matti , Palva J. Matias 
Published: June 2024

Abstract

Background: Mental health professionals’ (MHPs) views on video games are crucial for game-based digital mental health interventions. These interventions are actively developed, their successful implementation depends also on clinician acceptability, and they are related to the divisive topics of technological transformation and video games.
Objective: This qualitative study investigates how MHPs view video games. This aims to inform the user-centered design of game-based digital mental health interventions.
Methods: The study combined three (n = 19, n = 16, n= 6) distinct qualitative interview datasets, which explored the views of Finnish MHPs on video games. The combined data (n = 41) were analyzed using Reflexive Thematic Analysis (RTA). Then, two post hoc analyses were designed using complementary qualitative questionnaire data (n = 80), which was gathered together with the first interview dataset.
Results: The RTA generated three themes. 1) Personally games are recreation, clinically they are harmful. The MHPs’ personal gaming experiences were positive and associated with recreation, whereas their professional gaming experiences associated their clients’ gaming with harms. 2) Gaming is framed as adverse technology and meaningful culture. The MHPs made sense of gaming as a complex societal phenomenon with two complementary and conflicting frames. 3) Clients’ gaming is explored holistically. The MHPs evaluated all activities, gaming included, per their influence on other fields of life. They identified two courses where gaming could evolve from a solution to a problem: from connection to loneliness and from comfort to avoidance. The first post hoc analysis provided further evidence of the self-client attitude asymmetry identified in the first theme. The second post hoc analysis described the benefits MHPs expected from game-based interventions and for whom.
Conclusion: MHPs’ views on video games are characterized by self-client attitude asymmetry, conflicting framings, and holistic exploration. Thus, their views cannot be meaningfully simplified to a positive-negative -continuum. Game-based intervention researchers, designers, and developers benefit from considering these stakeholder perceptions when designing and implementing novel game-based digital mental health interventions.
Self-Myofascial Release Therapy Moderately Influence Bioelectrical Activity of Longissimus Muscle in Golfers
Authors: Banaśkiewicz Jan , Kasiak Przemysław , Chomiuk Tomasz , Mamcarz Artur , Śliż Daniel 
Published: June 2024

Abstract

Purpose
The Longissimus Dorsi (LD) is one of the most overloaded and injured muscles among golfers. Self-Myofascial Release (SMFR) therapy is a common injury prevention technique. However, impact of SMFR on LD bioelectrical activity among golfers is unknown. Therefore, we addressed this issue in the present study.
Materials and methods
31 golf players (28 males, age = 35.8 ± 13.1 years, BMI = 25.1 ± 3.9 kg·m− 2, training experience = 8.2 ± 5.4 years) underwent SMFR by foam rolling of LD 4 times for 30 seconds each. We performed electromyography of the thoracic and lumbar components of LD at rest and during the golf swing. Finally, we took measurements before and after foam rolling.
Results
The thoracic component of LD has higher bioelectrical activity at rest than the lumbar component (average = 7.2–8.7 µV vs 6.8–7.5 µV, p = 0.12–0.66; peak = 58.1–62.2 vs 41.2–51.2 µV, p = 0.28–0.73). On the contrary, the thoracic component has lower bioelectrical activity during swing than the lumbar component (average = 35.8–43.5 µV, p = 0.25–0.90; peak = 40.0-45.9 µV, p = 0.25–0.72). Comparison of average and peak voltages did not provide significant differences between the right and left sides (p = 0.06–0.94). Voltages between thoracic and lumbar components of LD also did not provide significant differences, but voltages after SMFR were slightly lower than before SMFR (p = 0.08-1.00).
Conclusions
SMFR moderately reduces the bioelectrical activity of the LD. The thoracic component of LD has higher voltage during rest and lower voltage during swing than the lumbar component of LD. Physiotherapists and sport practitioners should acknowledge bioelectrical activity of LD to properly apply SMFR therapy in golfers.
Prediction of intensity and scale variation trend of tropical cyclones combined the quantile regression with grey power model
Authors: Zhang Wenyu , Wang Xiangjun , Amjad Ali , Yang Hua , Huang Bin , Yang Junwei 
Published: June 2024

