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Found 6273 publications
Family-friendly workplaces in the public and private sectors
Publication Name: International Journal of Organizational Analysis
Publication Date: 2026-12-14
Volume: 34
Issue: 12
Page Range: 33-52
Description:
Purpose – The study aimed to examine family-friendly practices of employers in Hungary and compared public and private sector organisations to better understand their approaches to promoting the work–life balance of employees. Design/methodology/approach – A cross-sectional, quantitative survey was carried out between April and June 2023, involving 702 organisations certified as family-friendly workplaces in Hungary, of which 101 managers responded. The data were analysed using descriptive statistics and Pearson’s chi-squared tests to examine associations between sector and the prevalence of family-friendly practices. Findings – The findings indicate sectoral variation in the implementation of family-friendly practices. Private sector organisations more frequently reported flexible working arrangements, whereas public sector employers more often reported traditional measures such as childcare services and child-friendly work environments. Teleworking was available in 87.3% of private organisations, compared with 67.4% of public organisations (p = 0.016). Similarly, part-time work was offered by 87.3% of private organisations and 63.3% of public organisations (p = 0.004). Conversely, on-site childcare (52.2% vs. 21.8%, p = 0.002) and child-friendly workplaces (58.7% vs 23.6%, p < 0.001) were more prevalent in the public sector. Research limitations/implications – The study is geographically limited to Hungary and focuses mainly on certified family-friendly workplaces, which may not represent all organisations uniformly. However, it provides a basis for benchmarking international research on family-friendly workplace policies. In addition, it does not include a qualitative study to provide more in-depth insight or to capture the views of employees, but identifies further research directions in this way. Practical implications – Based on these findings, organisations should consider implementing family-friendly policies that better promote work–life balance. The study recommends that the public sector extend flexible working arrangements and increase family benefits to improve recruitment and retention. Conversely, private sector employers should focus on developing childcare facilities on-site and fostering family-friendly work environments to support their employees’ needs effectively, thereby increasing job satisfaction. Social implications – A better understanding of family-friendly workplace policies can help to raise awareness of the importance of promoting work–life balance. The implementation of these policies has the potential to improve the well-being of employees and contribute to wider societal goals, including gender equality, family stability and the development of a more sustainable society. Originality/value – The study provides a comprehensive analysis of family-friendly workplace policies in the various sectors in Hungary, highlighting sectoral strategies and practical recommendations for better promoting work–life balance and organisational efficiency.
Open Access: Yes
Generative AI and knowledge management in higher education: the impact of human development on student perceptions
Publication Name: Journal of Knowledge Management
Publication Date: 2026-12-14
Volume: 30
Issue: 11
Page Range: 293-318
Description:
Purpose – This study aims to explore how the Human Development Index (HDI) is associated with students’ perceived academic, personal and skill-development outcomes related to the integration of generative artificial intelligence, particularly ChatGPT, into higher education. From a knowledge management perspective, the research examines adaptive use of AI tools, structuring of information and support of autonomous learning in countries with varying development. Design/methodology/approach – The study draws on 11, 910 valid responses from the 2024 Global ChatGPT student survey, covering 58 countries. Based on 33 Likert-scale items, three reflective constructs were identified. To explore the relationships between HDI, usage intensity and perceived impacts, the analysis combined descriptive statistics, K-means clustering and a partial least squares structural equation modeling (PLS-SEM) mediation model. Findings – The regression analysis showed a weak but statistically significant negative correlation between HDI and perceived impacts: students from lower-HDI countries tended to view ChatGPT’s impacts more positively. The PLS-SEM results indicated that higher national development is associated with lower perceived academic, developmental and skill-related benefits. This relationship appears both direct and indirect, as students in more developed countries report using ChatGPT less frequently and less creatively for academic purposes. Practical implications – The findings highlight the need for context-sensitive, pedagogically grounded artificial intelligence strategies, particularly in highly developed countries and in the support of students from disadvantaged backgrounds. Originality/value – This study is among the first to examine how national development levels shape perceived ChatGPT impacts in higher education. By combining HDI, cluster analysis and mediation modeling, it offers a novel perspective on digital inequality.
