Khatam University

The COVID-19 pandemic accelerated the adoption of work-from-home (WFH) practices, raising important questions about their long-term implications for organisational performance. This issue is particularly salient for multinational enterprises (MNEs) and international small and medium-sized enterprises (SMEs), where digitalisation has significantly reshaped work arrangements. This study evaluates the advantages and disadvantages of WFH and their differential impacts on MNEs and international SMEs. A comparative analysis was conducted using expert pairwise judgements, assessed through linguistic terms with weakened hedges (LTWHs) within the Best–Worst Method (BWM) framework. The LTWHs approach enables experts to articulate nuanced and flexible preferences, extending traditional linguistic scales by softening the strength of evaluations. This makes it particularly suited for capturing subjective assessments of WFH impacts under conditions of uncertainty. The findings indicate substantial variation in WFH adoption, with private sector organisations demonstrating approximately 50 % greater willingness to adopt WFH compared to public authorities. The analysis further highlights the distinct advantages and disadvantages that shape the performance outcomes of MNEs and international SMEs. By introducing a novel hesitant fuzzy linguistic preference approach, this study develops a comprehensive framework for assessing the organisational consequences of WFH. The results offer valuable insights for managers and policymakers seeking to strike a balance between flexibility, productivity, and resilience in the design of post-pandemic work strategies. • Paper investigates the implications of work-from-home using digitalisation. • This is done on the performance of multinational enterprises and international SMEs. • Findings reveal a difference between the public and private sectors in their adoption of WFH. • Study highlights pros and cons of WFH, demonstrating their varying impacts.

Abstract The increasing production and consumption of medicinal substances and the presence of their residues in the environment have created potential dangers. Therefore, finding ways to reduce the environmental risks of pharmaceutical residues is one of the challenges facing researchers. Acetaminophen (ACE) is a widely utilized pharmaceutical worldwide, and its presence in the environment is concerning due to potential adverse effects. In this study, the efficiency of the photoelectro‐Fenton method for the ACE removal was evaluated. In the photoelectro‐Fenton method, a stainless steel plate was used as the cathode and a titanium plate as the anode. Lamps emitting wavelengths of 400 nm were used as UV light sources. In this method, at the first step, the effect of operating variables, including initial ACE concentration (10–120 mgL −1 ), initial H 2 O 2 volume (20–110 μL), pH (2–6) of the sample, and reaction time (20–50 min) was investigated by using response surface methodology (RSM). In the next step, in order to obtain optimal points, the mathematical model obtained with the two methods of desirability function (DF) and gray wolf meta‐heuristic algorithm was examined, and the results showed that the desirability function (with 91.0%) was more efficient than the gray wolf method (with 76.8). Based on these calculations and the desirability score of 1, the removal of ACE was optimized at 91.0% with the optimum values of the variables that were set as initial concentration of ACE 20.0 mg L −1 , H 2 O 2 value equal to 45.0 μL, pH = 3.0, and reaction time of 45.0 min.

This study investigated the effects of cadmium (Cd), microplastics (MPs), and pectin (Pec) supplementation on biochemical, oxidative, and immunological parameters in crayfish ( Astacus leptodactylus ). Four hundred fifty crayfish were acclimatized under controlled laboratory conditions and distributed into 15 experimental groups using a definitive screening design (DSD) approach. The groups were exposed to varying combinations of Cd (0, 20, and 40 µg/L), MP (0, 50, and 100 mg/L), and Pec‐supplemented diets (0%, 0.25%, and 0.5% per kg feed) for 45 days. The findings showed that Pec supplementation increased superoxide dismutase (SOD) and glutathione (GSH) peroxidase (GPx) activities but did not affect catalase (CAT) activity. Cd and MPs reduced SOD, CAT, and GPx activities, with Pec partially restoring CAT activity. Exposure to Cd and MPs elevated alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, triglycerides, cholesterol, creatinine, and glucose levels, while gamma‐glutamyl transpeptidase, lysozyme, total protein, and albumin decreased. Pec normalized triglyceride and alkaline phosphatase (ALP) activity but showed limited protective effects on GPx, cholesterol, creatinine, and glucose regulation. The results indicated that because crayfish were directly exposed to MPs and Cd, oral administration of the Pec supplement failed to restore some biochemical parameters to normal levels. These findings indicate Pec’s selective efficacy in mitigating Cd‐ and MP‐induced stress in crayfish.

Understanding the detection of salient auditory stimuli by the deep layer of the superior colliculus (dSC) during REM and NREM sleep offers valuable insights into the neurophysiological mechanisms of state-dependent auditory information processing. We recorded local field potentials (LFP) from dSC, electrocorticogram (ECoG) from frontal/parietal cortical regions, and neck electromyogram (EMG) in freely moving rats during sleep and awake states under oddball paradigm auditory stimulations. Our analysis focused on mismatch negativity (MMN) responses and event-related spectral perturbation (ERSP) in slow gamma (30-60 Hz) activity (SGA) and medium gamma (60-95 Hz) activity (MGA) frequency bands in wakefulness, REM and NREM sleep using three different intensities (35-, 55-, 80-dB) of stimulation. Data were analysed using repeated-measure two-way ANOVA and Linear Mixed Model. We found that the dSC exhibited significantly increased MMN responses to salient auditory stimuli across nearly all conditions (p < 0.05), specifically in REM, compared to other vigilance states. Additionally, stimulus intensity in pure tone experiments significantly enhances the MMN peak amplitude (p < 0.0001). The dSC further illustrated state-dependent spectral dynamics: SGA (30-60 Hz) ERSP substantially increased in NREM (p < 0.0001), while MGA (60-95 Hz) ERSP increased in both REM/NREM significantly (p < 0.001). These findings demonstrate that the dSC, a key node within the auditory processing network, retains robust auditory salience detection in sleep states.

This study examines how blockchain technology (BT) enhances sustainability and resilience in construction supply chains (CSCs). Recognizing the sector’s vulnerability to disruptions and inefficiencies, the research aims to identify key blockchain facilitators (BTFs) that enhance environmental, economic, and risk-related performance metrics. Using an integrated multi-criteria decision-making methodology based on intuitionistic fuzzy cognitive maps and an active Hebbian learning algorithm, causal relationships between BTFs and sustainability indicators are modeled and analyzed. Data is collected from ten experts through structured interviews and surveys, ensuring methodological rigor via sensitivity and consistency analyses. Results reveal that transparency, traceability, and smart contracts are the most influential facilitators, significantly improving environmental impact, stakeholder collaboration, and economic efficiency within CSCs. Decentralized and secure databases also emerged as critical enablers of resilience and cost reduction. Simulation results demonstrate that full-scale adoption of BT can improve sustainability performance by up to 35%, whereas partial adoption yields limited benefits. The study presents a novel decision-support framework for prioritizing BT facilitators, offering actionable insights for managers, policymakers, and construction firms seeking digital transformation and sustainable development. Overall, this research advances the understanding of BT’s strategic role in construction supply chains and offers a practical roadmap for its effective implementation. • Identify blockchain technology facilitators for enhancing construction supply chain sustainability and resilience. • Apply intuitionistic fuzzy cognitive mapping to model causal links between blockchain enablers and sustainability outcomes. • Propose a structured decision-making framework connecting blockchain adoption to supply chain sustainability performance. • Highlight blockchain’s role in improving transparency, reducing inefficiencies, and strengthening supply chain resilience. • Offer practical insights for managers and policymakers to optimize blockchain investment for sustainable operations.