bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adolescents’ difficulties, strengths and feelings of insecurity: a cross-sectional descriptive survey in Finland
Authors: Kokkonen Pinja , Athanasopoulou Christina , Leino-Kilpi Helena , Puukka Pauli , Sakellari Evanthia 
Published: August 2023

AbstractThe present study aimed to describe adolescents’ self-reported emotional and behavioural strengths and difficulties, as well as their insecurity feeling. In addition, the aim was to examine the association with background characteristics, and explore the association between strengths and difficulties and insecurity factors. The study was conducted among 114 secondary school pupils in Finland, using an online questionnaire. Adolescents’ emotional and behavioural difficulties and strengths, were mostly classified as normal. Strengths and Difficulties Questionnaire total score as well as internal and external score, were inversely associated with insecurity factors. Girls had significantly higher prosocial behavior compared to boys (P = 0.0007). The age of adolescents was found to be related to their internal difficulties (P = 0.02) and prosocial behavior (P = 0.01). Adolescent’s perception of their family relations as poor was associated with external difficulties (P = 0.04). The current results, can be helpful for mental health professionals who work with adolescents in order to implement appropriate and needs specific mental health promotion interventions at individual but also community level. Finally, more research is needed to validate measures for insecurity. This will support mental health professionals in their clinical practice by providing them with all the important factors needed to support adolescents.
Framing responsive architecture with soft robots—the exploratory practice of soft pneumatic robotic architectural system
Authors: Wang Si-Yuan Rylan 
Published: August 2023

AbstractInspired by intelligent skin, this research constructs a soft pneumatic robotic architectural system based on the interaction between inflatable material agents and the human body. It aims to provide flexibly changeable scene modes for dynamic inhabiting through responsive spatial performance. From the idea of the Fun Palace and the structure and performance spatial methodology to the proposal of responsive/soft architecture and relevant examples such as Furl and Robot Soft, the literature review provides the foundation and direction for the establishment of research experiments. The research methodology is based on structure and performance, oriented to explore soft material agents, link input information and output modules to realize the manifestation of human-space interaction and spatial performance and assemble the basic configuration of the system. As a result, a synergistic architectural interaction system like a media center that can provide a variety of adaptive space scenes is built, which can realize real-time perception and responsive control of the interactive process, and at the same time provide richness of scene performance beyond established architectural configurations, confirming the possibility of creating a behaviorally responsive architecture by integrating modularly morphing spaces, AI-sensing systems, and interaction technologies. This study explored responsive human settlements by expanding soft pneumatic robots in architecture. It can expand to fields such as machine cognition at the input level, further realize the real-time feedback system at the output level, and can evolve with the information interconnection of urban landscapes and residential communities in terms of spatial interaction. The work gives a convincing vision of architectural intelligence through soft robotics and is expected to continue to develop and bring more inspiring innovations with its integrated methods and connotations.
Efficient Machine Learning and Factional Calculus Based Mathematical Model for Early COVID Prediction
Authors: Chandra Saroj Kumar , Bajpai Manish Kumar 
Published: August 2023

AbstractDiseases are increasing with exponential rate worldwide. Its detection is challenging task due to unavailability of the experts. Machine learning models provide automated mechanism to detect diseases once trained. It has been used to predict and detect many diseases such as cancer, heart attack, liver infections, kidney infections. The new coronavirus has become one of the deadliest diseases. Its case escalated in unexpected ways. In the literature, many machine learning models such as Extreme Gradient Boosting (XGBoosting), Support Vector Machine (SVM), regression, and Logistic regression have been used. It has been observed that these models can predict COVID cases early but are unable to find the peak point and deadline of the disease. Hence, mathematical models have been designed to early predict and find peak point and dead-line in disease prediction. These mathematical models use integral calculus-based Ordinary Differential Equations (ODEs) to predict COVID cases. Governments are dependent on these models’ pre- diction for early preparation of hospitalization, medicines, and many more. Hence, higher prediction accuracy is required. It has been found in the literature that fractional calculus-based models are more accurate in disease prediction and detection. Fractional models provides to choose order of derivative with fractional value due to which information processing capability increases. In the present work, mathematical model using fractional calculus has been devised for prediction of COVID cases. In the model, quarantine, symptomatic and asymptomatic cases have been incorporated for accurate prediction. It is found that the proposed fractional model not only predicts COVID cases more accurately but also gives peak point and dead-line of the disease.
Sleep problems in children and adolescents in an attention deficit hyperactivity disorder service
Authors: Bond L. , McTiernan D. , Connaughton M. , Heron E. A. , Coogan A. N. , McGrath J. 
Published: August 2023

