OpenAIRE

Permanent URI for this collectionhttp://hdl.handle.net/10084/89004

Kolekce určená pro sklízení infrastrukturou OpenAIRE; obsahuje otevřeně přístupné publikace, případně další publikace, které jsou výsledkem projektů rámcových programů Evropské komise (7. RP, H2020, Horizon Europe).

Browse

Now showing 1 - 20 out of 5435 results

The impact of remote work on employee engagement: a case study of public sector employees in the Czech Republic
(Springer Nature, 2026) Poláková, Gabriela; Mokrá, Kateřina; Horváthová, Petra
During the covid-19 pandemic, many civil servants in the Czech Republic engaged in remote work. Detailed information regarding the influence of remote work on engagement is restricted. The main goal is to determine levels of work engagement among civil servants and compare this before the pandemic and now (May 2022). Engagement and factors associated with remote work and changes in organizational culture were examined among 984 civil servants. Data were collected using the Utrecht Work Engagement Scale-9 questionnaire. The Pearson correlation revealed the magnitude and direction of the relationship between the pre-pandemic engagement and current engagement. The paired t-test verified if engagement increased in the covid-19 pandemic. The independent t-test verified if engagement differs significantly between women and men. The one-way ANOVA was used to reveal if remote work reduces engagement significantly and checked engagement between respondents in different age categories. The findings indicate that remote work holds significance and the challenging time of the covid-19 pandemic does not necessarily mean a drop in employee engagement. The practical suggestion derived from this study for employers in the civil service sector in the Czech Republic, in the event of a similar future situation, is to adopt a hybrid model that preserves employee engagement without compromising it.
Bridging tradition and innovation: generational dynamics in family business succession
(Springer Nature, 2026) Subhani, Muhammad Kamal; Mikušová, Marie; Nierostek, Lech
This study explores intergenerational challenges in family businesses, focusing on differences between Generation X and Generation Y regarding socioemotional wealth, innovation, social media, technology adoption, and succession planning. The research aims to identify generational differences in perceptions and behaviors that affect family legacy preservation and succession processes. A qualitative design was used, combining literature review with 18 semi-structured interviews of GenX and GenY owners of small and medium-sized family firms. Thematic and cluster analyses were applied to identify patterns across generations. Findings reveal a clear generational divide. These tensions impact on maintaining the family legacy. The results show that even for companies that have already experienced the changeover at least twice, there remains a generational gap in the approach to modernization. It can be argued that the approach to change exhibited by the next generation is not different from that of previous generations. Insights can guide family firms in balancing tradition with innovation through intergenerational dialogue, structured succession planning, and embracing technology.
Enhancing the mechanical performance of laser powder bed fusion prepared 316L stainless steel by deformation post-processing at ambient temperature
(MDPI, 2026) Kocich, Radim; Kunčická, Lenka
Preparation of metallic materials via laser powder bed fusion has gained high popularity primarily due to the versatility of the processed materials and the complexity of the available component geometries. However, the prepared components feature characteristic shortcomings. Among the ways to successfully reduce/eliminate printing issues and homogenize the properties within additively prepared materials is optimized post-processing. In this study, we present the positive effects of deformation post-processing at ambient (room) temperature on the microstructure and mechanical properties of AISI 316L stainless steel prepared by laser powder bed fusion. The post-processing was performed by the industrially applicable method of rotary swaging, for which varying swaging degrees were applied. The selected swaging degree influenced primarily the interactions between the dynamic strengthening and softening processes and consequently the strength/plasticity ratio, although all the applied swaging degrees successfully eliminated the residual porosity and imparted (sub)structure development and grain refinement. The ultimate tensile strength (UTS) for the original workpiece was 282 MPa, and it increased up to more than 1400 MPa after the final swaging while maintaining favorable plasticity (elongation to failure over 30%). The study thus proposes a way to successfully enhance the performance of additively manufactured AISI 316L steel with the use of a commercially applicable plastic deformation technology.
