Search Results (301)

This study aims to investigate the static performance of water-lubricated rubber bearings (WLRBs) with axial grooves. To achieve this objective, an analytical approach is employed that combines a modified Reynolds equation, accounting for surface groove effects and rubber deformation, with a Winkler model and finite element analysis of pressure distribution. By developing a fluid–structure interaction model that incorporates rubber liner deformation, this research reveals the interaction between WLRB geometry and steady-state performance parameters. The investigation evaluates the influence of geometric characteristics, including groove shape, number, and size, on the performance of elastomeric liner WLRBs, while assessing optimal groove depths under various conditions. The study analyzes five distinct groove geometries, including semi-cylindrical, rectangular prism, and three pyramidal types with different apex positions, in a six-groove bearing configuration, presenting their qualitative effects on the behavior of the examined bearings. The key findings indicate that increasing groove size or quantity reduces maximum pressure and load-carrying capacity while elevating friction coefficients. As groove count rises, supporting surfaces diminish, causing pressure distribution to intensify and minimum film thickness to decrease under a specified external load. A notable result reveals that when groove depth exceeds film thickness, performance becomes geometry-independent; however, shallower grooves exhibit significant geometric effects. Additionally, the study identifies groove ends as critical functional zones where film thickness reduction substantially enhances pressure distribution and static performance. Comparative analysis shows that longitudinal grooves with triangular cross sections outperform semi-circular and rectangular variants, with the backward triangular configuration demonstrating superior characteristics due to optimal end-film properties. In conclusion, this research provides a detailed understanding of how groove geometry influences the static performance of WLRBs, highlighting the importance of groove design, particularly at the groove ends, in optimizing bearing functionality. The findings offer valuable insights for the design and selection of groove configurations in water-lubricated rubber bearing applications. Full article

In many empirical studies, researchers face challenges when addressing sensitive topics as respondents may be reluctant to provide truthful answers due to privacy concerns. Traditional direct survey methods often yield biased or unreliable estimates in such contexts. The randomized response technique offers a robust alternative by improving data validity while protecting respondent confidentiality. This paper proposes a novel quantitative three-stage randomized response model, introducing a new Horvitz–Thompson (HT)-type estimator for estimating the means of two sensitive variables under a general sampling design. Simulation studies indicate that the proposed estimator can achieve lower bias and mean squared error (MSE) compared to other existing estimators in the literature. Additionally, an empirical investigation was conducted using data from Shahid Chamran University of Ahvaz to estimate the average rates of exam cheating and cigarette consumption among students under a simple random sampling scheme, further demonstrating the practical utility of the proposed approach. Full article

After large-scale disasters, swift and robust humanitarian logistics are crucial to provide timely assistance to injured people and displaced individuals. This study proposes a bi-objective optimization model for humanitarian logistics network design to simultaneously consider the facility location-allocation decisions, along with the transportation operation issues under uncertainty. The framework addresses the needs of both severely and mildly injured casualties and homeless populations. A hybrid robust optimization approach is accordingly developed that incorporates scenario-based, box-type, and polyhedral uncertainty representations to handle the uncertainty of factors such as casualty volume, travel times, facility failures, and demands for resources. More recently, machine learning methods have been applied to classify casualties and displaced individuals with respect to their geographic distribution and severity, further improving demand estimates and operational efficacy. This study seeks to develop a data-driven and robust optimization framework for designing humanitarian logistics networks under uncertainty, enabling decision-makers and emergency planners to gain insights into enhancing casualty evacuation, medical treatment, and shelter allocation in disaster response operations. The case of the Kermanshah earthquake in Iran is used for assessing the applicability of the model. The computational experiments and comparative analyses conducted show that the developed model exhibits high efficiency and robustness. The results are useful for guiding disaster preparedness and strategic decisions in humanitarian logistics. Besides operational performance, the model optimizes sustainability in the area of emergency response based on cost efficiency and social fairness, as underlined by SDGs 3 and 11. Full article

