bluuebunny/crossref_metadata_2025_split huggingface dataset:
Attachment to others and callous-unemotional traits in a sample of high school students
Authors: Baroncelli Andrea , Facci Carolina , Sica Luigia Simona , Fusco Luca , Di Palma Tiziana , Ciucci Enrica 
Published: January 2023

AbstractAlthough several evidences suggested the importance to consider the quality of relationships with others as a key element for the understanding of callous-unemotional traits in youths, to date few studies investigated the specific role of youths’ attachment. The aim of the present study was to explore the association between attachment styles and callous-unemotional traits within a community sample of 786 high school students (41.48% females, M age = 16.90 years, SD = 1.45 years). A linear hierarchical regression approach showed that, over and above gender, age, and levels of both internalizing and externalizing problems, unique variance in callous-unemotional traits was accounted for by low confidence, high discomfort with closeness, and low preoccupation with relationships. Moreover, focusing on specific subcomponents of callous-unemotional traits, it was found that high levels of perceiving relationships as secondary were related to the callous-lack of empathy component, while higher levels in discomfort with closeness were associated to the restricted affect component. Emerged results were discussed within the context of the Sensitivity to Threat and Affiliative Reward (STAR) Model, that was recently advanced to in-depth understand callous-unemotional traits in children and adolescents.
Social and Emotional Wellbeing Among Young People; the Mitigating Role of Ecological Domains
Authors: Turkmani Sabera , Bista Sarita , Wang Joanna J. J. , O’Donnell Alexander W. , Thomson Catherine , Radcliffe Natasha Jane , Skattebol Jennifer , Redmond Gerry , Brooks Fiona 
Published: January 2023

AbstractTo examine the role of neighbourhood, what Bronfenbrenner describes as an element in the exosystem, as a protective asset for adolescents’ social and emotional wellbeing. The study used a subset of national data reported by adolescents and their parents from the Longitudinal Study of Australian Children (LSAC). A linear mixed-effect model was used to estimate the association between neighbourhood indicators and trajectories in a measure of social and emotional wellbeing (the SDQ Total Difficulties score) at ages 12–13, 14–15 and 16–17, controlling for age and sex, peer and family relationships and household material resources. The analysis revealed that parents’ perceptions of belonging and their subjective assessments of the condition of housing in the neighbourhood, as well as externally sourced data on neighbourhood accessibility and socio-economic status, were significantly associated with adolescents’ total difficulties scores over time. The findings revealed the role of neighbourhood level protective assets as a potential influence on adolescents’ social and emotional wellbeing. Greater attention should be given to understanding the complex interactions between the resources mobilised by individuals and their families, and the influence of wider environments and social structures on young people’s social and emotional wellbeing.
HistoTrust: tracing AI behavior with secure hardware and blockchain technology
Authors: Paulin Dylan , Joud Raphaël , Hennebert Christine , Moëllic Pierre-Alain , Franco-Rondisson Thibault , Jayles Romain 
Published: January 2023

AbstractIn areas of activity where the notion of accountability is strong, the adoption of artificial intelligence (AI) is limited by the opacity and lack of understanding of its behavior, all the more so in the embedded domain where neural networks are compressed and executed on microcontrollers. While the NIST introduced in 2021 several principles allowing the AI explainability, this paper introduces a novel scheme, HistoTrust, combining secure hardware and blockchain technology to bring trust in the traceability of AI behavior and allow its explainability. HistoTrust attests in an Ethereum ledger all the relevant data produced by a physical device, especially the heuristics inferred by AI. Thus, the audition of the ledger allows security verifications and AI behavior analysis.
Olov Oscarsson (1931–1996) of Lund University, a Pioneer in Cerebellar Neurobiology
Authors: Triarhou Lazaros C. , Manto Mario 
Published: January 2023

Abstract
The present Cerebellar Classic highlights the experimental work of the Swedish neurophysiologist Olov Oscarsson (1931–1996) on the afferent innervation of the cerebellum by axons emanating from neurons in the spinal cord and the inferior olive. Historically, the schemes of cerebellar division had been principally based on the external morphology of lobules and fissures. However, the macroscopic anatomical division of the cerebellum does not coincide with its pattern of functional organization. By defining a system of longitudinal somatotopy, Oscarsson contributed to the much needed plan of cerebellar division that correlates experimental information on axonal connections with physiology. His contribution has ultimately led to the currently accepted microzonal modular scheme of cerebellar corticonuclear microcomplexes.
Handheld NDVI sensor-based rice productivity assessment under combinations of fertilizer soil amendment and irrigation water management in lower Moshi irrigation scheme, North Tanzania
Authors: Kimaro Oforo Didas , Gebre Sintayehu Legesse , Hieronimo Proches , Kihupi Nganga , Feger Karl-Heinz , Kimaro Didas N. 
Published: January 2023