Reverse auction as purchasing tool: Literature review and research agenda
(University of Warsaw, 2025) Urminský, Jaroslav; Zajarošová, Markéta
Purpose: The study aims to organize and analyse the fragmented knowledge base on reverse auctions that has emerged across multiple disciplines due to global digitization. It seeks to identify key research themes, methodologies, and trends in both private and public sector applications. Design/methodology/approach: A systematic literature review was conducted covering two decades of research indexed in the Web of Science and Scopus databases. Hundreds of articles addressing diverse aspects of reverse auctions were examined and categorized through network and content analysis to uncover thematic clusters and methodological tendencies. Findings: The analysis indicates a growing academic interest in reverse auctions within three main research areas: Computer Science, Engineering, and Business/Economics. In business-oriented studies, analytical, mathematical, theoretical, and conceptual methods dominate, often employing experiments, simulations, and comparative analyses. Four major thematic clusters were identified: Sustainability context, Decision-making support tools, Multi-attribute reverse auction design, and Insiders' view. Additionally, five promising directions for future research were proposed. Research limitations/implications: The study is limited to literature indexed in the Web of Science and Scopus databases and focuses primarily on English-language publications. Future research may broaden this scope by including regional or non-English studies and expanding to emerging digital auction platforms. Practical implications: The findings provide guidance for practitioners and policymakers interested in optimizing reverse auction design, integrating sustainability criteria, and improving decision-support mechanisms in procurement and supply chain management. Originality/value: This paper offers the comprehensive, multidisciplinary mapping of reverse auction research over two decades. By synthesizing diverse academic perspectives and identifying key themes, it provides a structured foundation for advancing both theoretical and practical understanding of reverse auctions.
Synergistic light-thermal-mass engineering of metal-coordinated covalent organic framework membranes for water purification
(Wiley, 2026) Sheng, Kai; Xiao, Zijie; Meng, Jiakun; Tian, Miaomiao; Cao, Xueli; Hou, Jingwei; Sun, Shi-Peng; Zhang, Yatao; Zhu, Junyong; Van der Bruggen, Bart
Membrane-based photothermal evaporation and separation offer a sustainable solution for both clean water access and environmental remediation. Covalent organic framework (COF) membranes are highly attractive due to their ordered porosity and chemical tunability, yet efficient light-to-heat-to-mass conversion at the interface remains challenging. Here we present a synergistic light-thermal-mass engineering strategy to overcome this limitation by utilizing cation-coordinated COF membranes. Through interfacial polymerization, we synthesized a photothermal COF with abundant nitrogen and oxygen chelating sites, followed by coordination with various divalent cations. Experimental and simulation results reveal that atomic dispersion of Co centers within a COF layer facilitates steeper interfacial gradients under one-sun irradiation, driving intensified buoyant convection to enhance mass transport and evaporation. The representative cobalt-COF (Co-COF) membrane achieves an extraordinary 99.996% ion removal, which meets stringent WHO standards. Complementary frontier molecular orbital analysis indicates substantial shifts in the HOMO and LUMO energy levels, resulting in a pronounced near-infrared redshift of the optical absorption edge. This substantially increases the photon budget for highly efficient photothermal and photocatalytic processes, conferring a high removal efficiency of volatile organic contaminants. This work underscores how precise metal ion coordination within COF structures significantly boosts both photothermal and photocatalytic efficiencies for sustainable water treatment.
Time-domain geoelectrical modeling and experimental validation of Ground Potential Rise in multilayer soil structures during fault events
(Wiley, 2026) Mbasso, Wulfran Fendzi; Harrison, Ambe; Dagal, Idriss; Mahmoud, Mohamed Metwally; Tsobze, Kenfack Saatong; Jangir, Pradeep; Shaikh, Muhammad Suhail; Smerat, Aseel
Accurate characterization of subsurface electrical behavior during high-energy fault events is critical for both geotechnical safety assessment and the protection of power infrastructure. This study presents a geophysically driven, time-domain modeling framework for Ground Potential Rise (GPR) in multilayer and anisotropic soils, integrating electromagnetic field theory with physics-informed arc resistance modeling. The methodology employs apparent resistivity profiling and soil impedance mapping, enabling high-resolution simulation of current density and voltage gradients under realistic subsurface conditions. A coupled numerical-experimental approach is implemented: finite-element simulations incorporating layered earth resistivity are calibrated against controlled fault injection tests using scaled grounding grids in stratified soil. The model achieves an average deviation of less than 4.7% from measured GPR and step/touch voltages, demonstrating strong predictive reliability. Results reveal that conventional steady-state and homogeneous soil assumptions can underestimate hazardous step voltages by up to 63% and misrepresent the spatial extent of GPR zones by more than a factor of two. Comparative analyses show that optimized grounding grids reduce surface current densities by over 90% compared to isolated systems, significantly enhancing compliance with safety thresholds. Beyond its immediate application to substation and renewable energy grounding, the framework offers a transferable geoelectrical tool for infrastructure risk mapping, lightning hazard assessment, and geotechnical site evaluations in complex soil environments.
