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Search Results (2,282)

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2 pages, 137 KB  
Correction
Correction: Atangana et al. Adsorption of Organic Pollutants from Wastewater Using Chitosan-Based Adsorbents. Polymers 2025, 17, 502
by Ernestine Atangana, Timothy Oladiran Ajiboye, Abolaji Abiodun Mafolasire, Soumya Ghosh and Bello Hakeem
Polymers 2026, 18(2), 225; https://doi.org/10.3390/polym18020225 - 15 Jan 2026
Abstract
There were some errors in the original publication [...] Full article
(This article belongs to the Section Circular and Green Sustainable Polymer Science)
18 pages, 1081 KB  
Review
Pharmacogenomics and Opioid Efficacy in Sickle Cell Disease
by Rabab H. Elshaikh, Asaad M. Babker, Sanaa Elfatih Hussein, Khalid Abdelsamea Mohamed Ahmed, Ashok Kumar Sah and Ayman Hussein Alfeel
Medicina 2026, 62(1), 172; https://doi.org/10.3390/medicina62010172 - 15 Jan 2026
Abstract
The impact of genetic variation in sickle cell patients plays a significant role in opioid therapy individual response and pain management. This review aims to provide a comprehensive overview of the importance of exploring genetic variability and its impact on pain management in [...] Read more.
The impact of genetic variation in sickle cell patients plays a significant role in opioid therapy individual response and pain management. This review aims to provide a comprehensive overview of the importance of exploring genetic variability and its impact on pain management in patients with sickle cell disease. It also explores opioid therapy variability and opioid Safety. With respect to literature, the polymorphisms in the key metabolic enzymes CYP2D6, UGT2B7, and COMT, as well as variations in the OPRM1, are important modifiers of the pharmacokinetics and pharmacodynamics of opioids. Variations in the COMT gene can influence how the body manages certain brain chemicals and how pain is experienced, while changes in the OPRM1 gene can alter how well opioids bind to their receptors. They help determine how opioids are broken down in the body, how well they attach to pain receptors, and how pain is felt by someone with sickle cell disease. Patients with reduced-function and ultra-rapid CYP2D6 alleles have a modified metabolism of codeine and tramadol, which presents either a reduced analgesic response or a risk for increased toxicity. These observations support the case for the need for tailored opioid prescriptions in a population that is genetically diverse, as well as the risk of not having standardized pain measurement, and the absence of clinical implementation. There remains the risk of unrecognized pharmacogenomics, lack of data, and personalized opioid descriptions persist. Future research should focus on integrating genetic testing into clinical practice to optimize opioid selection, personalize medicine, minimize adverse effects, and ensure each patient receives treatment that is both effective and safe to enhance quality of life for individuals with sickle cell disease. Full article
(This article belongs to the Section Hematology and Immunology)
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15 pages, 3341 KB  
Article
Probabilistic Modeling and Pattern Discovery-Based Sindhi Information Retrieval System
by Dil Nawaz Hakro, Abdullah Abbasi, Anjum Zameer Bhat, Saleem Raza, Muhammad Babar and Osama Al Rahbi
Information 2026, 17(1), 82; https://doi.org/10.3390/info17010082 - 13 Jan 2026
Viewed by 38
Abstract
Natural language processing is the technology used to interact with computers using human languages. An overlapping technology is Information Retrieval (IR), in which a user searches for the demanded or required documents from among a number of documents that are already stored. The [...] Read more.
