bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three-Dimensional Finite Element Model for FrameBeam Anchor Support Reinforcement of Frozen Soil Slopes
Authors: Cui Zhengnan , Tian Wentong , Liu Kun , Guo Dingnan , Yang Bo 
Published: October 2023

Abstract

To investigate the distinctive characteristics of deformation and internal force variations in frame beam anchor structure supporting frozen soil slopes during freezing-induced frost heave, a comprehensive three-dimensional finite element model was developed. This model, utilizing the Winkler elastic foundation beam theory, is engineered to examine frost heave occurrences in frame anchor structures during freezing periods. The frame beam is modeled as a homogeneous elastic Euler-Bernoulli continuous beam, while the frozen soil behind the slope is represented through simplified pre-compressed soil springs. Simultaneously, based on the heat conduction differential equation during the phase coexistence of solid and liquid in the freezing-expansion process, the freezing expansion distribution force acting on the frame beam is obtained. By employing MATLAB programming and leveraging existing engineering cases, customized calculation programs were developed and compared against numerical simulation outcomes. The findings underscore the efficacy of the proposed method in accurately portraying the free frost heave displacement of frozen soil on slopes. Lateral displacements and bending moments obtained through this approach are consistently aligned with the results of numerical simulations. Moreover, the proposed calculation method offers a swift means of assessing frost heave displacement and the stress state of frame anchor structures, requiring only a minimal set of parameters. The research outcomes not only present a comprehensive insight into the three-dimensional dynamics between frozen soil and frame anchor support structures but also provide invaluable scientific guidance for designing frame anchor slope structures in cold regions.
Towards an integrative approach of healthcare. Implementing Positive Health in three cases in the Netherlands
Authors: de Bekker Ankie , Beijer Maarten , Lemmens Lidwien 
Published: October 2023

Abstract

Background: The healthcare system is under tremendous pressure. One possible solution towards relieving some of this pressure is to use Positive Health, which takes ‘health’ as a starting point, rather than ‘illness’. Positive Health provides opportunities for stimulating integrated care.
Methods: Three cases in the Netherlands are studied in this paper. Their way of working with Positive Health is investigated through semi-structured and narrative interviews, using realist-evaluation and thematic analyses.
Results: Seven ‘working elements’ are identified that enhance the chances of successfully implementing Positive Health in practice (part 1). The interviews show that healthcare professionals have noticed that people adopt a healthier lifestyle and gain a greater degree of control over their own health. This boosts job satisfaction for healthcare professionals too. The organisations and professionals involved are enthusiastic about working with Positive Health, but still experience barriers (part 2).
Conclusions: The results of this study imply that implementing Positive Health in practice can facilitate collaboration between organisations and professionals from different disciplines, such as healthcare, welfare, and municipal health services. Operating from the perspective of a shared goal, professionals from different disciplines will find it easier to jointly organise activities to foster citizens’ health. Additionally, more attention is paid to non-medical problems affecting people’s well-being, such as loneliness or financial problems.
APELA promotes luteal angiogenesis through the regulation of TGF-β/SMAD3 signaling pathway
Authors: Zhao Hongru , Liu Hui , Yin Jiting , Lu Siying , Zhang Yulu , Li Yue , Zhu Jun , Cheng Yanmin , Yang Bei , Kuang Haibin 
Published: October 2023

