Browse Items (16481 total)
Sort by:
-
Treatment of Attachment Trauma: Effects of an Online EMDR Couple Protocol on Trauma Symptoms, Conflict Resolution, and Forgiveness
Background: Incidents characterised by betrayal, abandonment, or emotional neglect within a romantic relationship can profoundly impact relational functioning and lead to post-traumatic stress symptoms in both partners. Although in-person therapies, such as Emotionally Focused Couples Therapy and Eye Movement Desensitisation and Reprocessing (EMDR), have shown promise, the feasibility and effectiveness of delivering EMDR online to address attachment trauma remain underexplored. Aims: This study aimed to evaluate the effects of an online EMDR couple protocol in reducing trauma-related symptoms, improving conflict resolution strategies, and increasing willingness to forgive among couples with a history of attachment trauma. Subgroup analysis was carried out based on gender, partner roles (offending and injured), and types of conflict (single incident and complex). A secondary aim was to determine if gains were sustained at a one-month follow-up. Methods: Participants were 34 individuals (17 couples) presenting with attachment trauma, with a subjective unit of disturbance score over 5. Couples received a two-phase online EMDR intervention comprising individual and conjoint sessions. Pre-intervention, post-intervention, and 1-month follow-up measures of post-traumatic stress (Impact of Events Scale), conflict behaviours (Romantic Partner Conflict Scale), and offence-specific forgiveness (Marriage OffenceSpecific Forgiveness Scale) were collected. Repeated measures ANOVAs were used to analyse changes over time, with follow-up t-tests examining gender and role differences. Results: Participants demonstrated significant reductions in intrusion, avoidance, hyperarousal, and overall trauma impact, with improvements largely maintained at 1-month follow-up. Conflict styles, notably compromise and submission, showed statistically significant positive shifts. Forgiveness scores improved through reductions in resentment avoidance. No significant gender, partner role, or type of conflict differences emerged, indicating uniform benefits across subgroups. Conclusion: Findings suggest that an online EMDR couple protocol can effectively alleviate trauma-related distress, enhance constructive conflict resolution, and facilitate forgiveness in couples with attachment trauma. EMDR is equally beneficial for both offending and injured partners, as well as complex and single-incident conflicts. Trial Registration: Trial registered by the Clinical Trial Registry of India (CTRI). Registration Number: CTRI/2023/07/055625, registered on July 25, 2023. https://ctri.nic.in/Clinicaltrials/showallp.php?mid=87803&EncHid=&userName=CTRI/2023/07/055625. 2025 British Association for Counselling and Psychotherapy. -
Diversity of Endophytic Fungi in Plant Species: Traditional vs. High-Throughput Sequencing Approaches
The plant microbiome significantly impacts plant life, with fungi playing a crucial role in shaping interactions and classifications. Advances in cultivation technologies have refined fungal classification, and research highlights the vital connection between endophytic fungi and their plant hosts. The present study employs morphological and phylogenetic techniques, predicting the Internal Transcribed Spacer 2 (ITS2) secondary structure and using next-generation sequencing (NGS) data to detect fungal endophytes in plant leaves via both traditional and conventional approaches. The research area, with its hot semi-arid environment and red and black soils, supports drought-resistant plants like Senna auriculata, Ziziphus mauritiana, and Catunaregam spinosa, known for their medicinal properties. These plants, rich in antioxidants, play a vital role in traditional medicine and highlight the region's rich ethno-botanical heritage. The culture-dependent study on the foliage yielded a total of 17 isolates from S. auriculata and 16 each from both C. spinosa and Z. mauritiana. The most common genera, Alternaria and Nigrospora, account for 18.3% of all isolated endophytic fungi. Three plants were colonized with Nigrospora and Lasiodiplodia, and their morphotypes were determined using ITS2 secondary structure prediction. Recent ecological studies highlight unculturable taxa, or dark taxa, where many species cannot sporulate or be cultured, emphasizing the need for High - Throughput Sequencing (HTS) approaches. The study gathered 68,791 reads from S. auriculata with 101 operational taxonomic units (OTUs), 58,620 from C. spinosa with 219 OTUs, and 66,087 from Z. mauritiana with 193 OTUs, with the majority of OTUs related to Colletotrichum (69%) and a minimum of Myrmaecium (2%). A total of 49 fungal isolates were obtained from traditional methods, whereas 513 fungal OTUs were retrieved through HTS methods, confirming the presence of a highly abundant fungus population in plant samples. The study reveals that using the ITS short amplicon sequencing technique provides distinct insights into endophytic fungal communities in three plant samples. In conclusion, analyzing plant fungal components using a combination of culture-dependent and culture-independent techniques may be a novel strategy. 2025 Wiley-VHCA AG, Zurich, Switzerland. -
