bluuebunny/crossref_metadata_2025_split huggingface dataset:
Longitudinal relationships of psychotic-like experiences with suicidal ideation and self-harm in adolescents
Authors: Zhou Rui , Foo Jerome Clifford , Nishida Asuka , Ogawa Sayoko , Togo Fumiharu , Sasaki Tsukasa 
Published: June 2023

Abstract
Background Research in adolescents suggests associations between psychotic-like experiences (PLEs) and self-injurious thoughts and behaviors (SITBs), but insights into their temporal relationship, which may inform prediction, have been limited. Psychological distress (PD; symptoms of depression and anxiety) has been related to both PLEs and SITBs, and may modulate this relationship. Given that PLEs have been linked to the development of several mental disorders, and the relationships between SITBs and suicide, it is important to better understand their relationship.
Methods The present study sought to investigate these factors using a longitudinal school-based design. Adolescents (n = 1685, ages 12-18) completed annual self-report assessments (6 time points) on PLEs, SITBs (suicidal ideation (SI) and self-harm (SH)), as well as PD. The longitudinal associations between PLEs and SITBs were analyzed, employing two cross-lagged panel models (CLPMs), with and without adjustment for PD.
Results Unadjusted CLPMs revealed significant bidirectional temporal associations between PLEs and SITBs (both SI and SH), suggesting that PLEs both predicted and were predicted by SITBs. When adjusting for PD, the effect of SI on PLEs remained significant, but not PLEs on SI; bidirectional associations between PLEs and SH also remained significant.
Conclusion A bidirectional longitudinal relationship where both PLEs and SITBs can precede (and perhaps predict) each other was suggested in adolescents. PD may play a particular role in situations where PLEs are followed by SI. Heightened awareness about relationships between these phenotypes may be an important step towards facilitating timely interventions for both mental disorders and suicide.
Ethanol-Producing Enterocloster bolteae is enriched in Hepatitis B Virus-Associated Gut Dysbiosis: A Case-Control Culturomics Study
Authors: WASFY Reham MAGDY , MBAYE Babacar , BORENTAIN Patrick , ALOU Maryam TIDJANI , RUIZ Maria Leticia MURILLO , CAPUTO Aurelia , ANDRIEU Claudia , ARMSTRONG Nicholas , RAOULT Didier , MILLION Matthieu , GEROLAMI Rene 
Published: June 2023

Abstract
Background
Hepatitis B virus (HBV) infection is a global health epidemic that causes fatal complications leading to liver cirrhosis and hepatocellular carcinoma. The link between HBV-related dysbiosis and specific bacterial taxa is still under investigation. Enterocloster is emerging as a new genus (formerly Clostridium), including Enterocloster bolteae, a gut pathogen previously associated with dysbiosis and human diseases such as autism, multiple sclerosis, and inflammatory bowel diseases. Its role in liver diseases, especially HBV infection, is not reported.
Methods
We analyzed the fecal samples of eight patients with HBV and ten healthy individuals using the high-throughput culturomics approach compared to 16S rRNA sequencing. Quantification of ethanol, known for its damaging effect on the liver, produced from bacterial strains enriched in HBV was carried out by gas chromatography-mass spectrometry.
Results
By culturomics, 29,120 isolated colonies were analyzed by MALDI-TOF to identify 340 species (240 species in HBV samples, 254 species in control samples) belonging to 169 genera and six phyla. In the HBV group, 48 species were already known in humans but had not been previously found in the gut, 17 known species not previously found in humans, and six new species were isolated. Comparing bacterial species frequency, we serendipitously found three bacterial genera with significantly enriched bacterial diversity in HBV gut dysbiosis: Enterocloster, Clostridium, and Streptococcus (p = 0.0016, p = 0.041, p = 0.053, respectively). However, metagenomics could not identify this enrichment, possibly concerning its insufficient taxonomical resolution (equivocal assignment of operational taxonomic units). At the species level, significantly enriched species in HBV almost all belonged to class Clostridia as Clostridium perfringens, Clostridium sporogenes, Enterocloster aldenensis, Enterocloster bolteae, Enterocloster clostridioformis, and Clostridium innocuum. Two E. bolteae strains, isolated from two different HBV patients, showed high ethanol production (27 and 200 mM).
Conclusion
Culturomics allowed us to identify Enterocloster species, and specifically E. bolteae, that are enriched in the gut microbiota of HBV patients. These species have never been isolated in HBV patients so far. Moreover, ethanol production by E. Boltea strains isolated from HBV patients could play a role in liver disease progression. Additionally, culturomics might be critical for better elucidating the relationship between dysbiosis and HBV infection in the future.
Comparison of antibacterial activity and biocompatibility of non-leaching nitrofuran bone cement loaded with vancomycin, gentamicin and tigecycline
Authors: Gao Zhe , Xu Yang , Kan Yuchen , Guo Rui , Han Luyang , Bo Wenhan , Chu Jianjun 
Published: June 2023

