bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of Patterns of Hospitalizations in Child and Adolescent Mental Health Service
Authors: Urben Sébastien , Golay Philippe , Forte Alberto , Courousse Swen , Kapp Carole , Plessen Kerstin Jessica , Armando Marco 
Published: June 2024

AbstractAdolescence is a time of increased vulnerability to mental health conditions, which may necessitate hospitalization. This study sought to identify and characterize patterns of adolescent (re-)hospitalizations. The one-year (re-)hospitalization patterns of 233 adolescents were analyzed. The sequences of hospitalization and discharge was examined using cluster analyses. Results revealed five distinct (re-)hospitalization patterns or clusters: Cluster A represented brief hospitalizations with 56 cases (24.03%) averaging 7.71 days; cluster B consisted of repetitive short hospitalizations involving 97 cases (41.63%) with an average of 19.90 days; cluster C encompassed repetitive medium hospitalizations included 66 cases (28.33%) averaging 41.33 days; cluster D included long hospitalizations with 11 cases (4.72%) and an average of 99.36 days; cluster E depicted chronic hospitalizations, accounting for 3 cases (1.29%) with an average stay of 138.67 days. Despite no age-based differences across clusters, distinctions were noted in terms of sex, diagnoses, and severity of clinical and psychosocial difficulties. The study identified characteristics of both regular and atypical adolescent hospitalization users, emphasizing the distribution of hospitalization days and their associated clinical attributes. Such insights are pivotal for enhancing the organization of child and adolescent mental health services to cater to the growing care requirements of this age group.
Zur Wirksamkeit hochschuldidaktischer Weiterbildungsmaßnahmen an deutschen Universitäten und Hochschulen: Eine systematische Überblicksstudie
Authors: Hoffmann Selina , Klinger Melanie , Deutscher Viola 
Published: June 2024

ZusammenfassungDiese Arbeit gibt einen Überblick über die Effekte hochschuldidaktischer Weiterbildungsmaßnahmen an deutschen Hochschulen seit Einführung des Qualitätspakts Lehre. Dabei werden insbesondere die Lehrkompetenzen der Dozierenden fokussiert. Die Ergebnisse von dreizehn Primärstudien, welche die Wirksamkeit hochschuldidaktischer Interventionen auf die Lehrkompetenzen untersuchen, werden in einem systematischen Review zusammengefasst und in einem Modell akademischer Lehrkompetenz verortet. Da die Wirkungsdimensionen Selbstwirksamkeitserwartungen von Lehrenden und Studierendenfokussierung eine ausreichende Studienzahl aufweisen, wird für diese zwei Subbereiche auf Basis von quantitativen Meta-Analysen untersucht, ob sich die Wirksamkeit der hochschuldidaktischen Maßnahmen studienübergreifend empirisch absichern lässt. Die Ergebnisse lassen die Schlussfolgerung zu, dass hochschuldidaktische Weiterbildungsmaßnahmen einen positiven Einfluss auf die Entwicklung der Lehrkompetenz haben – zumindest gemessen an der Selbsteinschätzung der Dozierenden. Aufgrund der eingeschränkten Studienlage ist weitere Forschung notwendig, um eine effektive Gestaltung hochschuldidaktischer Maßnahmen evidenzbasiert zu unterstützen.
The Impact of Cholecystectomy in Patients with Post-Bariatric Surgery Hypoglycemia
Authors: Sardão Daniel , Santos-Sousa Hugo , Peleteiro Bárbara , Resende Fernando , Costa-Pinho André , Preto John , Lima-da-Costa Eduardo , Freitas Paula ,   CRI-O Group
Published: June 2024

Abstract
Background
Metabolic surgery is the foremost treatment for obesity and its associated medical conditions. Nonetheless, post-bariatric hypoglycemia (PBH) emerges as a prevalent complication. PBH pathophysiology implicates heightened insulin and glucagon-like peptide 1 (GLP-1) levels, with bile acids (BA) contributing to GLP-1 release. A plausible association exists between cholecystectomy and PBH, which is attributed to alterations in BA metabolism and ensuing hormonal responses. The objective of this retrospective cohort study was to evaluate the impact of cholecystectomy on PBH pharmacological treatment, diagnostic timelines and metabolic parameters.

