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13 pages, 1649 KB

Open AccessArticle

Functional Prediction of AT5G35460 Reveals Its Regulatory Role in Reproductive Development and Lipid Remodeling in Arabidopsis thaliana

by Muhammad Asif Shabbir, Mustansar Mubeen, Muhammad Umer, Aqleem Abbas, Amjad Ali, Sarmad Ali Qureshi, Muhammad Junaid Rao, Yasir Iftikhar, Esmael M. Alyami and Ahmed Ezzat Ahmed

Membranes 2026, 16(3), 88; https://doi.org/10.3390/membranes16030088 (registering DOI) - 28 Feb 2026

Abstract

Membrane lipid remodeling plays a pivotal role in regulating plant growth, reproductive development, and adaptive responses to environmental stress. However, several lipid-modifying enzymes remain uncharacterized in Arabidopsis thaliana. Here, we provide the first comprehensive in silico functional characterization of the unannotated gene [...] Read more.

Membrane lipid remodeling plays a pivotal role in regulating plant growth, reproductive development, and adaptive responses to environmental stress. However, several lipid-modifying enzymes remain uncharacterized in Arabidopsis thaliana. Here, we provide the first comprehensive in silico functional characterization of the unannotated gene AT5G35460, integrating domain architecture, AlphaFold-supported structural validation, and phylogenetic, expression, and regulatory analyses. Domain architecture and conserved DUF2838 signatures, together with transmembrane topology and validation using AlphaFold-predicted structural data, support its identity as a glycerophosphocholine acyltransferase (GPCAT1). Phylogenetic reconstruction showed that GPCAT1 clustered closely with its orthologs of major angiosperms, suggesting deep evolutionary preservation. Expression profiling revealed over a tenfold higher transcript abundance in mature pollen, detected 6–8 times more than during leaf senescence, indicating strong developmental control. Co-expression network analysis revealed links to the lipid metabolism genes (CDS2, LACS8, and SBH1) as well as factors involved in response to stress, indicating that AT5G35460 may act at the level of phosphatidylcholine remodeling, membrane resistance and stress response. Analysis of the promoter sequences showed AACTAAA, ABRE and G-box elements (pollen-specific, ABA-responsive and stress-inducible motif respectively), suggesting appropriate transcriptional regulation consistent with its expression profile. As a whole, the findings revealed that AT5G35460 is an unexplored membrane-localized acyltransferase involved in lipid maintenance during reproductive development and environmental responses. This study serves as a basis for subsequent functional characterization and identifies AT5G35460 as a potential target for modifying pollen viability, senescence kinetics and stress tolerance in plants. Full article

18 pages, 3855 KB

Open AccessArticle

Airports in SUMP: Multi-Criteria Sustainability Assessment

by Marcin Jacek Kłos, Grzegorz Sierpiński, Grażyna Rosa, Leszek Mindur and Maciej Mindur

Sustainability 2026, 18(5), 2369; https://doi.org/10.3390/su18052369 (registering DOI) - 28 Feb 2026

Abstract

Modern urban transport systems face the critical challenge of fully integrating regional and international hubs into local mobility strategies. This article addresses the role of airports in shaping sustainable urban mobility, with a specific focus on their inclusion in Sustainable Urban Mobility Plans [...] Read more.

Modern urban transport systems face the critical challenge of fully integrating regional and international hubs into local mobility strategies. This article addresses the role of airports in shaping sustainable urban mobility, with a specific focus on their inclusion in Sustainable Urban Mobility Plans (SUMPs). Despite airports being major generators of passenger and freight traffic, they are often treated as isolated “transport islands” in spatial planning. The primary objective of this research is to develop and validate an original method for assessing the integration and transport accessibility of airports using the AirportSustainIndex. The methodology is based on a mathematical Weighted Sum Model (WSM), integrating twelve technical, economic, and environmental criteria, including travel times and costs for public vs. private transport, frequency of rail and bus connections, availability of electric vehicle infrastructure, and tariff integration. The analysis is supported by Geographic Information Systems (GIS) tools and OpenStreetMap data, allowing for a precise reflection of real-world network accessibility. The study covers two significant aviation hubs in Poland: Katowice Airport in Pyrzowice and Poznań-Ławica Airport. The results reveal a paradox: Katowice Airport, despite its significant distance from the agglomeration center (approx. 36 km), achieved a markedly higher sustainability index (0.554) than Poznań-Ławica Airport (0.301), which is located close to the city center (approx. 7 km). Key factors determining this outcome include the high frequency of metropolitan bus lines (“M” lines), the implementation of new rail infrastructure, and a coherent parking policy for low-emission vehicles. The article demonstrates that physical distance from the center is not the primary barrier to building sustainable mobility, provided that high intermodality and integration within the SUMP framework are ensured. The presented research tool is universal and can be applied by policymakers and urban planners to optimize airport-city connectivity, a necessary condition for achieving EU climate goals in the transport sector. Full article

