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Thermophysical Property Prediction of R32, R1234yf, and R454B Refrigerants Using Artificial Neural Networks
No full textAccurate prediction of the thermophysical properties of next-generation refrigerants is essential to improving the energy efficiency and environmental compatibility of cooling systems. Therefore, this paper developed an artificial neural network-based data-driven framework for the prediction of the density and viscosity of R32, R1234yf, and R454B at a wide range of temperatures (Ts) and pressures (Ps). Extensive datasets, validated by high-accuracy experimental measurements, were used to train and validate multilayer feedforward networks developed to provide nonlinear thermodynamic dependency features. The resulting models displayed good quantitative accuracy on all refrigerants. The root mean square errors regarding R32 were found to be 40.70 kg/ m3 density and 0.0237 mPa center dot s viscosity, while the coefficients of determination of 0.98031 and 0.97195 were achieved for density and viscosity, respectively. In the case of R1234yf, the foregoing errors were 51.07 kg/m3 and 0.0256 mPa center dot s. Meanwhile, the coefficients were given as 0.96488 and 0.97983. The R454B model achieved the Maximum (Max) performance with 22.01 kg/m3 errors concerning density and 0.0044 mPa center dot s concerning viscosity, while attaining correlation coefficients of 0.99895 and 0.9937, respectively. Relative error analysis showed that all refrigerants had Maximum and mean deviations below 8 % and 25 %, respectively, for density and viscosity. That trend in predictions confirmed that density increased as T gradually increased, remaining nearly P-independent, while viscosity decreased nonlinearly with increasing T. The viscosity sets themselves showed little sensitivity to P. These results could validate the highly accurate and computationally efficient capabilities of artificial neural networks to replicate complex thermophysical behavior, as above, and hence serve as a rigorous alternative to empirical correlations for predictive design of sustainable refrigeration and airconditioning systems.Deanship of Research and Graduate Studies at King Khalid University, Saudi Arabia [RGP2/150/46]The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University, Saudi Arabia for funding this work through large Research Project under grant number RGP2/150/46.Science Citation Index Expande
Gypsum Integrated Phase Change Materials for Thermal Energy Efficiency in Buildings: A Review
No full textSadeq, Abdellatif M/0000-0002-0654-7774;Global energy consumption for heating and cooling in buildings, accounting for approximately 32 % of total energy use, demonstrating a critical challenge worsened by urban expansion and climate change, necessitating innovative solutions for building thermal efficiency. This review addresses this request by systematically analysing the integration of phase change materials (PCMs) with gypsum for enhanced building thermal management. The comprehensive literature review, spanning from 2010 to 2025, reveals that PCM-gypsum composites can significantly improve temperature stabilization and user comfort. Key insights include the identification of optimal PCM loading ranges, with 30 %-45 % by weight yielding the best thermal properties while maintaining adequate mechanical strength. However, higher PCM loadings can lead to mechanical weaknesses, necessitating a careful balance between thermal performance and structural integrity. Laboratory tests reveal these composites absorb 30-40 J/g of latent heat and achieve significant thermal conductivity reductions, up to 55.14 % compared to pure gypsum. For instance, heating gypsum walls with 7.5 % micro-capsule content resulted in 1.3 degrees C maximum temperature stability. Furthermore, lauryl alcohol-impregnated gypsum composites exhibited minimal thermal performance degradation after 1500 cycles, maintaining high enthalpy values (100.4-100.1 J/g). This review highlights PCM-enhanced gypsum as a sustainable solution for energy-efficient buildings, aiding waste utilisation, minimising carbon emissions, and improving indoor comfort, crucial for addressing future energy demands in climate-altered structures. Furthermore, the use of microencapsulated PCMs (mPCMs) can improve leakage protection amd thus enhanced durability. In this regard, the thermal conductivity of gypsum-based composites is around 0.4165 W/(m K) at a 40 % volume loading. This is an additional reducible with