bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adolescents hospitalized in an acute psychiatric ward: a retrospective comparison between the pre-Covid-19 and pandemic periods
Authors: lorenzo rosaria di , Cutino Anna , Morgante Martina , Panini Giulia , Rovesti Sergio , Filippini Tommaso , Ferri Paola 
Published: May 2023

Abstract

BACKGROUND. Covid-19 pandemic has negatively impacted child and adolescent mental health. The primary outcome of this study was the evaluation of Covid-19 impact on minors’ hospitalizations in an acute psychiatric ward. METHOD. With an observational and retrospective design, we collected selected variables among adolescents hospitalized in an acute psychiatric ward from 01/07/2017 to 30/06/2022. Data were statistically processed. RESULTS. Our sample was composed of 118 minors with an average age of 15.7 ± 1.2 SD, mostly represented by females (61%) and Italians (60.2%), who had 204 hospitalizations. The number of admissions by years drastically decreased in 2020 concomitantly with Covid19 lockdown and increased in the first half of 2022. Admission rates were higher in winter and spring, except in 2020 when admissions decreased (p = 0.000). In our sample, females more frequently had suicidal behaviour and acute anxiety (p = 0.000) at admissions and more often were discharged with acute stress reactions, eating disorders and mood disorder diagnoses. Differently, males were more frequently hospitalized for aggressive behaviour (p = 0.000) and were more often discharged with ADHD diagnosis (p = 0.000). At multiple linear regression, the duration of hospitalization (dependent variable) was negatively associated with “pandemic period” (p = 0.017) and “absent aggressive behaviour” (p = 0.003), and positively with “autism” diagnosis (p = 0.000). CONCLUSIONS. We highlighted the more stressful impact of Covid-19 pandemic on female adolescents, who required more psychiatric hospitalizations, in particular for suicidal behaviour, anxiety and mood disorders.
Optimized ANN-based Approach for Estimation of Shear Strength of Soil
Authors: RABBANI AHSAN , SAMUI PIJUSH , KUMARI SUNITA 
Published: May 2023

Abstract
The shear strength of the soil (SSS) is a significant attribute which is employed most frequently throughout the design phase of construction projects. The conventional approach of determining shear strength (SS) in the laboratory is one which is costlier as well as time taken process. The ability to precisely predict the SSS without the need for laborious and expensive testing in a laboratory is just one of the real-world needs of geotechnical professionals. In this paper an attempt has been made to develop a common methodology for predicting the SSS using optimized models. For this purpose, three additional optimized algorithms (GA, MPA, and PSO) were utilized to improve the bias and weight of the ANN's learning parameters, and three optimized ANNs (ANN-GA, ANN-MPA, and ANN-PSO) were developed. Validation of all the developed optimized models was executed using RMSE, R2, RSR, WI, and NSE, indices. After validation of optimized models it was found that out of three ANN-GA produces good modelling outcome in training as well as in testing phase and outperforming other models. It has been shown that the GA develops the most trustworthy ANN, and this was also validated by the rank analysis of developed models. When trying to predict SSS, it has been shown that the liquidity index (LI) is the key factor to take into consideration. This was determined by plotting the feature significance plot along with the feature selection plot. Following the LI, the water content (wc)) is the second most important input variable that has an effect on the value of the parameter of interest being investigated in the present investigation. In a broad sense, it was found that the factors associated to water were the primary characteristics that impact the prediction of SSS.
A Conceptual Framework on the Role of Backward Integration in Sustainable Access to Malaria Intervention Commodities in Nigeria
Authors: MOKUOLU Olugbenga Ayodeji , IDACHABA Innocent Odekina , BABATUNDE Musibau Adetunji , SULEIMAN Kafayat Oluwafunke , MOKUOLU Toluwani Ayobami , LAWAL Lukman , OSOFISAN Adenike Oyinlola 
Published: May 2023