Abstract

Global climate change has significantly altered the number and intensity of tropical cyclones in the Northwest Pacific Ocean, resulting in substantial losses for both residents and the economy in the southeast coastal regions of China, as well as affecting the operating efficiency and safety of offshore wind farms. Therefore, quantitatively analyzing the temporal characteristics of tropical cyclones and precisely predicting their trend is crucial for mitigating disasters in coastal countries. This paper analyzes the interannual variation characteristics of tropical cyclones making landfall in China from 1980 to 2022 based on the quantile regression method. Grey power model was also used to predict the quantile regression curves of key features of TCs making landfall in China in the next five normal, El Niño and La Niña years, and to speculate on the future changes of tropical cyclones in the northwestern Pacific Ocean with statistical data. The results show that the interannual pattern of maximum wind speeds of tropical TCs making landfall in China under the 0.1–0.9 quantile is significantly affected by the El Niño-Southern Oscillation (ENSO), and the maximum wind speeds of tropical cyclones in normal, El Niño, and La Niña years are all slightly increased and accompanied by an increase in the duration. The location of the landfalling TCs in normal and El Niño years is moving northeastward, and the latitude of the landfalling TCs in La Niña years is approaching 16 ° N. The predicted wind speeds of the TCs in normal and El Niño years are also slightly increased with the increase of the duration. From the quantile regression curves predicted using the gray power model, El Niño years will bring more extreme weather. Tropical cyclones making landfall in normal and El Niño years may decrease in the southern part of China and increase in the northern part, which may be related to the expansion of TCs due to global warming. The results of this research can provide useful references for climate change research, disaster prevention and mitigation, and related policy making in China.
A Multilingual SEIR Model for Public Opinion Dynamics: Integrating Social Enhancement and Cross-Transmission Mechanisms
Authors: 董 苏雅拉图 , Xu Linlin , Lan Zhong-Zhou , Yana A , Bu Fanyu , Hua Wu , Chunlai Qu , Yifei Li , Minjie Gao , Kai Ge 
Published: June 2024

Abstract

In multilingual environment, the propagation of public opinion exhibits increased complexity and uncertainty, necessitating a robust mathematical model for its description and analysis. Utilizing complex network theory and dynamical principles, this study integrates the social enhancement effects, forgetting mechanism, and cross-transmission mechanism into a SEIR model of opinion dynamics that accounts for linguistic factors. This paper explores the interaction and influence of public opinion across different language groups, assessing the stability and sensitivity of these opinions. Concurrently, this paper proposes an opinion control strategy based on optimal control theory, specifically tailored for multilingual contexts. This strategy aims to minimize the costs associated with controlling public opinion and to effectively guide and regulate it. Numerical simulation experiments validate the proposed model and methods, offering innovative approaches and tools for managing public opinion in multilingual settings.
Multi-response Optimisation of Wire-EDM for SLMed AlSi10Mg using Taguchi-Grey Relational Theory
Authors: R Murali Krishnan , Ranganathan Rajesh , A Saiyathibrahim , Velu Rajkumar , Jatti Vijaykumar S , Mohan Dhanesh G 
Published: June 2024

Abstract

The present research effort strives to optimise the multi-response during Wire Electrical Discharge Machining (Wire-EDM) of SLMed AlSi10Mg, applying Taguchi integrated Grey Relational Analysis (GRA). Selective Laser Melting (SLM) represents one of the best-known and most practicable Additive Manufacturing (AM) methods that have the prospective to serve as a replacement for many traditional production processes. Extremely intricate metallic support structures built up during SLM need more attention since they are too difficult to remove by hand. Therefore, post-processing adopting the Wire-EDM precision machining technique is performed in this study to assess the machinability of the SLMed AlSi10Mg as-built part. The multi-response optimisation used here seeks to achieve maximum material removal rate and lowest surface roughness while considering four important influencing elements (pulse On time, pulse Off time, servo voltage, and wire feed rate) at four distinct levels. Taguchi integrated Grey Relational Analysis (GRA) revealed that a pulse On time of 118 µs (Level 3), a pulse Off time of 44 µs (Level 1), a servo voltage of 60 V (Level 4), and a wire feed rate of 7 m/s (Level 4) are suggested to achieve optimal machining of SLMed AlSi10Mg. Furthermore, the derived optimisation results were diligently verified using a confirmatory experiment, and a 38.57% improvement in multi-response characteristics was found when compared to the initial Wire-EDM parameter settings. The methodology suggested in this work offers a standard approach that has the potential to be implemented for the rapid and precise prediction and optimisation of surface roughness while achieving better material removal during Wire-EDM of SLMed AlSi10Mg.
LAASO algorithm-based bioinformatics analysis for exploring the pathogenesis and immune infiltration of atrial fibrillation and dilated cardiomyopathy
Authors: Li Hongdao , Chen Yuyang , Liang Shumin , Mai Bifang , Tu Wenqing , Lin Yuhan , Chen Qi , Xie Shuanglun 
Published: June 2024