AbstractObjectives:Sleep problems are common amongst children and adolescents with attention deficit hyperactivity disorder (ADHD). The purpose of this study was to investigate sleep problems in children and adolescents attending a specialist ADHD service.Methods:This was a cross-sectional online survey combined with a retrospective chart review, conducted in the ADHD Assessment, Diagnosis, Management, initiation, Research and Education (ADMiRE) service, the first public specialist ADHD service for young people in Ireland. Participants were caregivers of children and adolescents with ADHD attending ADMiRE. Sleep was assessed using The Children’s Sleep Habits Questionnaire (CSHQ) and ADHD symptoms were assessed using an abbreviated version of the Swanson, Nolan and Pelham Teacher and Parent Rating Scale (SNAP-IV). Details regarding patient demographics, co-morbidities and medication were collected from patient records.Results:Eighty-four percent of young people scored above the clinical cut-off for a sleep disorder. The most frequently reported sleep problems were related to sleep onset and sleep duration, and 64% of respondents met the criteria for two or more sleep problems. ADHD severity was associated with greater sleep problems. Co-morbid physical, neurodevelopmental, and mental health disorders as well as stimulant use were not associated with greater sleep problems.Conclusion:Sleep problems are very common amongst children and adolescents with ADHD. This study has demonstrated an association between more sleep problems and ADHD severity. These findings highlight the need for both effective ADHD treatment to ensure optional sleep in young people as well as effective interventions for sleep problems to prevent worsening of ADHD symptoms.
The impact of disaggregated formal institutional distance variables on entry mode decision: Evidence from Japan
Authors: Ahmed Kashif , Bebenroth Ralf 
Published: August 2023

Abstract
Grounded in the organizational legitimacy perspective, this study examines the influence of formal institutional distance (FID) on the entry mode choice of Japanese cross-border acquirers. By disaggregating the FID variable using the Worldwide Governance Indicators, we provide a nuanced understanding of the relationship between FID dimensions and acquisition behavior. We find that out of the six disaggregated FID measures, three dimensions significantly impact acquisition decisions. Specifically, FID related to ‘regulatory quality’ and ‘control of corruption’ negatively affects the likelihood of full acquisitions, while FID related to the ‘rule of law’ positively influences full acquisitions. Our findings challenge the use of aggregated measures and highlight the importance of considering institutional variations. Japanese acquirers demonstrate a preference for higher control in uncertain legal environments. This study contributes to the literature by offering insights into the specific FID dimensions that drive the choice between partial and full acquisitions for Japanese firms.
How and when employees’ boundary-spanning behavior improves their creative performance: A moderated mediation model
Authors: Zhang Zheng , Li Ran 
Published: August 2023

AbstractThis article draws on status characteristics theory to explore the mechanisms of individual-level boundary-spanning behavior on employee creative performance, as well as the mediating role of informal status and the moderating role of Zhongyong thinking. The results of a two-wave questionnaire survey of 202 employees show that boundary-spanning behavior has a significant positive relationship with employees’ creative performance, informal status mediates the link between boundary-spanning behavior and creative performance of this employee, Zhongyong thinking plays a moderating role between employees’ boundary-spanning behavior and their informal status, and Zhongyong thinking also moderates the mediating role of informal status between boundary-spanning behavior and employee creative performance. In this paper, a moderated mediation model is established to enhance the understanding of the effects and mechanisms of individual boundary-spanning behavior, as well as to provide some constructive insight into how boundary-spanning behavior can be effectively employed in management practice within the Chinese context.
Bayesian parameter estimation in glacier mass-balance modelling using observations with distinct temporal resolutions and uncertainties
Authors: Sjursen Kamilla H. , Dunse Thorben , Tambue Antoine , Schuler Thomas V. , Andreassen Liss M. 
Published: August 2023