AbstractHandheld optical sensor was used to measure canopy reflectance at red region (656 nm) and near-infrared region (774 nm) to generate NDVI data for monitoring rice productivity under soil amendment with combinations of fertilizers at two levels of water regime in smallholder Irrigation Scheme, in Lower Moshi, North Tanzania. The study was carried out in an experimental design which consisted of two irrigation water levels (flooding and system of rice intensification) with multi-nutrients (NPK) and single nutrient (urea) application replicated three times in a randomized complete block design. Flood irrigation water was applied at 7 cm height throughout the growing season, while SRI treatment irrigation water was applied at 4 cm height under alternate wetting and drying conditions. The annual rates of fertilizers applied was 120 kg N/ha, 20 kg P/ha, and 25 kg K/ha. The variety SARO-5 was used in this experiment. Simple correlation coefficient (r) was used to measure the degree of association between field crop performance parameters (plant height, number of tillers, biomass, yield) and NDVI across growth stages and three positions of the sensor above the canopy in the tested fertilizer combinations and water regimes. Results show that at any given fertiliser combinations and water levels, there was no significant correlation between plant height and NDVI except for the plant height at a vegetative stage for 0.6 m above the crop canopy and booting stage at 0.3 m and 0.6 m above the canopy, respectively (P < 0.05). A good correlation was also observed between NDVI at booting and full booting stage regardless of the position of the sensor above the canopy and the number of tillers at full booting growth stage (P < 0.05). A significant relationship was observed between rice grain yield and NDVI at the vegetative, booting, and full booting stage. The simple linear regression models explained only slightly < 30% of the yield predictions by NDVI at the early stage of the crop growth, decreasing gradually to 5% at the full booting growth stage. Results demonstrate a positive linear relationship between rice grain yield and NDVI for the tested soil fertiliser amendments and irrigation water regimes. Thus, we conclude that handheld NDVI-based sensor can be used in smallholder rice yield predictions for optimising soil fertiliser use and irrigation water management. This allows future multi-functional land management within the soil–water-food nexus.
Understanding the Experiences of How Mindfulness is Used by People with Cystic Fibrosis: Barriers and Enablers
Authors: Kauser Sophia , Mantzios Michail , Keyte Rebecca , Egan Helen 
Published: January 2023

Abstract
Objectives
Mindfulness practices are increasingly being recognised as beneficial in supporting health, wellbeing, and psychological functioning. There is currently limited evidence of how mindfulness is used within a population of individuals with cystic fibrosis (CF). In order to effectively inform the development of future psychological mindfulness-based interventions for this population, it is imperative to first understand how individuals with CF are currently engaging with mindfulness.

Method
Internet-mediated research (IMR) was used to explore attitudes, beliefs, and experiences regarding the use of mindfulness practices across a CF population. IMR allowed for a natural, unobtrusive method of data collection that involved the collection of publicly available posts from two global online CF forums.

Results
A variety of formal and informal mindfulness practices were positively experienced by the CF community, with beneficial impacts upon emotional and psychological wellbeing, and physical health. The data highlighted a clear interest in proactive mindfulness practice, whilst also exploring some of the associated challenges with certain practices.

Conclusions
Proactive psychological support that considers the use of mindfulness and self-care practices may form a particularly valuable tool in supporting the quality of life for present and future generations of people with CF. Increased awareness and education regarding the use of different formal and informal mindfulness practices in CF care would be beneficial in enabling people to make more informed choices.
Simulating the Impact of Shared Mobility on Demand: a Study of Future Transportation Systems in Gothenburg, Sweden
Authors: Lorig Fabian , Persson Jan A. , Michielsen Astrid 
Published: January 2023

AbstractSelf-driving cars enable dynamic shared mobility, where customers are independent of schedules and fixed stops. This study aims to investigate the potential effects shared mobility can have on future transportation. We simulate multiple scenarios to analyze the effects different service designs might have on vehicle kilometers, on the required number of shared vehicles, on the potential replacement of private cars, and on service metrics such as waiting times, travel times, and detour levels. To demonstrate how simulation can be used to analyze future mobility, we present a case study of the city of Gothenburg in Sweden, where we model travel demand in the morning hours of a workday. The results show that a significant decrease of vehicle kilometers can be achieved if all private car trips are replaced by rideshare and that shared vehicles can potentially replace at least 5 private cars during the morning peak.
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Toward ML-Assisted Advanced Manufacturing
Authors: Howland Scott , Kassab Lara , Kappagantula Keerti , Kvinge Henry , Emerson Tegan 
Published: January 2023

