bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relationship between family income and trajectories of adjustment in adolescence: Sleep and physical activity as moderators
Authors: Gillis Brian T. , Hinnant J. Benjamin , Erath Stephen A. , El‐Sheikh Mona 
Published: December 2022

AbstractIntroductionYouth from lower‐income families experience adjustment problems at higher rates than higher‐income peers. While adolescents have little control over family income, they do have some agency over their sleep and physical activity, two factors that have been shown to mitigate the risk of maladjustment. To test this, sleep and physical activity were examined as moderators of the longitudinal relationship between family income (indexed by income‐to‐needs ratio) and trajectories of adolescent adjustment problems.MethodsParticipants included a socioeconomically diverse community sample of 252 US youth (53% female; 33% Black, 67% White) in 2012–2015. Actigraphy‐based sleep duration and quality were indexed, respectively, by minutes (sleep onset to wake excluding awakenings) and efficiency (% minutes scored as sleep from onset to wake). Physical activity and adjustment were youth‐reported. Outcomes included internalizing (anxious/depressive) and rule‐breaking behavior. Latent growth models estimated trajectories of adjustment across ages 16 and 18 years conditional on family income, sleep, physical activity, and their interactions.ResultsRelationships between family income and change in internalizing symptoms were moderated by sleep minutes, and associations between income and change in internalizing symptoms and rule‐breaking behavior were moderated conjointly by sleep efficiency and physical activity.ConclusionsUnder conditions of high‐quality sleep and more physical activity, adolescents with lower income reported fewer adjustment problems. Conversely, youth with both poor sleep and low physical activity were at the highest risk for maladjustment over time. Findings enhance understanding of individual differences in trajectories of mental health associated with bioregulation, health behaviors, and the sociocultural context.
The association between trauma and interpersonal problems in a United States community mental health setting
Authors: Goldstein Elena , King Catherine , Crits‐Christoph Paul , Connolly Gibbons Mary Beth 
Published: December 2022

AbstractObjectivePrevious research has documented associations between trauma and interpersonal problems. We examined the impact of trauma on interpersonal problems among depressed patients seeking treatment in a community mental health setting.MethodsA total of 453 patients seeking treatment and screened for a comparative effectiveness study of therapies for depression were included. We conducted analyses relating the 32‐item inventory of interpersonal problems (IIP‐32) to trauma measures.Results99.1% of the sample experienced a traumatic event. There were significant associations between the total number of traumas, the number of sexually and physically assaultive traumas, and both gender and race. The number of sexually assaultive traumas was significantly related to the IIP‐32 “too caring” subscale (simple r = 0.167, p < 0.001). Controlling for demographics and other IIP‐32 subscales, the total number of traumas remained significantly related to the IIP‐32 “too caring” domain (partial r = 0.163, p < 0.001).ConclusionsTraumatic events are prevalent among community populations and these experiences are associated with certain interpersonal problems. Trauma and interpersonal problems are key issues for the treatment of patients in the community mental health setting.
Impact of facemasks on psychotherapy: Clinician's confidence and emotion recognition
Authors: Bani Marco , Ardenghi Stefano , Rampoldi Giulia , Russo Selena , Strepparava Maria Grazia 
Published: December 2022

AbstractObjectivesFacial emotion recognition is a key component of human interactions, and in clinical relationships contributes to building and maintaining the therapeutic alliance with patients. The introduction of facemasks has reduced the availability of facial information in private and professional relationships. This study aimed to assess the impact of facemasks on clinicians' perception of clinical interactions as well as their ability to read facial expressions.MethodsIn this cross‐sectional study, a purposive sample of 342 clinical psychologists or psychotherapists completed an online survey including the assessment of burnout, alexithymia, emotion dysregulation, and self‐perceived ability to build effective relationships and communication with patients with/without facemasks. Participants were randomly assigned to the standardized facial emotion recognition task Diagnostic Analysis of Nonverbal Accuracy FACES 2‐Adult Faces including 24 faces representing anger, fear, sadness, and happiness.ResultsFacemasks impaired the self‐perceived ability of clinicians to build effective relationships and communicate with patients and reduced satisfaction in clinical encounters. The ability of clinicians to recognize facial emotions is significantly reduced for masked happy and angry faces, but not for sad and afraid ones. The perceived difficulty in building good relationships and communication with patients had a positive correlation with alexithymia and emotion dysregulation; higher levels of discomfort when wearing facemasks had a positive correlation with burnout and emotion dysregulation.ConclusionFacemasks reduced clinicians' self‐confidence in clinical encounters with patients wearing facemasks, but their facial emotion recognition performance was only partially impaired.
Development and validation of the facilitative interpersonal skills scale for clients
Authors: Santos João M. , Barata Matilde , Rathenau Sara , Amaro Inês , Vaz Alexandre , Sousa Daniel , Severino Margarida , Taveira Mafalda 
Published: December 2022