Abstract
Empirical glacier mass-balance models are commonly used in assessments of glacier and runoff evolution. Recent satellite-borne geodetic mass-balance observations of global coverage facilitate large-scale model calibration that previously relied on sparse in situ observations of glacier mass change. Geodetic observations constitute temporally aggregated mass-balance signals with significant uncertainty, raising questions about the role of observations with different temporal resolutions and uncertainties in constraining model parameters. We employ a Bayesian approach and demonstrate the sensitivity of parameter values to commonly used mass-balance observations of seasonal, annual and decadal resolution with uncertainties characteristic to in situ and satellite-borne observations. For glaciers along a continentality gradient in Norway, the use of annual mass balances results in around 20% lower magnitude of modelled ablation and accumulation (1960–2020), compared to employing seasonal balances. Decadal mass balance also underestimates magnitudes of ablation and accumulation, but parameter values are strongly influenced by the prior distribution. The datasets yield similar estimates of annual mass balance with different margins of uncertainty. Decadal observations are afflicted with considerable uncertainty in mass-balance sensitivity due to high parameter uncertainty. Our results highlight the importance of seasonal observations when model applications require accurate magnitudes of ablation, e.g. to estimate meltwater runoff.
Content and uptake of macroelements in green fodder of mixtures of narrowleaf lupin with spring triticale
Authors: Górski R. , Płaza A. 
Published: August 2023

AbstractThis paper presents the results of a study conducted in 2016–2018 in the temperate conditions to evaluate the content and uptake of P, K, Ca and Mg in mixtures of narrowleaf lupin with spring triticale grown for green fodder. Two factors were analysed in the experiment: A – the proportion of components in the mixture: narrowleaf lupine 100%, narrowleaf lupine + spring triticale 75 + 25%, 50 + 50%, 25 + 75%, and spring triticale 100%; B – the harvest stage the flowering stage of narrowleaf lupine, the stage of flat green pod of narrowleaf lupine. Increasing the proportion of spring triticale in the sown mixtures in relation to narrowleaf lupine resulted in a decrease in the content of the analysed macroelements by 8.9%–28.7% on a g/kg DM basis. The greatest uptake on a kg/ha basis of macroelements was found in the mixture with an equal share of both components. Harvesting mixtures at a later stage of development increased the uptake of P, K, Ca and Mg by 98.7%–111.8% because of greater DM yield, but reduced the content of these macroelements by 12.6%–20.8% in the more mature fodder. Mixtures of narrowleaf lupine with spring triticale can provide valuable mineral nutrients for livestock.
Is the hangul Cervus hanglu hanglu in Kashmir drifting towards extinction? Evidence from 19 years of monitoring
Authors: Ahmad Khursheed , Mirelli Marco , Charoo Samina , Nigam Parag , Qureshi Qamar , Naqash Rashid Y. , Focardi Stefano 
Published: August 2023

AbstractThe Tarim red deer Cervus hanglu has been recently recognized as a separate deer species with populations in China, Central Asia and Kashmir. These populations are few, isolated and at risk of extinction. The documented range of the Kashmir population of the hangul, now recognized as Cervus hanglu hanglu, is restricted to c. 808 km2 and comprises < 200 individuals, confined mainly to the 141 km2 Dachigam National Park. A few relict herds inhabit the surrounding landscape. Here we analyse the results of almost 20 years of population monitoring (January 2001–March 2020). We found that this population is unable to increase despite full protection within Dachigam National Park. We performed a population viability analysis using both deterministic and stochastic simulations and found that further population decrease is likely. We recommend the use of improved monitoring methods to investigate the population dynamics of the hangul and the implementation of measures to reduce the risk of extinction faced by this small population. Science-based conservation policies, including ex situ conservation and reintroduction programmes, will be required to increase the hangul population size and range.
The Ecological Resilience Framework: The Justice Ambassadors Youth Council as a model for community-based resilience
Authors: Burrows Brooke , Daniels Jarrell , Starks UniQue C. , Amso Dima , Downey Geraldine 
Published: August 2023