Materials and methods
Patients diagnosed with PBH after bariatric surgery were evaluated based on their history of cholecystectomy. Demographic, anthropometric and clinical data were collected. Mixed meal tolerance tests (MMTT) results were compiled to assess metabolic responses.

Results
Of the 131 patients with PBH included in the study, 29 had prior cholecystectomy. The time to PBH diagnosis was similar across groups. Patients with prior cholecystectomy required higher doses of acarbose (p = 0.046), compared to those without prior cholecystectomy. Additionally, MMTT revealed higher insulin (t = 60 min: p = 0.010 and t = 90 min: p = 0.034) and c-peptide levels (t = 60 min: p = 0.008) and greater glycemic variability in patients with prior cholecystectomy (p = 0.049), highlighting the impact of cholecystectomy on glucose metabolism.

Conclusion
Our study offers novel insights into PBH pharmacotherapy, indicating that PBH patients with a history of cholecystectomy require elevated doses of acarbose for symptom control than PBH patients without such surgical history. Furthermore, our findings underscore the pivotal role of hyperinsulinism in PBH aetiology, emphasizing the significance of the BA-GLP-1-insulin axis.

Graphical Abstract
Relationships Between Changes in Serum Ketone Body Levels and Metabolic Effects in Patients with Severe Obesity Who Underwent Laparoscopic Sleeve Gastrectomy
Authors: Umemura Akira , Sasaki Akira , Kumagai Hideki , Tanahashi Yota , Iwasaki Takafumi , Nitta Hiroyuki 
Published: June 2024

Abstract
Background
Serum ketone bodies increase due to dynamic changes in the lipid metabolisms of patients undergoing bariatric surgery. However, there have been few studies on the role of ketone bodies after bariatric surgery. We aimed to clarify the role of and relationship between the changes in serum ketone bodies and weight loss, as well as between those changes and the metabolic effects after laparoscopic sleeve gastrectomy (LSG).

Methods
We recruited 52 patients with severe obesity who underwent LSG. We measured acetoacetic acid (AcAc) and β-hydroxybutyric acid (β-OHB) at the baseline, 1 month, and 6 months after LSG. Subsequently, we compared the changes in the serum ketone bodies with weight-loss effects and various metabolic parameters.

Results
At 1 month after LSG, β-OHB significantly increased (p = 0.009), then significantly decreased 6 months after LSG (p = 0.002). In addition, β-OHB in patients without Type 2 diabetes (T2D) and metabolic dysfunction-associated steatohepatitis (MASH) was notably higher than in patients with T2D at 1 month after LSG (p < 0.001).
In the early phase, both AcAc and β-OHB mainly had strong positive correlations with changes in T2D- and MASH-related parameters. In the middle term after LSG, changes in both AcAc and β-OHB were positively correlated with changes in lipid parameters and chronic kidney disease-related parameters.

Conclusion
We demonstrated that the postoperative surge of ketone bodies plays a crucial function in controlling metabolic effects after LSG. These findings suggest the cause- and consequence-related roles of ketone bodies in the metabolic benefits of bariatric surgery.

Graphical Abstract
The robo bias in conversational reviews: How the solicitation medium anthropomorphism affects product rating valence and review helpfulness
Authors: Tsekouras Dimitrios , Gutt Dominik , Heimbach Irina 
Published: June 2024

AbstractCompanies are increasingly introducing conversational reviews—reviews solicited via chatbots—to gain customer feedback. However, little is known about how chatbot-mediated solicitation influences rating valence and review helpfulness compared to conventional online forms. Therefore, we conceptualized these review solicitation media on the continuum of anthropomorphism and investigated how various levels of anthropomorphism affect rating valence and review helpfulness, showing that more anthropomorphic media lead to more positive and less helpful reviews. We found that moderate levels of anthropomorphism lead to increased interaction enjoyment, and high levels increase social presence, thus inflating the rating valence and decreasing review helpfulness. Further, the effect of anthropomorphism remains robust across review solicitors’ salience (sellers vs. platforms) and expressed emotionality in conversations. Our study is among the first to investigate chatbots as a new form of technology to solicit online reviews, providing insights to inform various stakeholders of the advantages, drawbacks, and potential ethical concerns of anthropomorphic technology in customer feedback solicitation.
Gender differences in homicides. A comparative analysis of 106 fatalities in forensic autopsy data
Authors: Walz Cleo , Eifert Steffen , Görg Johanna , Schwarz Clara-Sophie , Steffan Christian , Brettel Hauke , Germerott Tanja 
Published: June 2024

