bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gender dysphoria in adolescence: examining the rapid-onset hypothesis
Authors: Leonhardt André , Fuchs Martin , Gander Manuela , Sevecke Kathrin 
Published: July 2024

SummaryThe sharp rise in the number of predominantly natal female adolescents experiencing gender dysphoria and seeking treatment in specialized clinics has sparked a contentious and polarized debate among both the scientific community and the public sphere. Few explanations have been offered for these recent developments. One proposal that has generated considerable attention is the notion of “rapid-onset” gender dysphoria, which is assumed to apply to a subset of adolescents and young adults. First introduced by Lisa Littman in a 2018 study of parental reports, it describes a subset of youth, primarily natal females, with no childhood indicators of gender dysphoria but with a sudden emergence of gender dysphoria symptoms during puberty or after its completion. For them, identifying as transgender is assumed to serve as a maladaptive coping mechanism for underlying mental health issues and is linked to social influences from peer groups and through social media. The purpose of this article is to analyze this theory and its associated hypotheses against the existing evidence base and to discuss its potential implications for future research and the advancement of treatment paradigms.
Can quantum Rabi model with $${\varvec{A}}^\textbf{2}$$-term avoid no-go theorem and make quantum simulation of mass-enhancement in SUSY breaking?
Authors: Hirokawa Masao 
Published: July 2024

AbstractWe study the model of a mass enhancement in the supersymmetric quantum mechanics. This model is so simple that it may be implemented as a quantum simulation of the mass enhancement taking place when supersymmetry (SUSY) is spontaneously broken. It is evolved from a prototype based on the quantum Rabi model. Here, our quantum simulation means the realization of the target quantum phenomenon as a physical entity with some quantum-information devices. The original prototype is given as a mathematical model, and has the transition from the $${\mathcal {N}}=2$$

N
=
2

SUSY to its spontaneous breaking, though it has no mass enhancement. It is recently reported that the transition is observed for this prototype in a trapped-ion experiment with devising a method experimentally to realize the transition. The model proposed in this paper describes how the mass enhancement takes place in the fermionic states by the excitation of the 1-mode light boson in the SUSY breaking. In this model, the bosonic and fermionic states are graded by qubits. Although our model’s interaction does not have the Higgs potential, the mass enhancement in the fermionic states is caused by the radiative enhancement with the help of the X-gate’s swap between the fermionic and bosonic states.
Cognitive reserve modulates mental health in adulthood
Authors: Porricelli Daniele , Tecilla Margherita , Pucci Veronica , Di Rosa Elisa , Mondini Sara , Cappelletti Marinella 
Published: July 2024

AbstractCognitive Reserve (CR) reflects acquired knowledge, skills, and abilities throughout life, and it is known for modulating cognitive efficiency in healthy and clinical populations. CR, which was initially proposed to explain individual differences in the clinical presentation of dementia, has subsequently been extended to healthy ageing, showing its role in cognitive efficiency also during middle age. Recently, CR has been linked to affective processes in psychiatric conditions such as schizophrenia, major depressive and anxiety symptoms, and psychological distress, suggesting its potential role in emotional expression and regulation. Whether the role of CR in mental health extends to non-pathological adults, and whether this is only relevant in older age is not yet clear. The aim of this work was therefore to explore the relationship between CR and mental health in healthy adults, with a focus on middle adulthood (40–60). In a sample of 96 participants, we found a positive association between CR and mental health outcomes, such that a higher cognitive reserve index corresponded to fewer mental health reported symptoms. Specifically, a higher CR reflecting professional activities was associated with lower stress levels, especially in middle agers. Taken together, these data therefore suggest that engaging occupations may help maintain a robust mental health, especially by reducing stress symptoms during middle age. These results broaden previous findings suggesting that CR relates to affective components of mental health in middle aged and older adults.
Understanding post-impact biomechanics of ballistic cranial injury by smoothed particle hydrodynamics numerical modelling
Authors: Chattrairat Akanae , Kandare Everson , Aimmanee Sontipee , Tran Phuong , Das Raj 
Published: July 2024