(This article belongs to the Special Issue Smart Mobility for Sustainable Development)

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33 pages, 20788 KB

Open AccessArticle

Composition of Chlorite as a Proxy for Fluid Evolution and Gold Precipitation Mechanisms in the Jinshan Gold Deposit, Dexing District, South China

by Danli Wang, Tao Zhang, Minjuan Zhou, Shaohao Zou, Xilian Chen, Deru Xu, Yongwen Zhang and Cui Yang

Minerals 2026, 16(3), 269; https://doi.org/10.3390/min16030269 (registering DOI) - 28 Feb 2026

Abstract

The physicochemical controls on gold precipitation in orogenic gold deposits remain poorly constrained, with traditional fluid inclusion and isotopic studies often yielding ambiguous results due to overprinting or incomplete records. This study addresses this challenge using chlorite—a sensitive mineral proxy for fluid conditions—as [...] Read more.

The physicochemical controls on gold precipitation in orogenic gold deposits remain poorly constrained, with traditional fluid inclusion and isotopic studies often yielding ambiguous results due to overprinting or incomplete records. This study addresses this challenge using chlorite—a sensitive mineral proxy for fluid conditions—as a quantitative sensor in the Jinshan orogenic gold deposit (>200 t Au) of the Jiangnan orogenic belt, South China. Hosted in Neoproterozoic phyllite within NE–NNE-trending ductile–brittle shear zones, Jinshan features auriferous quartz–polymetallic sulfide veins with prominent chlorite alteration. Integrating high-resolution SEM-EPMA analyses of multi-generational chlorite with thermodynamic modeling, we reconstruct the temporal evolution of temperature, oxygen fugacity (fO₂), pH and sulfur fugacity (fS₂) during ore formation. Four paragenetic stages are identified: Stage 1 (ankerite–quartz), Stage 2 (pyrite–arsenopyrite–quartz), Stage 3 (quartz–gold–polymetallic sulfide), and Stage 4 (chlorite–carbonate–quartz). Electron microprobe analysis reveals that the chlorite composition changes from Fe-rich chamosite (Stage 2) to Mg-rich clinochlore (Stage 3) and then to Fe-rich chamosite (Stage 4). Chlorite from Stage 2 (Chl-1) formed metasomatically at low fluid/rock ratios, while Stage 3 and 4 chlorites (Chl-2 and Chl-3) precipitated directly from higher fluid/rock ratio fluids. Chlorite compositions record a critical Stage 2–3 transition involving cooling from ~ 320 °C to ~ 260 °C, reduction (log fO₂ from –33.6 to –39.7), and alkalinization, and sulfur fugacity remained stable within a narrow range (log fS₂ = –13.6 to –8.0), followed in Stage 4 by minor reheating to ~280 °C, re-acidification, and a slight rebound in oxygen fugacity. Thermodynamic simulations reveal that the destabilization of Au(HS)₂^- complexes, primarily driven by the synergistic effects of cooling, pH increase, and decreasing oxygen fugacity, triggered gold precipitation during the main ore stage. Results demonstrate that abrupt cooling coupled with fluid alkalinization and reduction exerted the dominant control on gold precipitation in Jinshan, resolving long-standing debates on ore-forming mechanisms and highlighting chlorite as a robust quantitative sensor for fluid evolution. Full article

(This article belongs to the Special Issue Gold Deposits: From Primary to Placers and Tailings After Mining)

22 pages, 533 KB

Open AccessArticle

Bonding Without Bridging: Social Capital, Integration, and Well-Being Among Filipina Marriage Migrants in South Korea

by Asterio T. Miranda, Jr., Juneth Lourdes F. Miranda and Eungi Kim

Int. J. Environ. Res. Public Health 2026, 23(3), 305; https://doi.org/10.3390/ijerph23030305 (registering DOI) - 28 Feb 2026

Abstract

This study examined whether strong ethnic community participation facilitates social integration or reinforces social separation among Filipina marriage migrants in the Daegu–Gyeongbuk region of South Korea. A mixed-methods design combined survey data collected between 2018 and 2019 with a media discourse analysis covering [...] Read more.