Abstract
Luteal angiogenesis is absolutely required for the development and function of corpus luteum. Recently, APELA has been shown to be essential to embryonic development and angiogenesis. However, whether APELA is involved in the luteal development and angiogenesis remains unknown. In this study, we established a PMSG/hCG superovulating model and spheroid-based angiogenesis assay of HUVECs to analyze the roles of APELA through APLNR in the luteal development and angiogenesis. Our immunohistochemical results showed that APELA and APLNR were highly expressed in the ovarian corpus luteum, but their expression levels significantly decreased in the PGF2α-induced luteolysis model. ML221 treatment of APLNR antagonist could inhibit the development and endocrine function of corpus luteum as evidenced by the downregulation of luteal area and serum progesterone and estradiol and ovarian steroidogenic enzymes mRNA. Furthermore, ML221 significantly suppressed ovarian CD31 staining and expression levels of Ang2, Tie2, Vegfa and Hif1 mRNA, followed by decreased expression of ovarian P-SMAD3/SMAD3, TGFβR1 and TGFβ1 proteins. In vitro experiments demonstrated that recombinant APELA significantly increased the rate of sprouts/spheroid and sprout length and tip-cells at the extremity of sprouts, enhanced expression levels of related angiogenic factors and molecules of TGFβ signaling pathway of HUVECs. Nevertheless, ML221 cotreatment could abrogated the promotional effect of APELA. In summary, we conclude that APELA acting through APLNR has an obligatory role in the luteal angiogenesis and corpus luteum formation.
Applying Machine Learning with Tree Ensemble Methods and SHAP Values based on Routine Circulating Biomarkers to Detect Left Atrial Morphological and Functional Remodeling in Hypertension
Authors: Wang Shaobo , Pan Yu , Fu Tingting , Sun Qiaobing , Jiao Zengtao , Liu Youjun , Jiang Yinong , Liu Yan 
Published: October 2023

Abstract
Introduction: Hypertension induces left atrial (LA) dysfunction and stiffness. Machine learning (ML) has been increasingly used in clinical diagnosis and prognosis prediction. To detect LA stiffness using ML with tree ensemble methods and SHAP values based on clinical biomarkers which were routinely measured in hypertension.
Methods: 351 hypertensive patients were enrolled and measured LA volume (LAV) using the biplane modified Simpson’s method and LA reservoir strain (LAS-S) using 2D speckle-tracking echocardiography. The LA stiffness index (LASI) was defined as the ratio of E/eʹ to LAS-S. Four tree-based ML algorithms, including XGBoost, GBDT, Random Forest (RF), and LightGBM were used to discriminate the increased LASI (≥0.29) and LAV index (LAVI) ( ≥ 28 mL/m2) based on the routine circulating biomarkers including 38 features. We also used the SHAP values to evaluate features importance and interactions.
Results: The top 20 selected variables were used as inputs for four ML models, GBDT presented the highest AUC/ROC (0.85, 95% CI 0.70-0.94) for predicting LASI, and RF model exhibited the best AUC/ROC (0.75, CI 0.57-0.92) for predicting LAVI. SHAP summary plot was applied on GBDT or RF model to identify feature contribution to LA stiffness and LA enlargement, and SHAP also revealed the interactions between variables.
Conclusions: tree-based ML models with the SHAP method combining routine circulating biomarkers predicted LA stiffness with high accuracy. ML models can be useful to screen hypertensive patients with preclinical cardiac TOD, in order to improve personalized medical care at low cost.
Early outcome prediction (NEWS, EWSO2 and HRV) for spontaneously breathing ICU patients - A data-warehousing analysis
Authors: FERRIERE Nicolas , BODENES Laetitia , DE LONGEAUX Kahaia , LELLOUCHE François , L'HER Erwan 
Published: October 2023

Abstract
Purpose
Predicting models using physiological parameters have been developed for use in the emergency department. The aim of our study was to evaluate NEWS (New Early Warning Score), EWSO2 (Early Warning Score Oxygen), and Heart rate variability (HRV) as outcome predictors for spontaneously breathing patients attending the ICU.
Methods
A post-hoc analysis of a prospective datawarehousing project (ReaSTOC clinicalTrials identifier NCT 02893462). Physiological data and raw PPG curves were prospectively collected during the first 24-hrs of ICU admission. NEWS, EWSO2 and HRV were calculated and the best thresholds to predict the need for invasive ventilation and mortality were determined.
Results
From 112 patients, 8 and 18 patients died within the ICU and during their hospitalization respectively. Patients who died in ICU had a highest NEWS score as compared to ICU survivors (9,0 [5,0–11,6] vs. 6,0 [5,0–7,0]; p = 0.03), highest EWSO2 index (18,4 [15, 7–19, 8] vs. 9,0 [5, 8–20, 9], p = 0.008). Considering a composite prognostic outcome including ICU mortality and/or the need of invasive ventilation and/or a length of stay superior to the median length of stay of patients without invasive ventilation, there was also a significantly difference for NEWS, HRV and EWSO2.
Conclusion
For spontaneously breathing patients attending the ICU, NEWS, EWSO2 and HRV were significantly different in between ICU and hospital survivors and non-survivors. These parameters also enabled an early detection of subsequent additional respiratory assistance (e.g high flow oxygen, noninvasive ventilation) but not the requirement for endotracheal intubation.
Improved Gated Recurrent Units together with Fusion for Semantic Segmentation of Remote Sensing Images based on Parallel Hybrid Network
Authors: Zhou Tongchi , He Hongyu , Wang Yanzhao , Liao Yuan 
Published: October 2023