Natural language processing is the technology used to interact with computers using human languages. An overlapping technology is Information Retrieval (IR), in which a user searches for the demanded or required documents from among a number of documents that are already stored. The required document is retrieved according to the relevance of the query of the user, and the results are presented in descending order. Many of the languages have their own IR systems, whereas a dedicated IR system for Sindhi still needs attention. Various approaches to effective information retrieval have been proposed. As Sindhi is an old language with a rich history and literature, it needs IR. For the development of Sindhi IR, a document database is required so that the documents can be retrieved accordingly. Many Sindhi documents were identified and collected from various sources, such as books, journal, magazines, and newspapers. These documents were identified as having potential for use in indexing and other forms of processing. Probabilistic modeling and pattern discovery were used to find patterns and for effective retrieval and relevancy. The results for Sindhi Information Retrieval systems are promising and presented more than 90% relevancy. The time elapsed was recorded as ranging from 0.2 to 4.8 s for a single word and 4.6 s with a Sindhi sentence, with the same starting time of 0.2 s. The IR system for Sindhi can be fine-tuned and utilized for other languages with the same characteristics, which adopt Arabic script. Full article
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17 pages, 1573 KB  
Article
From Risk to Returns: An Analysis of Asset Quality, Financial Ratios, and Market Valuation in Indian Banks
by Shireen Rosario and Sudha Mavuri
Risks 2026, 14(1), 16; https://doi.org/10.3390/risks14010016 - 13 Jan 2026
Viewed by 40
Abstract
This study investigates the interplay between asset quality, financial ratios, and market valuation in Indian commercial banks over a twelve-year period (2014–2025). Using a hybrid approach combining Structural Equation Modeling, correlation analysis, and trend evaluation, the research examines whether Non-Performing Assets (NPAs) influence [...] Read more.
This study investigates the interplay between asset quality, financial ratios, and market valuation in Indian commercial banks over a twelve-year period (2014–2025). Using a hybrid approach combining Structural Equation Modeling, correlation analysis, and trend evaluation, the research examines whether Non-Performing Assets (NPAs) influence market capitalization directly or through Return on Equity (ROE) as an intermediary. The findings reveal that NPAs exert a significant negative impact on both ROE and market value, while Net Interest Margin (NIM) emerges as a strong positive determinant of valuation. Conversely, Capital Adequacy Ratio (CAR), though vital for regulatory compliance, shows no direct effect on market prices. Mediation analysis challenges conventional assumptions, indicating that profitability alone does not fully explain valuation dynamics. These insights underscore the need for integrated strategies addressing asset quality and operational efficiency, offering practical implications for policymakers, investors, and bank management in strengthening resilience and optimizing shareholder value. Full article
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16 pages, 1663 KB  
Article
Unveiling the HIV Landscape in Oman: A Retrospective Study of Prevalence, Risk Factors, Treatment Efficacy and Clinical Outcomes
by Mohan B. Sannathimmappa, Salima Al-Maqbali, Chhaya Divecha, Manjiri Hawal, Rajeev Aravindakshan, Khamis Al-Hosni, Elham Said Al-Risi and Vinod Nambiar
Sci 2026, 8(1), 16; https://doi.org/10.3390/sci8010016 - 13 Jan 2026
Viewed by 71
Abstract
Introduction: The sustained global epidemic of Human Immunodeficiency Virus (HIV) necessitates comprehensive, region-specific surveillance to inform public health policy. This 30-year retrospective observational cohort study delineated the epidemiological patterns, transmission dynamics, treatment efficacy, and long-term clinical outcomes of HIV infection in Oman to [...] Read more.
Introduction: The sustained global epidemic of Human Immunodeficiency Virus (HIV) necessitates comprehensive, region-specific surveillance to inform public health policy. This 30-year retrospective observational cohort study delineated the epidemiological patterns, transmission dynamics, treatment efficacy, and long-term clinical outcomes of HIV infection in Oman to strategically align preventative and therapeutic programs with Oman’s Vision 2040 framework. Methods: We analyzed the clinical and epidemiological data of 429 confirmed HIV-positive patients with a minimum follow-up period of six months, registered at a secondary care facility in North Batinah, Oman, between January 1995 and December 2024. Predictors of mortality were rigorously assessed utilizing Kaplan–Meier survival analysis and Cox proportional hazards regression