This study examined whether strong ethnic community participation facilitates social integration or reinforces social separation among Filipina marriage migrants in the Daegu–Gyeongbuk region of South Korea. A mixed-methods design combined survey data collected between 2018 and 2019 with a media discourse analysis covering 2020 to 2025. Survey results indicate extensive ethnic network participation, with 94.5% of respondents involved in religious or Filipino community organizations, yet persistent integration challenges. Language barriers were reported by 54.8% of respondents and cultural misunderstandings by 40%, suggesting strong bonding social capital alongside limited bridging social capital even after prolonged residence. Drawing on Putnam’s social capital theory, 328 news articles on Filipino–Korean relations were screened, of which only 10 directly addressed marriage migrants. None examined the routine experiences identified in the survey, reflecting discursive erasure shaped by polarized narratives of victimization or exceptional success. The temporal separation between the datasets enables an assessment of whether documented integration patterns are acknowledged in public discourse. The findings raise concerns about policy approaches that prioritize ethnic community centers without providing sustained opportunities for intercultural interaction, particularly given that many respondents entered marriage through religious matching programs that embedded them within ethnic networks, with potential health implications. Full article

(This article belongs to the Special Issue Health Equity and Social Determinants of Maternal, Child, and Minority Health)

17 pages, 354 KB

Open AccessArticle

Factors Associated with Quality of Life Among Patients with Cardiac Pacemakers Assessed by Two Scales

by Eirini Stavrou, Georgios Vasilopoulos, Dionyssios Leftheriotis, Panagiota Flevari and Maria Polikandrioti

Clin. Pract. 2026, 16(3), 53; https://doi.org/10.3390/clinpract16030053 (registering DOI) - 28 Feb 2026

Abstract

Background/Objectives: Permanent cardiac pacemakers (PPMs) are small electronic implanted devices that regulate cardiac rhythm. Measurement of quality of life (QoL) serves as a powerful tool for gaining in-depth insights into pacing therapy and ultimately guiding patient-centered management strategies. The aim of the [...] Read more.

Background/Objectives: Permanent cardiac pacemakers (PPMs) are small electronic implanted devices that regulate cardiac rhythm. Measurement of quality of life (QoL) serves as a powerful tool for gaining in-depth insights into pacing therapy and ultimately guiding patient-centered management strategies. The aim of the present study was to evaluate factors affecting QoL among PPM patients by applying the two generic questionnaires: SF-36 and EQ-5D-5L. Materials and Methods: A total of 120 patients with PPM were enrolled. QoL data were collected through interviews using the 36-Item Short Form Health Survey (SF-36) and the Euro QoL 5-Dimensions 5-Levels Health Questionnaire (EQ-5D-5L). Patients’ characteristics were also recorded. Results: The majority of participants were male (54.2%), retired (83.3%) residents in urban areas (75.5%), had a DDD pacemaker (82.5%), had rate response programmed on (77.5%), and had comorbidities (83.3%). Regarding QoL measured by SF-36, the Physical Component Summary Score (PCS) was significantly associated with programming rate response in their pacemaker (p = 0.046), comorbidities (p = 0.047), and the NYHA functional class (p = 0.047). The Mental Component Summary Score (MCS) was significantly associated with sex (p = 0.034), place of residence (p = 0.003), NYHA functional class (p = 0.001), and patients’ level of information about the device (p = 0.039). Patients’ QoL, as measured by the EQ-5D-5L, was significantly associated with sex (p = 0.001), age (p = 0.019), occupation (p = 0.040), pacing mode (p = 0.034), comorbidities (p = 0.019), NYHA functional class (p = 0.047), and level of information about the device (p = 0.005). Conclusions: NYHA functional class, comorbidities, and level of information as reported by patients were the factors associated with QoL, as shown by the two scales. All three factors guide a personalized care plan since NYHA class shows the burden of disease, comorbidities add to the complexity, and patient information determines the effectiveness of management. Full article

15 pages, 3945 KB

Open AccessArticle

Frailty and Socioeconomic Development in the European Region—Associations with Mortality in Middle-Aged and Older Adults

by Rónán O’Caoimh, Aoife Wall and Mark R. O’Donovan

Int. J. Environ. Res. Public Health 2026, 23(3), 307; https://doi.org/10.3390/ijerph23030307 (registering DOI) - 28 Feb 2026

Abstract

The Sociodemographic Index (SDI) captures a country’s or region’s relative socioeconomic development and has been linked to age-related disease burden and life expectancy. Frailty is a multidimensional geriatric syndrome associated with adverse health outcomes and mortality. This study examined the relationship between country-level [...] Read more.