Enhanced PID controller tuning for nonlinear continuous stirred-tank heaters using a modified Newton-Raphson optimizer with random opposition and Lévy-flight learning
(Springer Nature, 2025) Rizk-Allah, Rizk M.; Ekinci, Serdar; Jabari, Mostafa; Izci, Davut; Bajaj, Mohit; Blažek, Vojtěch; Rubanenko, Olena
Accurate temperature regulation in continuous stirred-tank heater (CSTH) systems is vital in chemical and thermal process industries, where deviations can cause energy inefficiencies, product quality degradation, or even safety hazards. However, CSTH systems pose a formidable control challenge due to inherent nonlinearities, parameter uncertainties, and susceptibility to external disturbances. Conventional proportional-integral-derivative (PID) tuning methods often struggle to handle these complexities, resulting in sluggish responses or instability. This study introduces a modified Newton-Raphson-based optimization (mNRBO), for optimal PID tuning tailored to nonlinear CSTH environments. The mNRBO framework integrates two key innovations: random opposition learning, to enhance population diversity and prevent premature convergence, and L & eacute;vy-flight-based guided learning, to improve global exploration and escape local optima. These mechanisms are systematically embedded into the Newton-Raphson-based optimizer (NRBO) to achieve a robust exploration-exploitation balance. A CSTH dynamic model is formulated using mass and energy conservation principles, and a multi-objective cost function evaluates rise time, settling time, overshoot, and steady-state error under realistic process constraints. Simulation studies compare mNRBO with NRBO, hippopotamus optimization, golden eagle optimizer, and slime mould algorithm. Results show that mNRBO achieves the lowest cost function value 53.29, smooth convergence with standard deviation 0.90, and superior closed-loop performance with rise time 62.05 s, settling time 206.88 s, overshoot 1.41%, and steady-state error 0.006%. These findings confirm that mNRBO delivers high-precision, disturbance-resilient control and is a promising solution for industrial thermal processes requiring reliability, efficiency, and precision.
Design and development of a flexural spindle mechanism enabled in micro drilling machine tool within a PLM environment
(Frontiers Media S.A., 2026) Shinde, Sachin Manohar; Solanke, Sachin; Diwan, Mohit; Bhole, Kiran S.; Salunkhe, Sachin; Čep, Robert; Nasr, Emad Abouel
The advent of designing flexural systems was to provide accurate micro and nano displacement between the assembly members of the mechanism. Applications that used these mechanisms included linear compressors, optomechanical devices, Stirling engines, cryocoolers, microcheck valves, Flexure-based Electromagnetic Linear actuators, and so on. This paper focuses on the machine-tool fabrication of a novel flexural mechanism encased within the spindle head of the microdrilling head. The mechanism cushioned the micro drill and protected it from permanent damage when encountering undeclared resistance in the material matrix. Furthermore, this paper focuses solely on building a 3-axis drilling machine tool in a Product Lifecycle Management environment. The study follows a systematized approach for validating the machine tool design, starting with the hierarchical assembly of components using various kinematic chains. The next phase involves assigning the necessary motions to these components. The final stage utilizes a virtual controller and post-processor to simulate and control machine tool movements. Validation is then performed on the simulated workpiece to ensure design accuracy and functionality. The key findings of the studies indicate that the designed mechanism can move in and out and can also puncture micro-holes in metal. This is the mechanism's capability, which is the novelty.