Efficient Photocatalytic Degradation of Methylene Blue From Aqueous Solution Using Hybrid Biomass-Derived Nanostructured Carbon-TiO2 Photocatalyst
Industrial dye usage results in substantial wastewater discharge, posing environmental and health hazards. Hence, developing efficient, sustainable, and cost-effective treatment technologies is crucial. Photocatalysis using TiO? has emerged as a promising approach for dye degradation. This study explores the photocatalytic removal of methylene blue (MB), a model dye pollutant, using a composite of biomass-derived carbon nanoparticles (CNPs) and nanosized TiO? under UV light. The CNPs were synthesized via one-step pyrolysis from waste coffee leaves, offering a sustainable carbon source. The resulting CNPs (CL-10) and the TiO?-CNP composite (PC@CL-10) were thoroughly characterized using advanced techniques. Incorporating carbon significantly reduces the band gap of TiO? from ?3.2eV to 2.90eV, enhancing photocatalytic activity. Degradation studies under varying catalyst doses, dye concentrations, and pH levels demonstrate effective MB removal under UV irradiation. Photocatalytic experiments revealed up to 99% degradation of MB under UV light, while tests conducted in the dark showed negligible activity, confirming the light-dependent efficiency. Kinetic analysis indicated that intra-particle diffusion (IPD) governs the dye degradation process. Moreover, recyclability tests over seven cycles showed consistent performance with minimal decline, highlighting the catalyst's stability and reusability. These findings suggest that PC@CL-10 is a highly effective, low-cost photocatalyst with strong potential for large-scale wastewater treatment applications. 2025 The Author(s). Chemistry A European Journal published by Wiley-VCH GmbH. -
Harnessing MOF Derived Frustrated Lewis Pair-CeO2 Nano Catalyst for CO2-Activated Soft Oxidation of Furfural to Furoic Acid
CO2 as a soft oxidant is scarcely explored in literature for furfural oxidation to furoic acid, and where CeO2, capitalizes on the synergistic effect of FLPs for enhanced CO2 reduction and furfural oxidation. This study presents a comparative analysis by the synthesis method to produce hydrothermal and MOF-derived CeO2 nanocatalyst and their effect on the formation of oxygen vacancies and metastable Ce3+ ions. The normalized surface concentration derived from XPS At% and specific surface area effectively quantifies accessible Ce3+ sites and oxygen vacancies, capturing FLP sites. Oxygen vacancies near surface Ce3+ sites (FLPs) critically modulated the catalytic performance, and evidenced by high turnover number (TON). FTIR adsorption study revealed that CO2 forms bidentate carbonate species and furfural, bi-coordination via ?2- (C, O) mode on the catalyst surface. Further active site masking strategy helped to understand and validate the crucial role of FLPs. The Central Composite Design model was utilized to optimize the reaction conditions and obtained high furfural conversion (99%) and furoic acid selectivity (99%). The catalyst was resistant to active site leaching and exhibited excellent stability, recyclability, and robustness. The findings highlight a potential pathway for the catalytic soft oxidation of furfural to furoic acid by CO2 utilization. 2025 Wiley-VCH GmbH. -
Dynamic Carboxylic Acid Arms Enable Proton Shuttling in Iron-Based Hydrogen Catalysis
Devising artificial electrocatalyst with smartly installed proton relay motifs, as present in natural hydrogenase enzyme has long been proved to be an effective strategy. Proton responsive groups properly positioned near the active center act as a proton shuttle site and facilitate H2 generation via an easy hydride/proton coupling step. Herein we investigated a series of Fe (III) complexes of substituted picolinic acid which undergoes reversible dechelation and chelation in presence of acids and base respectively, making free carboxylic acid arms available near the metal center in acid conditions (CF3COOH/HBF4). Investigations on the electrocatalytic activity of these complexes showcased the involvement of these free carboxylic acid arms in electrocatalytic hydrogen evolution reaction (HER). Further, detailed mechanistic analysis reveals sequential two-electron reductions followed by protonation, enabled by pendant carboxylic acid arms, allow the formation of a metal hydride intermediate which facilitates efficient H2 generation. The catalyst showed efficient HER activity achieving maximum turnover frequency (TOFmax) of 10,000 s?1 with faradaic efficiency above 90%. These findings underscore the importance of tailored secondary-sphere interactions in designing efficient, earth-abundant electrocatalysts and these insights could be useful for future design principles of catalyst for several small molecule activation reactions. 2026 Wiley-VCH GmbH. -