The Sociodemographic Index (SDI) captures a country’s or region’s relative socioeconomic development and has been linked to age-related disease burden and life expectancy. Frailty is a multidimensional geriatric syndrome associated with adverse health outcomes and mortality. This study examined the relationship between country-level SDI, frailty prevalence, and mortality across Europe. We conducted a secondary analysis of community-dwelling adults aged 50 years and older from 12 countries participating in the Survey of Health, Ageing and Retirement in Europe (SHARE). Frailty status and SDI were assessed at Wave 2 (2007), with mortality follow-up at Wave 4 (2011). Countries were categorised into lower- and higher-SDI groups using the median as a cut-off. Frailty was measured using a 70-item frailty index (FI ≥ 0.25) and a modified Fried frailty phenotype (FP ≥ 3 criteria). Frailty prevalence varied substantially by country and assessment method, ranging from 7 to 40% using the FI and 4–21% using the FP. Prevalence was lowest in Switzerland and highest in Poland and was strongly correlated with national SDI scores (r ≥ 0.8). After adjustment for age and sex, lower SDI was independently associated with higher odds of frailty using both frailty measures. Although mortality was lower in higher-SDI countries, this association was not statistically significant after adjusting for age, sex, and frailty. Lower social development was strongly associated with frailty prevalence but did not independently predict mortality, highlighting frailty as a potential pathway linking social context to later-life health outcomes in Europe. Full article

(This article belongs to the Special Issue Rehabilitation Approaches to Reduce Frailty and Promote Healthy Aging)

34 pages, 6320 KB

Open AccessArticle

A Hybrid Intelligent Fault Diagnosis Framework for Rolling Bearings and Gears Based on BAYES-ICEEMDAN-SNR Feature Enhancement and ITOC-LSSVM

by Xiaoxu He, Xingwei Ge, Zhe Wu, Qiang Zhang, Yiying Yang and Yachao Cao

Sensors 2026, 26(5), 1543; https://doi.org/10.3390/s26051543 (registering DOI) - 28 Feb 2026

Abstract

To address the challenges of difficult feature extraction for rolling bearing vibration signals, low efficiency in optimizing diagnostic model parameters, and the tendency to get trapped in local optima, this paper proposes an improved ICEEMDAN feature extraction method based on Bayesian optimization and [...] Read more.

To address the challenges of difficult feature extraction for rolling bearing vibration signals, low efficiency in optimizing diagnostic model parameters, and the tendency to get trapped in local optima, this paper proposes an improved ICEEMDAN feature extraction method based on Bayesian optimization and adaptive noise signal ratio enhancement (BAYES-ICEEMDAN-SNR) and combines it with the improved Coriolis force optimization algorithm (ITOC) to optimize the least squares support vector machine (LSSVM) fault diagnosis model. Firstly, Bayesian optimization is used to adaptively determine the noise parameters and introduce a dynamic signal-to-noise ratio adjustment mechanism to enhance the robustness of feature extraction; secondly, Chebyshev chaotic mapping, Cauchy mutation, and dynamic reverse learning strategies are applied to enhance the global search and local escape capabilities of ITOC, thereby optimizing the hyperparameters of LSSVM; and finally, the Keesey-Chestnut University bearing dataset and Huazhong University of Science and Technology gear dataset are used for verification. The experimental results show that the average fault identification accuracy of the proposed method reaches over 97%, which is superior to that of the comparison models, and the effectiveness of each core improvement module of the proposed model is verified through ablation experiments, providing an effective solution for intelligent fault diagnosis of rolling bearings and gears. Full article

(This article belongs to the Section Fault Diagnosis & Sensors)

14 pages, 4978 KB

Open AccessArticle

Quantitative Comparison and Effectiveness Evaluation of Striking and Sliding Excitation Methods in Acoustic Identification of Concrete Voids

by Ziru Zhang, Wenlong Zhang, Haoyu Wang, Shibin Teng and Fang Zhao

Buildings 2026, 16(5), 959; https://doi.org/10.3390/buildings16050959 (registering DOI) - 28 Feb 2026

Abstract

The long-term safety and durability of concrete building structures depend largely on their internal quality. Wall voids, as typical hidden defects, directly affect the structural bearing capacity and service life. Such defects may not only lead to surface hollowing and peeling but also [...] Read more.