Abstract

Transformer together with convolutional neural network (CNN) has achieved better performance than the pure module-based methods. However, the advantages of both coding styles are not well considered, and the designed fusion modules have not achieved good effect in the aspect of remote sensing image (RSI) semantic segmentation. In this paper, to exploit local and global pixel dependencies, improved Gated Recurrent Units combined with fusion, are proposed to harness the complementary advantages of Parallel Hybrid Network for semantic segmentation of RSIs. The proposed network core is feature selection and fusion module (FSFM), which is composed by both feature selection units (FSU) and feature fusion units (FFU), named FSFM-PHN. Concretely, to precisely incorporate local and global representations, the improved reset and update gates of ConvGRU are treated as FSU and is realized the feature selection of the advantageous segmentation task. To merge the outputs from ResNet, Swin Transformer and FSU, feature fusion units (FFU) based on stack and sequential convolutional block operations is constructed. On the public Vaihingen, Potsdam and BLU datasets, the experimental results show that FSFM is effective, which outperforms state-of-the-art methods in some famous remote image semantic segmentation tasks.
Exogenous input autoregressive model based on mixed variables for offline prediction thermal errors of CNC Swiss lathes.
Authors: Wu Shan , Kong Lingfei , Wang Aokun , Lu Qianhai , Feng Xiaoyang 
Published: October 2023

Abstract
Accurate prediction models of thermal errors are very useful for improving the machining accuracy of machine tools; it is also the core of thermal error compensation technology. Often, it is preferable to predict thermal deformation using a dynamic model, as opposed to computational inaccuracy and non-robustness existing in the static model. Autoregressive models are one of the most commonly used dynamic models. However, the autoregressive model needs to measure the thermal error online, which can be intrusive to the production process and reduce production efficiency. This paper presents a new exogenous input autoregressive modeling approach based on mixed variables (MV-ARX) in CNC Swiss lathes. In addition, offline prediction is achieved by replacing online measurements with estimates of thermal errors. The effects of factors on thermal error, such as ambient temperature and spindle speed, are analyzed through thermal characteristic experiments. The K-means clustering method was used to select the thermal critical point, and the exogenous input autoregressive prediction model was optimized by combining the selected temperature variables with the spindle speed to improve the accuracy and robustness of offline prediction. Compared with the model based on temperature-variable autoregression (TV-ARX) and multivariate linear regression (MLR), the proposed model shows better prediction performance. The offline prediction of thermal errors also showed good performance under non-training conditions, with an offline prediction accuracy of up to 83.52%. The modeling method proposed in this work may pave the way for improving the prediction of other errors with similar nonlinear hysteresis dynamical systems.
The Taxonomy of Predict-Observe-Explain (POE) as a Teaching Strategy and Thinking Process of Chemistry Stakeholders
Authors: Mirabueno Dolores 
Published: October 2023

Abstract
Predict-observe-explain (POE) is a strategy being used during scientific investigations and experiments. However, POE-related studies mainly focused on its validity and reliability as a teaching strategy in classrooms. Thus, this paper extends the context of POE strategy as science process skills, as cognitive thinking skills in performing experiments, and answering scientific inquiries among chemistry stakeholders: students, teachers, and chemists. The study sees POE as a way to develop critical thinking and builds the skills needed for further academic and professional endeavors in the different fields of science. Through a constructivist grounded theory methodology using focus group discussions for students and in-depth interviews with the teachers and chemists, the study: described how students, teachers, and chemists exemplified POE strategy in terms of its process, and identified mutual patterns of POE process from the chemistry stakeholders. The study revealed that: student POE taxonomy is focused on basic processes and structures of POE; teacher POE taxonomy is a guide in their lesson planning; and chemist POE taxonomy is based on local and international compliance during experimentation. Therefore, POE is a science process skill for chemistry stakeholders where the POE taxonomy used by the chemistry stakeholders are different based on experiences, needs, and context.
Perceptions of uncertainty in medical care among non-medical citizens and nurses in Japan: A cross- sectional internet-based survey
Authors: Akiyama Naomi , Kajiwara Shihoko , Uozumi Ryuji , Akiyama Tomoya , Hayashida Kenshi , Sim Jasmine , Morikawa Mie 
Published: October 2023