High-Performance Ammonia Sensing with Citrus Hystrix-Mediated ZnO Nanoparticles in TFT-Based Devices
We present a sustainable green synthesis approach for zinc oxide nanoparticles (ZnO NPs) utilizing Citrus hystrix leaf extract and their application as an active medium in a thin film transistor (TFT)-based ammonia gas sensor. For the first time, ZnO NPs derived from Citrus hystrix serve as a receptor layer in a thin film transistor (TFT) device, enabling selective ammonia detection at a significantly reduced initiation temperature. The synthesized ZnO NPs, with a wurtzite structure and an average crystallite size of approximately 14 nm, are deposited onto the TFT sensor without the need for an external conducting layer. The sensor demonstrates excellent sensitivity and selectivity, achieving a maximum response of ~85 % at 20 ppm, with a rapid response time of about 10 seconds at room temperature. Notably, the TFT device exhibits an electron mobility of ~10.2 cm2/V ? s and a high on/off ratio (>10?) at room temperature. The sensing mechanism is attributed to the oxidation-reduction interactions between surface-adsorbed oxygen and NH? molecules on the ZnO NPs, which modulate the device's electrical conductivity. This work underscores the importance of eco-friendly fabrication of high-performance, durable devices, addressing contemporary environmental and economic concerns. 2025 Wiley-VCH GmbH. -
Porous Carbon Nanospheres Derived From Caesalpinia Sappan Pods as Novel Antibacterial Agents
The current work shows how catalyst-free carbon nanospheres (CNS) can be produced utilizing straightforward one-step pyrolysis methods employing biowaste Caesalpinia sappan pods as a carbon precursor. The manufactured CNS with a particle size range of 4050 nm that is obtained show a porous nature and contain more than 87% carbon. The synthesized CNS are used as potential antibacterial agents against E. coli and S. aureus by microscopic analysis. By observing the distorted cell envelopes of both E. coli and S. aureus compared with those of untreated cells, it is well understood that CNS, by binding to the outer envelope of cells, renders some changes in the peptidoglycan layer of both Gram-positive and Gram-negative microbes, which in turn restricts their further growth. This study confirms the first report of use of CNS as an effective antibacterial agent. 2025 Wiley-VCH GmbH. -
Effects of Dispersion on Thermal Conductivity and Viscosity in Biomass-Based Nano Systems
Ensuring the long-term stability of nanofluids (NFs) remains a challenge due to nanoparticle aggregation, precipitation, and poor dispersion. Zeta potential (ZP) plays a crucial role in preventing agglomeration and enhancing stability. This study investigates, for the first time, the combined effect of stability and thermal conductivity (TC) enhancement in nanofluids based on biomass-derived carbon nanospheres (CNSs). CNSs synthesized from eight different biowaste sources exhibited ZP values ranging from ?17.0 to ?45.6 mV, influencing dispersion and fluid behavior. These NFs demonstrated exceptional stability for up to 40 days without surfactants and achieved a TC enhancement of up to 111.8%. The research also explores the influence of ZP on TC, dynamic viscosity (V), and thermal diffusivity. The NFs displayed shear-thinning, non-Newtonian behavior, with viscosity values depending on CNS concentration, reaching 0.0000000302 Pas. The effect of pH (312) on stability and TC revealed maximum performance at pH 8, while optimal TC enhancement was achieved at 0.1 wt% CNS concentration. This study bridges the gap between laboratory research and industrial applications, offering sustainable, low-cost, and high-efficiency coolant solutions for the automotive sector. It supports seven Sustainable Development Goals (SDGs) through an innovative waste-to-wealth approach. 2025 Wiley-VCH GmbH. -
Dual-Responsive Excited-State Intramolecular Double-Proton Transfer-Based Optical Probe for Hypochlorite and Picric Acid Detection With Applications in 3D-Printed Indicators, Biosensing, and Theranostics