AbstractWhile most homicides worldwide are committed against men, women and girls are disproportionately affected by domestic violence and its fatal consequences. The Istanbul Convention mandates the prevention of gender-based violence, particularly against women. This study analyzes the characteristics of male and female victims of homicides to provide a comprehensive understanding of the different situations and ways in which men and women are killed. Files of 106 forensic autopsies of homicide victims aged 14 years and older (51.9% males, 48.1% females) from 2012 to 2019 were reviewed. Demographic data, previous history with a focus on the perpetrator-victim relationship, substance influence, type of violence and law enforcement data were recorded. A gender-separated statistical analysis was carried out. Male victims were killed most often outside their own home (63.6%) by acquaintances or friends (54.5%). They were frequently under the influence of substances (56.4%). The perpetrators suffered from addictive diseases in 49.1%, and 52.7% had prior convictions. In both groups, stab/cut injuries were the most common causes of death, but stab/cut and gunshot injuries occurred more frequently in male victims. Female victims were killed most often in their own homes (76.5%) by intimate partners (62.7%). Compared to male victims, violent asphyxiation and blunt force trauma were more common causes of death. Furthermore, there was a higher frequency of multiple injuries (33.3%). The prevalence of a guilty verdict of the perpetrators was nearly equal in both groups. Gender-specific aspects should be considered when investigating homicides and establishing prevention and intervention strategies for interpersonal violence. Protective concepts are easier to establish in the public sphere than in private homes, which is why homicides against women require special attention in society, law enforcement, and legislation. Significant gender differences were found in the circumstances and the perpetrator-victim relationships of homicides. Gender-specific aspects should be taken into account when investigating homicides and developing prevention and intervention strategies. Homicides against women require special attention in society, law enforcement and legislation.
Quantitative Expression of Latent Disease Factors in Individuals Associated with Psychopathology Dimensions and Treatment Response
Authors: Zhao Shaoling , Lv Qian , Zhang Ge , Zhang Jiangtao , Wang Heqiu , Zhang Jianmin , Wang Meiyun , Wang Zheng 
Published: June 2024

AbstractPsychiatric comorbidity is common in symptom-based diagnoses like autism spectrum disorder (ASD), attention/deficit hyper-activity disorder (ADHD), and obsessive-compulsive disorder (OCD). However, these co-occurring symptoms mediated by shared and/or distinct neural mechanisms are difficult to profile at the individual level. Capitalizing on unsupervised machine learning with a hierarchical Bayesian framework, we derived latent disease factors from resting-state functional connectivity data in a hybrid cohort of ASD and ADHD and delineated individual associations with dimensional symptoms based on canonical correlation analysis. Models based on the same factors generalized to previously unseen individuals in a subclinical cohort and one local OCD database with a subset of patients undergoing neurosurgical intervention. Four factors, identified as variably co-expressed in each patient, were significantly correlated with distinct symptom domains (r = –0.26–0.53, P < 0.05): behavioral regulation (Factor-1), communication (Factor-2), anxiety (Factor-3), adaptive behaviors (Factor-4). Moreover, we demonstrated Factor-1 expressed in patients with OCD and Factor-3 expressed in participants with anxiety, at the degree to which factor expression was significantly predictive of individual symptom scores (r = 0.18–0.5, P < 0.01). Importantly, peri-intervention changes in Factor-1 of OCD were associated with variable treatment outcomes (r = 0.39, P < 0.05). Our results indicate that these data-derived latent disease factors quantify individual factor expression to inform dimensional symptom and treatment outcomes across cohorts, which may promote quantitative psychiatric diagnosis and personalized intervention.
Using Artificial Neural Networks and Spectral Indices to Predict Water Availability in New Capital (IKN) and Its’ Surroundings
Authors: Arif Nursida , Toersilowati Laras 
Published: June 2024