shape-stabilized PCMs derived from agricultural byproducts. The results of this review have signified the PCM-enhanced gypsum as a sustainable solution for energy-effective buildings, helping to minimize the waste utilisation besides reducing carbon emissions while upgrading indoor comfort. However, a focus should be made in the future research to resolve the associated barriers of compatibility between encapsulated PCMs, leakage deterrence at high PCM loadings and gypsum matrix, and long-term mechanical stability. Undoubtedly, exploring enhanced encapsulation techniques and integrated smart building materials would introduce innovative, energy-autonomous buildings that can familiarize different climatic conditions, expressively contributing to sustainable architectural practices
Higher-Order Nonlinear Schrödinger Equation: Conservation Laws, Soliton Dynamics, and Bifurcation Analysis
No full textThe higher-order nonlinear Schrödinger equation (h-oNLSE) with cubic–quintic nonlinearity governs the propagation of ultrashort optical pulses in nonlinear fiber systems and plasma environments, where higher-order dispersive and nonlinear perturbations crucially affect pulse stability and shape. Despite extensive studies, the interplay of cubic–quintic nonlinearities with higher-order effects remains insufficiently characterized. In this work, we develop a generalized analytical framework based on a Modified Sardar Sub-Equation Method (mSSEM) to construct new classes of exact solutions to the higher-order cubic–quintic NLSE. This approach systematically uncovers diverse nonlinear waveforms, including previously inaccessible bright and dark solitons, periodic states, and singular structures. Importantly, our results reveal how higher-order dispersion and nonlinear contributions reshape amplitude-phase coupling and stability regimes, offering predictive insights into ultrafast pulse dynamics. By bridging analytical theory with experimentally relevant scenarios in optics and plasma physics, these findings extend the fundamental solution landscape of the cubic–quintic NLSE and establish a versatile methodology applicable across nonlinear evolution equations in applied mathematics and wave science. For the (h-oNLSE) with cubic–quintic nonlinearity, the associated conservation laws have been identified. The analysis confirms the presence of three fundamental conserved quantities corresponding to the bright soliton solutions of the equation. The essential features and physical significance of the conservation laws are discussed, highlighting their role in ensuring the stability and persistence of soliton structures in nonlinear optical media. © 2026 World Scientific Publishing Company
Brain Oscillations in Bipolar Disorder: Insights from Quantitative EEG Studies
No full textIntroduction: Quantitative electroencephalography (QEEG) is a neurophysiological tool that analyzes brain oscillations across frequency bands, providing insights into psychiatric conditions like bipolar disorder (BD). This disorder, marked by mood fluctuations, poses diagnostic and treatment challenges, highlighting the need for reliable biomarkers. Objective: This systematic review aims to evaluate QEEG changes in BD patients, investigate its diagnostic and therapeutic potential, and differentiate BD from major depressive disorder (MDD) and schizophrenia. Methods: Following PRISMA 2020 guidelines, a comprehensive search of PubMed, Scopus, Web of Science, and Embase was conducted till 30th of October 2024 without timeline restrictions. Studies involving BD patients assessed using QEEG were included. Key outcomes focused on frequency band alterations, treatment responses, and diagnostic differentiation. Results: The review included 20 studies with 475 BD patients. Increased gamma and beta activity were consistently observed in BD. However, the directionality of alpha and theta band changes varied, with differences observed depending on brain region and mood state. Delta band alterations were more prominent in BD I. Treatment responses showed reduced power in gamma, theta, and alpha bands. QEEG also distinguished BD from MDD and schizophrenia based on frequency band characteristics. Conclusion: QEEG demonstrates significant promise as a diagnostic and therapeutic tool for BD. Despite methodological variability, its integration with machine learning could enhance diagnostic precision and guide personalized treatments. Further research is needed to standardize methodologies and validate findings. © EEG and Clinical Neuroscience Society (ECNS) 2025Science Citation Index Expande