AbstractObjectivePsychotherapy studies have revealed that therapist characteristics are responsible for 5% to 9% of outcome variance. The therapist‐facilitative interpersonal skills (FIS) have been shown to predict both alliance and outcomes, indicating that higher FIS therapists are more effective than lower FIS therapists. The current study focused on the development and validation of the FIS‐client version (FIS‐C) instrument, aimed at collecting the clients' perspectives on relevant therapist characteristics.MethodThe clinical outcomes in routine evaluation—outcome measures, the session rating scale, and the FIS questionnaire—client version were filled out by psychotherapy clients. Exploratory, confirmatory factor, and test–retest analysis were conducted.ResultsResults indicate robust psychometric characteristics, in terms of validity (factorial, convergent, discriminant, and nomological), reliability, and sensitivity.ConclusionThe validation of the FIS‐C represents an important contribution to clinical research and practice, namely to the field of client feedback and therapist expertise.
Chest X‐ray‐based opportunistic screening of sarcopenia using deep learning
Authors: Ryu Jin , Eom Sujeong , Kim Hyeon Chang , Kim Chang Oh , Rhee Yumie , You Seng Chan , Hong Namki 
Published: December 2022

AbstractBackgroundEarly detection and management of sarcopenia is of clinical importance. We aimed to develop a chest X‐ray‐based deep learning model to predict presence of sarcopenia.MethodsData of participants who visited osteoporosis clinic at Severance Hospital, Seoul, South Korea, between January 2020 and June 2021 were used as derivation cohort as split to train, validation and test set (65:15:20). A community‐based older adults cohort (KURE) was used as external test set. Sarcopenia was defined based on Asian Working Group 2019 guideline. A deep learning model was trained to predict appendicular lean mass (ALM), handgrip strength (HGS) and chair rise test performance from chest X‐ray images; then the machine learning model (SARC‐CXR score) was built using the age, sex, body mass index and chest X‐ray predicted muscle parameters along with estimation uncertainty values.ResultsMean age of the derivation cohort (n = 926; women n = 700, 76%; sarcopenia n = 141, 15%) and the external test (n = 149; women n = 95, 64%; sarcopenia n = 18, 12%) cohort was 61.4 and 71.6 years, respectively. In the internal test set (a hold‐out set, n = 189, from the derivation cohort) and the external test set (n = 149), the concordance correlation coefficient for ALM prediction was 0.80 and 0.76, with an average difference of 0.18 ± 2.71 and 0.21 ± 2.28, respectively. Gradient‐weight class activation mapping for deep neural network models to predict ALM and HGS commonly showed highly weight pixel values at bilateral lung fields and part of the cardiac contour. SARC‐CXR score showed good discriminatory performance for sarcopenia in both internal test set [area under the receiver‐operating characteristics curve (AUROC) 0.813, area under the precision‐recall curve (AUPRC) 0.380, sensitivity 0.844, specificity 0.739, F1‐score 0.540] and external test set (AUROC 0.780, AUPRC 0.440, sensitivity 0.611, specificity 0.855, F1‐score 0.458). Among SARC‐CXR model features, predicted low ALM from chest X‐ray was the most important predictor of sarcopenia based on SHapley Additive exPlanations values. Higher estimation uncertainty of HGS contributed to elevate the predicted risk of sarcopenia. In internal test set, SARC‐CXR score showed better discriminatory performance than SARC‐F score (AUROC 0.813 vs. 0.691, P = 0.029).ConclusionsChest X‐ray‐based deep leaning model improved detection of sarcopenia, which merits further investigation.
Relative telomere length impact on mortality of COVID‐19: Sex differences
Authors: Virseda‐Berdices Ana , Concostrina‐Martinez Leyre , Martínez‐González Oscar , Blancas Rafael , Resino Salvador , Ryan Pablo , Martin‐Vicente María , Brochado‐Kith Oscar , Blanca‐López Natalia , Mallol Poyato María J. , López Matamala Blanca , Martín Parra Carmen , Jiménez‐Sousa María Á , Fernández‐Rodríguez Amanda 
Published: December 2022