AbstractVirtual crime scene investigation using numerical models has the potential to assist in the forensic investigation of firearm-related fatalities, where ethical concerns and expensive resources limit the scope of physical experiments to comprehend the post-impact biomechanics comprehensively. The human cranial numerical model developed in this study incorporates three main components (skin, skull, and brain) with dynamic biomaterial properties. The virtual model provides valuable insights into the post-impact biomechanics of cranial ballistic injuries, particularly in high-speed events beyond conventional investigative capabilities, including the velocity of ejected blood backspatter, cavitation collapsing, and pressure waves. The validation of the numerical model, both quantitatively and qualitatively, demonstrates its ability to replicate similar bone fractures, entrance wound shapes, and backward skin ballooning observed in physical experiments of the human cranial geometry. The model also yields similar temporary cavity sizes, wound sizes, and blood backspatter time against the physical cranial model, aiding in bloodstain pattern analysis. Additionally, the numerical model enables exploration of ballistic factors that vary in each crime scene environment and influence cranial injuries, such as projectile type, velocity, impact location, and impact angle. These established injury patterns contribute to crime scene reconstruction by providing essential information on projectile trajectory, discharge distance, and firearm type, assisting in the resolution of court cases. In conclusion, the developed human cranial geometry in this study offers a reliable tool for investigating firearm-related cranial injuries, serving as a statistical reference in forensic science. Virtual crime scene investigations
using these models
have the potential to enhance the accuracy and efficiency of forensic analyses.
Food Cue Reactivity Meets the Reinforcer Pathology Model: Behavioral Economic Measures of Cue-Induced Changes in Food Reinforcer Efficacy
Authors: Musquez Morgan , Rasmussen Erin B. 
Published: July 2024

AbstractFood cue reactivity, or behavioral sensitivity to conditioned food cues, is an eating pattern observed in those with obesity and binge-eating disorder. The reinforcer pathology model, which characterizes overconsumption of a reinforcer such as food may be relevant to food cue reactivity, especially in those with obesity and binge-eating disorder. The reinforcer pathology model posits that steep delay discounting (DD) and demand elasticity are processes involved in the overconsumption of food. Two of our recent studies examine the extent to which reactivity to conditioned food cues may be involved in food reinforcer pathologies. First, food cues were conditioned with Oreo cookies with binge-eating prone (BEP) and binge-eating resistant (BER) rats. Delay discounting was compared before and after conditioning. Food cues induced steeper DD for rats, though BEP rats showed some evidence for greater sensitivity to this effect than BER rats, albeit this difference was not significant. Second, healthy-weight humans and humans with overweight/obese BMI underwent conditioning of visual cues paired with M&M candies. After acquisition, cues induced greater demand intensity and inelasticity for food compared to baseline. Participants with overweight/obese BMI, compared to controls, also showed some evidence for greater sensitivity to this change ininelasticity compared to healthy-weight participants, but this difference was also not significant. Food cues, then, may induce changes in DD and economic demand, supporting the relevance of reinforcer pathologies.
Self-Healing Dynamic Hydrogel Microparticles with Structural Color for Wound Management
Authors: Wang Li , Ding Xiaoya , Fan Lu , Filppula Anne M. , Li Qinyu , Zhang Hongbo , Zhao Yuanjin , Shang Luoran 
Published: July 2024

AbstractChronic diabetic wounds confront a significant medical challenge because of increasing prevalence and difficult-healing circumstances. It is vital to develop multifunctional hydrogel dressings, with well-designed morphology and structure to enhance flexibility and effectiveness in wound management. To achieve these, we propose a self-healing hydrogel dressing based on structural color microspheres for wound management. The microsphere comprised a photothermal-responsive inverse opal framework, which was constructed by hyaluronic acid methacryloyl, silk fibroin methacryloyl and black phosphorus quantum dots (BPQDs), and was further re-filled with a dynamic hydrogel. The dynamic hydrogel filler was formed by Knoevenagel condensation reaction between cyanoacetate and benzaldehyde-functionalized dextran (DEX-CA and DEX-BA). Notably, the composite microspheres can be applied arbitrarily, and they can adhere together upon near-infrared irradiation by leveraging the BPQDs-mediated photothermal effect and the thermoreversible stiffness change of dynamic hydrogel. Additionally, eumenitin and vascular endothelial growth factor were co-loaded in the microspheres and their release behavior can be regulated by the same mechanism. Moreover, effective monitoring of the drug release process can be achieved through visual color variations. The microsphere system has demonstrated desired capabilities of controllable drug release and efficient wound management. These characteristics suggest broad prospects for the proposed composite microspheres in clinical applications.
Transient Response and Ionic Dynamics in Organic Electrochemical Transistors
Authors: Zhao Chao , Yang Jintao , Ma Wei 
Published: July 2024