A dual-mode fluorescent probe incorporating aggregation-induced emission (AIE) activity, named 2-((E)-1-(((E)-4-(diethylamino)-2-hydroxybenzylidene)hydrazineylidene)ethyl)naphthalen-1-ol (DHN), was formulated and synthesized for the selective detection of explosive picric acid (PA) and hypochlorite (OCl?) via suppression of the excited-state intramolecular double-proton transfer (ESIDPT) mechanism. A significant fluorescence quenching of DHN at 535 nm was observed upon interaction with both PA and OCl? with the detection limits at 0.012 ?M and 2.34 ?M as well as high quenching efficiencies (Ksv) of 3.811 104 M?1 and 1.164 104 M?1, respectively. To elucidate the sensing behavior, various spectroscopic techniques were employed. Interestingly, DHN exhibited AIE behavior in high water content, showing a red-shifted emission accompanied by a visible fluorescence change from whitish green to yellow. As a novel application, DHN was incorporated into a 3D-printed polymer system, demonstrating its practical utility in detecting PA and OCl?. Further, for biological relevance, the interaction of DHN with OCl? was explored for its cytotoxicity against MCF-7 breast cancer cells and its imaging capability in physiological media. Therefore, we believe that the present work provides a promising direction for the future development of optical-based detection of hypochlorite and picric acid in liquid as well as solid phases. 2026 Wiley-VCH GmbH. -
Investigating Factors for an Inclusive Workforce for Women in the Logistics and Supply Chain Industry
This study seeks to identify and analyze the major factors that contribute to an inclusive workforce for women in the area of logistics and supply chain. It further addresses the need for gender diversity and inclusivity in a traditionally male-dominated field by adopting a human-centric approach. This study employs a combination of Fuzzy Delphi Method (FDM) and Fuzzy Best Worst Method (FBWM) for methodically identifying and prioritizing factors that influence inclusiveness for women in the logistics and supply chain industry. FDM gathers experts' opinions and achieves a consensus on the identified relevant factors. Subsequently, FBWM is used to analyze the factors, providing a clear priority ranking based on their relative significance. The analysis identified potential factors that are crucial for fostering an inclusive workforce in the logistics and supply chain industry for women. The factors were classified into three main categories: employee growth and culture, inclusive business ecosystems, and accessibility and diversity factors. Based on the global weights, the top three ranked factors are: gender-inclusive supply chain practices, skill development workshops, and supporting women-owned businesses. This study is original in terms of gender inclusiveness in the logistics and supply chain industry. The innovative combination of multiple methods stipulates a robust methodology for identifying and analyzing the factors that impact inclusiveness, offering a novel contribution to the literature and practical applications in this field. 2025 The Author(s). Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd. -
Energy-Efficient Cluster-Based Reliable Routing Using Hybrid Nutcracker and Improved Sand Cat Optimization Algorithm for Extending Network Lifetime in WSNs
In wireless sensor networks (WSNs), sensor nodes are deployed in a target region for sensing environmental physical parameters to attain the objective of reactive decision-making. These sensor nodes necessitate energy for processing and forwarding the sensed data to the base station (BS) for better data delivery in WSNs. Balanced energy utilization in WSNs prevents the problem of hotspot, and dynamic cluster head (CH) selection with reliable route establishment is a vital decision-making approach that helps in optimal path selection with maximized energy conservation. In this paper, a nutcracker and sand cat optimization algorithm (NCSCOA)based multiobjective CH selection and sink node mobility scheme is propounded for enabling rapid and reliable data transmission with reduced energy consumption in heterogeneous WSNs. This NCSCOA handled the problem of hotspot as well as isolated nodes and facilitated loop-free routing with the support of the improved nutcracker optimization algorithm (INCOA) that makes the decision of routing using local and global search optimization processes. It constructed an energy-level matrix (ELM) by deriving the impactful factors of intercluster formation, distance between CH and BS, residual energy (RE), and node density for achieving optimal CH selection and route determination. In specific, improved sand cat optimization algorithm (ISCOA) is used during the intercluster formation phase by discovering the optimized path between source and destination during route establishment. Simulation-based findings of the proposed NCSCOA confirmed its efficacy by improving the mean number of alive nodes by 23.18%, reducing energy consumption and delay by 21.86% and 20.98% compared to benchmarked protocols. 2025 John Wiley & Sons Ltd. -
Improving Signal Coverage in Millimeter-Wave Massive MIMO via Efficient Predefined-Time Adaptive Neural NetworkBased Beam Training