Open Access: Yes
Ensemble deep learning approach for traffic video analytics in edge computing
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
Video analytics is the new era of computer vision in identifying and classifying objects. Traffic surveillance videos can be analysed to using computer vision to comprehend the road traffic. Monitoring the real-time road traffic is essential to control them. Computer vision helps in identifying the vehicles on the road, but the present techniques either perform the video analysis on the cloud platform or the edge platform. The former introduces more delay in processing while controlling is needed in real-time, the latter is not accurate in estimating the current road traffic. YOLO algorithms are the most notable ones for efficient real-time object detection. To make such object detections feasible in lightweight environments, its tinier version called Tiny YOLO is used. Edge computing is the efficient framework to have its computation done on the edge of the physical layer without the need to move data into the cloud to reduce latency. A novel hybrid model of vehicle detection and classification using Tiny YOLO and YOLOR is constructed at the edge layer. This hybrid model processes the video frames at a higher rate and produces the traffic estimate. The numerical traffic volume is sent to Ensemble Learning in Traffic Video Analytics (ELITVA) which uses F-RNN to make decisions in reducing the traffic flow seamlessly. The experimental results performed on drone dataset captured at road signals show an increase in precision by 13.8%, accuracy by 4.8%, recall by 17.4%, F1 score by 19.9%, and frame rate processing by 12.8% compared to other existing traffic surveillance systems and efficient controlling of road traffic.
Open Access: Yes
Unraveling the Bäcklund Transformation and Interaction Phenomena in Nonlinear Dispersive Media Describing Combined pKP-BKP System in (3+1) Dimensions
Publication Name: Journal of Nonlinear Mathematical Physics
Publication Date: 2026-12-01
Volume: 33
Issue: 1
Page Range: Unknown
Description:
This work studies the exact solutions of the integrable (3+1)-dimensional combined potential Kadomtsev-Petviashvili (pKP) equation with the B-type Kadomtsev-Petviashvili (BKP) equation, which is used to characterize several nonlinear oscillations occurring in hydrodynamics, plasma physics, and nonlinear optics. A bilinear representation of the pKP-BKP model is used to study the properties of different wave solutions. A variety of ansatzes are utilized to derive lump cross-kink waves, lump cross-periodic waves, rogue waves, as well as two, three, and multi-wave solutions pertinent to the model. In addition, a traveling wave transformation is applied to transform the problem into an ordinary differential equation. The new auxiliary equation methodology yields solutions including rational, exponential, hyperbolic, and trigonometric functions. Graphical visualizations using 2D plots, contour plots, and 3D plots show the dynamics of the obtained solutions. These solutions are of great importance in nonlinear fiber optics and telecommunications, which contribute to our understanding of the fundamental physical models.
Open Access: Yes
Molecular characterisation of the invasive terrestrial nemertean Geonemertes pelaensis: long and complex mitogenome and presence of NUMTs
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
The complete mitochondrial genome of the invasive terrestrial nemertean Geonemertes pelaensis Semper, 1863 (Nemertea: Prosorhochmidae) was sequenced from two specimens collected in geographically distant French overseas territories—Martinique in the Caribbean and New Caledonia in the South-West Pacific. In both specimens, the mitogenome contained 13 protein-coding genes, two rRNA genes, and 21 tRNA genes, and was unusually large, approaching 32 kb. The two genomes differed by only four single nucleotide polymorphisms and one indel. A comparison with 22 cox1 sequences available in GenBank confirmed this high level of genetic conservation, suggesting a recent introduction from related source populations. The extraordinary length of the mitogenome was largely attributable to two extended regions comprising only tRNA genes and long intergenic sequences. These results were contrasted with data from an unpublished SRA sequencing project (SRS20559370) of an unlocalized specimen identified as G. pelaensis; its reconstructed mitogenome was only 18 kb in length (14 kb shorter) and showed extensive sequence divergence. Phylogenetic analyses placed this specimen as the sister lineage to G. pelaensis, highlighting the need for further investigation of this taxon. In the Martinique specimen, several NUMTs (nuclear mitochondrial pseudogenes) were also detected, which could complicate future studies relying solely on Sanger sequencing. Sequencing additionally revealed prey DNA from the gut contents of both worms: the New Caledonian specimen had consumed an unidentified noctuid moth, while the Martinique specimen had likely fed on the invasive cockroach Periplaneta australasiae (Fabricius, 1775), itself an introduced species.