AbstractWe present an ‘Ecological Resilience Framework’ (ERF) to demonstrate how resilience is created through the Justice Ambassadors Youth Council (JAYC) program. JAYC is a platform in which New York government representatives collaboratively learn and develop policy solutions alongside emerging adults who are criminal legal system impacted and reside in predominantly Black and Hispanic communities characterized by chronically high levels of poverty, violence, and incarceration. We focus our work on the process of developing resilience in the context of structural social inequity and injustice. We argue that resilience can best be understood in the context of the adversity to which it is a response, not as an isolated individual quality. Therefore, resilience science is at its best when it incorporates a multi-disciplinary scientific perspective, one that addresses a continuum from individual- to community- to society-level physical, cognitive, relationship, and mental health variables. To demonstrate how our ERF incorporates this approach, we outline how JAYC not only supports young adult participants in understanding their individual life trajectories and narrative identity, but also actively connects them within a diverse social network of mentors and to various opportunities that support a healthy transition to adult resilience.
Compositional Verification in Rewriting Logic
Authors: MARTÍN ÓSCAR , VERDEJO ALBERTO , MARTÍ-OLIET NARCISO 
Published: August 2023

AbstractIn previous work, summarized in this paper, we proposed an operation of parallel composition for rewriting-logic theories, allowing compositional specification of systems and reusability of components. The present paper focuses on compositional verification. We show how the assume/guarantee technique can be transposed to our setting, by giving appropriate definitions of satisfaction based on transition structures and path semantics. We also show that simulation and equational abstraction can be done componentwise. Appropriate concepts of fairness and deadlock for our composition operation are discussed, as they affect satisfaction of temporal formulas. We keep in parallel a distributed and a global view of composed systems. We show that these views are equivalent and interchangeable, which may help our intuition and also has practical uses as, for example, it allows global-style verification of a modularly specified system. Under consideration in Theory and Practice of Logic Programming (TPLP).
Critique of digital constitutionalism: Deconstruction and reconstruction from a societal perspective
Authors: Golia Angelo Jr 
Published: August 2023

AbstractDigital constitutionalism is a strand of scholarship that focuses on the relationship between constitutional law and the socio-legal challenges posed by the digital revolution. However, such scholarship often builds uncritically on the tenets of liberal, state-centred constitutional theory, giving rise to contradictions between analytical starting points and normative aspirations. Against this background, with an approach inspired by societal constitutionalism, this article engages with digital constitutionalism as both an object and a means of critique. As an object, digital constitutionalism is assessed in the light of its contradictions. As a means, digital constitutionalism is used to assess the limits of traditional, liberal, state-centred constitutional theory. In other words, societal constitutionalism is the theoretical lens used to both deconstruct and reconstruct digital constitutionalism according to its normative aspirations. The article has three main goals: first, linking different discourses within digital constitutionalism, highlighting its critical potential; second, advancing some proposals based on such reflections; and third, bringing digital constitutionalism closer to the broader global constitutionalism discourse. After an overview of societal constitutionalism, the article focuses on digital constitutionalism’s definition and three functionally differentiated systems: politics, economy and law. For each of them, it highlights analytical and normative gains deriving from the societal constitutionalism-based approach as well as policy proposals to be developed further.
Single-cell massively-parallel multiplexed microbial sequencing (M3-seq) identifies rare bacterial populations and profiles phage infection
Authors: Wang Bruce , Lin Aaron E. , Yuan Jiayi , Novak Katherine E. , Koch Matthias D. , Wingreen Ned S. , Adamson Britt , Gitai Zemer 
Published: August 2023