Abstract
Background
Non-leaching antibacterial bone cement can generate long-term antibacterial activity, it cannot treat serious infections that have occurred like antibiotic-loaded bone cement. Currently, the antibacterial activity and biocompatibility of non-leaching cement when loaded with antibiotics have yet to be determined.
Methods
Non-leaching antibacterial nitrofuran bone cement (NFBC) specimens were prepared with low dose and high dose antibiotics. The antibacterial activity and biocompatibility of NFBC loaded with vancomycin, gentamicin, and tigecycline were compared. The agar diffusion method was employed to observe the inhibition zone of the samples against two bacterial strains from day one to day seven. The CCK-8 assay and acute liver and kidney toxicity test were conducted to assess the effects of the samples on mouse embryo osteoblast precursor cells and C57 mice, respectively.
Results
Gentamicin-loaded cement exhibited the most potent antibacterial activity, effectively inhibiting both bacterial strains at a low dose. Tigecycline-loaded cement demonstrated superior biocompatibility, showing no acute liver and kidney toxicity in mice and minimal cytotoxicity to osteoblasts.
Conclusions
NFBC loaded with gentamicin, vancomycin, and tigecycline not only maintains sustained antibacterial activity but also exhibits excellent biocompatibility.
The impact of rotavirus vaccination on acute diarrhea in Thai children under 5 years of age after the first year of universal implementation of rotavirus vaccines in the National Immunization Program (NIP) in Thailand: A 6-year analysis
Authors: Charoenwat Busara , Suwannaying Kunanya , Paibool Watuhatai , Laoaroon Napat , Sutra Sumitr , Thepsuthammarat Kaewjai 
Published: June 2023

Abstract
Background: Two types of rotavirus vaccines (RVs), Rotarix (RV1) and RotaTeq (RV5), were licensed as optional vaccines in 2012 and became part of the National Immunization Program (NIP) in 2020 in Thailand. The main objective was to evaluate the impact of rotavirus vaccines on the burden of acute diarrheal severity ranging from mild (outpatient department, OPD) to moderately severe as diarrheal-related admission or deaths in pre- and post-NIP periods. The minor objectives were assessed on the monthly admission rate, rotavirus vaccine coverage rate and rotavirus vaccine completed dose (RotaC).
Methods: Data regarding OPD, admission, and death cases under the Thailand National Health Coverage (NHC) between 2015-2019 (pre-NIP period) and in 2020 as the post-NPI year, which were recorded as International Classification of Diseases and Related Health Problem 10th (ICD-10), were analyzed.
Results: The burden of diarrheal-related disease was diminished after the rotavirus vaccine was introduced. The OPD visit rate decreased from 10.1 to 8.3 visits per 100 person-years pre- and post-NIP, respectively (P<0.001). The admission rate significantly declined from 31.4 to 30.5 cases per 1,000 person-years pre- and post-NIP, respectively (P<0.001). The diarrheal-related mortality rate also subsided from 10.2 to 8.1 cases per 100,000 person-years pre- and post-NIP, respectively (P 0.3). The major population in both admission and deaths was infants under 1 year of age (P<0.001). Seasonality was seen as a constant bimodal pattern for cool and rainy reasons. RotaC was as high as 37.4%, even in the first year of the NIP.
Conclusions: The rotavirus vaccine had a great impact on the diarrheal disease burden of all outpatient visits, hospitalization, and mortality, especially in infants under one year of age. Seasonality outbreaks of acute diarrhea were observed in each examination year. The RotaC was high even in the first year of the NIP of the rotavirus vaccine. of rotavirus vaccine quality should be warranted. Trial registration: number TCTR20220120003, date of registration: 20/01/2022, site: Thai Clinical Trials Registry, URL https://www.thaiclinicaltrials.org/show/TCTR20220120003
Responsiveness to sudden disturbances in manufacturing through dynamic job shop scheduling using Quantum Annealing
Authors: Schworm Philipp , Wu Xiangqian , Glatt Moritz , Aurich Jan C. 
Published: June 2023