AbstractThis study aims to predict water availability in New Capital (IKN) and its surroundings using artificial neural networks and spectral indices as predictors. The study uses Sentinel-2 A imagery from the year 2022 analyzed directly from Google Earth Engine (GEE) to calculate three spectral indices, including the Land Surface Water Index (LSWI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI), and uses these indices as predictors in the artificial neural network model. The study carried out four simulations to determine the best prediction results, and the best results were obtained using ANN parameters: 2 hidden layers (HL); learning rate (LR) 0.01; momentum (M) 0.4; root mean square (RMS) 0.001 and iteration (I) 25,000 with overall accuracy (OA) 97.7% and kappa index 0.96. The results show that the percentage of water availability in the study area is high water/HW (0.51%), vegetation water/VW (20.41%), and non-water/NW (79.08%). The study concludes that artificial neural networks and spectral indices can effectively predict water availability.
An oversampling algorithm of multi-label data based on cluster-specific samples and fuzzy rough set theory
Authors: Liu Jinming , Huang Kai , Chen Chen , Mao Jian 
Published: June 2024

AbstractImbalanced class distributions are common in real-world scenarios, including datasets with multiple labels. One widely acknowledged approach to addressing imbalanced distributions is through oversampling, a technique that both balances the class distribution and improves the effectiveness of classification models. However, when generating synthetic data for multi-label datasets, complexities arise due to the presence of multiple-label sets, which require careful placement and labeling. We propose MLCSMOTE-FRST, an algorithm for synthetic data generation based on label-specific clustering and fuzzy rough set theory. Generation ratios and dependency samples are provided by clusters specific to each label, with a focus on the overall label distribution and the distribution within each cluster. The labels are supported by intra-cluster positive samples, determined using fuzzy rough set theory, which helps to capture the consensus label set. Experimental results on multi-label datasets using four classifiers demonstrate the effectiveness of the proposed method in terms of macro-F1 and micro-F1 scores.
Recent Advance in Synaptic Plasticity Modulation Techniques for Neuromorphic Applications
Authors: Sun Yilin , Wang Huaipeng , Xie Dan 
Published: June 2024

AbstractManipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artificial intelligence. However, great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few years. Recent progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation, improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing functions. Herein, several fascinating strategies for synaptic plasticity modulation through chemical techniques, device structure design, and physical signal sensing are reviewed. For chemical techniques, the underlying mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also highlighted. Based on device structure design, the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic functions. Besides, integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light, strain, and temperature. Finally, considering that the relevant technology is still in the basic exploration stage, some prospects or development suggestions are put forward to promote the development of neuromorphic devices.
Improving PID Controller Performance in Nonlinear Oscillatory Automatic Generation Control Systems Using a Multi-objective Marine Predator Algorithm with Enhanced Diversity
Authors: Yang Yang , Gao Yuchao , Wu Jinran , Ding Zhe , Zhao Shangrui 
Published: June 2024

AbstractPower systems are pivotal in providing sustainable energy across various sectors. However, optimizing their performance to meet modern demands remains a significant challenge. This paper introduces an innovative strategy to improve the optimization of PID controllers within nonlinear oscillatory Automatic Generation Control (AGC) systems, essential for the stability of power systems. Our approach aims to reduce the integrated time squared error, the integrated time absolute error, and the rate of change in deviation, facilitating faster convergence, diminished overshoot, and decreased oscillations. By incorporating the spiral model from the Whale Optimization Algorithm (WOA) into the Multi-Objective Marine Predator Algorithm (MOMPA), our method effectively broadens the diversity of solution sets and finely tunes the balance between exploration and exploitation strategies. Furthermore, the QQSMOMPA framework integrates quasi-oppositional learning and Q-learning to overcome local optima, thereby generating optimal Pareto solutions. When applied to nonlinear AGC systems featuring governor dead zones, the PID controllers optimized by QQSMOMPA not only achieve 14$$\%$$
%
reduction in the frequency settling time but also exhibit robustness against uncertainties in load disturbance inputs.
Fuzzy Neural Network Model for Intelligent Course Development in Music and Dance Education
Authors: Zhao Lin , Sun Ying , Tian Tian 
Published: June 2024