Open Access: Yes
Modelling optimal investment planning for household photovoltaic and battery systems under dynamic electricity market conditions
Publication Name: Discover Sustainability
Publication Date: 2026-12-01
Volume: 7
Issue: 1
Page Range: Unknown
Description:
Capacity sizing and calculating cost savings for residential households in a rapidly evolving energy market, influenced by fluctuating electricity prices and changing government incentives, is a highly complex problem. The key challenges stem from multiple interacting factors, including retail electricity prices, the desired payback period, household size, applicable electricity schemes, and the capacity factor of the photovoltaic (PV) system. The nominal power output of the solar energy system is constrained by both the specifications and the number of installed inverters and PV panels. As solar generation is intermittent and non-dispatchable, it is inherently weather-dependent and often unable to align with the dynamic fluctuations in household electricity consumption. From a financial modelling perspective, the length of the accounting period directly determines the time resolution of the model, influencing both the accuracy of cash flow estimation and investment decision-making. The proposed two-level investment planning model is based on the process network synthesis approach. At the upper level of the process model, solar generation technologies, including inverters and solar panels, are technically and economically assessed. At the lower level, which represents the load consumption side, the periodical energy balances for production, storage, demand, and purchase are considered. In order to accurately evaluate the solar energy system, the model is developed with both a monthly framework and a detailed hourly framework. The time resolution allows the model to account for grid intake, electricity sold, and storage inventory conditions over the defined periods, ultimately providing the optimal sizing for a solar system equipped with battery storage. Case studies are conducted to investigate the effects of household size, extended payback periods, varying retail electricity prices, and grid reliability. These scenarios demonstrate the key parameters that significantly influence the economic feasibility and optimal sizing of the solar energy system, which are discussed in detail in this paper.
Open Access: Yes
The effect of mixed fatigue on knee biomechanics and muscle activation during sidestep cutting in elite soccer players
Publication Name: BMC Sports Science Medicine and Rehabilitation
Publication Date: 2026-12-01
Volume: 18
Issue: 1
Page Range: Unknown
Description:
Background: Football is one of the most popular sports in the world, and it is also a sport with a high rate of injury. The study aims to investigate the effects of physical and mental mixed fatigue (PMF) on knee biomechanics during sidestep cutting maneuvers in elite male soccer players, thereby assessing the potential mechanisms underlying non-contact knee injuries. Methods: Thirty-six elite male soccer players were recruited (age: 21.61 ± 1.22 years; body mass: 75.16 ± 6.34 kg; height: 175.8 ± 3.53 cm; shoe size: 41–44 EUR). Following a targeted fatigue induction protocol, key lower limb biomechanical data were acquired during anticipated sidestep cutting maneuvers both pre- and post-PMF. Statistical analyses were performed utilizing paired sample t-tests and one-dimensional Statistical Parametric Mapping (SPM1d). Results: Following PMF, knee valgus increased at initial contact (P = 0.022). Kinetic analysis, supported by SPM1d, revealed a marked transition from an extensor-dominant to a flexor-dominant pattern in sagittal knee moments (P = 0.007), alongside elevated knee valgus moments (P = 0.039). Neuromuscularly, quadriceps and lateral gastrocnemius activation (iEMG/RMS) significantly decreased, whereas compensatory increases were observed in the hamstrings and medial gastrocnemius (all P < 0.001). Conclusion: While PMF preserved most kinematics, the statistically significant increase in knee valgus, though small in magnitude, suggests an impaired frontal-plane control that may elevate Anterior Cruciate Ligament (ACL) strain. The shift from quadriceps to hamstring dominance reflects a compensatory neuromuscular strategy. These findings emphasize the importance of incorporating cognitive load into injury-prevention programs and monitoring mental fatigue to reduce non-contact knee injury risks.