AbstractIncreasing age is associated with severity and higher mortality of COVID‐19. Telomere shortening is associated with higher risk of infections and may be used to identify those patients who are more likely to die. We evaluated the association between relative telomere length (RTL) and COVID‐19 mortality. RTL was measured in patients hospitalized because of COVID‐19. We used Kaplan–Meier method to analyze survival probabilities, and Cox regression to investigate the association between RTL and mortality (30 and 90 days). Six hundred and eight patients were included in the analysis (mean age =72.5 years, 41.1% women, and 53.8% Caucasic). During the study period, 75 people died from COVID‐19 and 533 survived. Lower RTL was associated with a higher risk of death in women either at 30 (adjusted hazard ratio [HR] (aHR) = 3.33; 95% confidence interval [CI] = 1.05–10.00; p = 0.040) and at 90 days (aHR = 3.57; 95%CI = 1.23–11.11; p = 0.019). Lower RTL was associated with a higher risk of dying of COVID‐19 in women. This finding suggests that RTL has an essential role in the prognosis of this subset of the population.
Temperature‐Sensitive Dual Dispersive Wave Generation of Higher‐Order Modes in Liquid‐Core Fibers
Authors: Scheibinger Ramona , Hofmann Johannes , Schaarschmidt Kay , Chemnitz Mario , Schmidt Markus A. 
Published: December 2022

AbstractThe emission of resonant radiation from temporal solitary waves—also known as dispersive wave generation—allows efficient energy transfer to far‐distant spectral domains. This coherent radiation can deliver large spectral densities at selected wavelengths once control over the individual soliton is achieved. Here, the concepts of few‐mode operation and local temperature tuning are combined for precise steering of cascaded dispersive wave generation in liquid‐core optical fibers. By exciting higher‐order TM and TE modes with femtosecond pulses at 1600 nm, the generation of two dispersive waves tunable by up to 33 nm K−1 through adjusting a selected part of the waveguide is observed. Sophisticated soliton‐driven nonlinear dynamics arising from thermally transitioning from anomalous to all‐normal dispersion with temperature changes of only a few Kelvin have been found, including soliton steering, soliton breakdown, and soliton post‐fission tuning. All experimental results are verified by nonlinear simulations and semi‐analytic phase‐matching calculations, overall providing a cost‐effective and practical toolbox for discovering unexplored states of light as well as for developing dynamically tunable broadband light sources.
Device‐System End‐to‐End Design of Photonic Neuromorphic Processor Using Reinforcement Learning
Authors: Tang Yingheng , Zamani Princess Tara , Chen Ruiyang , Ma Jianzhu , Qi Minghao , Yu Cunxi , Gao Weilu 
Published: December 2022

AbstractThe incorporation of high‐performance optoelectronic devices into photonic neuromorphic processors can substantially accelerate computationally intensive matrix multiplication operations in machine learning (ML) algorithms. However, the conventional designs of individual devices and system are largely disconnected, and the system optimization is limited to the manual exploration of a small design space. Here, a device‐system end‐to‐end design methodology is reported to optimize a free‐space optical general matrix multiplication (GEMM) hardware accelerator by engineering a spatially reconfigurable array made from chalcogenide phase change materials. With a highly parallelized integrated hardware emulator with experimental information, the design of unit device to directly optimize GEMM calculation accuracy is achieved by exploring a large parameter space through reinforcement learning algorithms, including deep Q‐learning neural network, Bayesian optimization, and their cascaded approach. The algorithm‐generated physical quantities show a clear correlation between system performance metrics and device specifications. Furthermore, physics‐aware training approaches are employed to deploy optimized hardware to the tasks of image classification, materials discovery, and a closed‐loop design of optical ML accelerators. The demonstrated framework offers insights into the end‐to‐end and co‐design of optoelectronic devices and systems with reduced human supervision and domain knowledge barriers.
A story to sell: The influence of storytelling on consumers' purchasing behavior
Authors: Júnior João Ricardo de Oliveira , Limongi Ricardo , Lim Weng Marc , Eastman Jacqueline K. , Kumar Satish 
Published: December 2022