Peroneal electric transcutaneous neuromodulation versus solifenacin in the treatment of the overactive bladder wet
(Polish Urological Association, 2025) Krhut, Jan; Rejchrt, Michal; Slovák, Martin; Peter, Lukáš; Zvara, Peter
Introduction Peroneal electrical Transcutaneous NeuroModulation (peroneal eTNM (R)) is a non-invasive treatment for overactive bladder (OAB). In the previous randomized study in female patients with OAB, both dry and wet, peroneal eTNM (R) demonstrated significantly better safety and comparable efficacy to solifenacin. This subgroup analysis aimed to compare the safety and efficacy of peroneal eTNM (R) versus solifenacin in OAB wet population. Material and methods In the primary study, eligible subjects were randomized in a 2 : 1 ratio to receive either 12 weeks of daily peroneal eTNM (R) for 30 minutes or solifenacin 5 mg daily. This subgroup analysis included participants who presented with at least one incontinence episode at baseline and completed the study according to protocol. The primary endpoint was safety, secondary endpoint was proportion of continent subjects after treatment. Additional efficacy assessments included change in bladder diary variables, OAB V8 score, and quality of life (QoL). Results In the peroneal eTNM (R) group (n = 26), three treatment-related adverse events (TRAEs) were recorded, while nine TRAEs occured in the solifenacin group (n = 16). The proportion of patients who achieved continence after 4, 8 and 12 weeks of treatment was 50%, 62%, and 65% in the peroneal eTNM (R) and 56%, 50%, and 56% in the solifenacin group, respectively. Both treatments led to significant and similar improvements in all bladder diary variables, OAB V8 score, and QoL. Conclusions The results of this secondary analysis confirm that peroneal eTNM (R) has significantly better safety profile and comparable efficacy versus solifenacin in the subgroup of incontinent OAB patients.
Nanomaterial-based inkjet printing for electrochemical sensing
(Wiley, 2026) Panáček, David; Urban, Massimo; Silvestri, Alessandro; Dědek, Ivan; Nalepa, Martin-Alex; Merkoçi, Arben; Prato, Maurizio; Otyepka, Michal
Inkjet printing (IJP) has emerged as a transformative technology for printed and flexible electronics, redefining electrode engineering for (bio)chemical sensing. It enables maskless, picoliter-scale, additive deposition with high spatial precision, uniformity, and material efficiency. We provide a comprehensive overview of IJP as both a fabrication and post-fabrication functionalization platform for electrochemical working electrodes and fully printed devices. We integrate advances in ink formulation, jetting behavior, and substrate interactions with performance metrics such as layer thickness, roughness, electrochemical surface area, sensitivity, detection limit, and reproducibility. Comparative analyses with drop-casting and screen-printing highlight IJP's advantages in reproducibility, scalability, and material economy. Particular emphasis is placed on nanomaterial- and bioink-based systems, including carbon nanomaterials, MXenes, and hybrid inks, where controlled deposition governs electrode functionality. We also discuss emerging opportunities in hybrid architectures, reactive printing, and sustainable approaches using biodegradable substrates and water-based inks. Finally, we outline a roadmap toward automated, digitally controlled, and environmentally responsible manufacturing of customizable sensors for wearable, biomedical, food, and environmental applications. Collectively, these developments position inkjet printing as an enabling framework for the next generation of intelligent, reproducible, and sustainable sensing technologies.
Comprehensive experimental performance investigation of conducted electromagnetic interference in split-phase induction motors: Common-mode
(Sage Publications, 2026) Miloudi, Mohamed; Miloudi, Houcine; Ardjoun, Sid Ahmed El Mehdi; Elzein, I. M.; Mahmoud, Mohamed Metwally; Mbasso, Wulfran Fendzi; Hussein, Hany S.; Ewais, Ahmed M.
Motors in Adjustable Speed Drive (ASD) systems are the major sources of conducted Electromagnetic Interference (EMI), and they are mainly the Common-Mode (CM) currents and voltages. Compliance with Electromagnetic Compatibility (EMC) standards is of utmost importance when maintaining system reliability in the face of ever-stricter Electromagnetic Compatibility standards in the industrial sectors. This work presents the first systematic experimental evaluation of CM impedance in Split Phase Induction Motors (SPIMs) in a wide frequency range (100 Hz to 100 MHz). Unlike prior studies that were limited to either a differential-mode analysis or limited frequencies in the experiment, the study provides comprehensive CM impedance data of two different SPIM setups, explaining resonance and anti-resonance behaviors that have direct implications on EMC performance. It is experimentally proven that high impedance designed motors significantly reduce CM current transfer, thus reducing EMI emissions and enhance EMC compliance. Particularly, the impedance peak of SPIM (I) was 8k at 100 MHz that translated to a 45% decrease in CM current and -15 dB attenuation of conducted EMI compared to SPIM (II). The resonance and anti-resonance frequencies determined the influence of motor architecture on its susceptibility to EMI. As a result, the findings provide prescriptive design information to the optimization of SPIMs in applications, for example, industrial automation and electric vehicle platforms, where very high EMI mitigation levels are of crucial importance.