AbstractBacterial populations are highly adaptive. They can respond to stress and survive in shifting environments. How the behaviours of individual bacteria vary during stress, however, is poorly understood. To identify and characterize rare bacterial subpopulations, technologies for single-cell transcriptional profiling have been developed. Existing approaches show some degree of limitation, for example, in terms of number of cells or transcripts that can be profiled. Due in part to these limitations, few conditions have been studied with these tools. Here we develop massively-parallel, multiplexed, microbial sequencing (M3-seq)—a single-cell RNA-sequencing platform for bacteria that pairs combinatorial cell indexing with post hoc rRNA depletion. We show that M3-seq can profile bacterial cells from different species under a range of conditions in single experiments. We then apply M3-seq to hundreds of thousands of cells, revealing rare populations and insights into bet-hedging associated with stress responses and characterizing phage infection.
Multielement Z-tag imaging by X-ray fluorescence microscopy for next-generation multiplex imaging
Authors: Strotton Merrick , Hosogane Tsuyoshi , di Michiel Marco , Moch Holger , Varga Zsuzsanna , Bodenmiller Bernd 
Published: August 2023

AbstractRapid, highly multiplexed, nondestructive imaging that spans the molecular to the supra-cellular scale would be a powerful tool for tissue analysis. However, the physical constraints of established imaging methods limit the simultaneous improvement of these parameters. Whole-organism to atomic-level imaging is possible with tissue-penetrant, picometer-wavelength X-rays. To enable highly multiplexed X-ray imaging, we developed multielement Z-tag X-ray fluorescence (MEZ-XRF) that can operate at kHz speeds when combined with signal amplification by exchange reaction (SABER)-amplified Z-tag reagents. We demonstrated parallel imaging of 20 Z-tag or SABER Z-tag reagents at subcellular resolution in cell lines and multiple human tissues. We benchmarked MEZ-XRF against imaging mass cytometry and demonstrated the nondestructive multiscale repeat imaging capabilities of MEZ-XRF with rapid tissue overview scans, followed by slower, more sensitive imaging of low-abundance markers such as immune checkpoint proteins. The unique multiscale, nondestructive nature of MEZ-XRF, combined with SABER Z-tags for high sensitivity or enhanced speed, enables highly multiplexed bioimaging across biological scales.
Artificial intelligence in ovarian cancer histopathology: a systematic review
Authors: Breen Jack , Allen Katie , Zucker Kieran , Adusumilli Pratik , Scarsbrook Andrew , Hall Geoff , Orsi Nicolas M. , Ravikumar Nishant 
Published: August 2023

AbstractThis study evaluates the quality of published research using artificial intelligence (AI) for ovarian cancer diagnosis or prognosis using histopathology data. A systematic search of PubMed, Scopus, Web of Science, Cochrane CENTRAL, and WHO-ICTRP was conducted up to May 19, 2023. Inclusion criteria required that AI was used for prognostic or diagnostic inferences in human ovarian cancer histopathology images. Risk of bias was assessed using PROBAST. Information about each model was tabulated and summary statistics were reported. The study was registered on PROSPERO (CRD42022334730) and PRISMA 2020 reporting guidelines were followed. Searches identified 1573 records, of which 45 were eligible for inclusion. These studies contained 80 models of interest, including 37 diagnostic models, 22 prognostic models, and 21 other diagnostically relevant models. Common tasks included treatment response prediction (11/80), malignancy status classification (10/80), stain quantification (9/80), and histological subtyping (7/80). Models were developed using 1–1375 histopathology slides from 1–776 ovarian cancer patients. A high or unclear risk of bias was found in all studies, most frequently due to limited analysis and incomplete reporting regarding participant recruitment. Limited research has been conducted on the application of AI to histopathology images for diagnostic or prognostic purposes in ovarian cancer, and none of the models have been demonstrated to be ready for real-world implementation. Key aspects to accelerate clinical translation include transparent and comprehensive reporting of data provenance and modelling approaches, and improved quantitative evaluation using cross-validation and external validations. This work was funded by the Engineering and Physical Sciences Research Council.