AbstractStorytelling can arouse consumers' emotions and affect purchasing behavior through desires and attitudes. While the marketing literature discusses storytelling, there is a lack of consensus because of the diverse conceptual and operational definitions used. To untangle the complexities and consolidate the fragmented knowledge about storytelling in marketing, this research examines how the marketing literature has addressed the influence of storytelling on consumers' purchasing behavior. The findings aid in understanding how the topic has been discussed from a marketing perspective in consumer behavior studies. Through a systematic literature review using a bibliometric analysis, we demonstrate that the marketing literature features four strands about the uses of storytelling to influence consumers' purchasing behavior. First, storytelling stimulates the consumer's identification with the brand. Second, storytelling allows consumers to experience emotional value. Third, storytelling supports engagement behaviors. Finally, storytelling has a downside in that it also propagates harmful speech. This study concludes with a roadmap for future research about how storytelling impacts consumers' purchasing behavior.
Allergenicity and IgE Recognition of New Dau c 1 Allergens from Carrot
Authors: Hendrich Julian M. , Wangorsch Andrea , Rödel Katharina , Jacob Thessa , Mahler Vera , Wöhrl Birgitta M. 
Published: December 2022

ScopeCarrot (Daucus carota) allergy is caused by the major carrot allergen Dau c 1, which is a mixture of several isoallergens and variants with sequence identities of >67% or >90%, respectively. However, little is known about the qualitative and quantitative composition of natural Dau c 1.Methods and resultsMass spectrometry of isolated natural Dau c 1 reveals the existence of several yet unknown Dau c 1‐like proteins. The study expresses four Dau c 1‐like proteins in Escherichia coli. Two of the purified proteins, designated Dau c 1.0501 and 1.0601, exhibit sequence identities to Dau c 1.0101 and 1.0401 between 54% and 87%. They possess allergenic potential and are accepted as new isoallergens. One protein, designated as Dau c 1‐like is >50% identical with the new isoallergens but exhibits no allergenicity. Sequence and structural comparisons of this protein with the known Dau c 1 isoallergens offer relevant clues about putative structural IgE epitopes.ConclusionIdentification of new isoallergens and the identification of IgE epitopes may contribute to a more refined component resolved diagnosis and may lay ground for further epitope mapping and personalized targeted treatment approaches of carrot allergy in preclinical and clinical studies.
Mild and Rapid Light‐Driven Suzuki‐Miyaura Reactions Catalyzed by AuPd Nanoparticles in Water at Room Temperature
Authors: Nazar de Souza Ana Paula , de Souza Tomaso Luiz Phelipe , S. da Silva Vitor Alexandre , S. da Silva Gabriel Francisco , Santos Evelyn C. S. , de S. Baêta Eustáquio , Brant de Campos José , Carvalho Nakédia M. F. , Malta Luiz Fernando B. , Senra Jaqueline D. 
Published: December 2022

AbstractOrganic reactions carried out in water under mild conditions are state‐of‐the‐art in terms of environmentally benign chemical processes. In this direction, plasmonic catalysis can aid in accomplishing such tasks. In the present work, cyclodextrin‐mediated AuPd bimetallic nanoparticles (NPs) were applied in room‐temperature aqueous Suzuki‐Miyaura reactions aiming at preparing biaryl products based on fluorene, isatin, benzimidazole and resorcinol, with yields of 77 % up to 95 %. AuPd NPs were revealed to be a physical mixture of Au and Pd particles circa 20 and 2 nm, respectively, through X‐ray diffraction, dynamic light scattering, UV‐Vis spectroscopy and transmission electron microscopy analyses.
Craft a job better, recover better? The roles of work–nonwork conflict and work demands
Authors: Shi Yanwei , Su Jingxuan , Zhang Nan , Ma Hongyu 
Published: December 2022

