The search for sustainable ways to produce important petrochemicals like light olefins has been accelerated by the increasing CO2 levels in the atmosphere and the worsening effects of global warming. While the methanol-to-olefins (MTO) technique shows potential for reducing reliance on fossil fuel feedstocks, it remains extremely energy-intensive and requires significant environmental considerations. Concurrently, the proper disposal of hazardous refinery wastes-especially oil sludge-has become a major problem worldwide. A process-simulation framework for evaluating sustainable routes to find optimization possibilities and to evaluate the performance of waste-derived feedstocks in petrochemical uses was developed and tested using a fully integrated 4E (energy, exergy, economic, and environmental) framework. The Aspen HYSYS model allows a thorough investigation of system behavior under industrially pertinent settings by including all the main thermochemical conversion, methanol synthesis, and olefin manufacturing units. The findings indicate that methanol production is the main cause of exergy destruction (87%), followed by gasification (7%) and light olefin synthesis (4%). The largest cumulative thermodynamic losses come from heat exchangers, which account for 49% of all exergy destruction and 58% of all energy use because of non-ideal heat recovery setups. Exergoeconomic analyses show that compressors are the most expensive units (with an exergoeconomic factor of about 95%), but most heat exchangers show factors less than 15%, which means there is a lot of room for inexpensive improvements. The exergoenvironmental study reveals that during the gasification and compression phases, environmental effects rise dramatically as the cracked gas stream increases from 1,980 to 8230 Pts/h and then to 25,004 Pts/h following compression due to shaft power inputs and exergy destruction. The mixed syngas used to make methanol has the biggest environmental impact in the plant (52,805 Pts/h). In contrast, the environmental impact per exergy unit of the final light olefin products remains rather low (approximate to 12.9 Pts/GJ), and olefin synthesis reactors show great environmental efficiency (environmental factor > 90%). Because they show the highest environmental load, purification columns and a number of heat exchangers are top priorities for development.
The present study aimed to qualitatively study the lived experience of husbands with wives with cleanliness problems using a phenomenological approach. Using purposive sampling and theoretical saturation criteria, 15 men who referred to counseling centers in Isfahan in 1401 participated in this study. To diagnose cleanliness problems in their wives, the diagnosis of Isfahan counseling centers was used. In-depth semi-structured interviews were used to collect data. The content of the interviews was analyzed using the Claise 7-step method. The main categories included: 1- Initial perceptions of obsession; 2- Consequences in relationships with others; 3- Effects on the mood of the obsessive person and other family members; 4- Effects on relationships with the spouse; 5- Effects on the relationships of the obsessive person and his/her spouse with children; 6- Effects on the desire to have children; 7- Effects on raising children; 8- Effects on emotional and marital relationships; 9- Economic consequences; 10- Effects on recreation and hobbies; and 11- Expectations of the obsessive wife from her husband. Each of the main categories included subcategories, totaling 44 items.The results showed that living with a spouse with a cleanliness obsession, at least for some people, presents specific challenges that require attention, precision, and adaptation, and this issue can also be considered in pre- and post-marital counseling.
The remarkable capacity of bound states in the continuum (BICs) to confine light and enhance light–matter interactions renders them highly promising for advanced photonic applications. In this work, we propose two asymmetric strategies for realizing high-quality quasi-BICs in bulk tungsten disulfide (WS₂) metasurfaces: one employing a circular air hole and the other utilizing an asymmetric lateral shift of a single nanorod within the unit cell. The reflectance spectra of these asymmetric metasurfaces exhibit tunable quasi-BIC resonances whose quality (Q) factors depend strongly on the asymmetry parameter, achieving values as high as 2 × 10⁵ at asymmetry levels of 0.35
Dependable transfer of brain signals from motor imagery EEG must adhere to strict latency and memory constraints while maintaining accuracy in the face of noise and drift. A hybrid Echo State Network-Long Short-Term Memory (ESN-LSTM) pipeline is shown here. This pipeline combines robust preprocessing with automatic time-lag alignment between predictions and targets. To capture structure lost by linear errors alone, the evaluation combines traditional regression metrics (MSE/MAE/R 2) with nonlinear dependence measures (time-resolved distance correlation and HHG omnibus testing). A leave-one-subject-out (LOSO) procedure is used to investigate cross-subject generalization, and multi-signal-to-noise ratio (SNR) stress tests are conducted to evaluate robustness. In ablation experiments, the impact of filtering, normalization, alignment, and important hyperparameters (reservoir size/spectral radius/leak; LSTM layers/hidden/dropout) is isolated. On the other hand, an efficiency snapshot reports latency and RAM usage under identical workloads for ESN-Only, LSTM-Only, and ESN-LSTM modes. Across all participants, the hybrid consistently improves explained variance and dependence scores while maintaining a controlled computational cost, indicating that it is feasible for near-real-time use. All tables and Figures are regenerated from logged CSVs using scripts, configuration files, and fixed seeds. This ensures that reproducibility is maintained.
This study optimizes reservoir operation for water quality enhancement by determining optimal withdrawal amounts. A meta-model-based optimization simulation approach is employed to improve outflow quality, addressing downstream water demands. Hydrodynamic and water quality simulations for the Ekbatan Dam were performed using the CE-QUAL-W2 (Comprehensive Water Quality - Water Quality Model 2) model. To mitigate computational costs associated with multiple CE-QUAL-W2 calls, a Supervised Learning (SL) surrogate model was developed and integrated with the Fruit-fly Optimization Algorithm (FOA), forming FOA-SL, for estimating Total Dissolved Solids (TDS) and minimizing outflow TDS concentration. The CE-QUAL-W2 model was calibrated and validated using 2019–2020 data, achieving acceptable performance metrics (NSE, MAE, RMSE). FOA-SL demonstrated rapid convergence, reaching solutions in just 300 iterations compared to 1,000,000 iterations for the standalone FOA. A comparative analysis with the Genetic Algorithm (GA) for operational optimization revealed that FOA-SL achieved superior objective function values (lower TDS). While GA offered faster individual run times (approximately 38 min), FOA-SL achieved greater accuracy. The optimized operation led to an approximate 0.3
