bluuebunny/crossref_metadata_2025_split huggingface dataset:
Healthcare professionals’ well-being at work: a professional and organizational identity perspective
Authors: Nunes Francisco Guilherme , Oliveira Vanessa Duarte Correia de , Nascimento Generosa do 
Published: July 2024

PurposeThe purpose of this study is to test a model of healthcare professionals’ well-being seen as a consequence of a process of motivated professional identity construction, a variable that mediates the influence of the organizational identity (utilitarian or normative) and the perceived reputation of the profession on well-being.Design/methodology/approachCross-sectional design, based on a survey of 384 healthcare professionals. Structural equation modeling with latent variables was used to test the model.FindingsThe data provide empirical evidence supporting the proposed model. We find that organizational identity (utilitarian and normative) and perceived professional reputation positively relate to professional identity, a variable that positively relates to well-being. Professional identity mediates the relationship between organizational identity (normative and utilitarian) and perceived professional reputation and well-being. Utilitarian organizational identity and perceived professional reputation are also directly related to well-being.Originality/valueThis research significantly departs from the current focus of explaining the well-being of healthcare professionals by resorting mainly to individual factors and introduces organizational and institutional determinants.
What characterizes strategy research in Latin America? A bibliometric analysis for the 1990–2023 period
Authors: Rivera-Rodríguez Hugo-Alberto , Beltrán Duque Alejandro , Sánchez-López Juan Camilo 
Published: July 2024

Purpose
This article examines strategic management research across Latin America from 1990 to 2023, addressing four critical inquiries: the themes prevalent in strategic discussions, the leading countries in strategic management (SM) publications, the defining characteristics of strategic research in major Latin American economies and the reflection on whether Latin America is a region that generates or follows the knowledge of the Global North.

Design/methodology/approach
Utilizing co-occurrence analysis, this study maps the terrain of SM research in the region, analyzing 4,963 articles indexed in the Scopus database. The authors employed a co-occurrence analysis to map SM research in Latin America, analyzing 4,963 articles from the Scopus database.

Findings
Predominant themes include the theoretical underpinnings of strategy, sustainable development, innovation, tourism and international trade. Brazil, Mexico, Colombia and Chile have emerged as leaders in research volume and thematic diversity, particularly in sustainable development and innovation.

Practical implications
By identifying patterns, behaviors and trends in SM research, the authors uncover methods and tools that, once contextualized for the region, can significantly enhance organizational performance.

Originality/value
This investigation is a pioneering effort, providing a focused analysis on SM research within Latin America. It highlights significant contributions since 1990 across the region's main economies. This study represents one of the first comprehensive mappings of this academic field within Latin America. This is the first article, to the authors’ knowledge, developed to map the intellectual structure of the SM field in Latin America through an analysis of co-occurrences, with emphasis on the region's main economies.
Love of life as a measure of quality of life
Authors: Abdel-Khalek Ahmed M. 
Published: July 2024

Purpose
Love of life (LOL) is a new construct in positive psychology. LOL is defined by a generally positive evaluation of one’s own life, positive regard towards life and a pleasurable attachment to life. The purpose of this study is that LOL is associated with quality of life (QOL) and could be predicted by some of its subscales.

Design/methodology/approach
A sample of Alexandria University undergraduates took part in this study (n = 298). They responded to the WHOQOL Brief and LOL scales.

Findings
Men obtained significantly higher mean total scores than did women for general health, and the physical and psychological domains of QOL. All the Pearson correlations between LOL and QOL were significant except for two correlations for women. The strongest correlation with LOL is for the psychological QOL domain. Principal components analysis extracted one component for men which was labeled “QOL and LOL.” For women, two components were extracted, which were labeled “QOL and LOL” and “General and physical health.” Predictors of LOL were psychological and social QOL domains (men), and psychological, social and environmental QOL domains (women). It was concluded that LOL is associated with QOL, in particular, the psychological subscale. Furthermore, LOL can predict QOL, in particular, the psychological and social domains.