Exploring the hepatoprotective and cytotoxic activities of Thalictrum foliolosum and Cordia dichotoma for targeting acute liver injury
(Elsevier, 2026) Raghuvanshi, Disha; Raghuvanshi, Komal; Kumar, Sunil; Thakur, Mehak; Kumar, Deepak; Khan, Azhar; Kumar, Dinesh; Verma, Rachna; Farshori, Nida N.; Al-Sheddi, Ebtesam S.; Al-Oqail, Mai M.; Malik, Tabarak
Liver diseases remain a significant global health burden despite advancements in hepatology. Plant-based therapies offer promising hepatoprotective potential, highlighting the need to evaluate medicinal plants with therapeutic activity. Therefore, the present study aims to evaluate the methanolic extracts of the root and leaves of Thalictrum foliolosum and the leaves of Cordia dichotoma for antibacterial, anti-inflammatory, cytotoxic, and hepatoprotective effects. Antimicrobial analysis revealed that T. foliolosum leaves extract showed maximum inhibition against E. coli (19.0 f 1.0 mm) and the root extract against S. typhi (22.0 f 1.0 mm), while C. dichotoma leaves extract against Bacillus sp. (17.3 f 1.5 mm). Anti-inflammatory analysis showed that at 300 mu g/mL, C. dichotoma leaves exhibited 48.10 f 0.34 % inhibition, while T. foliolosum root and leaves extracts showed 46.35 f 0.90 % and 44.77 f 1.49 % inhibition, respectively. Furthermore, both extracts exhibited dosedependent cytotoxicity toward HepG2 cells, with T. foliolosum root and C. dichotoma leaf extracts showing CTC50 values of 110.7 and 250.7 mu g/mL, respectively. In-vivo studies showed that both the extracts significantly restored liver biomarkers in CCl4-induced hepatotoxicity in Wistar albino rats. T. foliolosum roots extract (200 mg/kg) reduced total bilirubin to 0.33 f 0.06 mg%, conjugated bilirubin to 0.05 f 0.02 mg%, serum glutamate oxaloacetate transaminase (SGOT) to 120.50 f 12.02 IU/L, serum glutamate pyruvate transaminase (SGPT) to 52.00 f 16.97 IU/L, and alkaline phosphate (ALP) to 205.50 f 27.58 IU/L, while restoring total protein (5.70 f 0.14 g%) and albumin (3.30 f 0.14 g%). Similarly, C. dichotoma leaves extract (200 mg/kg) lowered total bilirubin to 0.34 f 0.03 mg%, conjugated bilirubin to 0.06 f 0.03 mg%, SGOT to 122.00 f 2.83 IU/L, SGPT to 44.50 f 3.54 IU/L, and ALP to 185.00 f 29.70 IU/L, with improved total protein (5.60 f 0.57 g%) and albumin (3.30 f 0.14 g%). Molecular docking further supported the bioactivity of the extracts. Senecionine showed good affinity for the antibacterial target 4KR4 (-7.6 kcal/mol), while rutin exhibited the strongest binding to the antiinflammatory (5IKR, -8.5 kcal/mol) and hepatoprotective (3SU4, -7.7 kcal/mol) targets. Overall, these findings revealed that C. dichotoma leaf extract exhibits stronger hepatoprotective activity than T. foliolosum root extract, supporting its further investigation in future studies.