Abstract

Background: Over the last two decades, global stakeholders and the Nigerian government have invested approximately $2 billion in malaria control, reducing parasite prevalence to 23% from 42% in 2010. However, there is a risk that the modest gains will be reversed due to unmet resource gaps. Backward integration is presented in this paper as a viable option for sustainable funding of malaria intervention commodities in Nigeria.
Methods: Following a critical appraisal of the resource profile and malaria expenditure, a conceptual framework on backward integration as a means of ensuring long-term supply of malaria intervention commodities was developed. The study analyzed secondary annual data from the National Malaria Elimination Programme to estimate commodity needs for the period 2018-2020, as well as total resources committed and the financial gap.
Findings: The funds needed to implement national malaria interventions from 2018 to 2020 totaled US$ 1,122,332,318, of which US$ 531,228,984 (47.3%) were funded. The Nigerian government contributed 2.5%, the Global Fund (26.7%), the President's Malaria Initiative [PMI] (16.5%), and the Department for International Development [DFID] (6.2%). The funding shortfall was $591,103,335, or 52.7% of the needs. Various funding scenarios were evaluated for their relative merits and limitations, including advocacy for more external funding, bank borrowing, increased domestic resources, and backward integration.
Interpretation: The study concluded that backward integration should be used, based on a government-led public-private partnership that will increase local production of malaria intervention commodities that are accessible and affordable through market-based demand and supply arrangements.
Hybrid Collaborative Intrusion Detection System Based on Blockchain &amp; Machine Learning
Authors: Jemili Farah , Korbaa Ouajdi 
Published: May 2023

Abstract
Intrusion Detection Systems (IDS) have traditionally been designed with a centralized structure, where a single device is responsible for monitoring the entire network. However, with the increasing complexity and scale of modern networks, this approach has become less effective. Centralized IDS can suffer from performance issues, limited scalability, and vulnerability to targeted attacks. To address these limitations, there is a growing need to develop collaborative IDS that can distribute the workload across multiple devices and better handle large-scale networks. Collaboration enables IDS to detect intrusions more effectively by combining and analyzing data from multiple sources. The adoption of blockchain technology is essential in achieving a collaborative IDS. Blockchain provides a secure, decentralized way to store and exchange information between different devices, which is critical for building trust and ensuring the integrity of the system. Furthermore, machine learning algorithms can be used to improve the performance of IDS by detecting new and emerging threats. Machine learning can help to identify patterns and anomalies in network traffic, enabling the system to detect and respond to attacks more effectively. By combining these approaches, a reliable and scalable detection system can be developed. The collaborative IDS using blockchain technology and machine learning algorithms can improve the accuracy and efficiency of detecting network intrusions while maintaining the security and integrity of the system.
Employability skills of alumni students: requirements and expectancies
Authors: Utkirov Abbos 
Published: May 2023

Abstract
Purpose – The aim of this study is to explore the views of young and experienced professionals in Uzbekistan and their relevance to labour market requirements in order to improve employment.
Design/methodology/approach – The data was collected using a quantitative approach; online semi-structured questionnaire was disseminated to 607 WIUT alumni students applying a Likert Scale question.
Findings – The results indicate that WIUT library program is current and well-planned. However, the activities do not fully meet the needs of young and experienced graduates. Shortage of staff impacted on applying LRC curriculum effectively.
Research limitations – The factors that impact an individual's income are numerous, and the data that has been collected is not in-depth enough to make substantive correlations between library usage and income.
Practical implications – The findings will assist in planning LRC activities and developing teaching approaches at WIUT. Furthermore, existing and new graduates can advance market driven skills and boost their employability.
Originality/value – This research is the initial investigation conducted in Uzbekistan that examines how university library operations impact the employability skills of graduates. It is also one of the earliest studies that looks into the experiences of former students in terms of employability skills.
Effect of kuratsuki Kocuria on sake’s taste varies depending on the combination with different sake yeast strains
Authors: Yazaki Ayano , Nishida Hiromi 
Published: May 2023