This paper proposes an advanced deep learning framework for efficient beam training in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. To overcome the limitations of conventional beam training approaches such as high overhead, slow adaptation to dynamic environments, and poor scalability, an Improving Signal Coverage in Millimeter Wave Massive MIMO via Efficient Predefined Time Adaptive Neural Network based Beam Training (ISC-MMIMO-EPTANN-BT) model is proposed. The proposed model used deep neural network (DNN) to learn complicated nonlinearities in channel power leakage (CPL) and used an efficient predefined time adaptive neural network (EPTANN) to provide real-time responsiveness and temporal synchronism in beam training. The parameters of the model are also optimized using fire hawk optimization algorithm (FHOA) to get better convergence speed and signal coverage. The proposed technique is executed in MATLAB. The proposed approach attains better performance under successful rate by significantly less beam training overhead and also increases signal coverage based on simulation results. The proposed ISC-MMIMO-EPTANN-BT method attains 26.15%, 21.08%, and 33.75% higher successful rates and 16.32%, 28.94%, and 20.24% lower normalized mean square error compared with existing methods such as deep learning for beam training in millimeter wave massive MIMO schemes (BT-MMIMO-DNN), deep learning for combined feedback and channel prediction in large-scale MIMO systems (CNN-JCS-MMIMO), and triple-refined hybrid-field beam training in mmWave extremely large-scale MIMO (TR-FBT-MIMO), respectively. The ISC-MMIMO-EPTANN-BT technique reduced beam training overhead, enhanced signal coverage, and identified a promising candidate for successful beam training in mmWave massive MIMO schemes. 2025 John Wiley & Sons Ltd. -
Adaptive Hybrid Multi-Objective Evolutionary Algorithm for Wireless Sensor Network Optimization: A Comprehensive Framework Integrating Opposition-Based Learning and Levy Flight Strategies
Wireless sensor networks constitute a foundational technology for ubiquitous monitoring and data acquisition across diverse application domains ranging from environmental surveillance to critical infrastructure management. The operational efficacy and longevity of these networks critically depend on strategic configuration of multiple design parameters including field coverage, sensors per cluster in-charge, sensor out-of-range error, overlaps per cluster in-charge, and network energy consumption. These objectives exhibit inherent trade-offs, rendering the optimization problem a complex multi-objective challenge characterized by conflicting criteria and high-dimensional search spaces. This research presents a novel adaptive hybrid multi-objective evolutionary algorithm that synergistically integrates opposition-based learning for enhanced population diversity and initialization, Levy Flight mutation for effective escape from local optima, and adaptive operator selection for dynamic adjustment of genetic operator probabilities. We conducted exhaustive empirical evaluation comprising independent runs with individuals evolved over multiple generations, benchmarking the proposed algorithm against three state-of-the-art approaches. Performance metrics were computed using global normalization with respect to theoretical problem bounds to ensure measurement validity and cross-algorithm comparability. Statistical analysis including non-parametric rank tests, pairwise comparisons, and effect size quantification confirm the proposed algorithm achieves statistically significant improvements with very large practical significance. The algorithm demonstrates superior convergence characteristics, solution diversity, and Pareto front quality, establishing a robust framework for automated wireless sensor network configuration in resource-constrained environments. 2026 The Author(s). Engineering Reports published by John Wiley & Sons Ltd. -
Air Jet Erosion Behavior of FDM-Printed PLA Composites Reinforced With Steel Powder Fillers
This paper reports the air jet erosion behavior of FDM-printed polylactic acid (PLA) composites reinforced with 5 wt% and 10 wt% steel powder for solving the problem of the development of durable, sustainable, and high-performance materials for engineering applications. Test specimens were fabricated by fused deposition method with uniform dispersion of steel particles based on a twin-screw extrusion and were tested using ASTM G76 air jet erosion with angular Al2O3 particles as erodent at impact angles of 30, 60, and 90. For the material loss, pure PLA showed the maximum material loss, while steel filled composite showed significantly reduced erosion (2.38% and 14.29%, 8.16% and 18.37%, and 16.07% and 26% at 30, 60 and 90, respectively) and showed the durability of the materials and their material effective utilization. The presence of embedded steel particles was verified by SEM and confocal microscopy showing that the embedded steel particles really acted as crack stoppers, diverted the crack propagation, minimized plowing and crater formation, and improved the toughness, thus extended the potential service life and supported resource-efficient engineering solutions. Among all the compositions, the 10 wt% composite showed a better erosion resistance and the smoothest post-erosion surface owing to a higher particle density with efficiency of stress transfer. Overall, steel reinforcement significantly enhanced the erosion resistance, especially in normal impact conditions and confirmed steel-filled PLA as a suitable material for components in harsh erosive environments. 2026 The Author(s). Engineering Reports published by John Wiley & Sons Ltd. -
