bluuebunny/crossref_metadata_2025_split huggingface dataset:
Does wearing facemasks during small animal surgery reduce the incidence of surgical site infections?
Authors: Bartlett Alexander 
Published: October 2024

Question
In small animals undergoing theatre-based surgical procedures does having all theatre personnel masked, compared with not having all theatre personnel masked, result in a reduced incidence of surgical site infections?

Clinical bottom line
The category of research question was:
Incidence.

The number and type of study designs that were critically appraised were:
Zero. No records relevant to the PICO question were retrieved from the literature search.

Critical appraisal of the selected papers meeting the inclusion criteria collectively provide zero/weak/moderate/strong evidence in terms of their experimental design and implementation:
Zero.

The outcomes reported are summarised as follows…
There is no published evidence specific to small animals that assesses the effect of wearing facemasks during surgical procedures on the rate of postoperative surgical site infections.

In view of the strength of evidence and the outcomes from the studies the following conclusion is made…
In small animals undergoing theatre-based surgical procedures, there is no published evidence evaluating the effect of having all theatre personnel masked compared with not having all theatre personnel masked on the incidence of surgical site infections. However, this lack of evidence should not be interpreted as lack of efficacy.
Bacterial Profiles and Antibiotic Resistance in Chronic Obstructive Pulmonary Disease Patients with Exacerbation and Type 2 Respiratory Failure at Adam Malik General Hospital
Authors: Lia Mutia Annisa  , Fajrinur Syarani  , Andika Pradana  , Erna Mutiara  
Published: October 2024

Highlights:1. This study provides a comprehensive analysis of various factors such as age, sex, education, occupation, BMI, and comorbidities, and their relationship with bacterial infections in COPD patients experiencing exacerbation and type 2 respiratory failure.2. While the COPD patients experiencing exacerbation did not exhibit resistance to linezolid and vancomycin, they demonstrated specific antibiotic resistance patterns characterized by high resistance rates to commonly used antibiotics such as meropenem and amikacin.3. The findings enhance the understanding of the complex interplay of factors influencing infection patterns in this patient population.

Abstract
Chronic obstructive pulmonary disease (COPD) is a prevalent condition characterized by persistent respiratory symptoms and airflow limitation. Bacterial infections may trigger COPD exacerbations, leading to more severe symptoms as well as increased morbidity and mortality rates. This study aimed to investigate the bacterial profiles and antibiotic resistance in COPD patients who had experienced exacerbation and type 2 respiratory failure at Adam Malik Central General Hospital, Medan, Indonesia. This retrospective study utilized medical records spanning from January 1, 2020, to December 1, 2022. The sample included patients aged 40–90 years who had experienced COPD exacerbation and type 2 respiratory failure. The exclusion criteria were patients who had received antibiotic therapy within 48 hours before admission, were severely immunocompromised, and had severe malignancy. The analysis results were presented in the form of means, standard deviations, and frequency distributions. Additionally, an analysis of the relationship between the categorical variables was performed using the Chi-squared test (p<0.05). The study analyzed 25 subjects with an average age of 63.6 years, primarily consisting of men (84%). It was shown that severe exacerbations were prevalent (92%), accompanied by the presence of common comorbidities including pneumonia (52%), diabetes mellitus (32%), and other non-communicable diseases (44%). Bacterial growth was observed in 76% of the subjects, predominantly involving Gram-negative bacteria (89.4%). Klebsiella pneumoniae (26.3%) and Pseudomonas aeruginosa (21.1%) were the most frequently isolated species. The antibiotic resistance patterns indicated that meropenem and amikacin had the highest resistance rates (100%). Cefepime, ertapenem, and gentamicin exhibited notable resistance rates of 66.7%, 66.7%, and 75.0%, respectively. This study highlights the high prevalence of Gram-negative bacteria and significant antibiotic resistance in COPD patients who exhibit exacerbation and type 2 respiratory failure.
Sexual Abuse and Neglect during Childhood are Associated with an Increased Prevalence of Mental Health Problems among University Students in Surakarta, Indonesia
Authors: Ni Putu Dian Apriandary  , Muthmainah Muthmainah , Rohmaningtyas Hidayah Setyaningrum  , Debree Septiawan  
Published: October 2024

Hihglights:
1. This study reiterates the long-term negative impact of childhood trauma on young adults' mental health.2. This study contributes to the prevention of mental disorders through the identification of risk factors associated with mental health problems.