Frozen slab method mediated sulfur-affinitive single-atom catalysts for efficient reversible sodium storage
(Royal Society of Chemistry, 2026) Cui, Kai; Qi, Zijia; Legut, Dominik; Zhao, Wanxiang; Chen, Biao; Wu, Ningning; Zhang, Qiuyu; Wang, Tianshuai
Carbon-supported single-atom catalysts (C-SAMs) have recently emerged as a frontier strategy to address the issue of irreversible reactions in MoS2-based sodium-ion batteries. However, conventional C-SAMs designed solely considering the d-p orbital coupling theory often yield distorted adsorption energy predictions for Na2S, as it overlooks the roles of Na-N bond interactions and structural deformation. Herein, we introduce the frozen slab method to evaluate the influence of C-SAMs' affinities toward Na and S on Na2S adsorption. Based on their relative adsorption strengths, C-SAMs are classified into three categories: S-affinitive, amphiphilic, and Na-affinitive. Theoretical calculations reveal that S-affinitive C-SAMs strongly adsorb S atoms, thereby weakening the Na-S bond in Na2S and facilitating bond cleavage during charging. This reduces the decomposition energy barrier of Na2S and enhances the reversibility of the conversion reaction. Experimental results confirm that S-affinitive C-SAV can accelerate Na+ storage kinetics in MoS2, enabling highly efficient reversible conversion during charging. As a result, after 1000 cycles at a high current density of 5 A g-1, the MoS2/C-SAV electrode exhibits a specific capacity of 332.8 mAh g-1, with a capacity retention rate as high as 98.87% and an average capacity decay of only 0.001% per cycle.
Design of novel exponential PDN controller via quadratic interpolation optimiser for nonlinear and unstable ball and beam system
(Wiley, 2026) Izci, Davut; Ekinci, Serdar; Çelik, Emre; Uyar, Murat; Bajaj, Mohit; Blažek, Vojtěch; Rubanenko, Olena
This study presents a novel exponential proportional-derivative controller with filter (exp-PDN) for stabilising the nonlinear and underactuated ball and beam system. Unlike conventional PID-based approaches, the proposed controller removes the integral term, resulting in faster transient responses and improved robustness. It incorporates nonlinear exponential shaping of both the error and its derivative, along with a filtered derivative path for enhanced noise handling. A custom multi-objective cost function, comprising the squared error, settling time, and percent overshoot, is proposed to evaluate control performance. The quadratic interpolation optimiser (QIO), a recently developed metaheuristic based on analytical interpolation, is employed to optimise the controller parameters. To validate its effectiveness, the exp-PDN controller is compared against five state-of-the-art metaheuristic algorithms: QIO, spider wasp optimiser, komodo mlipir algorithm, golden eagle optimiser, and slime mould algorithm. The QIO-optimised exp-PDN achieves the best performance, with the lowest cost value (0.3211), minimal overshoot (5.52%), fast rise time (0.97 s), and smallest steady-state error (4.1643 x 10- 4). Further comparisons with QIO-optimised phase-lead and PID-with-filter controllers demonstrate the superiority of the proposed method in both transient and steady-state behaviour. In summary, this work advances the control of nonlinear unstable systems by delivering a structurally simple yet highly responsive control architecture. The combination of dual-channel exponential shaping and efficient metaheuristic optimisation results in state-of-the-art closed-loop performance, highlighting the practical value of the proposed exp-PDN framework for real-world control applications.
Lunar regolith simulant-based triboelectric nanogenerators: Toward sustainable energy harvesting from resources on the moon
(Elsevier, 2026) Yohannan, Alex; Vaghasiya, Jayraj V.; Sonigara, Keval K.; Pumera, Martin
The exploration of extraterrestrial materials for energy harvesting, generation and storage is important for futuristic material evolution and use. Thus, study and use of extraterrestrial materials simulants becomes straightforward way to identify potential of those materials. Such as Lunar Regolith Simulants are tested as reference material to explore suitability for construction, solar cell components and beyond. However, aiming futuristic space exploration, on-site energy generator development from Lunar regolith materials is unexplored and necessary to unveil it. In this work, we introduce a lightweight, flexible triboelectric nanogenerator (TENG) that uses lunar regolith simulant particles (LRPs) embedded in polydimethoxysilane (PDMS) to harvest mechanical energy as first proof-of-concept. Under cyclic contact-separation, the optimized device containing 30 wt % of <= 45 mu m LRPs yields an open-circuit voltage V-oc of similar to 10.5 V, a short-circuit current I-sc of similar to 2.2 mu A, and a peak power density reached its maximum at 3.0 mu W cm(-)(2) under a force of 2.5 N at 10 Hz. Systematic optimization of grain size and weight fraction of LRPs in PDMS film is analyzed and resulted in the voltage output of 1.6 times and current density by 2.1 times compared to the bare PDMS material. Furthermore, the device shows 95 % performance retention of its output after 36,000 operation cycles, underscoring its good stability and potential for sustainable energy harvesting in ambient environments. These results demonstrate that utilizing extraterrestrial fillers, such as LRPs, is a useful approach for enhancing TENG performance in future terrestrial settings, offering insight for future space materials employed in composite design for TENG devices.