models. Continuous variables were evaluated using independent sample t-tests or Mann–Whitney U tests, while categorical variables employed chi-square or Fisher’s exact tests. Results: The cohort exhibited a male predominance (70.6%) with a mean age at diagnosis of 32.8 years (SD ± 12.17). Heterosexual contact constituted the predominant mode of acquisition (56%), followed by bisexual (17%) and homosexual (12%) contacts. Although 67.1% of patients presented with early, asymptomatic disease (WHO Stage 1), opportunistic infections were evident in 28.1% of the cohort, with recurrent sepsis (8.4%) and bacterial pneumonia (3.5%) being the most frequent complications. The WHO clinical stage at presentation was confirmed as a highly significant predictor of survival (p < 0.0001). Stage 1 patients achieved excellent long-term prognosis (approximately 75% survival beyond 30 years), markedly contrasting with Stage 4 patients, whose survival declined sharply (median survival of approximately 8 years, and only 10–15% surviving past 20 years). The tenofovir/emtricitabine/efavirenz regimen showed superior efficacy, achieving 75% survival at 30 years, relative to zidovudine-based regimens, which showed significantly poorer performance (15–20% survival at 20 years). Conclusions: This investigation substantiates the shift toward predominant heterosexual transmission and emphasizes the critical prognostic significance of the clinical stage at diagnosis. Optimal long-term survival mandates prompt diagnosis, timely initiation of contemporary antiretroviral therapies, and sustained viral suppression. These findings offer crucial evidence to strengthen HIV prevention and treatment programs within Oman. Full article
(This article belongs to the Section Biology Research and Life Sciences)
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30 pages, 6746 KB  
Article
Securing IoT Networks Using Machine Learning-Resistant Physical Unclonable Functions (PUFs) on Edge Devices
by Abdul Manan Sheikh, Md. Rafiqul Islam, Mohamed Hadi Habaebi, Suriza Ahmad Zabidi, Athaur Rahman bin Najeeb and Mazhar Baloch
Network 2026, 6(1), 6; https://doi.org/10.3390/network6010006 - 12 Jan 2026
Viewed by 100
Abstract
The Internet of Things (IoT) has transformed global connectivity by linking people, smart devices, and data. However, as the number of connected devices continues to grow, ensuring secure data transmission and communication has become increasingly challenging. IoT security threats arise at the device [...] Read more.
The Internet of Things (IoT) has transformed global connectivity by linking people, smart devices, and data. However, as the number of connected devices continues to grow, ensuring secure data transmission and communication has become increasingly challenging. IoT security threats arise at the device level due to limited computing resources, mobility, and the large diversity of devices, as well as at the network level, where the use of varied protocols by different vendors introduces further vulnerabilities. Physical Unclonable Functions (PUFs) provide a lightweight, hardware-based security primitive that exploits inherent device-specific variations to ensure uniqueness, unpredictability, and enhanced protection of data and user privacy. Additionally, modeling attacks against PUF architectures is challenging due to the random and unpredictable physical variations inherent in their design, making it nearly impossible for attackers to accurately replicate their unique responses. This study collected approximately 80,000 Challenge Response Pairs (CRPs) from a Ring Oscillator (RO) PUF design to evaluate its resilience against modeling attacks. The predictive performance of five machine learning algorithms, i.e., Support Vector Machines, Logistic Regression, Artificial Neural Networks with a Multilayer Perceptron, K-Nearest Neighbors, and Gradient Boosting, was analyzed, and the results showed an average accuracy of approximately 60%, demonstrating the strong resistance of the RO PUF to these attacks. The NIST statistical test suite was applied to the CRP data of the RO PUF to evaluate its randomness quality. The p-values from the 15 statistical tests confirm that the CRP data exhibit true randomness, with most values exceeding the 0.01 threshold and supporting the null hypothesis of randomness. Full article
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22 pages, 3447 KB  
Article
Leveraging Machine Learning Flood Forecasting: A Multi-Dimensional Approach to Hydrological Predictive Modeling
by Ghazi Al-Rawas, Mohammad Reza Nikoo, Nasim Sadra and Malik Al-Wardy
Water 2026, 18(2), 192; https://doi.org/10.3390/w18020192 - 12 Jan 2026
Viewed by 100
Abstract
Flash flood events are some of the most life-threatening natural disasters, so it is important to predict extreme rainfall events effectively. This study introduces an LSTM model that utilizes a customized loss function to effectively predict extreme rainfall events. The proposed model incorporates [...] Read more.