Abstract
The prevalence of mental health problems is a global public health concern. Young adults, such as university students, are highly vulnerable to the onset of mental health problems due to biological, psychological, and social factors. In particular, abusive and traumatic experiences during childhood may increase the risk of developing mental health problems during adulthood. The prevalence of child abuse cases in Indonesia is concerning. This abuse includes physical, emotional, and sexual abuse, in addition to neglect. This study aimed to assess the relationship between the occurrence of mental disorder symptoms during young adulthood and the preceding child abuse. A total of 191 undergraduate students in Surakarta, Indonesia, participated in this study. The participants completed the Child Abuse and Trauma Scale (CATS) for the evaluation of maltreatment experienced during childhood and adolescence as well as the Self-Reporting Questionnaire-20 (SRQ-20) for the measurement of mental health problem symptoms. The association of the degree of child abuse and trauma with mental health problems was analyzed using a logistic regression test, which was selected because the dependent variable (mental health problems) had binary outcomes. The level of statistical significance was set at p<0.05. We found that 33% of the participants reported mental health problems. In addition, sexual abuse and neglect were found to be associated with mental health problems. The analysis of the sexual abuse variable revealed a statistically significant value of p=0.03, an odds ratio (OR) of 1.39, and a 95% confidence interval (CI) of 1.03-1.88. Additionally, the analysis of the neglect variable yielded comparable results with values of p=0.03, OR=1.26, and 95% CI=1.02-1.55. Our findings suggest that child abuse, particularly sexual abuse and neglect, may have a long-term deleterious impact on an individual’s mental health.
Tools for effective patient education to manage outcome expectations in paediatric facial reanimation: a systematic review
Authors: Reissis Dimitris , Zubler Cédric , Buitleir Edel de , Brown Sam , Leckenby Jonathan , Grobbelaar Adriaan 
Published: October 2024

Aim: Informed consent for paediatric facial reanimation requires effective patient/parent education and involvement in a shared decision-making (SDM) process to help set their expectations and understanding from the outset. No article in the current literature has systematically reviewed the available tools for facilitating effective patient/parent education and the validity of informed consent in the context of paediatric facial reanimation.
Methods: A systematic literature review was undertaken, following the Preferred Reporting Items of Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines. MEDLINE via PubMed, Embase and Cochrane Library were searched and the results screened and reviewed in accordance with pre-defined inclusion and exclusion criteria.
Results: The initial search yielded 478 articles, of which only 4 fulfilled the study’s inclusion criteria. One cohort study evaluated qualitative feedback from patients and their relatives participating in a family education and support day for paediatric facial palsy, while another article from the same group reviewed the readability of online education resources. The remaining two articles represented educational reviews focusing on treatment and patient education based on expert opinion without providing original outcome data.
Conclusion: There is a paucity of evidence regarding patient/parent education to support the informed consent process for children undergoing paediatric facial reanimation. There remains a need for further resources and platforms to be developed that may support children and their parents in engaging in a SDM process, setting appropriate expectations, and providing valid informed consent for their surgery.
Novel Image-Analytic Approach Reveals New Insights in Fine Tuning of Slime Mould Network Adaptation
Authors: Rosina Philipp , Grube Martin 
Published: October 2024