Abstract
Sake brewery-inhabiting (kuratsuki) bacteria affect the flavor of sake and sake yeast mainly produces the flavor of sake. Thus, kuratsuki bacteria may alter the metabolism of sake yeast through interactions between kuratsuki bacteria and sake yeast. In this study, we used the kuratsuki Kocuria strain TGY1127_2 and three sake yeast strains, AK25, K901, and K1801. Although the Brix and acidity during sake production using AK25 differed between sake with and without kuratsuki Kocuria, those using K901 and K1801 did not differ. Thus, sake yeast AK25 interacted with kuratsuki Kocuria and changed its metabolic characteristics. Based on the Brix and acidity changes, it is uncertain whether the K901 and K1801 strains affect sake yeast metabolism. In contrast, the effect of kuratsuki Kocuria on sake’s taste varied depending on the combination of different sake yeast strains. Thus, each sake yeast strain interacted with the kuratsuki bacterium and changed its metabolic characteristics, resulting in a change in the taste of sake. The findings of this study can lead to the brewing of sake using different types of kuratsuki bacteria which can affect the sake’s taste.
Mesoporous Effects on SiC Fiber Matrix Combined with Active Metal Oxides for Atmospheric Gas Sensing under High Temperature Conditions
Authors: Otgonbayar Zambaga , JOO Young Jun , Cho Kwang Youn , Park Sang Yul , Park Kwang Youl , Oh Won-Chun 
Published: May 2023

Abstract

CO2 and O2 gas sensing tests were conducted on mesoporous WO3 (mWO3) and β−SiC/In2O3/SnO2/mWO3 (SCISOW) quaternary structured gas sensor materials at room temperature and under various high-temperature conditions. The recorded results indicated the incorporation of mWO3 effectively improved gas detection responses compared to the results of our previous studies. The electrochemical properties and surface morphology of the nanocomposites were analyzed by XRD, SEM, TEM, EDX, XPS, Raman, EIS, PL, Tafel and LSV methods. All quaternary-structured nanocomposites showed a good response to gas at different temperature variations. Therefore, the excellent electronic conductivity and topography of the nanocomposite increased its gas-sensing ability and changed the usability of the β−SiC/In2O3/SnO2/mWO3 nanocomposite. Gas sensing tests indicated that SCISOW103 nanocomposites showed high resistivity with excellent gas sensing response to CO2, compared to other quaternary nanocomposites and mWO3. Therefore, the electrochemical and technical parameters that change its value are directly related to the electrical conductivity of the sensor material, and the conductivity/resistivity of the sensor material plays a critical role in adjusting the sensitivity of a gas sensor. We believe that the quaternary SCISOW nanocomposites we propose offer new advanced materials for gas sensing tests and open up new opportunities in the field of research.
Identification of Alzheimer's disease from MRI image employing a probabilistic deep learning-based approach and the VGG16
Authors: GUPTA ASHISH , GUPTA DEEPAK , GUPTA SHYAM SUNDER 
Published: May 2023

Abstract
Deep learning model performance is the major factor in dealing with this problem. Several learning techniques such as deep feature extraction and classification were introduced. The presented deep triplet network employs a function of a conditional loss. To make up for the model's short sample size and enhance performance. The described deep triplet network incorporates a conditional loss function. The basic network of this architecture is influenced by VGG16, and testing is being done on an open-access set of imaging data. Experiments reveal that the presented approach has better cutting-edge techniques in regard to effectiveness. However, a number of researchers and scientists are working to develop techniques for earlier identification utilising MRI images in an effort to slow the progression of AD. In this study, two MRI datasets that included 6900, as well as 6136 images, as well as 6136 images have been utilised for the early identification of AD. The DL algorithm is applied by employing a deep Triplet network, producing the outcome in terms of accuracy, sensitivity, precision, and F1-score as (99.62%, 97.25, 98.39, and 97.14), and (96.1%, 95.71, 95.75, and 95.11) for dataset 1 as well as dataset 2. The results are also contrasted with those of earlier studies, which came to the conclusion that the presented approach performs better. Finally, The study is also useful for identifying different ML and DL methods which can be applied to research AD stage detection and identification early.
Electrofluids as liquid conductors with tunable gauge factors
Authors: Schmidt Dominik , Kraus Tobias , Gonzalez-Garcia Lola 
Published: May 2023