Flash flood events are some of the most life-threatening natural disasters, so it is important to predict extreme rainfall events effectively. This study introduces an LSTM model that utilizes a customized loss function to effectively predict extreme rainfall events. The proposed model incorporates dynamic environmental variables, such as rainfall, LST, and NDVI, and incorporates additional static variables such as soil type and proximity to infrastructure. Wavelet transformation decomposes the time series into low- and high-frequency components to isolate long-term trends and short-term events. Model performance was compared against Random Forest (RF), Support Vector Machines (SVMs), Artificial Neural Networks (ANNs), and an LSTM-RF ensemble. The custom loss LSTM achieved the best performance (MAE = 0.022 mm/day, RMSE = 0.110 mm/day, R2 = 0.807, SMAPE = 7.62%), with statistical validation via a Kruskal–Wallis ANOVA, confirming that the improvement is significant. Model uncertainty is quantified using a Bayesian MCMC framework, yielding posterior estimates and credible intervals that explicitly characterize predictive uncertainty under extreme rainfall conditions. The sensitivity analysis highlights rainfall and LST as the most influential predictors, while wavelet decomposition provides multi-scale insights into environmental dynamics. The study concludes that customized loss functions can be highly effective in extreme rainfall event prediction and thus useful in managing flash flood events. Full article
(This article belongs to the Section Hydrology)
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30 pages, 2181 KB  
Review
Ready-to-Eat Sandwich Microbiota: Diversity, Antibiotic Resistance, and Strategies to Enhance Food Safety
by Ismail M. Al-Bulushi, Zahra S. Al-Kharousi, Mohammed K. Al-Khusaibi, Kamla N. Al-Sarmi and Mohamedsaid Albloushi
Foods 2026, 15(2), 251; https://doi.org/10.3390/foods15020251 - 10 Jan 2026
Viewed by 286
Abstract
Ready-to-eat (RTE) sandwiches are consumed globally due to their convenience, availability, and affordability. Sandwich processing practices and their ingredients expose the sandwiches to various sources of contamination, which can enhance their microbial diversity and introduce certain pathogenic and spoilage bacteria, thereby affecting their [...] Read more.
Ready-to-eat (RTE) sandwiches are consumed globally due to their convenience, availability, and affordability. Sandwich processing practices and their ingredients expose the sandwiches to various sources of contamination, which can enhance their microbial diversity and introduce certain pathogenic and spoilage bacteria, thereby affecting their safety and quality. Sandwiches may not receive safe cooking temperatures sufficient to destroy food poisoning bacteria, as they are often cooked and served quickly to meet high consumer demand. Improper storage temperatures can enhance microbial growth, and frequent improper handling makes this food a good vehicle for various pathogens such as Escherichia coli, Listeria monocytogenes, Salmonella spp., Staphylococcus aureus, and norovirus. Many pathogenic sandwich-associated bacteria, such as L. monocytogenes, showed resistance to clinically important antibiotics. Sandwich microbiota have been investigated; however, their diversity, antimicrobial resistance, and importance to sandwich safety and quality have been rarely reviewed. Therefore, this review elucidates the diversity of sandwich microbiota as an impact of ingredients, handling practices, and storage, with emphasis on the importance of this diversity on sandwich safety and quality. It also discusses strategies, control measures, and recommendations to reduce the risk of contamination of sandwiches with pathogenic bacteria or their antibiotic resistance genes, thereby safeguarding public health. Full article
(This article belongs to the Section Food Microbiology)
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14 pages, 290 KB  
Article
Nagata and Serre Conjecture Rings: A Unified Pullback Perspective
by Noômen Jarboui and Bana Al Subaiei
Mathematics 2026, 14(2), 237; https://doi.org/10.3390/math14020237 - 8 Jan 2026
Viewed by 84
Abstract
We study the strong S-property for Nagata and Serre conjecture rings through the framework of (T,M,D) construction rings, providing a unified approach that streamlines and extends previous results. Our main contribution is a concise, conceptual proof [...] Read more.