Abstract

This study introduces a novel methodology to explore the network dynamics of Physarum polycephalum, an organism celebrated for its remarkable adaptive capabilities. We used two innovative techniques to analyse its growth behaviour and network modifications under varying stress conditions, including starvation and differential epinephrine exposures. The first method provided a quantitative assessment of growth and exploration over time, revealing significant reductions under stress. The second method provided a detailed examination of vein diameter and contraction patterns, illuminating the physiological adjustments P. polycephalum undergoes in response to environmental challenges. By integrating these approaches, we were able to estimate the total network volume of the organism, with a focus on the normalised estimated volume, unveiling insightful aspects of its structural adaptations. While starvation reduced the volume, indicating a significant structural compromise, low and high epinephrine concentrations maintained a volume-to-area ratio comparable to the control. These methods, unprecedented in their application to P. polycephalum, enhance our ability to measure complex biological phenomena and offer a replicable framework for future research in similar systems. This research establishes a foundation for exploring complex network behaviours in biological systems, highlighting the potential of the organism in bioengineering and adaptive network design.
WITHDRAWN: Performance of Plastic Aggregate along with Steel Slag in the Concrete through the Mechanical Tests and Microstructural Analysis
Authors: Rani Kavita , SENTHIL KASILINGAM 
Published: October 2024

Abstract

The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Computational Mechanisms of Learning and Forgetting Differentiate Affective and Substance Use Disorders
Authors: Hakimi Navid , Chou Ko-Ping , Stewart Jennifer , Paulus Martin , Smith Ryan 
Published: October 2024

Abstract

Depression and anxiety are common, highly co-morbid conditions associated with a range of learning and decision-making deficits. While the computational mechanisms underlying these deficits have received growing attention, the transdiagnostic vs. diagnosis-specific nature of these mechanisms remains insufficiently characterized. Individuals with affective disorders (iADs; i.e., depression with or without co-morbid anxiety; N = 168 and 74, respectively) completed a widely-used decision-making task. To establish diagnostic specificity, we also incorporated data from a sample of individuals with substance use disorders (iSUDs; N = 147) and healthy comparisons (HCs; N = 54). Computational modeling afforded separate measures of learning and forgetting rates, among other parameters. Compared to HCs, forgetting rates (reflecting recency bias) were elevated in both iADs and iSUDs (p = 0.007, η² = 0.022). In contrast, iADs showed faster learning rates for negative outcomes than iSUDs (p = 0.027, η² = 0.017), but they did not differ from HCs. Other model parameters associated with learning and information-seeking also showed suggestive relationships with early adversity and impulsivity. Our findings demonstrate distinct differences in learning and forgetting rates between iSUDs, iADs, and HCs, suggesting that different cognitive processes are affected in these conditions. These differences in decision-making processes and their correlations with symptom dimensions suggest that one could specifically develop interventions that target changing forgetting rates and/or learning from negative outcomes. These results pave the way for replication studies to confirm these relationships and establish their clinical implications.
Privacy-Preserving Non-negative Matrix Factorization for Decentralized-Data Using Correlated Noise
Authors: Imtiaz Hafiz , Karmakar Tusher , Mohonta Protoye Kumar 
Published: October 2024

Abstract

Several matrix factorization algorithms are employed in machine learning applications. Among these, Non-negative Matrix Factorization (NMF) gained attention due to the ability to extract meaningful features from inherently non-negative data, such as images or videos. However, such data are often privacy-sensitive, which necessitates formal privacy guarantees of the machine learning model training algorithm. Additionally, modern data are typically stored in different nodes or clients, rather than a centralized server. Conventional decentralized privacy-preserving schemes suffer from too much noise and consequently, much smaller utility compared to their centralized counterparts. This motivates us to develop an efficient privacy-preserving NMF algorithm that can operate on decentralized data, and closely approximates the performance of centralized/non-privacy-preserving approach, while offering strict privacy guarantees. We design our method and demonstrate our results in such a way that the clients/data holders have the control to select the degree of privacy guarantee based on the required utility. We show the effectiveness of our proposed algorithm on six real datasets. Our experimental results show that our proposed method easily outperforms conventional privacy-preserving scheme, while achieving close approximation of the non-privacy-preserving approach under some parameter choices.
Integrative hyperspectral, transcriptomic, and metabolomic analysis reveals the mechanism of tea plants in response to sooty mold disease
Authors: Wang Shuangshuang , Xu Yang , Shen Jiazhi , Chen Hao , Wang Yu , Ding Zhaotang 
Published: October 2024