Abstract
Background
Patient safety impacts not only patients and their relatives but also patients’ health outcomes and lives. While medical care providers make efforts to prevent medical accidents, medical care is inherently characterized by uncertainty in its processes and outcomes. This study aimed to compare tolerance of uncertainty in medical care between non-medical citizens and nurses.
Methods
We conducted a cross-sectional internet-based survey. Participants included 2,100 individuals (600 nurses and 1,500 non-medical citizens) from different parts of Japan, aged 20 years and above. Of these, we excluded 70 participants who were classified as non-medical citizens but were registered nurses. Finally, we analyzed data from 2,030 participants (600 nurses and 1,430 non-medical citizens). Three registered nurses and nursing researchers developed an original questionnaire on tolerance of uncertainty in medical care. Data regarding participants’ characteristics (age, sex, education level, marital status, having children, population size of the residential area, medical care usage, and occupation) were obtained. We conducted a one-way analysis of variance to compare data from non-medical citizens and nurses and used a multiple regression model to investigate the factors related to the scores of tolerance of uncertainty in medical care.
Results
A high percentage of participants were aged 40−50 years (n = 745, 36.7%); the sample mostly consisted of female participants (n = 1,210, 59.6%) and had a higher percentage of medical care users (n = 1,309, 64.5%). Non-medical citizens were found to be less tolerant of uncertainty than nurses, and uncertainty scores were associated with medical care usage, occupation, and population size of the residential area.
Conclusions
Our results indicated differences in the perceptions of uncertainty in medical care between non-medical citizens and medical care providers. To reduce conflicts related to medical issues, medical care providers need to improve citizen education regarding perceptions of uncertainty in medical care.
Real-world behavioral practices of cancer patients: time to shift from health related-QoL to real-life-QoL
Authors: Shachar Eliya , Peleg-Hasson Shira , Vorobiof Daniel , Moisa Noy , Waller Emanuel , Safra Tamar , Wolf Ido 
Published: October 2023

Abstract
Background
Health-related quality of life (HR-QoL) is an assessments tool commonly used as an endpoint in clinical trials. While it evaluates the presence of various symptoms, it does not measure patients’ ability to maintain normal daily activities during cancer therapy. We designed a real-life quality of life (RL-QoL) tool, validated among a cohort of actively treated cancer patients at a single cancer center prior to the COVID-19 pandemic. Using this tool we discovered that most patients reported compromised daily activities. In this study we aimed to examine RL-QoL in an international cohort of patients.
Methods
A locally validated questionnaire was distributed internationally using the Belong.life digital health platform. We examined real-world patient reported practices, provided by patients voluntarily and anonymously. The survey consisted of demographic, clinical, behavioral parameters and sources guiding and supporting patient practices. Independent clinical and demographic variables were analyzed, and a multivariate logistic regression was performed identifying factors predicting restrictive behavior.
Results
The study comprised 1,395 patient reported outcomes. Most respondents were from the United Stated (1142, 78.43%), 225 (15.45%) from Israel, and a minority (89, 6.11%) from other countries. The majority of participants (1,005, 72.88%) reported at least one adopted limitation in daily activities, and 305 (21.86%) maintained more than half of these constraints. Daily life restrictions included avoiding sun exposure (779, 57.83%), international travel (417, 33.33%), indoor public places (431, 33.13%), hair dyeing (271, 22.72%), domestic tourism (284, 21.93%), contact with friends and family (231, 17.69%), children and grandchildren (202, 16.33%), outdoor public spaces (190, 14.62%), and contact with pets (135, 10.41%). Multiple sources were implicated by patients guiding their behavior, including health-care professionals (951, 65.95%), non-medical authorities including the internet, patient forums, partners, friends, and family (171, 11.86%), and both non-medical authorities and the health-care team (320, 22.19%).
There was no association between country of origin (p=0.118), and education level (p=0.3591) across patients who maintained strict (≥50% of the limitations) and less strict restrictions (<50% of the limitations). A significant association was noted between younger age (p=0.0014), female sex (p=0.0141) and primary cancer site (p<0.0001), and the adoption of strict restrictions.
Conclusion
The majority of patients globally reported compromised daily activities, which are likely attributed to misconceptions about therapy and disease. These findings call for the assessment of an overlooked measure, RL-QoL, as an additional endpoint of clinical trials, aiming to achieve the ultimate benefit for our patients, a measure of a full and meaningful life.
Electrolyte Disorders Induced by Multikinase Inhibitors Therapy for Renal Cell Carcinoma：A Large-Scale Pharmacovigilance Analysis
Authors: She Xianhua , Wang Shuyun , Yin Donghong , Wang Xuyan 
Published: October 2023