We study the strong S-property for Nagata and Serre conjecture rings through the framework of (T,M,D) construction rings, providing a unified approach that streamlines and extends previous results. Our main contribution is a concise, conceptual proof showing that the strong S-property of R(X) versus RX depends solely on the transcendence degree of the residue field extension K/k, where k is the quotient field of D. This perspective yields new, transparent counterexamples to both the Malik–Mott conjecture and a question of Cahen et al., and provides a clear characterization of the catenarity of Serre conjecture rings, Rn. The approach is based on pullback constructions and the geometric structure of prime ideals, replacing intricate case analyses with arguments driven by natural invariants. Full article
(This article belongs to the Special Issue Advanced Research in Pure and Applied Algebra, 2nd Edition)
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16 pages, 278 KB  
Article
Investigating Course Level Effects on Student Evaluations of Teaching in Higher Education
by William M. Bart, Mohammed A. A. Abulela and Mustafa Ali Khalaf
Educ. Sci. 2026, 16(1), 94; https://doi.org/10.3390/educsci16010094 - 8 Jan 2026
Viewed by 183
Abstract
Although student evaluations of teaching (SET) in higher education have recently gained considerable interest, little is known about whether course level influences these evaluations. Accordingly, two datasets, obtained from a large public university in the U.S. Midwest, were analyzed to investigate whether course [...] Read more.
Although student evaluations of teaching (SET) in higher education have recently gained considerable interest, little is known about whether course level influences these evaluations. Accordingly, two datasets, obtained from a large public university in the U.S. Midwest, were analyzed to investigate whether course level makes a difference in SET. The first dataset included 25,306 evaluations across eight course levels collected using the SET questionnaire. A one-way multivariate analysis of variance (MANOVA), followed by univariate analyses of variance (ANOVAs), was conducted to test whether course level makes a difference in SET scores. To cross-validate the results and ensure generalizability, the same analyses were conducted using a second, smaller dataset (N = 444). MANOVA results revealed a statistically significant effect for course level on the combined SET dimensions across both campuses. All univariate ANOVAs were also significant across both campuses. Follow-up post hoc comparisons, with level 1 as the reference group, were statistically significant, especially for level 8. Overall, these results underscore the importance of accounting for course level when interpreting SET and encourage researchers to include key covariates (e.g., class size, discipline, instructor experience, and student composition) to identify the factors driving course-level differences. Full article
(This article belongs to the Section Higher Education)
27 pages, 1133 KB  
Review
Recent Advances in Scaling Up Microbial Fuel Cell Systems for Wastewater Treatment, Energy Recovery, and Environmental Sustainability
by Tahereh Jafary, Ali Mousavi, Anteneh Mesfin Yeneneh, Mohammed Saif Al-Kalbani and Buthaina Mahfoud Al-Wahaibi
Sustainability 2026, 18(2), 638; https://doi.org/10.3390/su18020638 - 8 Jan 2026
Viewed by 169
Abstract
Microbial fuel cells (MFCs) are a promising technology for simultaneously treating wastewater and recovering energy, yet scaling them from lab prototypes to practical systems poses persistent challenges. This review addresses the scale-up gap by systematically examining recent pilot-scale MFC studies from multiple perspectives, [...] Read more.
Microbial fuel cells (MFCs) are a promising technology for simultaneously treating wastewater and recovering energy, yet scaling them from lab prototypes to practical systems poses persistent challenges. This review addresses the scale-up gap by systematically examining recent pilot-scale MFC studies from multiple perspectives, including reactor design configurations, materials innovations, treatment performance, energy recovery, and environmental impact. The findings show that pilot MFCs reliably achieve significant chemical oxygen demand (COD) removal (often 50–90%), but power densities remain modest (typically 0.1–10 W m−3)—far below levels needed for major energy generation. Key engineering advances have improved performance; modular stacking maintains higher power output, low-cost electrodes and membranes reduce costs (with some efficiency trade-offs), and power-management strategies mitigate issues like cell reversal. Life cycle assessments indicate that while MFC systems can outperform conventional treatment in specific scenarios, overall sustainability gains depend on boosting energy yields and optimizing materials. The findings highlight common trade-offs and emerging strategies. By consolidating recent insights, a roadmap of design principles and research directions to advance MFC technology toward sustainable, energy-positive wastewater treatment was outlined. Full article
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22 pages, 1330 KB  
Article
Configurational Pathways to Technology Venture Creation: How Spousal Endorsement and Informal Support Enable Omani Women’s Entrepreneurship
by Husam N. Yasin, Samir Hammami, Ahmed Samour and Faris Alshubiri
Adm. Sci. 2026, 16(1), 32; https://doi.org/10.3390/admsci16010032 - 8 Jan 2026
Viewed by 155
Abstract
This study investigates the configurational pathways enabling women in Oman to translate entrepreneurial intentions into technology venture creation. By integrating institutional theory and resource-based view, we develop a novel framework examining how formal institutional support (FIS), informal institutional support (IIS), and digital self-efficacy [...] Read more.