Abstract

Background Sooty mold (SM) is one of the most destructive diseases of tea plants, causing considerable damage and productivity losses. However, the roles of defense genes and metabolites in different SM-infected canopy layers of tea plants remain largely unclear. To investigate the immune mechanisms of tea plants, we utilized hyperspectral, transcriptomic, and metabolomic data from leaves of three canopy layers infected by SM (A1, A2, and A3). Results The hyperspectral analysis indicated that the spectral characteristics of the three canopy layers significantly differed, and three inflection spots were located close to the 552, 673, and 800 nm wavelengths. Transcriptome analysis showed that the differentially expressed genes were mainly enriched in metabolic pathways, biosynthesis of secondary metabolites, and plant-pathogen interaction. The cluster analysis revealed an elevated immune response in the A2 and A3 samples. A total of 733 metabolites were co-changed in leaves infected by SM, with alcohol, lipids (free fatty acids), hydrocarbons, and amino acids significantly accumulating in A1, while flavonoids were predominantly upregulated in A2 and A3. WGCNA analysis revealed that five hub genes (Dormancy-associated protein, Serine/threonine-protein phosphatase, ABC transporter, and some uncharacterized proteins) and two hub metabolites (D-Mannitol and 17-Hydroxylinolenic Acid) have significant relationships with the DEGs and metabolites. Further co-expression showed that tea plants mainly employed genes and metabolites related to the biosynthesis of secondary metabolites, plant hormone signal transduction, and plant-pathogen interaction to defend against SM. Conclusion This study established a foundation for elucidating the immune mechanisms of different canopy layers of tea plants infected by SM, and provided candidate genes and metabolites for improving tea plant breeding.
STAT-LSTM: A multivariate spatiotemporal feature aggregation model for SPEI-based drought prediction
Authors: Chen Ying , Wu Huanping , Xie Nengfu , Liang Xiaohe , Jiang Lihua , Qiu Minghui , Li Yonglei 
Published: October 2024

Abstract

In recent decades, shifts in the spatiotemporal patterns of precipitation and extreme temperatures have contributed to more frequent droughts. These changes impact not only agricultural production but also food security, ecological sys- tems, and social stability. Advanced techniques such as machine learning and deep learning models outperform traditional models by improving meteorolog- ical drought prediction. Specifically, this study proposes a novel model named the multivariate feature aggregation-based temporal convolutional network for meteorological drought spatiotemporal prediction (STAT-LSTM). The method consists of three parts: a feature aggregation module, which aggregates multi- variate features to extract initial features; a self-attention-temporal convolutional network (SA-TCN), which extracts time series features and uses the self-attention module’s weighting mechanism to automatically capture global dependencies in the sequential data; and a long short-term memory network (LSTM), which cap- tures long-term dependencies. The performance of the STAT-LSTM model was assessed and compared via performance indicators (i.e., MAE, RMSE, and R2 ). The results indicated that STAT-LSTM provided the most accurate SPEI pre- diction (MAE = 0.474, RMSE = 0.63, and R2 = 0.613 for SPEI-3; MAE = 0.356, RMSE = 0.468, and R2 = 0.748 for SPEI-6; MAE = 0.284, RMSE = 0.437, and R2 = 0.813 for SPEI-9; and MAE = 0.182, RMSE = 0.267, and R2 = 0.934 for SPEI-12).
Emotion Recognition in Kurdish Speech from the Sorani Dialect Corpus
Authors: Nematullah Omar , Askar Shavan , Wahhab Shahab , Khidir Bzar 
Published: October 2024