Open Access: Yes
Evaluating blockchain-based waste management investments in smart cities using a multi-criteria decision support framework
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
With growing urbanization, there are increasing demands on waste management systems that can be performed in an environmentally friendly way as well as efficiently. Current approaches to managing waste often have issues with efficiency, transparency, and engaging with the public. Blockchain technology has been identified as one potential solution to these problems because it offers several benefits including decentralization, security, and transparency. The selection of the best blockchain-based waste management (BBWM) system is very difficult due to the many different evaluation criteria that may conflict with each other. Therefore this research uses a multi-criteria decision making (MCDM) approach using CIMAS (Criteria Importance Assessment), for determining weights based upon subjective input, and LOPCOW (Logarithmic Percentage Change-Driven Objective Weighing), for determining weights based upon objective data within the MCDM framework. To rank alternatives effectively, an Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN) technique is applied, ensuring a precise evaluation process. The use of T-Spherical Fuzzy Sets (T-SFS) captures all three (membership, non-membership, hesitation degree) and is used to address the variability that exists when making an expert judgment. Some of the key factors include; Technological Feasibility, Operational Costs, Scalability, Data Security, Regulatory Compliance, Environmental Impact. Based on the evaluation criteria, it appears that the Blockchain Enabled Waste Tracking System is the most appropriate alternative due to its high potential for Transparency, Regulatory Compliance and Fraud Prevention. In addition, this research will provide Policymakers, Urban Planners and Investors with a methodical way of making Data Driven Decisions on BBWM Investments.
Open Access: Yes
Enhancing heat and mass transfer in hybrid nanofluid with gyrotactic microbes and local thermal non equlibrium effects using artificial neural network
Publication Name: Discover Nano
Publication Date: 2026-12-01
Volume: 21
Issue: 1
Page Range: Unknown
Description:
This study analyzes the impact of local thermal non-equilibrium on the bioconvection flow of hybrid nanofluid across a slender extending sheet containing gyrotactic bacteria using artificial neural networks trained using a Bayesian regularization backpropagation approach (ANN-BRS). The effects of magnetic fields, thermal radiation, and Hall current are all things related to fluid flow. The suggested model has particular applicability in microscale drug delivery systems, where gyrotactic microorganisms and hybrid nanofluid can be employed to control nutrition and medication dispersion under non-equilibrium temperature circumstances. It can be used in lab-on-chip and organ-on-chip technologies to improve bio-mixing and accurate heat control. The model also applies to micro-solar collectors and porous micro-heat exchangers, which use hybrid nanoparticles to boost thermal efficiency. It can also be used in bioreactors and biomedical cooling systems, where local thermal non-equilibrium effects and ANN-based prediction allow for precise control of heat, mass, and microbe transfer, resulting in optimal performance. Similarity transformations are used to convert the original nonlinear PDEs into non-dimensional ODEs and the bvp4c program is applied to numerically resolve the resulting boundary-value problem. The training, testing, and validation processes yield the expected outcomes for every scenario based on the chosen data points. Regression analysis, histograms of error, and mean square error (MSE) metrics are employed to assess the ANN-BRS model's outcome. The liquid phase heat thermal profile increases as the interphase heat transfer parameter values rise, while the solid phase thermal profile decreases.
Open Access: Yes