This study investigates the configurational pathways enabling women in Oman to translate entrepreneurial intentions into technology venture creation. By integrating institutional theory and resource-based view, we develop a novel framework examining how formal institutional support (FIS), informal institutional support (IIS), and digital self-efficacy (DSE) interact in Oman’s conservative context. We emphasize the significant enabling role of work–life balance resources (WLBR) and the cultural legitimacy of spousal endorsement. Our mixed-methods design utilizes survey data from 418 female IT graduates and 20 semi-structured interviews, analyzed through fuzzy-set Qualitative Comparative Analysis (fsQCA). The findings indicate that FIS predicts entrepreneurial intention (β = 0.34, p < 0.001) but not venture creation (OR = 0.85, p = 0.298), revealing a visibility gap in policy implementation. IIS predicts venture creation (OR = 1.43, p = 0.033), with spousal endorsement acting as a cultural legitimacy signal. DSE alone fails to predict venture creation but is vital when combined with WLBR. FsQCA identifies a sufficient configuration pathway characterized by the combination of spousal endorsement, domestic support, DSE, and WLBR with solution consistency of 0.93 and coverage of 0.78. WLBR is a necessary condition with necessity consistency of 0.96, demonstrating that venture creation is improbable without it. Qualitative evidence shows founders reposition conservative norms as legitimacy signals, while non-founders emphasize funding barriers despite policy awareness. We recommend that policymakers subsidize care infrastructure, leverage women-led community networks for targeted outreach, and formalize state-backed legitimacy programs that reduce kinship dependency while building autonomy-focused alternatives. Full article
(This article belongs to the Section Gender, Race and Diversity in Organizations)
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16 pages, 5352 KB  
Article
CIGS Electrodeposition from Diluted Electrolyte: Effect of Current Density and Pulse Timing on Deposition Quality and Film Properties
by Mahfouz Saeed
Chemistry 2026, 8(1), 6; https://doi.org/10.3390/chemistry8010006 - 8 Jan 2026
Viewed by 113
Abstract
Among the most promising alloys for photovoltaic applications is copper–indium–gallium–selenide (CIGS) because of its enhanced optical properties. This study examines the influence of current density and pulse timing on the electrodeposition of Cu(In, Ga)Se2 (CIGS) thin films from a dilute electrolyte. It [...] Read more.
Among the most promising alloys for photovoltaic applications is copper–indium–gallium–selenide (CIGS) because of its enhanced optical properties. This study examines the influence of current density and pulse timing on the electrodeposition of Cu(In, Ga)Se2 (CIGS) thin films from a dilute electrolyte. It assesses how these parameters affect deposition quality, film characteristics, and device performance. CIGS absorber layers were electrodeposited using a pulsed-current method, with systematic variations in current density and pulse on/off durations in a low-concentration solution. The deposited precursors were subsequently selenized and incorporated into fully assembled CIGS solar cell architectures. Structural characteristics were analyzed by X-ray diffraction (XRD), whereas composition and elemental distribution were assessed by energy-dispersive X-ray spectroscopy (EDS). Optical properties pertinent to photovoltaic performance were evaluated through transmittance and reflectance measurements. The results indicate that moderate current densities, when combined with brief off-times, produce dense, microcrack-free films exhibiting enhanced crystallinity and near-stoichiometric Cu/(In + Ga) and Ga/(In + Ga) ratios, in contrast to films deposited at higher current densities and extended off-times. These optimized pulse parameters also produce absorber layers with advantageous optical band gaps and improved device performance. Overall, the study demonstrates that regulating pulse parameters in attenuated electrolytes is an effective strategy to optimize CIGS film quality and to facilitate the advancement of economical, solution-based fabrication methods for high-performance CIGS solar cells. Full article
(This article belongs to the Section Electrochemistry and Photoredox Processes)
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42 pages, 1583 KB  
Article
Hybrid Sine–Cosine with Hummingbird Foraging Algorithm for Engineering Design Optimisation
by Jamal Zraqou, Ahmad Sami Al-Shamayleh, Riyad Alrousan, Hussam Fakhouri, Faten Hamad and Niveen Halalsheh
Computers 2026, 15(1), 35; https://doi.org/10.3390/computers15010035 - 7 Jan 2026
Viewed by 93
Abstract
We introduce AHA–SCA, a compact hybrid optimiser that alternates the wave-based exploration of the Sine–Cosine Algorithm (SCA) with the exploitation skills of the Artificial Hummingbird Algorithm (AHA) within a single population. Even iterations perform SCA moves with a linearly decaying sinusoidal amplitude to [...] Read more.