The long-term safety and durability of concrete building structures depend largely on their internal quality. Wall voids, as typical hidden defects, directly affect the structural bearing capacity and service life. Such defects may not only lead to surface hollowing and peeling but also develop into serious safety accidents such as local collapse. At present, acoustic detection methods are widely used in engineering practice due to their convenience and efficiency. Among them, the strike method and the slide method, as two basic excitation methods, are commonly used on-site detection methods. However, existing studies still lack the systematic comparative analysis of these two methods, especially in terms of objective evaluation based on quantitative characteristics. To fill this research gap, this study designed a strict controlled experimental scheme. By collecting acoustic signals under these two excitation methods, the time-domain waveform characteristics, frequency-domain response characteristics, and time-frequency distribution patterns were systematically analyzed. The results show that, compared with the traditional strike excitation, the slide excitation method shows significant advantages in concrete wall void detection. It not only has higher detection accuracy but also exhibits better stability and repeatability. Further analysis found that the slide signal is superior to the strike signal in terms of feature distinguish ability and anti-interference ability. Its voltage distribution curve shows more obvious separation characteristics, which significantly reduces the risk of misjudgment. Through systematic quantitative comparison, this study provides a reliable experimental basis for the acoustic detection of concrete wall voids and has important reference value for promoting the standardization and intelligent development of non-destructive testing technology. Full article

(This article belongs to the Section Building Structures)

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27 pages, 781 KB

Open AccessArticle

A ‘Standard of Care PLUS’ Model for Preterm Birth Prevention: Integrating Nutrient and Gene Variant Analysis with Targeted Interventions

by Leslie P. Stone, Emily Stone Rydbom, P. Michael Stone and Daniel Kim

J. Pers. Med. 2026, 16(3), 134; https://doi.org/10.3390/jpm16030134 (registering DOI) - 28 Feb 2026

Abstract

Background/Objectives: The rates of adverse maternal and neonatal outcomes—including preterm birth < 37 weeks’ gestation (PTB), hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), small for gestational age (SGA), and large for gestational age (LGA)—remain elevated in the United States. Preventive strategies [...] Read more.

Background/Objectives: The rates of adverse maternal and neonatal outcomes—including preterm birth < 37 weeks’ gestation (PTB), hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), small for gestational age (SGA), and large for gestational age (LGA)—remain elevated in the United States. Preventive strategies beyond the current standard of care (SOC) may be needed, particularly in diverse and socioeconomically vulnerable populations. The study evaluated a targeted diet and lifestyle intervention incorporating selected nutrient and gene variant analysis with personalized trimester-based counseling and supplementation (Standard of Care Plus, PLUS). Methods: The prospective observational study compared outcomes among participants receiving PLUS in addition to SOC with regional SOC data. A Nevada PLUS cohort (n = 15), consisting of high-risk participants with 100% Medicaid coverage, received the intervention virtually. An Oregon PLUS cohort (n = 387), consisting of moderate-risk participants with approximately 50% Medicaid coverage, received PLUS through in-person group sessions. Outcomes were compared with regional SOC rates and between PLUS cohorts. Cochran–Mantel–Haenszel (CMH) analyses were performed to account for site-level differences in pooled analyses. Primary outcome was PTB < 37 weeks’ gestation; secondary outcomes included HDP, GDM, SGA, and LGA. Results: The Nevada PLUS application was associated with lower adverse outcome rates compared with regional SOC; however, statistical significance was not observed, likely reflecting limited sample size. The Oregon PLUS cohort experienced statistically significant association with reductions across all five outcomes (all p < 0.001) compared to regional SOC. No statistically significant differences were observed between the Nevada (virtual) and Oregon (in-person) PLUS cohorts. In pooled analyses (n = 402), significant reductions compared with SOC were observed for PTB (RR = 0.23), HDP (RR = 0.11), GDM (RR = 0.06), SGA (RR = 0.25), and LGA (RR = 0.35) (all p < 0.001). Conclusions: The implementation of selected nutrient and gene variant analysis combined with targeted nutritional and lifestyle interventions, delivered in collaboration with standard obstetric care, was associated with reduced adverse maternal and neonatal outcomes. Interpretation of virtual delivery remains limited by small sample size. Full article