The Southwest Asia Anticyclone (SWAA) plays a pivotal role in governing the regional precipitation regime. This study analyzes the structure and spatiotemporal variability of the SWAA core at the 850, 700, and 500 hPa levels, and its relationship with precipitation across Southwest Asia. Monthly precipitation and geopotential height (HGT) data were obtained from ERA5 reanalysis with a 0.25° spatial resolution over 1940–2023. The results showed that in September the SWAA core migrates from northwestern and western Saudi Arabia, shifting southward during colder periods and retreating landward in warmer periods. At 850 hPa, the core is absent during June–August, while at 700 hPa it is positioned over the southeastern Caspian Sea. The SWAA has intensified in recent decades, and its directional shifts exert a marked influence on precipitation variability: northeastward, eastward, southeastward, and southward displacements enhance rainfall, whereas northward, northwestward, and westward movements suppress it. Overall, the intensity and positioning of the SWAA are strongly linked to precipitation patterns in Southwest Asia. These findings contribute to refining precipitation and climate projections and offer practical implications for water resource management and agricultural planning in the region. Full article

Conjugate heat transfer in non-Newtonian fluids is a fundamental phenomenon in thermal management systems. This study investigates the combined effects of magnetic field topology, heat absorption/generation, the thermal conductivity ratio, enclosure inclination, and power-law rheology using the lattice Boltzmann method. The parametric analysis shows that increasing the heat generation coefficient from −5 to +5 reduces the average Nusselt number by up to 97% for the pseudo-plastic fluids and up to 29% for the Newtonian fluids, while entropy generation increases by 44–86% depending on the thermal conductivity ratio. Increasing the inclination angle from 0° to 90° weakens convection and reduces heat transfer by nearly 77%. Magnetic field strengthening (Ha = 0–45) decreases the Nusselt number by 20–55% depending on the barrier temperature. Among all tested conditions, the highest thermal performance (maximum heat transfer and minimum entropy generation) occurs when using a pseudo-plastic fluid (n = 0.75), exhibiting high wall conductivity (TCR = 50) and heat absorption (HAPC = −5), a cold obstacle (${\mathsf{\theta }}_{\mathrm{b}}=0$), and zero inclination (λ = 0°), as well as in the absence of the magnetic field effects. These quantitative insights highlight the controllability of the conjugate heat transfer and irreversibility in the power-law fluids under coupled magnetothermal conditions. Full article

Background and Objectives: Female breast cancer (FBC) is an increasing public health concern in Iran, with notable geographic disparities that necessitate comprehensive burden assessments at national and provincial levels. This study presented the national and subnational burden and changes in FBC burden from 2010 to 2021 in Iran in comparison with global data. Materials and Methods: The GBD (2021) data on female BC were extracted from the Global Health Data Exchange (GHDx) query tool. Age-standardized incidence, deaths, prevalence, and adjusted years of life with disabilities (DALYs) rates (per 100,000) of FBC were extracted. Data were extracted globally, by continents, for Iran and its provinces, from 2010 to 2021. Results: Although the global FBC burden indicators remained almost stable, in Iran, there was a nearly twofold rise in incidence and prevalence and notable rises in mortality and DALYs. This study showed significant variation at the provincial level; Tehran, Qom, and Alborz consistently had the highest incidence, prevalence, mortality, and DALY rates, whereas Sistan and Baluchistan, Chahar Mahaal and Bakhtiari, Kohgiluyeh and Boyer-Ahmad, and Zanjan had the lowest rates. During 2010–2021, the provinces of Golestan, Ardebil, Sistan and Baluchistan, West Azarbayejan, Kohgiluyeh and Boyer-Ahmad, and North Khorasan experienced the most increasing trend in BC burden, while Yazd and Semnan showed smaller increases or modest decreases. Conclusions: The rising FBC burden in Iran underscores the urgent need to strengthen cancer registries, expand screening programs, ensure equitable resource distribution, and implement targeted regional interventions focused on modifiable risk factors and early detection to reduce health disparities nationwide. Full article