First Exclusive Reconstruction of the (Formula Presented), (Formula Presented), and (Formula Presented) Mesons and Precise Measurement of Their Masses
No full textUsing proton-proton collision data collected by the CMS experiment at (Formula presented) in 2016-2018, corresponding to an integrated luminosity of (Formula presented), the first full reconstruction of the three vector (Formula presented) meson states, (Formula presented), (Formula presented), and (Formula presented), is performed. The mass differences between the excited mesons and their corresponding ground states are measured to be (Formula presented), (Formula presented), and (Formula presented), where the first uncertainties are statistical and the second are systematic. These results improve on the precision of previous measurements by an order of magnitude. © 2026 CERN, for the CMS Collaboration
Corrigendum to “Thermo-Hydraulic Performance Improvement Inside Parabolic Trough Receiver Tube Using Passive Techniques: A Review”
No full textThe authors regret that the affiliation of Dr. Abdellatif M. Sadeq was incorrectly listed in the published article as “Mechanical and Industrial Engineering Department, College of Engineering, Qatar University, Doha, Qatar”. The correct affiliation is updated as above. In addition, the email address linked to Dr. Abdellatif M. Sadeq should be updated as above. The authors would like to apologise for any inconvenience caused. CRediT authorship contribution statement Yasser Abidnoor Jebbar: Conceptualization, Methodology, Writing – original draft. Farhan Lafta Rashid: Writing – original draft, Supervision, Project administration. Mudhar A. Al-Obaidi: Writing – original draft, Formal analysis, Investigation. Wisam J. Khudhayer: Formal analysis, Methodology, Writing – original draft. Ephraim Bonah Agyekum: Visualization, Resources, Investigation. Fadhil Khaddam Fuliful: Writing – review & editing, Validation. Abdellatif M. Sadeq: Funding acquisition, Writing – review & editing. © 2026 Elsevier Lt
An Interval-Valued Pythagorean Trapezoidal Fuzzy Multi-Criteria Decision Making Technique for Psychiatric Disorder Diagnosis
No full textMondal, Sankar Prasad/0000-0003-4690-2598Despite the abundance of reports of mental disorders in medical diagnosis, few studies have employed standard techniques on representative patient groups. Psychiatric disorders are currently the most frequent cause of extended absences due to illness. Fuzzy Multi-Criteria Decision-Making (MCDM) techniques can be helpful in selecting appropriate treatments or interventions for patients with psychiatric disorders. These techniques enable decision-makers to consider multiple criteria that may have varying levels of importance or uncertainty. In this paper, interval-valued Pythagorean trapezoidal fuzzy numbers (IVPTrFN) are used to handle uncertainty or imprecision in a more complex manner. The Fuzzy Analytic Hierarchy Process (FAHP) is used to determine the symptom weight of a patient with a psychiatric disorder. Using this weight, the rank of the alternative disorder of a patient is determined by the Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (FPROMETHEE) technique. Finally, sensitivity and comparative analyses are conducted to assess the reliability and consistency of the results.University Grants Commission (UGC), India [221610157877]; ST FIST Program, Govt. of India [SR/FST/MS-II/2021/101](I) This study received financial support from the University Grants Commission (UGC), India under Ref. No.:221610157877. (II) This research is also partially supported by DST FIST Program, Govt. of India (Ref. No. SR/FST/MS-II/2021/101(C))
Advances in Pyramid Solar Stills: A Comprehensive Review of Sustainable Water Desalination Innovations
No full textThis study presents a comprehensive investigation into recent advancements in pyramid solar stills (PSS), focusing on how internal and external modifications have enhanced both performance and sustainability. The research critically examines the limitations of conventional solar stills in providing clean water and proposes innovative solutions to improve their productivity. Internal improvements like the integration of phase change materials (PCMs), Nanoparticles (e.g., TiO2 and CNT-water Nanofluids), and energy storage materials (e.g., paraffin wax and quartz rock), meaningfully improve desalination output. PCM integration alone enhances water productivity by 35 to 101.5%, while Nanoparticle application assures an efficiency gains ranging between 