NiSe2@CdO Nanocomposite: A Next-Generation Electrode for Asymmetric Supercapacitors with Gel Electrolyte
This article investigates the electrochemical performance of NiSe2@CdO nanocomposites synthesized by combining melt-diffusion-synthesized NiSe2 and hydrothermally prepared CdO, followed by ball milling to obtain the final NiSe2@CdO composite. Structural, morphological, and electrochemical analyses revealed flake-like NiSe2 nanoparticles decorated with rod-shaped CdO nanostructures, exhibiting exceptional electrochemical performance. The nanocomposite electrode achieved a specific capacitance of 255 F/g at 10 mV/s from the three-electrode setup, and also, was achieved at an energy density of 48 Wh/kg at the power density 2000 W/kg by the NiSe2@CdO||AC asymmetric device. fourier transform infrared analysis confirmed the structural integrity, while transmission electron microscopy images revealed nanostructures with clear lattice fringes, and energy-dispersive X-ray Spectroscopy verified elemental uniformity. The device demonstrated 96.7% capacitance retention even after 5000 cycles and displayed superior energy and power density characteristics in the Ragone plot. These results in turn, highlight the potential of NiSe2@CdO nanocomposites for next-generation energy storage systems. 2025 Wiley-VCH GmbH. -
Effect of functionalization on the energy storage performance of super capacitors derived from wood charcoal
The electrochemical performance of wood charcoal is investigated with respect to the disorders in the system after subjecting to oxidation and exfoliation conditions. The Cyclic voltammetry and galvanostatic charge discharge curves indicate an improvement in the electrochemical behavior, resulting in a marginal increase in the specific capacitance values at higher exfoliation temperatures. The improvement is predominantly due to the change in the structural disorder in the system accompanied by the incorporation of oxygen functional groups which act as electrochemical active species. The exfoliation of wood charcoal at 160 and 200C yield a specific capacitance of 6.23 and 12.24 F/g at a current density of 0.01 A/g. The ESR values representing the overall resistance of the system are observed to be 6.07 ? for 200C as opposed to 10.41 ? of the bare material, making the material more conducting. The drastic change in the structural morphology along with the optimal amount of oxygen functional groups can be the reason for this behavior. The acquired results offer useful information for investigating the possibilities of fabricating supercapacitors with wood charcoal by tuning the defects of the system. 2024 American Institute of Chemical Engineers. -
Classification of Multiclass DDOS Attack Detection Using Bayesian Weighted Random Forest Optimized With Gazelle Optimization Algorithm
The increase in Distributed Denial of Service (DDoS) attacks poses a considerable threat to the security and stability of the current network, especially in Internet of Things (IoT) and cloud environments. Traditional detection methods often struggle with the inability to achieve a balance between detection accuracy and computational efficiency. In this manuscript, the Classification of Multiclass DDOS Attack Detection using Bayesian Weighted Random Forest Optimized with Gazelle Optimization Algorithm (DDOS-AD-BWRF-GOA) is proposed. First, the raw data is gathered from the CICDDoS2019 dataset. Then, input data are preprocessed utilizing Adaptive Bitonic Filtering for normalizing the values. The preprocessed data are fed to the Improved Feed Forward Long Short-Term Memory technique for selecting features that increase the model's execution time. The selected features are supplied to the Bayesian Weighted Random Forest (BWRF), which classifies the multiclass DDOS attack. In general, Bayesian Weighted Random Forest does not adopt any optimization methods to define optimal parameters to guarantee exact DDOS identification. Hence, GOA is proposed to optimize the Bayesian Weighted Random Forest classifier. The proposed method is implemented in MATLAB. The performance metrics, such as Accuracy, Precision, Recall, F1-score, Specificity, Error rate, and Computational time are evaluated. The proposed method attains 15.34%, 24.1%, and 18.9% higher accuracy and 12.4%, 18.24%, and 22.6% higher precision when analyzed with existing techniques: Hybrid deep learning method for DDOS detection and classification (HDL-DDOS-DC), Edge-HetIoT Defense against DDoS attack utilizing learning techniques (EHD-DDOS-LT), and Digital twin-enabled intelligent DDOS detection for autonomous core networks (DTI-DDOS-ACN), respectively. 2025 John Wiley & Sons Ltd. -