AbstractThe rapid development of organic electrochemical transistors (OECTs) has ushered in a new era in organic electronics, distinguishing itself through its application in a variety of domains, from high-speed logic circuits to sensitive biosensors, and neuromorphic devices like artificial synapses and organic electrochemical random-access memories. Despite recent strides in enhancing OECT performance, driven by the demand for superior transient response capabilities, a comprehensive understanding of the complex interplay between charge and ion transport, alongside electron–ion interactions, as well as the optimization strategies, remains elusive. This review aims to bridge this gap by providing a systematic overview on the fundamental working principles of OECT transient responses, emphasizing advancements in device physics and optimization approaches. We review the critical aspect of transient ion dynamics in both volatile and non-volatile applications, as well as the impact of materials, morphology, device structure strategies on optimizing transient responses. This paper not only offers a detailed overview of the current state of the art, but also identifies promising avenues for future research, aiming to drive future performance advancements in diversified applications."Image missing"
Computational approaches to modeling dynamos in galaxies
Authors: Korpi-Lagg Maarit J. , Mac Low Mordecai-Mark , Gent Frederick A. 
Published: July 2024

AbstractGalaxies are observed to host magnetic fields with a typical total strength of around 15 $$\upmu $$
μ
G. A coherent large-scale field constitutes up to a few microgauss of the total, while the rest is built from strong magnetic fluctuations over a wide range of spatial scales. This represents sufficient magnetic energy for it to be dynamically significant. Several questions immediately arise: What is the physical mechanism that gives rise to such magnetic fields? How do these magnetic fields affect the formation and evolution of galaxies? In which physical processes do magnetic fields play a role, and how can that role be characterized? Numerical modelling of magnetized flows in galaxies is playing an ever-increasing role in finding those answers. We review major techniques used for these models. Current results strongly support the conclusion that field growth occurs during the formation of the first galaxies on timescales shorter than their accretion timescales due to small-scale turbulent dynamos. The saturated small-scale dynamo maintains field strengths at only a few percent of equipartition with turbulence. This is in contradiction with the observed magnitude of turbulent fields, but may be reconciled by the further contribution to the turbulent field of the large-scale dynamo. The subsequent action of large-scale dynamos in differentially rotating discs produces field strengths observed in low redshift galaxies, where it reaches equipartition with the turbulence and has substantial power at large scales. The field structure resulting appears consistent with observations including Faraday rotation and polarisation from synchrotron and dust thermal emission. Major remaining challenges include scaling numerical models toward realistic scale separations and Prandtl and Reynolds numbers.
Integration of Sensor-Based Technology in Mental Healthcare: A Systematic Scoping Review
Authors: Bosch R. , Noordzij M. L. , Westerhof G. J. , Bohlmeijer E. T. 
Published: July 2024

AbstractSensor-based technologies can collect objective and real-time data on physiological, behavioral, and contextual factors related to mental disorders. This not only holds potential for mental healthcare but also comes with challenges, such as handling large amounts of data and supporting the integration of sensors in clinical practice. This systematic scoping review aims to provide an overview of studies explicitly addressing the integration of sensor-based technology in mental healthcare by reporting on the way that therapists and patients work with sensors. In addition, we explore barriers and facilitators for the integration of sensor-based technology in clinical practice. Four databases were searched on April 5, 2023. Studies on sensor-based technology integrated in mental healthcare were included. A total of 14 studies were included. In these studies, a variety of sensor-based technologies were used. All studies were conducted between 2016 and 2022. Most studies showed that sensor-based technologies are accepted by patients and that their use is associated with symptom reduction. However, most studies did not systematically report on barriers and facilitators and mainly focused on the technology itself rather than on the broader context of its intended use. Also, sensor-based technologies are not yet embedded in clinical protocols. From the current review, we can conclude that sensor-based technologies are sufficiently accepted and feasible, and that sensors are promising for enhancing clinical outcomes. However, sensors are not properly integrated in treatment protocols yet. Therefore, we propose a next phase in research on sensor-based technology in mental healthcare treatment. This next phase asks for a multifaceted approach consisting of (1) embedding sensor-based technology in treatment protocols in co-creation with patients and clinicians, (2) examining the feasibility of these interventions together with small-scale evidence studies, and (3) systematically examining the implementation of sensor-based technology in clinical practice using existing frameworks for technology implementation. Open Science Framework: https://doi.org/10.17605/OSF.IO/XQHSY.
The magnitude vector of images
Authors: Adamer Michael F. , De Brouwer Edward , O’Bray Leslie , Rieck Bastian 
Published: July 2024

AbstractThe magnitude of a finite metric space has recently emerged as a novel invariant quantity, allowing to measure the effective size of a metric space. Despite encouraging first results demonstrating the descriptive abilities of the magnitude, such as being able to detect the boundary of a metric space, the potential use cases of magnitude remain under-explored. In this work, we investigate the properties of the magnitude on images, an important data modality in many machine learning applications. By endowing each individual image with its own metric space, we are able to define the concept of magnitude on images and analyse the individual contribution of each pixel with the magnitude vector. In particular, we theoretically show that the previously known properties of boundary detection translate to edge detection abilities in images. Furthermore, we demonstrate practical use cases of magnitude for machine learning applications and propose a novel magnitude model that consists of a computationally efficient magnitude computation and a learnable metric. By doing so, we address one computational hurdle that used to make magnitude impractical for many applications and open the way for the adoption of magnitude in machine learning research.
Detecting review fraud using metaheuristic graph neural networks
Authors: Oak Rajvardhan 
Published: July 2024

