This study aimed to assess the moderating effect of emotional intelligence (EI) in the direct impact of the stress generated by the pandemic on work performance and counterproductive work behaviors (CWB) in a multioccupational sample of 1048 professionals (60.7% women). The participants filled the Wong and Law Emotional Intelligence Scale, the Impact of Event Scale 6 and the Individual Work Performance Questionnaire. The results proved a relationship between Covid stress, performance and EI, which has a moderating effect between the stress and both indicators of performance, even when sociodemographic variables were controlled. In essence, professionals with high levels of EI and low Covid stress showed the highest performance and the lowest CWB when compared to those who presented less emotional capabilities and higher stress. These results confirm the importance of EI in improving the effectiveness of work performance and reinforce the role of EI as a protective variable that can safeguard occupational health.
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http://dx.doi.org/10.1016/j.paid.2021.110986 | DOI Listing |
J Pathol
January 2025
The Institute for Molecular Bioscience, The University of Queensland, St Lucia, Queensland, Australia.
Spatial transcriptomics (ST) offers enormous potential to decipher the biological and pathological heterogeneity in precious archival cancer tissues. Traditionally, these tissues have rarely been used and only examined at a low throughput, most commonly by histopathological staining. ST adds thousands of times as many molecular features to histopathological images, but critical technical issues and limitations require more assessment of how ST performs on fixed archival tissues.
View Article and Find Full Text PDFLangmuir
January 2025
College of Materials Science and Engineering, Sichuan University, Chengdu 610064, China.
Metallic Zn is a promising anode for high-safety, low-cost, and large-scale energy storage systems. However, it is strongly hindered by unstable electrode/electrolyte interface issues, including zinc dendrite, corrosion, passivation, and hydrogen evolution reactions. In this work, an in situ interface protection strategy is established by turning the corrosion/passivation byproducts (zinc hydroxide sulfates, ZHSs) into a stable hybrid protection layer.
View Article and Find Full Text PDFEur Heart J Digit Health
January 2025
Division of Cardiovascular Medicine, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, SE-182 88 Stockholm, Sweden.
Aims: A simplified version of the history, electrocardiogram, age, risk factors, troponin (HEART) score, excluding troponin, has been proposed to rule-out major adverse cardiac events (MACEs). Computerized history taking (CHT) provides a systematic and automated method to obtain information necessary to calculate the HEAR score. We aimed to evaluate the efficacy and diagnostic accuracy of CHT in calculating the HEAR score for predicting MACE.
View Article and Find Full Text PDFMethodsX
June 2025
Department of Computer Engineering, Pimpri Chinchwad College of Engineering, Nigdi, Pune 411044, India.
Recent advancements in artificial intelligence (AI) have increased interest in intelligent transportation systems, particularly autonomous vehicles. Safe navigation in traffic-heavy environments requires accurate road scene segmentation, yet traditional computer vision methods struggle with complex scenarios. This study emphasizes the role of deep learning in improving semantic segmentation using datasets like the Indian Driving Dataset (IDD), which presents unique challenges in chaotic road conditions.
View Article and Find Full Text PDFEur J Obstet Gynecol Reprod Biol X
March 2025
Mother and Newborn Health Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
This review examines the emerging applications of machine learning (ML) and radiomics in the diagnosis and prediction of placenta accreta spectrum (PAS) disorders, addressing a significant challenge in obstetric care. It highlights recent advancements in ML algorithms and radiomic techniques that utilize medical imaging modalities like magnetic resonance imaging (MRI) and ultrasound for effective classification and risk stratification of PAS. The review discusses the efficacy of various deep learning models, such as nnU-Net and DenseNet-PAS, which have demonstrated superior performance over traditional diagnostic methods through high AUC scores.
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