Pratixa: A Cognitive Framework for Behavioral Decision-Making and Its Mathematical Formalization
The present study introduces pratixa, an internal cognitive structure that functions as a reference architecture guiding human decision-making. Pratixa is a dynamic, event-sensitive archive of anticipated outcomes of behavior, learned event-behavior-outcome associations, and adaptive behavioral responses, drawing on the theories from decision science, psychology, and behavioral adaptation. Past experiences shape pratixa, and iterative learning reinforces it. It supports predictive mental representations by enabling individuals to anticipate the outcomes of their own behavioral responses and adjust those responses when discrepancies arise between anticipated and actual outcomes. Pratixa supports anticipatory learning and real-time correction, making it a future-oriented cognitive structure for decision making. It matures in a spiral progression, from null pratixa, where no prior event-behavior-outcome associations exist, through quixotic pratixa, characterized by illusory or arbitrary associations, to realistic pratixa, where causal relationships are adequately approximated. This spiral maturation reflects how individuals adapt through experiential learning and reinforcement, transitioning from effortful reasoning to increasingly automatic and context-sensitive decision-making. By positioning decision-making within this evolving structure, pratixa offers a distinct perspective on predictive cognition in complex and ambiguous contexts, with implications for strategic foresight, behavioral economics, and adaptive behavioral decision making. The study also proposes a mathematical formulation to represent how this reference architecture evolves through reinforcement-based learning and guides decision-making, providing a computational basis for modeling human foresight and adaptation. 2025 John Wiley & Sons Ltd. -
Improving Flood Prediction Using Artificial Neural Networks With Optimal Feature Selection on a Benchmark Dataset
Disasters significantly impact people's lives; among them, flooding is the worst common, and it causes sudden and secure damage to both lives and property. Addressing such real-time crisis demands intricate and sophisticated flood prediction models with enhanced capabilities. The development of efficient flood prediction models is often hindered by the lack of available datasets and the need for optimal feature. To address the challenge of data availability, in the proposed research, we have manually prepared a novel dataset by collecting data from NASA's (National Aeronautics and Space Administration) Power Project. The proposed dataset is experimentally evaluated and verified and has been organized into a balanced benchmark dataset with 33 features using the SMOTE algorithm. To enhance the provenance of flood prediction model, we propose a novel feature selection method. This method integrates outcomes from three different feature selection techniques to identify the most prominent features. The proposed feature selection method improves the model's performance and efficiency by identifying optimal predictors. Experimental results demonstrate that the artificial neural network trained with the selected relevant features accurately predicts flood occurrences, showing enhanced accuracy compared to state-of-the-art methods. 2026 John Wiley & Sons Ltd. -
Investigating Salt-Finger Convection Under Time-Dependent Gravity Modulation in Micropolar Liquids
This paper investigates how gravity modulation affects salt-finger convection in a micropolar liquid layer confined between two parallel, infinitely long plates separated by a thin gap. The system is heated and has solute added from above. The study uses linear stability analysis to examine when and how salt-finger convection, driven by the salt-finger process, begins. To analyze this, the partial differential equations governing the system are solved numerically using normal mode analysis. The Venezian approach is applied to find the critical Rayleigh number and the solutal Rayleigh number, which are key to understanding the onset of convection. Also, the paper explores how different micropolar fluid parameterssuch as the coupling parameter, micropolar heat conduction parameter, couple stress parameter, and inertia parameteraffect the system when gravity modulation is present. It is found that gravity modulation can either stabilize or destabilize convection, depending on its frequency. At very high frequencies (approaching infinity), the effect of gravity modulation becomes minimal, having little impact on the convection process. The paper also examines the relationship between the critical Rayleigh number and the solutal Rayleigh number, which are related to heat and solute concentration, respectively. 2024 Wiley Periodicals LLC.