AbstractBased on the conservation of resources theory, this two‐wave study investigated the mediating role of work–nonwork conflict in the relationship between job crafting and employee recovery experience and examined the moderating role of work demands in this relationship. Participants were 486 employees (39.3% male and 60.7% female) from a medical company in the central region of China who responded to a paper‐and‐pencil survey twice with a 1‐month interval. Regression‐based results indicated that job crafting positively predicted recovery experience after work through lower work–nonwork conflict. Furthermore, the association between job crafting and work–nonwork conflict was moderated by work demands, such that the effect was stronger for employees with higher work demands. The present study explains how job crafting may improve employees' after‐work recovery experience and addresses whether this process could be more significant for employees with higher work demands. The conclusion has practical implications for improving employee recovery experience.
Reduced neural tracking of speech linguistic structures in children
Authors: Kong Lingzhi , Wang Mengying , Wu Danni , Lu Lingxi 
Published: December 2022

AbstractThe adult brain can efficiently track both lower‐level (i.e., syllable) and higher‐level (i.e., phrase) linguistic structures to comprehend speech. When children actively or passively listened to speech, we found robust neural tracking of syllabic structure but marginally significant tracking of phrasal structure.
Response surface optimization and finite element homogenization study of the effective elastic modulus and electrical conductivity of MXene‐polypyrrole hybrid nanocomposite as electrode material for electronic energy storage devices
Authors: Ezika Anthony Chidi , Sadiku Emmanuel Rotimi , Adekoya Gbolahan Joseph , Hamam Yskandar , Sinha Ray Suprakas 
Published: December 2022

AbstractElectrical energy storage devices are crucial for energy storage and distribution purposes. MXene (MX), a 2D material, and conductive organic polymers, such as polypyrrole (PPy), have been widely used as electrode material in electronic energy storage devices. This work calculated the elastic modulus and the electrical conductivity of a MX/PPy nanocomposite electrode using a finite element model. Response Surface Methodology (RSM) was used to optimize the electrical conductivity and elastic modulus response variables based on the finite element (FE) simulation findings. By assigning appropriate weights to these response factors in the optimization technique, the impacts of mass fraction and aspect ratio (AR) of MX inclusion on the electrical conductivity values and elastic modulus of the electrode were analyzed. When compared to the experimental findings, the results demonstrated that the suggested finite element model could provide a satisfactory estimate of the electrical conductivity and elastic modulus of the electrodes made of MX and PPy. However, these response variables might be optimized by using the response surface approach. Therefore, when RSM was employed, both electrical conductivity and Youngs modulus could be adjusted to close to their respective maximum optimal values, with a predicted electrical conductivity of 474.33 S/m and an elastic modulus of 3.24 GPa, at 50% mass fraction of the MX and the AR of 0.2. Based on these results, if a MX/PPy nanocomposite electrode could be built to achieve this modulus and electrical conductivity, such electrode would be a viable material for metal‐ion batteries.
Children in poverty: Time for action to address rising inequalities in the United Kingdom
Authors: Hayre Jatinder , Pollock Allyson M. 
Published: December 2022

AbstractChildren have been disproportionately affected by the response to COVID‐19 despite having a negligible risk of morbidity and mortality. Moreover, the response to COVID‐19 has magnified the inequalities generated by the decade‐long austerity regime imposed by the coalition, and current government. The numbers of children living in poverty are rising: some 30% of children, amounting to over four million children, are living in relative poverty in the United Kingdom. Poverty will deepen due to rising levels of unemployment, and with 25% of private sector workers experiencing a reduction in hours, this will disproportionately affect families with young children. The stage is set for deepening and more entrenched inequalities, superimposed on the pre‐existing inequalities of austerity. A comprehensive and radical set of policies is needed to address this and will require full government commitment at the highest level.