Hormozgan University

In many Middle Eastern countries, including Iran, freshwater resources are primarily allocated to agriculture, making the sector the dominant water consumer. However, increasing urban demand has shifted priorities toward municipal water supply, thereby intensifying the imbalance between water availability and consumption. In light of escalating water scarcity and environmental concerns, rainwater harvesting systems (RWHS) have gained attention as a sustainable and environmentally sound approach to water management. RWHS not only reduces the financial burden of water provision but also serves as a reliable source during droughts and periods of restricted access. Despite its potential, adoption of RWHS among farmers remains limited, posing a significant challenge for policymakers. This study investigates the determinants of farmers’ intention to adopt RWHS in Hamidieh County, located in southwestern Iran. An extended Technology Acceptance Model (TAM) was employed, incorporating additional constructs—Subjective Norms (SN), Performance Expectancy (PE), Facilitating Conditions (FC), and Self-Efficacy (SE)—alongside core variables such as Attitude (ATT), Perceived Usefulness (PU), and Perceived Ease of Use (PEU). The proposed model demonstrated strong explanatory power, accounting for 66.9

Various techniques are used to introduce new cultivars, especially in ornamental species like tuberose, which have limited genetic diversity. This study employed a completely randomized design with three replications to investigate the effects of different mutagens on mutation induction in tuberose bulbs. The mutagens tested included sodium azide at concentrations of 200, 300, and 400 mg L−1, ethyl methanesulfonate at 0.25, 0.5, and 0.75 mg L−1, and gamma rays at doses of 10, 20, and 30 Gy. After exposure to the mutagens, both mother and daughter bulbs were grown for two consecutive years under greenhouse conditions. Our results indicated an increase in the number of florets in bulbs treated with sodium azide, regardless of the concentration used. The largest floret diameter, measuring 47.82 mm, was recorded in samples treated with ethyl methanesulfonate at a concentration of 0.5 mg L−1. This same concentration also resulted in an increase in the reducing sugar content within the petals. The longest vase life, recorded at 8.66 days, was observed in samples exposed to gamma radiation at a dose of 10 Gy. Significant changes in enzymatic antioxidants were noted in bulbs treated with the different mutagens, both before and after harvest. In conclusion, all three mutagens had an influence on the growth of tuberose plants, affecting various morphological, physiological, and postharvest parameters.

In the challenging economic climate of Iran, men—often the primary breadwinners—are increasingly exposed to financial and psychological pressures. This situation can be accompanied by harms that need to be investigated. This study aimed to examine a model of the relationship between financial well-being, suicidality, and intimate partner violence (IPV), with an emphasis on the mediating role of defeat among Iranian men. This quantitative study employed a correlational design and structural equation modeling (SEM) method. A total of 385 married men residing in Karaj, Iran, voluntarily participated in the study in 2024 and completed the online research instruments. Data were collected using the InCharge Financial Distress/Financial Well-Being Scale (IFDFW), Defeat Scale (DS), Beck Scale for Suicidal Ideation (BSSI), and Revised Conflict Tactics Scales (CTS). Analyses were conducted using SPSS-26 and AMOS-24. The model indices indicated a good fit. The model showed that defeat was correlated with suicidal ideation (β = .484, p < .001) and IPV (β = .641, p < .001). Lower financial well-being was negatively correlated with suicidal ideation (β = .203, p < .001), IPV (β = .626, p < .001), and defeat (β = .364, p < .001). Furthermore, the indirect pathway showed that lower financial well-being was correlated with suicidal ideation (β = .145, p < .05) and IPV (β = .127, p < .05) through the mediation of defeat. According to the proposed conceptual model, defeat plays a key role in linking men’s financial conditions with psychological and interpersonal outcomes. Interventions aimed at reducing feelings of defeat, such as financial counseling, stress management programs, and psychosocial support, may help prevent suicidal ideation and IPV. These efforts can contribute not only to improving men’s mental health but also to the well-being of families and the broader community.

Source samples misclassification is a key source for the uncertainty in the aeolian sediment source tracking models. Therefore, identifying sources of aeolian sand and their samples correct classification are necessary to decrease the uncertainty associated with source tracking’s models. This research aimed to introduce deep clustering (DC) as a type of deep learning (DL) models for classifying the source samples for aeolian sand in a region with severe wind erosion and active sand dunes impacting on the railroad networks in the Zhongzaohuo in the Qaidam Basin of Tibetan Plateau, Northwest China. In this research, 40 samples taken from four potential source regions, and then, 40 geochemical elements and elementary compositions were measured in each sample by X-ray fluorescence spectrometer. To classify source samples of aeolian landforms, eight DC models based on deep Autoencoder (DAE) (e.g., Autoencoder, DCN, DEC, IDEC, DipDECK, DipEncoder, DDC and N2D) was employed to classify source samples of aeolian sand in our study area. Then, stepwise discriminant function analysis (DFA) was applied to explore the accuracy of source samples classified correctly in different source classification schemes provided by DC models. The results of the DC models revealed that the accuracy of source samples were classified correctly ranges between 82.5 and 100 An important source for uncertainty in the sediment source tracing models is source samples misclassification. In this study, we introduced eight deep clustering models based on deep autoencoder for classifying source samples of sand in the Qaidam Basin of Tibetan Plateau, Northwest China. 100

Biosorption has emerged as a promising and eco-friendly technology with wide applications, attracting considerable interest in recent years. Among various biosorbents, microalgae are particularly noteworthy due to their wide availability, high adsorption efficiency, and cost-effectiveness. In this study, the microalga Chlorella sorokiniana was employed for the bioremoval of acetaminophen from aqueous solutions. The effects of process duration (10-48 h) and initial acetaminophen concentration (10-120 mg l-1) and the removal efficiency were evaluated and modeled using response surface methodology (RSM) in Design-Expert software. Optimization of key parameters was performed using the Grey Wolf metaheuristic algorithm. The high determination coefficient (R2 =0.92) indicated strong predictive capability of the model. Using C. sorokiniana, acetaminophen removal efficiency ranged from 13.8% to 99.8%. Analysis results revealed that during the first 12 days, a large proportion of metabolites produced by C. sorokiniana were converted to carbon dioxide. Scanning Electron Microscopy (SEM) images showed that different acetaminophen concentrations induced cellular stress and altered algal cell size. Overall, the findings demonstrate that C. sorokiniana can effectively degrade acetaminophen in contaminated waters, likely utilizing it as an organic carbon source while enhancing its photosynthetic pigments, proteins, and lipids.