We introduce AHA–SCA, a compact hybrid optimiser that alternates the wave-based exploration of the Sine–Cosine Algorithm (SCA) with the exploitation skills of the Artificial Hummingbird Algorithm (AHA) within a single population. Even iterations perform SCA moves with a linearly decaying sinusoidal amplitude to explore widely around the current best solution, while odd iterations invoke guided and territorial hummingbird flights using axial, diagonal, and omnidirectional patterns to intensify the search in promising regions. This simple interleaving yields an explicit and tunable balance between exploration and exploitation and incurs negligible overhead beyond evaluating candidate solutions. The proposed approach is evaluated on the CEC2014, CEC2017, and CEC2022 benchmark suites and on several constrained engineering design problems, including welded beam, pressure vessel, tension/compression spring, speed reducer, and cantilever beam designs. Across these diverse tasks, AHA–SCA demonstrates competitive or superior performance relative to stand-alone SCA, AHA, and a broad panel of recent metaheuristics, delivering faster early-phase convergence and robust final solutions. Statistical analyses using non-parametric tests confirm that improvements are significant on many functions, and the method respects problem constraints without parameter tuning. The results suggest that alternating wave-driven exploration with hummingbird-inspired refinement is a promising general strategy for continuous engineering optimisation. Full article
(This article belongs to the Special Issue AI in Complex Engineering Systems)
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20 pages, 4080 KB  
Article
Integrated Preflash Drum Optimisation for Energy Efficiency and Profitability in Crude Distillation Units
by Sharif H. Zein, Chukwuchetam A. Akakuru, Khalaf J. Jabbar, Usama Ahmed and A. A. Jalil
ChemEngineering 2026, 10(1), 7; https://doi.org/10.3390/chemengineering10010007 - 7 Jan 2026
Viewed by 248
Abstract
Crude distillation units operate as the most energy-intensive refinery operations and generate substantial carbon dioxide emissions. This research models the crude distillation system through its three main components: the atmospheric distillation unit, the naphtha stabilisation unit, and the vacuum distillation unit. The simulation [...] Read more.
Crude distillation units operate as the most energy-intensive refinery operations and generate substantial carbon dioxide emissions. This research models the crude distillation system through its three main components: the atmospheric distillation unit, the naphtha stabilisation unit, and the vacuum distillation unit. The simulation platform Aspen HYSYS version 14.1 enabled optimisation of the preflash drum under product quality constraints, and the analysis included pinch analysis techniques and techno-economic evaluation. The optimisation results demonstrated an 8.95% reduction in atmospheric furnace duty, a 7.38% decrease in total hot utility consumption with the crude distillation system, and an increase in heat recovery capability from 35.57% to 42.71%. Although the preflash process alone decreases profitability because of increased steam demand, combining preflash operation with heat recovery measures maintains both energy conservation and favourable economic performance. The study shows that refinery optimisation requires treating the crude distillation system as a fully integrated process. This approach offers effective strategies to improve energy performance and reduce carbon dioxide emissions while sustaining economic viability. The work differs from previous studies by evaluating the entire distillation system as an integrated sequence and demonstrating how preflash optimisation affects overall energy demand, heat-recovery potential, and economic outcomes while maintaining product quality. Full article
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