Abstract
Flexible and stretchable electronics require both sensing elements and stretching-insensitive electrical connections. Conductive polymer composites and liquid metal structures are highly deformable but strongly change their conductivity upon elongation. Macroscopic Kirigami structures combine stretchability with constant conductivity, but their use is limited by geometrical restraints. Here, we introduce concentrated conductive particle suspensions based on Carbon Black as conductive “Electrofluid”. When using incompatible solvents, large agglomerates form that reduce the electrical percolation threshold by one order of magnitude and act as microscopic Kirigami-like structures with very small gauge factors < 0.4. In compatible solvents, well-dispersed fillers exhibit high percolation thresholds, high stiffness, and positive piezoresistivity (gauge factor > 2). Electrofluids enable the rational design of sustainable soft electronics components by simple solvent choice and can be used both as sensor and electrode materials, as we demonstrate.
Self-regulation of the posterior-frontal brain activity with real-time fMRI neurofeedback to influence conscious perception
Authors: Kim Sunjung , Rocha Josue Luiz Dalboni da , Birbaumer Niels , Sitaram Ranganatha 
Published: May 2023

Abstract
The Global Neuronal Workspace (GNW) hypothesis states that the visual percept is available to conscious awareness only if recurrent long-distance interactions among distributed brain regions activate neural circuitry extending from posterior regions to prefrontal regions above a certain excitation threshold. To directly test this hypothesis, we trained human participants to increase blood oxygenation level-dependent (BOLD) signals with real-time functional magnetic resonance imaging (rtfMRI) based neurofeedback simultaneously in four specific regions of the occipital, temporal, insular and prefrontal parts of the brain. Specifically, we hypothesized that up-regulation of the mean BOLD activity in the posterior-frontal brain regions lowers the perceptual threshold for visual stimuli, while down-regulation raises the threshold. Our results showed that participants were able to perform up-regulation of the posterior-frontal brain activity but not down-regulation. Furthermore, the up-regulation training led to a significant reduction of the visual perceptual threshold, but no significant change of perceptual threshold was observed after down-regulation training. These findings partially support the GNW hypothesis of consciousness perception, to the extent that up-regulation of the posterior-frontal regions improves conscious awareness of stimuli. However, further questions as to whether the posterior-frontal regions can be down-regulated at all, and whether down-regulation raises the perceptual threshold remain unanswered.
Dispel some mist on circulating biopterins: measurement, physiological interval and pathophysiological implication
Authors: Wang Shao-Ting , Wang Hai-Bo 
Published: May 2023

Abstract
BACKGROUND: Biopterins, including tetrahydrobiopterin (BH4), dihydrobiopterin (BH2) and biopterin (B), are critical cofactors for aromatic amino acid and nitric oxide synthases. Apart from their acknowledged significance in various endocrine diseases, there are noticeable research gaps and controversies on related experimental outcomes, for example analytical art, physiological interval and pathophysiological implication.
METHODS: Combining chemical derivatization and cold-induced phase separation in sample pretreatment, a new LC-MS/MS method was developed for global profiling biopterins in plasma. On this basis, the impact of anti-oxidation was specifically clarified. Afterwards, 215 apparently normal participates were enrolled to investigate the physiological interval of biopterins. And the relations between biopterins and the routine biochemical indicators were analyzed to explore the biopterins’ pathophysiological implications.
RESULTS: The method was validated to be reliable for detecting biopterins in the whole physiological ranges. Timely anti-oxidation was proved essential for accurate assessment of biopterins. The observed overall mean (± SDs) levels were 3.51 (± 0.94) ng/mL for BH4, 1.54 (± 0.48) ng/mL for BH2, 2.45 (± 0.84) for BH4/BH2 and 5.05 (± 1.14) ng/mL for total biopterins. The status of all the biopterins was tightly correlated with age. The levels of BH2 and BH4/BH2 revealed gender-specific differences. In specific, the healthy problems of hyperuricemia and overweight could cause distinct change on biopterins status in vivo.
CONCLUSIONS: Coupling with proper anti-oxidation, the newly developed method can accurately determine the global biopterins status in plasma. The observed physiological intervals and pathophysiological implications provide fundamental but inspiring supports for further biopterins-based researches.
Assessing Vitamin D Knowledge Among Syrian Adults: A population-based cross-sectional Study.
Authors: Malek Omar , Hajjeh Mhd Yaman Al , Safiah Mhd Homam , Alourfi Zaynab 
Published: May 2023