Abstract
An efficient production planning and control is inevitable for the economic operation of a manufacturing system. As an essential part of production planning and control, process scheduling aims to assign processes to the available resources of a manufacturing system under consideration of its objectives. This forms an optimization problem also known as job shop scheduling which can be solved with computer aided techniques. Exact solution methods are only practical up to a certain number of functional units and processes, therefore, approximation methods are used in industry. However, as the problem size increases, the computational solving time increases significantly and the solution quality decreases in equal measure. In order to react to the current effects of global crises, such as disruptions in supply chains, approaches for fast and efficient rescheduling are needed. A dynamic shop job scheduling approach using Quantum Annealing bears the potential to close this research gap. Previous work has shown that Quantum Annealing is able to solve static job shop scheduling problems within seconds while finding good solutions. However, in a flexible environment such as a manufacturing system, the static approach is not suitable for process scheduling. Therefore, a dynamic Quantum Annealing-based approach for job shop scheduling with consideration of machine breakdowns and new job arrivals is proposed. The approach monitors a manufacturing system and reacts to changes in the job pool or availabilities in functional units with rescheduling. The method is tested with several use cases involving small and large-scale problems and is compared with a simulated annealing approach. Thereby, the Quantum Annealing-based computations show better results regarding solution quality and computing time. Moreover, the dynamic approach bears the potential for industrial application, especially as a supplement to a conventional advanced planning system.
“A beacon of hope": a qualitative study on migrants' mental health needs and community-based organisations' responses during the COVID-19 pandemic in Antwerp, Belgium
Authors: Molenaar Jil , Robinson Hannah , Praag Lore Van 
Published: June 2023

Abstract
Background: The COVID-19 pandemic has highlighted the need for structurally informed mental health services that are sensitive to social inequalities and cultural differences. Community-level services and organisations are often referred to as having the potential to play a key role in providing such services to migrants, yet not many studies have documented how these types of services have been organised and experienced during the COVID-19 pandemic. The objective of our case study in Antwerp’s districts of Borgerhout and Antwerpen-Noord (Belgium) was to explore how community-level responses to the mental health impact of the COVID-19 crisis were organised and experienced by first-generation migrants and members of community-level organisations.
Methods: Semi-structured qualitative interviews were conducted with first-generation migrants in Borgerhout and Antwerpen-Noord (n = 19) and with professionals in the local psycho-social care sector (n=13).
Results: Our findings highlight the complex drivers of migrants’ mental health and the unique value and indispensability of local-level services and organisations in providing mental-health related services, particularly in a crisis context like the COVID-19 pandemic. Qualities that emerged to be particularly important included organisations’ awareness of local needs; their flexible nature which allows them to address bottlenecks and fill gaps left by other services; their capacity to respond holistically to a broad spectrum of needs; their ability to offer culturally sensitive care and support; and their physical accessibility. However, our findings also demonstrate the fragility and fragmentation of these local-level services and initiatives. In the face of the COVID-19 crisis, this related to serious challenges to the necessary physical accessibility of organisations’ services; services and initiatives becoming overloaded; and widespread fragmentation and lack of oversight of the available services forming a real barrier for both service users and providers.
Conclusions: This study underlines the importance of prioritising physical accessibility of mental health services at the community level, improving cultural sensitivity through training and employing professionals with a shared background or language proficiency with migrants, and promoting stronger collaborations between community-level organizations and city governments. The findings are informative to guide mental health policy and future crisis responses in similar communities and neighbourhoods.
Optimization of Q.Clear reconstruction for dynamic 18F PET imaging
Authors: Lysvik Elisabeth Kirkeby , Mikalsen Lars Tore Gyland , Rootwelt-Revheim Mona-Elisabeth , Emblem Kyrre Eeg , Hjørnevik Trine 
Published: June 2023