Research limitations/implications
This study used nonprobability sampling with a sample of students drawn from only one university. So, it may be difficult to generalize the findings.

Originality/value
LOL is a comparatively new concept in the field of positive psychology.
“The urge to tell and its consequences”: women’s memoirs of schizophrenia and schizoaffective disorder
Authors: Austin Rosalind 
Published: July 2024

Purpose
This paper aims to explore the efforts of four American women living with psychosis to chart their recovery process in published memoirs.

Design/methodology/approach
This paper looks at the different types of stigma that the patient-authors claim to encounter.

Findings
The author discusses the impact that the patient-authors see stigma as having on their recovery, and why they need artistic spaces to express themselves.

Originality/value
The memoirs offer a space for the women to revisit their memories of psychosis, and to achieve at least a partial acceptance of these experiences.
Autism spectrum disorder (ASD) and terrorism: a rapid evidence assessment of risk and vulnerability factors, and implications for intervention
Authors: Milburn Paige , Galvin Carol , Bryan Amanda Louise , Kennedy Patrick John 
Published: July 2024

Purpose
Factors that may influence risk and/or vulnerability to radicalisation or involvement in terrorism by individuals with autism spectrum disorder (ASD) are currently undetermined. The purpose of this rapid evidence assessment (REA) was to identify and review studies which consider the association between ASD and terrorism to explore potential risk or vulnerability factors and the implications for intervention.

Design/methodology/approach
The REA method was used to review the literature, with 16 papers meeting inclusion criteria.

Findings
Ten factors were identified as relevant to ASD and terrorism which were combined into four overarching themes: cognitive, social, psychological and ASD traits.

Originality/value
This REA presents a novel review of literature relating to ASD and terrorism. The findings are valuable to practitioners working with individuals with ASD who may present with the identified risk and/or vulnerability factors. The implications of these factors for intervention are discussed, along with directions for future research.
Text, time, and travel: temporal pathways of postsocialism and Islam
Authors: Yolaçan Serkan 
Published: July 2024

AbstractAs the concept of postsocialism faces increased scrutiny, there is a call to expand its spatiotemporal scope beyond socialist contexts in order to reclaim its analytical capacity. In Azerbaijan, the quiet resurgence of tezkirahs – biographical anthologies rooted in both the Islamic and Soviet traditions – presents an opportunity to explore how former Soviet citizens can bridge different histories, countries, and cultural traditions to nurture an expansive sense of collective presence and moral dignity after seventy years of communist rule and disconnect. These texts help Azerbaijanis chart their diverse roots in the former imperial domains of Persians, Turks, and Russians and absorb them into their vision of who they once were and could be again. Writers and readers of tezkirahs establish connections to non‐socialist pasts and places through what I refer to as temporal pathways, where traversing time becomes a journey to another place, and vice versa. By exploring this spatialized historical sensibility through the capacious ethnographic‐textual lens of an Islamic genre, this article sheds fresh light on postsocialist possibilities.
Age‐ and disease‐related autophagy impairment in Huntington disease: New insights from direct neuronal reprogramming
Authors: Luo Chuyang , Yang Junsheng 
Published: July 2024

AbstractAutophagy impairment in Huntington disease (HD) has been reported for almost two decades. However, the molecular mechanisms underlying this phenomenon are still unclear. This is partially because it is challenging to model the impact of the disease‐causing mutation, aging, as well as the selective vulnerability of neurons in a single model. Recently developed direct neuronal reprogramming that allows researchers to induce neurons‐of‐interest retaining biological aging information made it possible to establish HD cellular models to study more relevant age‐ and disease‐related molecular changes in neurons. We here summarized the findings from a few latest studies utilizing directly reprogrammed HD neurons and discussed the new insights they brought to the understanding of the age‐ and disease‐related autophagy impairment in HD.
Who benefits from digital interventions for bipolar disorder? Stage of illness characteristics as predictors of changes in quality of life
Authors: Tremain Hailey , Fletcher Kathryn , Meyer Denny , Murray Greg 
Published: July 2024