Abstract
Objective
To provide evidence for optimization of multi-kinase inhibitors (MKIs) use in the clinic, we use the public database to describe and evaluate electrolyte disorders related to various MKIs treated for renal cell carcinoma.
Methods
We analyzed spontaneous reports submitted to the Food and Drug Administration Adverse Events Reporting System (FAERS) in an observational and retrospective manner. Selecting electrolyte disorders' adverse events to multikinase inhibitors (axitinib, cabozantinib, lenvatinib, pazopanib, sunitinib, and sorafenib). We used Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms to analyze suspected adverse reactions of electrolyte disorders induced by MKIs (which were treated for renal cell carcinoma) between January 2004 and December 2022.
Results
As of December 2022, 2772 MKIs (which were treated for renal cell carcinoma) ICSRs were related to electrolyte disorders AEs. In general, there were more ADR cases in males, except lenvatinib and 71.8% of the cases were submitted from North America. ICSRs in this study, the age group most frequently affected by electrolyte disorders AEs was individuals aged 45–64 years for axitinib, cabozantinib, pazopanib, and sunitinib, whereas electrolyte disorders AEs were more common in older patients (65–74 years) for sorafenib and lenvatinib. For all EDs documented in ICSRs (excluding missing data), the most common adverse outcome was hospitalization(1429/2674, 53.4%), and the most serious outcome was death/life-threat(281/2674, 10.5%). The prevalence of mortality was highest for sunitinib-related EDs (145/616, 23.5%), excluding missing data (n = 68), followed by cabozantinib-related EDs (20/237, 8.4%), excluding missing data (n = 1). The distribution of time-to-onset of Each drug-related ICSRs was not all the same, and the difference was statistically significant (P = 0.001). With the criteria of ROR, the six MKIs were all significantly associated with electrolyte disorders AEs, the strongest association was the association between cabozantinib and hypermagnesaemia.
Conclusions
MKIs have been reported to have significant electrolyte disorders side effects. Patients and physicians need to recognize and monitor these potentially fatal adverse events.
Application of the fractional-rational functions for quantitative description of the basic principal components in voltammetric analysis of different apple juices by “electronic tongue".
Authors: Sidelnikov Artem , Nigmatullin Raoul , Budnikov Herman , Saburova Yulia , Mustafin Akhat , Bizhanova Guliya 
Published: October 2023

Abstract
For the purposes of a food chemistry, it is important to differentiate of complex liquids (as gels, emulsions, juices etc.) from each other. This paper presents for the first time a temporal approach to the study of the voltammetric behavior of multicomponent mixtures with implicit peaks of oxidation/reduction of electroactive components in the initial voltammetric data. It is shown that it is possible to structure voltammograms to obtain characteristic analytical signals due to the peculiarity of the evolution of the electrochemical electrode/solution system with their multiple functioning. Electrochemical analysis of the voltammograms and their subsequent processing with the help of principal component analysis (PCA) gives only qualitative picture. This method helps to differentiate the different components and separate them identifying different correlations. For the food industry it is very desirable to receive a set of quantitative parameters (not exceeding 20) in the significance/feature space that would separate one complex fluid from another one. The careful analysis helps to propose the class of fractional-rational functions allowing to solve this separation problem quantitavely.