AbstractAlthough online reviews play a critical role in shaping consumer behavior and establishing institutional trust, this reliance on online reviews has given rise to a proliferation of fake reviews. Consequently, there is an urgent need for the development of robust mechanisms to identify and mitigate these inauthentic reviews. In this study, we introduce an innovative approach for the detection of fake reviews, leveraging a metaheuristic graph neural network model. Our methodology begins by extracting distinctive features from review text, comprising of term frequency—inverse document frequency (TF-IDF) vectors and bidirectional encoder representation transformer (BERT) embedding vectors. We feed these features into a graph convolutional network (GCN) that uses message passing to label each review. Furthermore, we address the optimization of our graph neural network models using Harris Hawk and Cat Swarm optimization techniques. Our experiments reveal that optimization of the GNN with Harris Hawk Optimization yields a significantly enhanced model performance, further validating the efficacy of our detection framework. This research contributes to the ongoing efforts in the realm of online review authenticity and showcases the potential of advanced techniques to combat the proliferation of fraudulent reviews.
Assessing “Invisible Loss” During Medium-Term Earthquake Recovery: The Case of Indonesia's 2016 Aceh Earthquakes
Authors: Akter Sonia , Chairunissa Talitha Fauzia , Pundit Madhavi 
Published: July 2024

AbstractThis study presents the results of a medium-term assessment of earthquake recovery, aiming to measure non-economic welfare losses resulting from the indirect impacts of earthquakes. While most earthquake assessments concentrate on the economic loss and damage caused by direct impacts of earthquakes, this study focuses on capturing these less visible non-economic losses. The 2016 Aceh earthquakes in Indonesia serve as the case study for this assessment. By applying the difference-in-differences method, we compared the changes in a range of non-economic welfare indicators in earthquake-affected and unaffected villages two years before (2014) and two years after (2018) the catastrophic earthquakes. In addition to administrative data, we tested the suitability of average monthly and annual night-time light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument as an alternative way to capture non-economic welfare losses. The findings from administrative data suggested a significant deterioration in, poverty, access to healthcare and access to socio-economic services in earthquake-affected villages relative to unaffected villages in 2018, compared to 2014. The analysis of nightlights data revealed contrasting results, suggesting that disaster recovery assessments using nightlights may not accurately capture non-economic welfare changes on the ground. Our research indicates that the detrimental effects of earthquakes on non-economic welfare persisted for years following the initial devastation. Utilizing administrative data can help pinpoint the nature and extent of non-economic losses and inform the development of policies to aid in the effective recovery of affected communities.
The Initial Upper Paleolithic from Tolbor-16, Mongolia: Characteristics of the Lithic Assemblage and Their Evolutionary Implications
Authors: Zwyns Nicolas , Tsedendorj Bolorbat , Paine Clea H. , Flas Damien , Davaakhuu Odsuren , Allshouse Aurora F. , Gantumur Angaragdulguun , Galfi Jovan , Smith Kevin N. , Byambaa Gunchinsuren 
Published: July 2024

Abstract
According to fossil evidence, the Initial Upper Paleolithic (IUP) refers to archaeological assemblages associated with the early dispersal of Homo sapiens across Eurasia. These assemblages are often described as exhibiting a combination of Middle and Upper Paleolithic typo-technological features or, more broadly, as a technology in progression from the former to the latter. Genetic evidence indicates that as members of our species moved across Europe and Asia, they encountered Neanderthal, Denisovan, and possibly other local populations. At the Eurasian scale, the IUP shows considerable variation, but to what extent this corresponds to a relatively unified cultural package strictly associated with our species, or a suite of unrelated technologies reflecting the complex dynamics of a global population turnover, remains unclear. Like most archaeological assemblages, however, the IUP illustrates a combination of adaptive and normative behaviors, along with some stochastic variation. Here, we investigate what drives typo-technological variation within an IUP assemblage to identify traits relevant for larger scale inter-regional comparisons. Specifically, we describe a lithic assemblage dated to ca. 45 ka cal BP from the site of Tolbor-16 in northern Mongolia. We identify three defining aspects of the IUP at the site, namely variation in core shape and size, patterns of blade core reduction, and the presence of Middle Paleolithic typo-technological features. Our goal is to clarify the influence of dynamic reduction processes on assemblage composition and, within the variation observed, to identify typo-technological features that are relevant for inter-regional comparisons and scenarios of population dispersal.