AbstractObjectivesThis study explored the potential role of stage‐related variables in intervention outcomes in bipolar disorder (BD). Specifically, we aimed to identify which subgroups of individuals were most likely to experience improved quality of life following digitally delivered psychosocial interventions for BD.MethodsThe study involved a secondary analysis of combined data from two randomised control trials (RCTs). Each trial assessed the effectiveness of digitally delivered interventions for improving quality of life, in late‐stage (ORBIT RCT) or early‐stage (BETTER RCT) BD. Three iterations of cluster analyses were performed, identifying subgroups of individuals based on (i) current phenomenology, (ii) course of illness and (iii) medication response. The resultant subgroups were compared with regard to changes in quality of life pre‐post intervention, via repeated measures ANOVAs.ResultsIn each cluster analysis, two clusters were found. The current phenomenology clusters reflected two impairment levels, ‘moderate impairment’ and ‘low impairment’. The course of illness clusters reflected ‘more chronicity’ and ‘less chronicity’ and the medication response clusters reflected ‘good medication response’ and ‘poor medication response’. Differences in changes in quality of life over time were observed between the two current phenomenology clusters and between the medication response clusters, while the course of illness subgroups did not respond differently.ConclusionsThere are at least two distinct groups of treatment‐seeking individuals with established BD, based on illness features with previously established links to different illness stages. Clusters within the current phenomenology and medication response domains demonstrated significantly different trajectories of QoL change over time in the context of our interventions, highlighting potential implications for treatment selection aligned with precision psychiatry.
How does work during pregnancy affect maternal and infant health and development?
Authors: Pilarz Alejandra Ros , Pac Jessica 
Published: July 2024

AbstractIn the United States, most mothers work during pregnancy. Yet, until the passage of the Pregnant Workers Fairness Act in 2022, pregnant employees did not have a right to reasonable accommodations to work under safe conditions. This law is expected to increase employment among pregnant women, making it critical to understand the effects of work during pregnancy on health and the potential benefits of the law. Because the prenatal period has long‐lasting consequences for health, employment during pregnancy can affect children's health and development in childhood and beyond. In this article, we review theory and empirical evidence on the effects of work during pregnancy on maternal and infant health. We propose a conceptual framework that outlines the pathways through which work during pregnancy affects health, discuss policies that are expected to affect work during pregnancy and health and conclude with priorities for future research.
Learning to Rasterize Differentiably
Authors: Wu C. , Mailee H. , Montazeri Z. , Ritschel T. 
Published: July 2024

AbstractDifferentiable rasterization changes the standard formulation of primitive rasterization — by enabling gradient flow from a pixel to its underlying triangles — using distribution functions in different stages of rendering, creating a “soft” version of the original rasterizer. However, choosing the optimal softening function that ensures the best performance and convergence to a desired goal requires trial and error. Previous work has analyzed and compared several combinations of softening. In this work, we take it a step further and, instead of making a combinatorial choice of softening operations, parameterize the continuous space of common softening operations. We study meta‐learning tunable softness functions over a set of inverse rendering tasks (2D and 3D shape, pose and occlusion) so it generalizes to new and unseen differentiable rendering tasks with optimal softness.
Realistic Facial Age Transformation with 3D Uplifting
Authors: Li X. , Guarnera G. C. , Lin A. , Ghosh A. 
Published: July 2024