Abstract
Background
Q.Clear, a Bayesian penalized likelihood reconstruction algorithm, has shown high potential in improving quantitation accuracy in PET systems. The Q.Clear algorithm controls noise during the iterative reconstruction through a β penalization factor. This study aimed to determine the optimal β-factor for accurate quantitation of dynamic PET scans.
Methods
A Flangeless Esser PET Phantom with eight hollow spheres (4–25 mm) was scanned on a GE Discovery MI PET/CT system. Data was reconstructed into five sets of variable acquisition times using Q.Clear with 18 different β-factors ranging from 100 to 3500. The recovery coefficient (RC), coefficient of variation (CVRC) and root mean square error (RMSERC) were evaluated for the phantom data. Two male patients with recurrent glioblastoma were scanned on the same scanner using 18F-PSMA-1007. Using an irreversible 2-tissue compartment model, the area under curve (AUC) and the net influx rate Ki were calculated to assess the impact of different β-factors on the pharmacokinetic analysis of clinical PET brain data.
Results
In general, RC and CVRC decreased with increasing β-factor in the phantom data. For small spheres (< 10mm), and in particular for short acquisition times, low β-factors resulted in high variability and an overestimation of measured activity. Increasing the β-factor improves the variability, however at a cost of underestimating the measured activity. For the clinical data, AUC decreased and Ki increased with increased β-factor; a change in β-factor from 300 to 1000 resulted in a 25.5% increase in the Ki.
Conclusion
In a complex dynamic dataset with variable acquisition times, the optimal β-factor provides a balance between accuracy and precision. Based on our results, we suggest a β-factor of 300–500 for quantitation of small structures with dynamic PET imaging, while large structures may benefit from higher β-factors.
Trial registration:
Clinicaltrials.gov, NCT03951142. Registered 5 October 2019, https://clinicaltrials.gov/ct2/show/NCT03951142. EudraCT no 2018-003229-27. Registered 26 February 2019, https://www.clinicaltrialsregister.eu/ctr-search/trial/2018-003229-27/NO.
Towards Connection-Scalable RNIC Architecture
Authors: Kang Ning , Wang Zhan , Yang Fan , Ma Xiaoxiao , Ma Zhenlong , Yuan Guojun , Tan Guangming 
Published: June 2023

Abstract

RDMA is a widely adopted optimization strategy in datacenter networking that surpasses traditional kernel-based TCP/IP networking through mechanisms such as kernel bypass and hardware offloading. However, RDMA also faces a scalability challenge with regard to connection management due to limited on-chip memory capacity in the RDMA Network Interface Card (RNIC). This necessitates the storage of connection context within RNIC's memory and considerable performance degradation when maintaining a large number of connections.
In this paper, we propose a novel RNIC microarchitecture design that achieves peak performance with scalable connections. First, we model RNIC and identify two key factors that degrade performance when connections scale: head-of-line blocking when accessing the connection context and connection context dependency in transmission processing. To address the head-of-line blocking problem, we then combine a non-blocking connection requester and connection context management module to process prepared connections first, which achieves peak message rate when connections scale. Besides, to eliminate connection context dependency in RNIC, we deploy a latency-hiding connection context scheduling strategy, maintaining low latency when the number of connections increases. We implement and evaluate our design, demonstrating its successful maintenance of peak message rate (66.4Mop/s) and low latency (3.89us) while scaling to over 50k connections with less on-chip memory footprint.
Quiet quitting among employees: a proposed cut-off score for the “Quiet Quitting” Scale
Authors: Galanis Petros , Katsiroumpa Aglaia , Vraka Irene , Konstantakopoulou Olympia , Moisoglou Ioannis , Gallos Parisis , Kaitelidou Daphne 
Published: June 2023