AbstractThe research and development cycle of advanced manufacturing processes traditionally requires a large investment of time and resources. Experiments can be expensive and are hence conducted on relatively small scales. This poses problems for typically data-hungry machine learning tools which could otherwise expedite the development cycle. We build upon prior work by applying conditional generative adversarial networks (GANs) to scanning electron microscope (SEM) imagery from an emerging advanced manufacturing process, shear-assisted processing and extrusion (ShAPE). We generate realistic images conditioned on temper and either experimental parameters or material properties. In doing so, we are able to integrate machine learning into the development cycle, by allowing a user to immediately visualize the microstructure that would arise from particular process parameters or properties. This work forms a technical backbone for a fundamentally new approach for understanding manufacturing processes in the absence of first-principle models. By characterizing microstructure from a topological perspective, we are able to evaluate our models’ ability to capture the breadth and diversity of experimental scanning electron microscope (SEM) samples. Our method is successful in capturing the visual and general microstructural features arising from the considered process, with analysis highlighting directions to further improve the topological realism of our synthetic imagery.
Losses from cross-holdings in a duopoly with convex cost and strategic input price determination
Authors: Mukherjee Arijit 
Published: January 2023

AbstractIt is well-known that positive output externality on the outside firms is the reason for unprofitable passive cross-holding, which refers to a situation where a producer holds non-controlling shares in rival firms. Considering a final goods market with Cournot duopoly, where cross-holdings do not create positive output externality on the outside firms, we show that cross-holdings can be unprofitable under strategic input price determination by an input supplier if the final goods are produced with decreasing returns to scale technologies. Our results hold under symmetric and asymmetric cross-holdings. We show that cross-holdings can be unprofitable also under Bertrand duopoly in the final goods market. Thus, we provide a new reason for unprofitable passive cross-holdings. We also show the implications of a higher product differentiation on the profits and welfare.
An efficient weighted network centrality approach for exploring mechanisms of action of the Ruellia herbal formula for treating rheumatoid arthritis
Authors: Ochieng Peter Juma , Hussain Abrar , Dombi József , Krész Miklós 
Published: January 2023

AbstractAimThis study outlines an efficient weighted network centrality measure approach and its application in network pharmacology for exploring mechanisms of action of theRuellia prostrata(RP) andRuellia bignoniiflora(RB) herbal formula for treating rheumatoid arthritis.MethodIn our proposed method we first calculated interconnectivity scores all the network targets then computed weighted centrality score for all targets to identify of major network targets based on centrality score. We apply our technology to network pharmacology by constructing herb-compound-putative target network; compound-putative targets-RA target network; and imbalance multi-level herb-compound-putative target-RA target-PPI network. We then identify the major targets in the network based on our centrality measure approach. Finally we validated the major identified network targets using the enrichment analysis and a molecular docking simulation.ResultThe results reveled our proposed weighted network centrality approach outperform classical centrality measure in identification of influential nodes in four real complex networks based on SI model simulation. Application of our approach to network pharmacology shows that 57 major targets of which 33 targets including 8 compositive compounds, 15 putative target and 10 therapeutic targets played an important role in the network and directly linked to rheumatoid arthritis. Enrichment analysis confirmed that putative targets were frequently involved in TNF, CCR5, IL-17 and G-protein coupled receptors signaling pathways which are critical in the progression of rheumatoid arthritis. The molecular docking simulation indicated four targets had significant binding affinity to major protein targets. Glyceryl diacetate-2-Oleate and Oleoyl chloride showed the best binding affinity to all targets proteins and were within Lipinski limits. ADMET prediction also confirm both compounds had no toxic effect on human hence potential lead drug compounds for treating rheumatoid arthritis.ConclusionThis study developed an efficient weighted network centrality approach as tool for identification of major network targets. Network pharmacology findings provides promising results that could lead us to design and discover of alternative drug compounds. Though our approach is a purely in silico method, clinical experiments are required to test and validate the hypotheses of our computational methods.
Hemodynamic and fluid flow analysis of a cerebral aneurysm: a CFD simulation
Authors: Rahma Ahmed G. , Abdelhamid Talaat 
Published: January 2023

AbstractIn this study, we investigate the hemodynamics parameters and their impact on the aneurysm rupture. The simulations are performed on an ideal (benchmark) and realistic model for the intracranial aneurysm that appears at the anterior communicating artery. The realistic geometry was reconstructed from patient-specific cerebral arteries. The computational fluid dynamics simulations are utilized to investigate the hemodynamic parameters such as flow recirculation, wall shear stress, and wall pressure. The boundary conditions are measured from the patient using ultrasonography. The solution of the governing equations is obtained by using the ANSYS-FLUENT 19.2 package. The CFD results indicate that the flow recirculation appears in the aneurysms zone. The effect of the flow recirculation on the bulge hemodynamics wall parameters is discussed to identify the rupture zone.
Equivariant quantum graph circuits: constructions for universal approximation over graphs
Authors: Mernyei Péter , Meichanetzidis Konstantinos , Ceylan İsmail İlkan 
Published: January 2023