AbstractWhile current facial re‐ageing methods can produce realistic results, they purely focus on the 2D age transformation. In this work, we present an approach to transform the age of a person in both facial appearance and shape across different ages while preserving their identity. We employ an α‐(de)blending diffusion network with an age‐to‐α transformation to generate coarse structure changes, such as wrinkles. Additionally, we edit biophysical skin properties, including melanin and hemoglobin, to simulate skin color changes, producing realistic re‐ageing results from ages 10 to 80 years. We also propose a geometric neural network that alters the coarse scale facial geometry according to age, followed by a lightweight and efficient network that adds appropriate skin displacement on top of the coarse geometry. Both qualitative and quantitative comparisons show that our method outperforms current state‐of‐the‐art approaches.
Practical Appearance Model for Foundation Cosmetics
Authors: Lanza Dario , Padrón‐Griffe Juan Raúl , Pranovich Alina , Muñoz Adolfo , Frisvad Jeppe Revall , Jarabo Adrián 
Published: July 2024

AbstractCosmetic products have found their place in various aspects of human life, yet their digital appearance reproduction has received little attention. We present an appearance model for cosmetics, in particular for foundation layers, that reproduces a range of existing appearances of foundation cosmetics: from a glossy to a matte to an almost velvety look. Our model is a multilayered BSDF that reproduces the stacking of multiple layers of cosmetics. Inspired by the microscopic particulates used in cosmetics, we model each individual layer as a stochastic participating medium with two types of scatterers that mimic the most prominent visual features of cosmetics: spherical diffusers, resulting in a uniform distribution of radiance; and platelets, responsible for the glossy look of certain cosmetics. We implement our model on top of the position‐free Monte Carlo framework, that allows us to include multiple scattering. We validate our model against measured reflectance data, and demonstrate the versatility and expressiveness of our model by thoroughly exploring the range of appearances that it can produce.
Lossless Basis Expansion for Gradient‐Domain Rendering
Authors: Fang Q. , Hachisuka T. 
Published: July 2024

AbstractGradient‐domain rendering utilizes difference estimates with shift mapping to reduce variance in Monte Carlo rendering. Such difference estimates are effective under the assumption that pixels for difference estimates have similar integrands. This assumption is often violated because it is common to have spatially varying BSDFs with material maps, which potentially result in a very different integrand per pixel. We introduce an extension of gradient‐domain rendering that effectively supports such per‐pixel variation in BSDFs based on basis expansion. Basis expansion for BSDFs has been used extensively in other problems in rendering, where the goal is to approximate a given BSDF by a weighted sum of predefined basis functions. We instead utilize lossless basis expansion, representing a BSDF without any approximation by adding the remaining difference in the original basis expansion. This lossless basis expansion allows us to cancel more terms via shift mapping, resulting in low variance difference estimates even with per‐pixel BSDF variation. We also extend the Poisson reconstruction process to support this basis expansion. Regular gradient‐domain rendering can be expressed as a special case of our extension, where the basis is simply the BSDF per pixel (i.e., no basis expansion). We provide proof‐of‐concept experiments and showcase the effectiveness of our method for scenes with highly varying material maps. Our results show noticeable improvement over regular gradient‐domain rendering under both L1 and L2 reconstructions. The resulting formulation via basis expansion essentially serves as a new way of path reuse among pixels in the presence of per‐pixel variation.
Patch Decomposition for Efficient Mesh Contours Extraction
Authors: Tsiapkolis P. , Bénard P. 
Published: July 2024

AbstractObject‐space occluding contours of triangular meshes (a.k.a. mesh contours) are at the core of many methods in computer graphics and computational geometry. A number of hierarchical data‐structures have been proposed to accelerate their computation on the CPU, but they do not map well to the GPU for real‐time applications, such as video games. We show that a simple, flat data‐structure composed of patches bounded by a normal cone and a bounding sphere may reach this goal, provided it is constructed to maximize the probability for a patch to be culled over all viewpoints. We derive a heuristic metric to efficiently estimate this probability, and present a greedy, bottom‐up algorithm that constructs patches by grouping mesh edges according to this metric. In addition, we propose an effective way of computing their bounding sphere. We demonstrate through extensive experiments that this data‐structure achieves similar performance as the state‐of‐the‐art on the CPU but is also perfectly adapted to the GPU, leading to up to ×5 speedups.
Neural SSS: Lightweight Object Appearance Representation
Authors: TG T. , Tran D. M. , Jensen H. W. , Ramamoorthi R. , Frisvad J. R. 
Published: July 2024