Abstract

Background: It is well known that atrial fibrillation (AF) is a serious complication of dilated
cardiomyopathy (DCM) and they could affect each other. This study endeavors to uncover the shared diagnostic markers and immune pathways contributing to both disorders.
Methods: We downloaded AF and DCM data from the Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to clarify shared signaling pathways of DEGs. Further, the least absolute shrinkage and selection operator (LASSO) regression was applied to pinpoint key hub genes and construct a diagnostic model.
Results: A total of 20 common DEGs in AF and DCM were identified for subsequent analyses.
The LASSO analysis results showed that RGCC, KCNN2 and TGFBR3 are 3 most important cross-talk genes between these 2 diseases. The immune infiltration results revealed that Th17/Treg cells may play an important role in the pathogeneses of AF and DCM.
Conclusion: This pioneering study merges bioinformatics and machine learning to map the shared molecular landscape of AF and DCM, highlighting RGCC, KCNN2, and TGFBR3 as key diagnostic biomarkers. The imbalance of Th17/Treg may be vital in the progression of these 2 diseases.
Granular Neural Networks Learning for Time Series Prediction under a Federated Scenario
Authors: Song Mingli , Zhao Xinyu 
Published: June 2024

Abstract

Granular neural networks (GNNs) are a type of prediction models outputting information granules and GNNs not only provide more abstract results and a granular structure but also reveal a flexible nature that can be adjusted by users. As a promising tool, we apply GNNs to solve time series prediction problems under the federated learning (FL) scenario. Distributed time series prediction problems attract more attention recently due to the more usage of large quantity of IoT (Internet of Things) sensors and the development of Artificial Intelligence techniques. FL is the main approach to fix the distributed time series prediction problems. In this paper, we design a federated learning framework to refine granular weights of GNNs and then return better prediction results compared with the ones from centralized modeling. Different with the studies of FL using numeric neural networks, FL using GNNs is a study of aggregating parameters’ parameters under the federated scenario and thus the robustness and stability of the method is the most critical issue. To testify the two features of our method, we observe and compare from two aspects: different cases (several groups’ results) and different numbers of objectives (single-objective optimization and multiple-objective optimization). Experiments on predicting air quality index for 35 stations in Beijing (China) show the effectiveness of our method.
Information structure of heterogeneous criticality in a fish school
Authors: Niizato Takayuki , Sakamoto Kotaro , Mototake Yoh-ichi , Murakami Hisashi , Tomaru Takenori 
Published: June 2024

Abstract

The integrated information theory (IIT) measures the degree of consciousness in living organisms from an information-theoretic perspective. This theory can be extended to general systems such as those measuring criticality. Herein, we applied the IIT to actual collective behaviour (Plecoglossus altivelis). We found that the group integrity (i.e., Φ) could be maximised in the critical state and that several levels of criticalities existed in a group as subgroups. Furthermore, these fragmented critical groups coexisted with traditional criticality as a whole. The distribution of high-criticality subgroups was heterogeneous in terms of time and space. In particular, the core fish in the high-criticality group tended to be unaffected by internal and external stimulation, in contrast to those in the low-criticality group. The results of this study are consistent with previous interpretations of critical phenomena and provide a new interpretation of the detailed dynamics of an empirical critical state.
Double-shield TBM Mounted Seismic Ahead-prospecting System and its Application
Authors: Chen Lei , Li Zhongzhi , Li Kai , Zhang Xibin , Xu XInji , Cao Hongyi , Wang Fei 
Published: June 2024

Abstract

Double-shield tunnel boring machine (TBM) has been widely used in tunnel construction. However, the unknown adverse geological conditions in front of the tunnel face can easily disturb the construction progress of the double-shield TBM. To ensure the construction safety of double-shield TBM, it is necessary to predict the geological information in front of the tunnel face in advance. However, the unique tunnel environment with a double-shield TBM makes it hard to predict geological conditions by conventional detection techniques. Therefore, this paper proposes a double-shield TBM-mounted seismic ahead-prospecting system. According to the special structure of double-shield TBM, a geological detection system mainly including the vibration source and rod-sensing elements was developed. The mounted vibration source is excited by high-pressure gas, and the excited seismic signal has strong energy, which can realize long-distance disaster prospection. The rod-sensing element can directly contact the surrounding rock mass through the grouting hole and collect reflected wave signals with a higher signal-to-noise ratio. The system can directly excite and receive seismic waves in the rock mass around the tunnel. The proposed system has been mounted on double-shield TBMs and verified based on field.