6.1 to 54.4%. External modifications such as the integration of solar collectors, reflectors, and forced condensation systems, has increased water productivity. Statistically, the with water yield increases to 194% with a thermal efficiency up to 62.4%. Hybrid systems, that integrate multiple modifications, establish the greatest performance enhancements, delivering up to a 166% productivity growth when PCMs and reflectors are utilised in tandem. The results highlight that optimised PSS, developed through multidisciplinary approaches, offer a potential, sustainable, and cost-effective solution for freshwater production. However, a number of barriers linked to component integration and large-scale applications remain. More importantly, the associated findings of this review have stated a foundational framework to advance the design and operation of solar desalination technologies.University of GvleOpen access funding provided by University of Gavle
Inventive Tubular Solar Stills: Improving Desalination Performance Through Phase Change Materials and Upgraded Design for Sustainable Water Solutions
No full textLafta Rashid, Farhan/0000-0002-7609-6585; Al-Obaidi, Mudhar/0000-0002-1713-4860; Kadhim, Saif Ali/0000-0003-0359-5022; M. Ashour, Ali/0009-0000-6664-6638This paper reviews how tubular solar still designs can enhance thermal output and offer a sustainable desalination solution powered by solar energy. Conventional solar stills typically produce only 2-5 L/m(2)/day, highlighting the need for more efficient and practical designs for widespread adoption. Studies categorize performance improvement methods into two primary approaches, with particular emphasis on phase change materials due to their demonstrated efficacy. Experimental data shows that phase change materials can improve the system energy efficiency to a maximum of 30% and boost manufacturing capacity notably while reaching production quantities greater than 6 L/m(2)/day within optimal operating parameters. The review demonstrates how advanced wick materials, vacuum insulation together with reflective surfaces have enhanced both thermal performance and productivity of these systems. Geographical conditions, together with climate variables, influence the success of these enhancement methods; so, specific optimization measures must be developed for different locations. Recent experimental and theoretical research synthesis delivers important pathways for future development, which proves tubular solar stills as sustainable water scarcity solutions that produce less carbon than traditional desalination approaches.Emerging Sources Citation Inde
Mechanical Ventilation Strategies in Buildings: A Comprehensive Review of Climate Management, Indoor Air Quality, and Energy Efficiency
No full textLafta Rashid, Farhan/0000-0002-7609-6585; Chibani, Atef/0000-0002-5861-7498;As the demand for energy-efficient homes continues to rise, the importance of advanced mechanical ventilation systems in maintaining indoor air quality (IAQ) has become increasingly evident. However, challenges related to energy balance, IAQ, and occupant thermal comfort persist. This review examines the performance of mechanical ventilation systems in regulating indoor climate, improving air quality, and minimising energy consumption. The findings indicate that demand-controlled ventilation (DCV) can enhance energy efficiency by up to 88% while maintaining CO2 concentrations below 1000 ppm during 76% of the occupancy period. Heat recovery systems achieve efficiencies of nearly 90%, leading to a reduction in heating energy consumption by approximately 19%. Studies also show that employing mechanical rather than natural ventilation in schools lowers CO2 levels by 20-30%. Nevertheless, occupant misuse or poorly designed systems can result in CO2 concentrations exceeding 1600 ppm in residential environments. Hybrid ventilation systems have demonstrated improved thermal comfort, with predicted mean vote (PMV) values ranging from -0.41 to 0.37 when radiant heating is utilized. Despite ongoing technological advancements, issues such as system durability, user acceptance, and adaptability across climate zones remain. Smart, personalized ventilation strategies supported by modern control algorithms and continuous monitoring are essential for the development of resilient and health-promoting buildings. Future research should prioritize the integration of renewable energy sources and adaptive ventilation controls to further optimise system performance.Science Citation Index Expande