Abstract
OBJECTIVE To identify an appropriate cut-off point for the “Quiet Quitting” Scale (QQS) to discriminate quiet quitters from those with a low level of quiet quitting.
METHOD We conducted a cross-sectional in Greece during June 2023. We recruited adult employees from every job sector. Thus, we obtained a convenience sample. We used the Receiver Operating Characteristic analysis to calculate the best cut-off point for the QQS. In that case, we used “Job Satisfaction Survey” (JSS), “Copenhagen Burnout Inventory” (CBI), “Single Item Burnout” (SIB) measure, and turnover intention score as external criterions. For each criterion, we created a dichotomous variable using medians or suggested values from the literature as cut-off points.
RESULTS We found a significant predictive power of QQS for job satisfaction assessed by JSS, and for job burnout assessed by CBI and SIB measure. We found that the best cut-off point for the QQS was 2.06. In that case, we found the highest values for Youden’s index (0.34) and AUC (0.73). The 95% confidence interval for the AUC ranged from 0.70 to 0.76. Sensitivity and specificity of QQS were 0.68 and 0.66 respectively (p<0.001). Therefore, we considered employees with QQS score ≥2.06 as quiet quitters, and those with QQS score <2.06 as non quiet quitters.
CONCLUSIONS The best cut-off point for the QQS was 2.06. Employees with QQS score ≥2.06 as quiet quitters can be described as quiet quitters. Further research should be conducted to validate our results.
Text-Controlled GAN Inversion for Image Editing
Authors: Dere Vedant , Shinde Amita , Vast Prachi 
Published: June 2023

Abstract
This paper presents an optimization-based approach that allows for text-based image editing using Generative Adversarial Networks (GANs) with preserving specific details of the image. While recent Diffusion Models can generate images using text by training with text and image pairs, GANs are trained only with images, making it challenging to control the latent space according to text prompts. Therefore, this paper introduces two-step pivotal mechanisms that enable text instructions for StyleGAN in the latent space while maintaining the original image information during editing. This approach simplifies the editing process and eliminates the need for separate training to get the particular direction in the latent space. The paper demonstrates the effectiveness of this method with diverse input images and written text prompts, showing compelling editing results.
Security-enhanced firmware management scheme for smart home IoT devices using distributed ledger technologies
Authors: Wijesundara W M A B , Lee Joong-Sun , Tith Dara , Aloupogianni Eleni , Suzuki Hiroyuki , Obi Takashi 
Published: June 2023

Abstract
With the increase of IoT devices generating large amounts of user sensitive data, improper firmware harms users' security and privacy. Latest home appliances are integrated with features to assure compatibility with smart home IoT. However, applying complex security mechanisms to IoT is limited by device hardware capabilities, making them vulnerable to attacks. Such attacks have recently become frequent. To address this issue, we developed a secure verification mechanism for firmware released by the device's manufacturer. We proposed an IoT gateway for secure firmware verification and updating for smart home IoT devices utilizing the IOTA MAM (Masked Authenticated Messaging) protocol and a distributed file system with IPFS (Inter-Planetary File System) protocol. These two communication protocols ensure decentralized communication and firmware file distribution between the IoT device vendor and the IoT end device. The proposed scheme securely shares latest firmware content over IOTA and IPFS networks, performs a secure firmware update on IoT end devices and ensures authenticity and integrity of the firmware. Two types of validation methods were proposed for firmware updating and validation. We implemented the proposed scheme using three entities, Vendor, IoT gateway, and IoT end device. Our system yielded promising results in performing secure automated firmware updates on IoT end devices with very low computational power. The system's functionality was implemented using IOTA's MAM run on Raspberry-Pi as an IoT gateway along with an ESP8266 Wi-Fi microcontroller, demonstrating the effectiveness of our approach. Our proposed methodology can be used for secure firmware distribution on home IoT applications.
Hyperparameter Optimization for Deep NeuralNetwork Models: A Comprehensive Study onMethods and Techniques
Authors: Roy Sunita , Mehera Ranjan , Pal Rajat Kumar , Bandyopadhyay Samir Kumar 
Published: June 2023

Abstract
Advancements in computing and storage technologies have significantly contributed to the adoption of deep learning (DL)-based models among machinelearning (ML) experts. Although a generic model can be used in the search fora near-optimal solution in any problem domain, what makes these DL modelscontext-sensitive is the combination of the training data and the hyperparameters. Due to the lack of inherent explainability of DL models the HyperparameterOptimization (HPO) or tuning specific to each model is a combination of art,science, and experience. In this article, we have explored various existing methods or ways to identify the optimal set of values for the hyperparameters specificto the DL models along with the techniques to realize those methods in real-lifesituations. The article also includes a detailed comparative study among variousstate-of-the-art HPO techniques using the Keras Tuner tuning toolkit and highlights the observations describing how the model performance can be improvedby applying various HPO techniques.