AbstractInteractions are mandatory for online or offline music and dance education to improve understandability and learning efficacy. The course designed for such artistic education incorporates multi-point interactions and monotonous presentations. The validation of the key factor: interactivity is thus mandatory for enhancing efficiency. This article introduces an interactivity validation method (IVM) using combined fuzzy neural network (FNN) to aid artistic course development. The output of the existing course and its evaluation criteria are considered in enhancing its grade. The fuzzy performs interaction classification as mandatory and trivial based on the student’s performance. The neural network identifies the chances for maximum performance by increasing or decreasing the interaction rate. If a saturated performance is achieved at a high or low interactivity, then the further course design is performed based on the saturated interactivity factor. The failing factors are used for training the neural network for modifying the interactivity rate from the current course development suggestion. Such a process is keen on classifying and validating the impact of interactivity over artistic course design.
The impact of frailty on rectal prolapse repair: a retrospective analysis of the national inpatient sample for clinical outcomes and health resource utilization
Authors: McKechnie Tyler , Patel Janhavi , Jessani Ghazal , Lee Yung , Amin Nalin , Doumouras Aristithes , Hong Dennis , Eskicioglu Cagla 
Published: June 2024

Abstract
Purpose
Rectal prolapse commonly affects elderly, frail patients. The impact of frailty alone on surgical outcomes for rectal prolapse has not been thoroughly investigated. The aim of this study was to utilize the National Inpatient Sample and the modified frailty index (mFI-11) to compare postoperative outcomes between frail and robust patients undergoing surgery for rectal prolapse.

Methods
We conducted a retrospective population-based cohort study using the Healthcare Cost and Utilization Project (HCUP) NIS from 2015 to 2019. The mFI-11 was utilized to classify patients as frail or robust. The primary outcomes were overall in-hospital postoperative morbidity and mortality. The secondary outcomes included system-specific postoperative morbidity, length of stay (LOS), total in-hospital healthcare cost, and discharge disposition. These were assessed using univariable and multivariable regressions.

Results
A total of 2130 patients, 239 frail (mFI > 0.27) and 1,891 robust patients (mFI < 0.27) who underwent rectal prolapse repair were analyzed. After adjustment, frail patients had a higher rate of in-hospital mortality (OR 10.38, 95% CI 0.65–166.59, p = 0.098) and morbidity (OR 2.18, 95% CI 1.31–3.63, p = 0.003), longer LOS (MD 1.60 days, 95% CI 1.05–2.44, p = 0.028), and greater cost of treatment (MD $15,561.56, 95% CI − 6023.12–37,146.25, p = 0.157) than robust patients.

Conclusion
Frailty increases postoperative morbidity and mortality and cost more to the healthcare system overall for patients undergoing rectal prolapse repair. This retrospective study is limited by selection bias and residual confounding. Consideration of preoperative optimization programs for frail patients undergoing surgery for rectal prolapse is an important next step to mitigate these poor outcomes.
Far‐Field Groundwater Response to the Lamb Waves From the 2022 Hunga‐Tonga Volcano Eruption
Authors: Zhang Xin , Chen Mingyu , Zhong Tianren , De Santis Angelo , Han Peng 
Published: June 2024

AbstractOn 15 January 2022, the largest eruption of the Hunga‐Tonga volcano in recorded history produced a plume registered by multi‐parametric instruments around the world. However, the far‐field hydrogeological responses to Lamb waves from this eruption remain underexplored. We studied the responses of groundwater to the volcanic eruption in the far‐field over 8,700 km, including 274 wells. Results show that the Lamb waves with a speed of 316 m/s affects the groundwater system, leading to similar fluctuations in well water level (WL) and opposite phase fluctuation in borehole strain. Different wells exhibit diverse responses in WL amplitudes, possibly for heterogeneities in local aquifer systems. Gain values of 5 wells that simultaneously measure atmospheric pressure, borehole air pressure, borehole strain and WL are consistent with results obtained through cross‐power spectrum estimation. This work demonstrates a novel response in far‐field groundwater systems induced by Lamb waves and expects application for aquifer parameter estimation.