AbstractWe investigate quantum circuits for graph representation learning, and propose equivariant quantum graph circuits (EQGCs), as a class of parameterized quantum circuits with strong relational inductive bias for learning over graph-structured data. Conceptually, EQGCs serve as a unifying framework for quantum graph representation learning, allowing us to define several interesting subclasses subsuming existing proposals. In terms of the representation power, we prove that the subclasses of interest are universal approximators for functions over the bounded graph domain. This theoretical perspective on quantum graph machine learning methods opens many directions for further work, and could lead to models with capabilities beyond those of classical approaches. We also provide experimental evidence, and observe that the performance of EQGCs scales well with the depth of the model.
Efficacy of immune checkpoint inhibitor monotherapy or combined with other small molecule-targeted agents in ovarian cancer
Authors: Muaibati Munawaer , Abuduyilimu Abasi , Zhang Tao , Dai Yun , Li Ruyuan , Huang Fanwei , Li Kexin , Tong Qing , Huang Xiaoyuan , Zhuang Liang 
Published: January 2023

Abstract
Ovarian cancer is the most lethal female reproductive system tumour. Despite the great advances in surgery and systemic chemotherapy over the past two decades, almost all patients in stages III and IV relapse and develop resistance to chemotherapy after first-line treatment. Ovarian cancer has an extraordinarily complex immunosuppressive tumour microenvironment in which immune checkpoints negatively regulate T cells activation and weaken antitumour immune responses by delivering immunosuppressive signals. Therefore, inhibition of immune checkpoints can break down the state of immunosuppression. Indeed, Immune checkpoint inhibitors (ICIs) have revolutionised the therapeutic landscape of many solid tumours. However, ICIs have yielded modest benefits in ovarian cancer. Therefore, a more comprehensive understanding of the mechanistic basis of the immune checkpoints is needed to improve the efficacy of ICIs in ovarian cancer. In this review, we systematically introduce the mechanisms and expression of immune checkpoints in ovarian cancer. Moreover, this review summarises recent updates regarding ICI monotherapy or combined with other small-molecule-targeted agents in ovarian cancer.
Genotypic investigation of a rotavirus cluster at a quaternary-care pediatric hospital
Authors: Kitt Eimear M. , Yoon Hee-won , Comar Courtney E. , Smith Kenneth P. , Harris Rebecca M. , Esona Mathew D. , Gautam Rashi , Mijatovic-Rustempasic Slavica , Hopkins Amy L. , Jaimes Jose , Handy Lori K. 
Published: January 2023

AbstractRotavirus (RV) was a common healthcare-associated infection prior to the introduction of the RV vaccine. Following widespread RV vaccination, healthcare-associated rotavirus cases are rare. We describe an investigation of a cluster of rotavirus infections in a pediatric hospital in which an uncommon genotype not typically circulating in the United States was detected.
Determination of glycaemic response to the consumption of two specialised formulas for glycaemic control
Authors: Zanini Ana Claudia , Santos Hellin dos , Celes Ana Paula Monnerat , Giuntini Eliana Bistriche , Franco Bernadette Dora Gombossy de Melo 
Published: January 2023

AbstractTo assess the glycaemic response after ingestion of two specialised oral and enteral nutrition formulas for glycaemic control. The participants were sixteen healthy volunteers, aged 21–49 years, with normal glucose tolerance. The volunteers attended the tests fasting for 10 h, for 5 weeks, and consumed the reference food – glucose solution – for 3 weeks, and the two formulas DiamaxO and DiamaxIG in the following weeks, in amounts equivalent to 25 g of available carbohydrates. During the period of 120 min, seven blood samples were taken through capillary blood sampling to determine the glycaemic response. The glycaemic index (GI) was calculated according to the trapezoidal rule, ignoring areas below the fasting line. The glycaemic load (GL) was determined by the formula GL = ((GI(glucose = reference) × ‘g’ of available carbohydrate per serving]/100. The formulas showed low GI and GL. GI = 37·8 and GL = 6·6 for DiamaxO and GI = 21·5 and GL = 3·5 for DiamaxIG. The peak of the glycaemic response occurred 30 min after ingestion, with a marked difference in blood glucose between the Diamax products in relation to glucose. Differences were also significant at times 15, 45, 60 and 90 min in relation to glucose (ANOVA with post hoc Bonferroni, P < 0·005), but not between the two products. However, the AUC and the GI of DiamaxIG are significantly smaller than that of the DiamaxO second t test (P = 0·0059). The glycaemic response to the products is quite reduced, presenting a curve with a little accentuated shape, without high peak, especially in the modified product.