This study addresses the critical challenge of permanent deformation in asphalt pavements under high-temperature conditions by developing recycled high-density polyethylene (HDPE)-modified bitumen. Through systematic laboratory investigation, we quantified the dose-dependent effects of HDPE (2–9% wt.) on rheological and mechanical properties. Dynamic shear rheometry revealed a 472% increase in rutting resistance (G*/sinδ = 6.48 kPa) at 6% HDPE versus unmodified bitumen (1.13 kPa), alongside an 18–32% reduction in phase angle (58–88 °C). Rotational viscosity surged by 240% at 135 °C (1170 cP vs. 344 cP). Mechanically, Marshall Stability peaked at 19,000 N (46% enhancement) with 6% HDPE, while flow values minimized at 2.3 mm (15% reduction). Complementary tests confirmed superior temperature susceptibility control: penetration decreased by 50% and softening point increased by 43% (72.3 °C) at 9% HDPE, with Penetration Index shifting from −0.4 to +2.18. SEM microstructural analysis validated optimal polymer dispersion at 6%, forming a continuous reinforcing network, whereas agglomeration at higher doses induced defects. Statistical modeling identified a robust linear relationship for Marshall Quotient (Adjusted R² = 0.8383). The study establishes 6% HDPE as the optimal dosage, delivering synergistic high-temperature performance enhancement while utilizing recycled plastic. Future work should address long-term aging and field validation for sustainable pavement applications in tropical regions. Full article

Accurate estimation of flow discharge, Q, through hydraulic structures such as spillways and gates is of great importance in water resources engineering. Each hydraulic structure, due to its unique characteristics, requires a specific and comprehensive study. In this regard, the present study innovatively focuses on predicting Q through Rectangular Top-Hinged Gates (RTHGs) using advanced Gradient Boosting (GB) models. The GB models evaluated in this study include Categorical Boosting (CatBoost), Histogram-based Gradient Boosting (HistGBoost), Light Gradient Boosting Machine (LightGBoost), Natural Gradient Boosting (NGBoost), and Extreme Gradient Boosting (XGBoost). One of the essential factors in developing artificial intelligence models is the accurate and proper tuning of their hyperparameters. Therefore, four powerful metaheuristic algorithms—Covariance Matrix Adaptation Evolution Strategy (CMA-ES), Sparrow Search Algorithm (SSA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA)—were evaluated and compared for hyperparameter tuning, using LightGBoost as the baseline model. An assessment of error metrics, convergence speed, stability, and computational cost revealed that SSA achieved the best performance for the hyperparameter optimization of GB models. Consequently, hybrid models combining GB algorithms with SSA were developed to predict Q through RTHGs. Random split was used to divide the dataset into two sets, with 70% for training and 30% for testing. Prediction uncertainty was quantified via Confidence Intervals (CI) and the R-Factor index. CatBoost-SSA produced the most accurate prediction performance among the models (R² = 0.999 training, 0.984 testing), and NGBoost-SSA provided the lowest uncertainty (CI = 0.616, R-Factor = 3.596). The SHapley Additive exPlanations (SHAP) method identified h/B (upstream water depth to channel width ratio) and channel slope, S, as the most influential predictors. Overall, this study confirms the effectiveness of SSA-optimized boosting models for reliable and interpretable hydraulic modeling, offering a robust tool for the design and operation of gated flow control systems. Full article

Global brands are increasingly establishing dedicated administrative departments to strengthen sustainability and resilience in their supply chains. However, overlooking these aspects at the supplier level can result in significant costs and systemic vulnerabilities. This study addresses this gap through four key contributions: First, we provide a comprehensive sustainability assessment by simultaneously considering economic, environmental, and social pillars along with resilience, operationalized through twenty-four sub-criteria. Second, we explicitly incorporate human judgment and uncertainty by modeling supplier evaluation with interval weights, capturing the ambiguity and subjectivity inherent in expert decision-making. Third, we propose a novel hybrid methodology, integrating lexicographic goal programming (LGP), the analytical hierarchy process (AHP), and two-stage logarithmic goal programming (TLGP) in a systematic framework. Finally, we validate the approach in real-world contexts through case studies in the electronics and unmanned aerial vehicle (UAV) industries. The results reveal notable differences in supplier rankings when comparing LGP and TLGP, highlighting the methodological implications of advanced goal programming in uncertain environments. Overall, this study advances supplier selection research by offering both a validated decision-support tool for practitioners and methodological insights for scholars working on sustainability and resilience under uncertainty. Full article