Abstract
Background
The importance of vitamin D is increasing daily as more studies reveal its links to several benefits for the human body and the wide array of consequences that its deficiency has, that’s why we wanted to assess the knowledge level of vitamin D among the people living in Damascus, Syria.
Methods
This study was approved by the Institutional Review Board of the Syrian Private University. A validated self-administered questionnaire was asked to be filled in by Syrian adults aged 18 and above, using google forms, between the 8th of August 2022 and the 5th of October 2022.
Results
1168 participants were included. 1098 (94.1%) were of Syrian nationality, ages of [18–28 years] made the majority of the sample 634 (54.3%). Two-thirds of the sample does not belong to the medical field 769 (65.8%). The results of this paper showed a high level of knowledge among the participants for sources of vitamin D (83.9% ± 26.2%) and its benefits (75.8% ± 23.5%) but they lacked knowledge of treatment (50.6% ± 30.2%) and for the causes (45.1% ± 26.4%) and consequences (65.1% ± 47.7%) of deficiency, the general knowledge on vitamin D was (60.3% ± 18.6%).
Conclusion
This is the first population-based paper in Syria to evaluate the general awareness of vitamin D and it indicates an average of good knowledge. We discussed some of the inadequate knowledge regarding several aspects such as “Causes of vitamin D deficiency” which had the lowest knowledge (45.1% ± 26.4%). We found a strong correlation between vitamin D knowledge and level of education, father’s / mother’s level of education, economic status, working in the medical field and the source of knowledge on vitamin D. Effective strategies should be made to raise awareness, and further research is recommended for a nationwide assessment.
Farming the planet with better nitrogen use
Authors: Liu Pu , Xu Hang , Liu Sheng , Ding Jia , Lu Xiankai , Zhong Buqing , Guo Yixin , Lu Xiao , Zhao Yuanhong , Zhang Xiuying , Wang Songhan , Liu Xuejun , Xu Wen , Si Ruotong , Goulding Keith , Liu Lei 
Published: May 2023

Abstract
Feeding an increasingly affluent population is a huge challenge facing global agriculture. In contrast to “large-scale farming” in developed economies (e.g. Europe and the United States), developing countries are dominated by “smallholder farms” relying on traditional farming practices but increasingly with substantial nitrogen overuse leading to severe environmental degradation and adverse human health. Here, we explore the potential for better nitrogen use by synthesizing the global relationship between farm size and nitrogen use for 16 major crops, assess the impact of farm size on nitrogen flows, and link these with air quality modelling to produce an integrated assessment of nitrogen-related environmental and health outcomes related to farm size. We find that increasing farm size in developing countries can contribute to more efficient and sustainable farming practices, which could decrease nitrogen overuse, ammonia emissions and nitrogen deposition by 20-25%, increase nitrogen use efficiency by 2-8%, and save over 142,000 premature deaths per year related to PM2.5 air pollution. Although a large one-time investment is required for increasing farm size, there would be substantial progress towards achieving Sustainable Development Goals, associated with food security, a clean environment and improved human health.