Given the increasing need for interactive human-computer applications, the field of employing machine learning algorithms to discern emotions from speech has seen a substantial surge in interest. While emotion recognition systems have made substantial progress in languages like German, English, Spanish, Dutch, and Danish, the availability of comprehensive datasets for the Kurdish language remains notably limited. This paper addresses this gap by focusing on emotion recognition in Sorani Kurdish dialect speech data, which was carefully gathered from openly available videos from the YouTube platform and categorized into four clear supposed emotions: neutral, sadness, happiness, and anger. The study applied both natural Mel Spectrogram and Mel-Frequency Cepstral Coefficient (MFCC) features for various spectrals, followed by the classification models K-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP), and Support Vector Machine (SVM) to evaluate the results. By closely examining and contrasting the results of using several methods for feature extraction, it was found that SVM obtained a higher accuracy, reaching as much as 85.57%. This is so much more than the first Kurdish emotion classification technique for the recognition of the emotion of the words.
Разработка и валидация ПИТС-индекса для оценки тяжести синдрома последствий интенсивной терапии: описательное проспективное несравнительное когортное исследование
Authors: Белкин Андрей Августович , Рудник Е. Н. , Белкин В. А. , Нагаев Н. С. , Пинчук Е. А. , Рудник А. Е. , Ткачук М. М. 
Published: October 2024

INTRODUCTION: The post intensive care syndrome (PICS) is a clinical manifestation of “learned non-use” phenomena, resulting from the application of metabolic rest strategies such as bed rest, sedation, and ventilation. This leads to prolonged, multifocal dysfunction in vital functions. The lack of standardized diagnostic methods for this syndrome limits its study. For the diagnosis of PICS, we combined 15 signs of vital function disturbances that have the greatest impact on quality of life, with a scoring value of 0.5–1. The sum of these symptoms has been designated as the PICS-index. OBJECTIVE: To develop a scale for calculating the PICS-index with stratification of its values into three ranges of severity: mild, moderate and severe. MATERIALS AND METHODS: A descriptive, prospective, and unmatched cohort study was conducted on 169 patients who had a high dependency on medical care and were admitted to a rehabilitation center between 2022 and 2023. RESULTS: Using the PICS-index, showed that 100 % of patients who spent more than 72 hours in the ICU during the early recovery period (up to 6 months) developed PICS, with a predominance of moderate cases (35–52 %). The proportion of severe PICS forms reached its maximum (37 %) between 3 and 6 months. In the late recovery phase (more than 6 months), mild PICS forms were predominant (45 %). The severity of PICS was influenced by the duration of ICU stay and the timing of mechanical ventilation, but not the age of patients. CONCLUSIONS: The PICS-index is a clinically effective tool for the multidisciplinary diagnosis and assessment of the severity and progression of PICS. Using the PICS-index, we have devised a method for evaluating the predominance of specific signs. The most common signs are disturbance of the gravitational gradient, polyneuromyopathy, dysphagia. This confirms the essence of PICS as a clinical manifestation of the "learned non-use" phenomenon.
Mindat.org – the open access mineralogy database to accelerate data-intensive geoscience research
Authors: Ralph Jolyon , Von Bargen David , Martynov Pavel , Zhang Jiyin , Que Xiang , Prabhu Anirudh , Morrison Shaunna M. , Li Wenjia , Chen Weilin , Ma Xiaogang 
Published: October 2024

Abstract
The mindat.org website (Mindat) has been operating since October 2000 as a free, crowd-sourced, and expert-curated database particularly focused on mineral species and their occurrences worldwide. The project has transformed from a hobbyist site in the beginning into a resource that has found use in various scientific research projects and educational programs. Together with other open data resources, Mindat has helped accelerate scientific discoveries in many fields, such as mineral evolution, mineral ecology, and the co-evolution of the geosphere and biosphere. Recently, through open data efforts, machine interfaces and software packages have been established to enable flexible data discovery and download from Mindat. We assume the data access and usage will further scale up in the next years. Although Mindat is curated by a team of geoscience and database experts across the world, the crowd-sourced records in Mindat still pose some bias. In this paper we first present an overview of the primary data subjects in Mindat, and then we give extensive details about the characteristics and bias of three most popular data subjects: locality, mineral species, and mineral occurrence. In the discussion we also give an outlook on appropriate data usage and future extension of data records. We hope users can obtain a more comprehensive view of the Mindat database through this paper and thus better plan their data use. We also hope more people will be inspired to contribute to the data curation work to make Mindat a sustained data ecosystem for geoscience research.