The CRISPR-Cas9 system has transformed biomedical research by enabling precise genetic modifications. However, efficient delivery of CRISPR components remains a major hurdle for therapeutic applications. To address this, we employed a new modified cationic hyper-branched cyclodextrin-based polymer (Ppoly) system to deliver an integrating GFP gene using the TILD-CRISPR method, which couples donor DNA linearization with RNP complexes. The physicochemical properties, loading efficiency, and cellular uptake of RNP with Ppoly were studied. After transfection, antibiotic selection and single-cell cloning were performed. Junction PCR was then performed on the isolated clones, and we compared the knock-in efficiency of Ppoly with that of the commercial CRISPRMAX™ reagent (Thermo Fisher, Invitrogen™, Waltham, MA, USA). The results demonstrate the encapsulation efficiency of over 90% for RNP and Ppoly, and cell viability remaining above 80%, reflecting the minimal toxicity of this approach. These attributes facilitated successful GFP gene integration using the TILD-CRISPR with RNP delivered via cyclodextrin-based nanosponges. The present method achieved a remarkable 50% integration efficiency in CHO-K1 cells, significantly outperforming the 14% observed with CRISPRMAX™ while maintaining lower cytotoxicity. This study highlights a promising platform for precise and efficient genome editing, with strong potential for therapeutic and regenerative medicine applications. Full article

Accurate estimation of population distribution characteristics is a fundamental task in survey sampling and statistical inference. This paper introduces a new family of estimators for the cumulative distribution function (CDF) under probability proportional to size (PPS) sampling, incorporating auxiliary information to enhance efficiency. The proposed approach employs dual auxiliary variables in the estimation phase, while the sampling design relies on a single auxiliary variable. Theoretical properties, including bias and mean squared error (MSE), are rigorously derived to establish the efficiency of the new class. An extensive empirical evaluation using three distinct populations—fisheries data, wine chemistry data, and demographic records—demonstrates the superiority of the proposed estimators. In terms of accuracy, the best-performing proposed estimator achieves an MSE of 0.0012, compared to 0.0127 for the widely used GK estimator. Percentage relative efficiency (PRE) values further underscore these improvements, with gains ranging from 123% to over 328% across the three populations. Graphical comparisons confirm these trends, illustrating that the proposed estimators consistently dominate conventional approaches. Overall, the findings highlight both the theoretical soundness and practical utility of the proposed family, offering robust and computationally efficient improvements for CDF estimation in complex survey designs. Full article

Yazd province in central Iran is highly prone to dust and sand storms, causing significant environmental, economic, and health impacts. This study investigates the spatiotemporal dynamics of dust storms in Yazd over 2003–2022 using ground-based meteorological station records and satellite-derived aerosol optical depth (AOD) data from MODIS (MYD08_D3 v6.1) at monthly, seasonal, and annual scales. Analysis of ten synoptic stations data revealed an increasing trend of ~0.5 dusty days/year, with the highest frequency in spring and winter, particularly from March to May. MODIS AOD data confirmed these patterns and showed a rising annual aerosol load, peaking in May. Spatial analysis indicated that central and northern regions are most affected, consistent across datasets. The increasing frequency and intensity of dust storms are driven by natural and anthropogenic factors, including regional drought, desertification, drying wetlands, land use changes, and transboundary dust transport (from Iraq, Syria, Saudi Arabia). These findings underscore the value of integrating in situ and remote sensing observations to monitor dust events. To mitigate impacts, policymakers should prioritize long-term environmental monitoring and interventions addressing both natural and human factors influencing dust emissions. This study provides actionable insights for decision-makers to enhance environmental resilience and protect public health in arid regions. Full article

