This study examined the effect of information literacy (IL) on work performance with mediating role of lifelong learning and creativity among journalists in Pakistan. A cross-sectional survey using an online questionnaire was conducted in the press clubs of four provinces (e.g., Punjab, Sindh, Khyber Pakhtunkhwa, and Baluchistan) and the federal capital Islamabad for data collection. The received 1084 responses were analyzed using the partial least squares structural equation modelling. The results indicated that IL of journalists had a direct and indirect but positive influence on their work performance. The lifelong learning and creativity skills also mediated the relationship between IL and work performance. This study provided empirical evidence for how IL directly influence work performance and indirectly with the mediated role of lifelong learning and creativity. These pragmatic insights may inform academicians and enterprises about the IL importance at workplace for enhancement of organizational performance and achieving a competitive advantage. Such results may also initiate an instruction program for existing as well as for prospective journalists to impart IL education. This study could be a worthy contribution to the existing IL research in the workplace context in general and of journalists' workplace in particular as no such study has appeared so far.
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http://dx.doi.org/10.3390/bs13010024 | DOI Listing |
Mater Horiz
January 2025
Institute of Biomass Engineering, Key Laboratory of Energy Plants Resource and Utilization, Ministry of Agriculture and Rural Affairs, South China Agricultural University, Guangzhou, 510642, China.
Conversion of nitrogen (N) to ammonia (NH) is a significant process that occurs in environment and in the field of chemistry, but the traditional NH synthesis method requires high energy and pollutes the environment. In this work, the charge, orbital and spin order of the single-atom Fe loaded on heteroatom (X) doped-MoCS (X = B, N, O, F, P and Se) and its synergistic effect on electrochemical nitrogen reduction reaction (eNRR) were investigated using well-defined density functional theory (DFT) calculations. Results revealed that the X-element modified the charge loss capability of Fe atoms and thereby introduced a net spin through heteroatom doping, resulting in the magnetic moment modulation of Fe.
View Article and Find Full Text PDFFront Public Health
January 2025
Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia.
Introduction: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-invasive methods, which is crucial for managing cardiovascular diseases. This research aims to address the limitations of current healthcare systems, particularly in remote areas, by leveraging deep learning techniques in Smart Health Monitoring (SHM).
View Article and Find Full Text PDFProc (IEEE Conf Multimed Inf Process Retr)
August 2024
Department of Computer Science, University of Kentucky, Lexington, KY, USA.
Despite the prevalence of images and texts in machine learning, tabular data remains widely used across various domains. Existing deep learning models, such as convolutional neural networks and transformers, perform well however demand extensive preprocessing and tuning limiting accessibility and scalability. This work introduces an innovative approach based on a structured state-space model (SSM), MambaTab, for tabular data.
View Article and Find Full Text PDFComput Struct Biotechnol J
December 2024
Department of Computer Science, Virginia Tech, Blacksburg, 24061, VA, USA.
Quality estimation of the predicted interaction interface of protein complex structural models is not only important for complex model evaluation and selection but also useful for protein-protein docking. Despite recent progress fueled by symmetry-aware deep learning architectures and pretrained protein language models (pLMs), existing methods for estimating protein complex quality have yet to fully exploit the collective potentials of these advances for accurate estimation of protein-protein interface. Here we present EquiRank, an improved protein-protein interface quality estimation method by leveraging the strength of a symmetry-aware E(3) equivariant deep graph neural network (EGNN) and integrating pLM embeddings from the pretrained ESM-2 model.
View Article and Find Full Text PDFBrain Spine
December 2024
Department of Neurosurgery, Radboud University Medical Center, Nijmegen, the Netherlands.
Research Question: The goal of this study was to assess the diagnostic accuracy of spinal time-resolved contrast-enhanced MR angiography (4D-MRA) for the detection and localization of spinal dural arteriovenous fistulas (SDAVF) in our institution.
Material And Methods: Single center retrospective cohort study of patients with the clinical suspicion of a SDAVF. Patients were included who had undergone spinal 4D-MRA in the period January 2010-February 2021.
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