AbstractWe present a method for capturing the BSSRDF (bidirectional scattering‐surface reflectance distribution function) of arbitrary geometry with a neural network. We demonstrate how a compact neural network can represent the full 8‐dimensional light transport within an object including heterogeneous scattering. We develop an efficient rendering method using importance sampling that is able to render complex translucent objects under arbitrary lighting. Our method can also leverage the common planar half‐space assumption, which allows it to represent one BSSRDF model that can be used across a variety of geometries. Our results demonstrate that we can render heterogeneous translucent objects under arbitrary lighting and obtain results that match the reference rendered using volumetric path tracing.
METTL14‐mediated upregulation of lncRNA HOTAIR represses PP1α expression by promoting H3K4me1 demethylation in oxycodone‐treated mice
Authors: Liu Tian‐Cong , Li Hong‐Xi , Wan Yu‐Xiao , Shi Guang , Zhao Yun‐Peng , Liu Yi‐Fei , Fan Xin‐Yu 
Published: July 2024

AbstractN6‐methyladenosine (m6A) methylation is a vital epigenetic mechanism associated with drug addiction. However, the relationship between m6A modification and oxycodone rewarding is less well explored. Based on an open field test, the present study evaluated oxycodone rewarding using chromatin immunoprecipitation PCR, immunofluorescence, and RNA sequencing. A marked increase in METTL14 protein and a decrease in PP1α protein due to oxycodone abundance in the striatal neurons were observed in a dose‐ and time‐dependent manner. Oxycodone markedly increased LSD1 expression, and decreased H3K4me1 expression in the striatum. In the open field test, intra‐striatal injection of METTL14 siRNA, HOTAIR siRNA, or LSD1 shRNA blocked oxycodone‐induced increase in locomotor activity. The downregulation of PP1α was also inhibited after treatment with METTL14/HOTAIR siRNA and LSD1 shRNA. Enhanced binding of LSD1 with CoRest and of CoRest with the PP1α gene induced by oxycodone was also reversed by LSD1 shRNA. In addition, H3K4me1 demethylation was also blocked by the treatment. In summary, the investigation confirmed that METTL14‐mediated upregulation of HOTAIR resulted in the repression of PP1α, which in turn facilitated the recruitment of LSD1, thus catalyzing H3K4me1 demethylation and promoting oxycodone addiction.
Application of artificial intelligence‐based magnetic resonance imaging in diagnosis of cerebral small vessel disease
Authors: Hu Xiaofei , Liu Li , Xiong Ming , Lu Jie 
Published: July 2024

AbstractCerebral small vessel disease (CSVD) is an important cause of stroke, cognitive impairment, and other diseases, and its early quantitative evaluation can significantly improve patient prognosis. Magnetic resonance imaging (MRI) is an important method to evaluate the occurrence, development, and severity of CSVD. However, the diagnostic process lacks quantitative evaluation criteria and is limited by experience, which may easily lead to missed diagnoses and misdiagnoses. With the development of artificial intelligence technology based on deep learning, the extraction of high‐dimensional features in imaging can assist doctors in clinical decision‐making, and it has been widely used in brain function and mental disorders, and cardiovascular and cerebrovascular diseases. This paper summarizes the global research results in recent years and briefly describes the application of deep learning in evaluating CSVD signs in MRI imaging, including recent small subcortical infarcts, lacunes of presumed vascular origin, vascular white matter hyperintensity, enlarged perivascular spaces, cerebral microbleeds, brain atrophy, cortical superficial siderosis, and cortical cerebral microinfarct.