In the early 1990s, the decline of textile manufacturing due to various factors resulted in the abandonment of industrial sites previously utilized in Yazd. This study examines the regeneration of industrial heritage through place branding in a developing country, utilizing a case study approach. The objective is to design a framework for the development of a branding strategy aimed at the regeneration of industrial heritage sites in Yazd. By integrating both quantitative and qualitative methodologies, this study utilizes SWOT analysis through focus group discussions in conjunction with the Delphi method. Furthermore, in the strategy development process, the expert panel technique is employed to formulate Weihrich’s TOWS matrix. The findings indicate that the risk of textile heritage sites remaining unknown to tourists, as well as the potential for enhancing the identity of Yazd, received the highest mean scores. In contrast, the results indicate that the lowest mean scores were associated with the factors of multiple non-official brands in Yazd and the presence of basic tourist infrastructure. This study presents a comprehensive framework for the integration of place branding into industrial heritage regeneration initiatives, grounded in original empirical data, and offers valuable insights for policymakers, heritage managers, and urban planners. Full article

Combined Cycle Power Plants (CCPP) suffer from drops in power and efficiency due to summer time ambient conditions. This power reduction is especially important in regions with extreme summer ambient conditions. Given the substantial investment and labor involved in the establishment and operation of these power plants, mitigating power loss using various methods emerges as a promising solution. In this context, the integration of Concentrated Solar Power (CSP) technologies has been proposed in this research not primarily to improve the overall performance efficiency of power plants as other recent studies entail, but to ensure continuous power generation throughout summer days, improving stability. This research aims to address this issue by conducting an extensive study covering the different scenarios in which Concentrated Solar Power (CSP) can be integrated into the power plant. Multiple scenarios for integration were defined including CSP integration in the Heat Recovery Steam Generator, CSP-powered chiller for Gas Turbine Compressor Cooling and Gas Turbine Combustion Chamber Preheating using CSP, and scenarios with inlet air fog cooling and hybrid scenarios were studied. This systematic analysis resulted in the selection of the scenario where the CSP is integrated into the combined cycle power plant in the HRSG section as the best case. The selected scenario was benchmarked against its equivalent model operating in Seville’s ambient conditions. By comparing the final selected model, both Yazd and Seville experience a noticeable boost in power and efficiency while reaching the maximum integration capacity at different reflector lengths (800 m for Seville and 900 m for Yazd). However, both cities reach their minimum fuel consumption at an approximate 300 m total reflector length. Full article

Strain-induced deformations and phase evolutions are two hidden factors that may influence cytocompatibility of Gum Metal alloys during processing for relevant implant applications. In the present research, changes in cell viability of a new Gum Metal Ti-Nb-Zr alloy in its cold-rolled state and after heat treatments (at 700, 850, and 900 °C) were investigated by a comprehensive study of microstructural phases and their role in deformation mechanisms as well as mechanical properties. In its cold-rolled state, the alloy showed a lamellar microstructure along with stress-induced α″ martensite and ω phases, as confirmed by optical microscopy (OM) and X-ray diffractometry (XRD) analysis. The instability in the β phase led to a strain-induced martensitic (SIM) transformation from β to α′/α″ phases, causing lower viability of MG-63 cells compared with commercially pure titanium. MG-63 cell viability was significantly higher (p < 0.0001) in the alloy heat-treated at 900 °C compared with those heat-treated at 700 and 850 °C. This can be directly attributed to the increased portion of the stable and dominant β phase. The stabilized β phase greatly improved the alloy’s cellular response by reducing harmful phase interactions and maintaining mechanical compatibility with bone (admissible strain of 1.3%). Importantly, heat treatment at high temperatures (between 850 and 900 °C) effectively converted the stress-induced α″ and ω phases back into a stable β phase matrix as the dominant phase. Full article