Fractional analysis for multiple solutions of thermodynamic model of Casson fluid under hydrodynamic and non-hydrodynamic optimization
(Elsevier, 2026) Abro, Shahnila Yaseen; Souayeh, Basma; Flah, Aymen; Hamdi, Monia; Abro, Kashif Ali; Faizan, Muhammad
This study investigates the flow behavior of a non-Newtonian Casson fluid influenced by hydromagnetic and non-hydromagnetic effects over an oscillating plate, subject to combined gradients of temperature and mass concentration. The analysis is framed within the context of linear fractional differential equations incorporating the Caputo-Fabrizio fractional derivative with a non-singular kernel. A mathematical model is developed, employing a linear boundary condition to characterize the temperature distribution, mass concentration, and velocity profiles. The governing equations are first non-dimensionalized and then extended into their fractional forms. An analytical solution is obtained using integral transform techniques, specifically the Laplace transform with its inversion and the Fourier sine transform with inversion. The break down the data analysis process under rheological variation for temperature and concentration is explored through which generalization and comparison is investigated. The key findings are focused on the flow and heat transfer characteristics, examining the influence of key dimensionless parameters. Moreover, the comparison between fractional and classical approaches are found in excellent agreement.
Optimizing feature selection with random reversal and adaptive Gaussian based Dung beetle optimizer for intrusion detection system in IoT
(Springer Nature, 2025) Vurubindi, Padmavathi; Frnda, Jaroslav; Sujatha, Canavoy Narahari; Divakarachari, Parameshachari Bidare; Nijaguna, G. S.; Mahendar, A.
The Internet of Things (IoT) is an emerging, promising technology developed with the objective of establishing global connectivity among devices. IoT is highly susceptible to malicious attacks, owing to its resource-constrained architecture, insecure wireless communication, diverse device ecosystems, and the vast volume of sensor data transmitted over networks. An effective Intrusion Detection System (IDS) is essential to address these security concerns. However, challenges such as irrelevant features and poor class separability complicate its development. This research proposes a novel IDS by introducing an Improved Random Reversal Learning (IRRL) and Dimensional Adaptive Gaussian Variation (DAGV)-based Dung Beetle Optimizer (RGDBO) for optimal feature selection, enhancing exploration, and avoiding premature convergence. For classification, a Convolutional Neural Network (CNN) integrated with CosFace and ArcFace loss functions, termed CACNN, is employed to enhance intrusion classification through more efficient discrimination among classes. The combined RGDBO-CACNN framework is evaluated on three benchmark datasets: UNSW-NB15, NSL-KDD, and CICIDS-2017, using accuracy, recall, precision, and F1-score as performance metrics. A comparative analysis of existing methods, including GA-FR-CNN, GTO-BSA, and BMRF-RF, demonstrates the superiority of the proposed model, with RGDBO-CACNN achieving an accuracy of 99.999% on the UNSW-NB15 dataset.
Design and optimization of localized plasmon resonance sensing via square-slotted Ag-graphene-dielectric metasurfaces for dermatological cancer identification using machine learning
(Springer Nature, 2025) Alsharari, Meshari; Flah, Aymen; Aliqab, Khaled; Pergl, Ivo; Kumar, Abhinav; Armghan, Ammar
Skin cancer is a dangerous, life-threatening illness impacting countless individuals globally, requiring urgent awareness, prevention, and early detection. It is one of the most common forms of cancer, often caused by excessive sun exposure or tanning, and requires early detection for effective treatment. Early detection of skin cancer is achievable through advanced sensor designs that utilize graphene material. Graphene's exceptional properties make it extremely appropriate for creating sensitive, accurate, and non-invasive diagnostic tools to identify cancer at early stages. The integration of silver (Ag), graphene, and silicon dioxide (SiO2) materials forms a highly sensitive multilayer structure, significantly enhancing the surface plasmon resonance response, which enables precise detection of skin cancer biomarkers at extremely low concentrations. An exceptional sensitivity of 1050 nm/RIU is attained, enabling efficient skin cancer detection through advanced plasmonic biosensing technology. Optimizing the biosensor design by systematically varying key physical parameters-such as layer thicknesses, slot dimensions, and material configurations-significantly enhanced its sensitivity. The optimization is also achieved by using a Machine learning algorithm. The highest R2 value of 0.99 is achieved for this research. This strategic tuning of the structural and optical characteristics enabled more accurate detection capabilities, making the sensor highly effective for early skin cancer diagnosis through plasmonic resonance.
Global microplastic contamination in freshwater lakes: Spatial patterns, environmental drivers, and methodological challenges
(Elsevier, 2026) Jachimowicz, Piotr; Babkiewicz, Ewa; Gavlová, Anna; Lang, Jaroslav; Madzielewska, Weronika Irena; Maszczyk, Piotr; Mierzyńska, Karolina; Zieliński, Piotr
Microplastic (MP) pollution in freshwater lakes is an emerging global concern, yet comprehensive assessments remain limited. This review systematically analyzes 84 studies comprising 1268 individual sampling points across over 300 lakes worldwide, selecting only data based on FTIR and Raman spectroscopy to ensure identification reliability. MP concentrations in surface waters ranged from below 0.001 to over 200 MP/L, with the highest levels observed in shallow, lowland, and eutrophic systems. Fibers and fragments dominated MP shapes in both water and sediments, and polyethylene, polypropylene, and polyethylene terephthalate were the most commonly detected polymers, mirroring global plastic production trends. Environmental parameters such as trophic state, shoreline urbanization index and lake morphology were identified as key drivers of MP abundance and characteristics. A clear horizontal gradient was observed, with MP concentrations decreasing from shorelines toward lake centers. However, methodological inconsistencies remain a major obstacle to accurate assessments, including the dominance of surface-only sampling (96.5 % of lakes), limited spatial replication (over 70 % single-point sampling), and the frequent omission of MPs <300 mu m. These shortcomings highlight the urgent need for standardized, multi-depth, and year-round sampling strategies, as well as harmonized size fractionation and validation protocols, to ensure robust and comparable future assessments of MP pollution in freshwater ecosystems.
Shining the dynamics of the Economic Complexity Index on the European Union's climate change strategy: Evidence from the novel approach of MMQR
(Elsevier, 2026) Kömürcüoglu, Ömer Faruk; Kömürcüoglu, Elif Duygu; Koçak, Sinem; Çi̇l, Dilek; Karis, Çiğdem; Güven, Aykut Fatih; Bajaj, Mohit; Blažek, Vojtěch
For the European countries, the issue of combating climate change has become a matter of existence. Therefore, it is of extreme importance to present economic-based evidence for these countries' climate action. One emerging yet underexplored area is the environmental implications of the Economic Complexity Index (ECI), which reflects the knowledge intensity embedded in a country's production structure. Despite its relevance, studies examining the relationship between ECI and environmental degradation (ED) in the European context remain scarce. This paper aims to fill this gap by investigating the impact of ECI on ED between 1995 and 2021, focusing on the European Union countries recognized for their environmental sustainability efforts. For this purpose, the relationship between ECI and two of the pioneer indicators of ED-ecological footprint (EFP) and carbon emissions (CO2)-is assessed through two separate models. To address the dynamic and heterogeneous structure of the relationship, the novel Method of Moments Quantile Regression (MMQR) approach is employed. Empirical evidence suggests that ECI contributes to ED, with a stronger impact observed on CO2 emissions than on EFP. Another key finding is that higher levels of ED limit the negative environmental effects of ECI. However, the robustness of the findings is confirmed using the Driscoll-Kraay (D-K) standard error estimator and also, the symmetric causality test of Dumitrescu-Hurlin (D-H). As global leaders in environmental initiatives, EU countries must guarantee the availability and variety of green financing sources to expedite the transition to sustainable production methods in sectors impacting the ECI index via the European Investment Bank and the EU Innovation Fund. Policymakers can provide favorable tax incentives to industries that implement eco-friendly production methods to lower their expenses, thereby rewarding these industries and fostering acceptance of this strategy among sectors beyond this framework. Achieving higher ECI scores through the integration of renewable energy and green technologies is therefore essential for EU countries striving for a greener and more resilient future.

Browse

Recent Submissions