(This article belongs to the Section Personalized Medical Care)

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37 pages, 6668 KB

Open AccessReview

Sustainable Biopolymers for Environmental Applications: Advances and Future Perspectives Toward a Circular Economy

by Carlos A. Ligarda-Samanez, Mary L. Huamán-Carrión, Henry Palomino-Rincón, Fredy Taipe-Pardo, Elibet Moscoso-Moscoso, Domingo J. Cabel-Moscoso, Antonina J. Garcia-Espinoza, Dante Fermín Calderón Huamaní, Jackson M’coy Romero Plasencia, Jaime A. Martinez-Hernandez, Rober Luciano-Alipio and Jorge Apaza-Cruz

Polymers 2026, 18(5), 618; https://doi.org/10.3390/polym18050618 (registering DOI) - 28 Feb 2026

Abstract

In recent years, sustainable biopolymers have attracted increasing attention in environmental engineering as alternatives to conventional synthetic materials due to their renewable origins, biodegradability, and functional versatility. However, their performance and technological viability are strongly influenced by structural design, modification strategies, and behavior [...] Read more.

In recent years, sustainable biopolymers have attracted increasing attention in environmental engineering as alternatives to conventional synthetic materials due to their renewable origins, biodegradability, and functional versatility. However, their performance and technological viability are strongly influenced by structural design, modification strategies, and behavior under realistic environmental conditions. This review critically analyzes recent advances in biopolymers for environmental remediation, covering their main application formats such as hydrogels, membranes, beads, aerogels, and composites, their interaction mechanisms with contaminants, and their performance relative to conventional adsorbents. Particular emphasis is placed on emerging approaches, including advanced functionalization, integration with inorganic phases, and green synthesis technologies, which have significantly improved efficiency, selectivity, and operational stability. Despite these advances, key limitations persist, particularly regarding mechanical robustness, regenerability, reproducibility, and scalability, underscoring the need for standardized evaluation protocols in complex matrices. The role of biopolymers within circular economy frameworks is also examined, emphasizing their capacity to integrate material sustainability, resource recovery, and multifunctional environmental applications. Overall, sustainable biopolymers are positioned not only as substitutes for traditional materials but also as strategic platforms for the development of next-generation regenerative environmental technologies. Full article

(This article belongs to the Section Biobased and Biodegradable Polymers)

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6 pages, 232 KB

Open AccessEditorial

Editorial for Advances in 3D Printing Technologies of Metals—2nd Edition

by Irene Buj-Corral and Felip Fenollosa-Artés

Metals 2026, 16(3), 279; https://doi.org/10.3390/met16030279 (registering DOI) - 28 Feb 2026

Abstract

Once the 3D printing of plastics has been fully been integrated in our scientific, industrial, and even social environments, the next frontier of additive manufacturing processes is the world of metallic parts [...] Full article

(This article belongs to the Special Issue Advances in 3D Printing Technologies of Metals—2nd Edition)

20 pages, 2943 KB

Open AccessArticle

Impact of C-Terminal Amide N-Derivatization on the Conformational Dynamics and Antimitotic Activity of Cemadotin Analogues

by Dayana Alonso, Daniel Platero-Rochart, Pauline Stark, Leonardo G. Ceballos, Robert Rennert, Daniel G. Rivera, Julieta Coro-Bermello and Ludger A. Wessjohann

Molecules 2026, 31(5), 825; https://doi.org/10.3390/molecules31050825 (registering DOI) - 28 Feb 2026

Abstract

Tubulin is a heterodimeric protein composed of α- and β-subunits, which polymerize to form the cell’s microtubules. The latter are key components in mitotic spindle formation and essential targets in anticancer therapy. Compounds such as paclitaxel, tubulysins, dolastatins and synthetic analogues of these [...] Read more.

Tubulin is a heterodimeric protein composed of α- and β-subunits, which polymerize to form the cell’s microtubules. The latter are key components in mitotic spindle formation and essential targets in anticancer therapy. Compounds such as paclitaxel, tubulysins, dolastatins and synthetic analogues of these latter compounds, including cemadotin, exert their cytotoxic effects by disrupting microtubule dynamics. Previously, we reported the production and anticancer activity of a library of cemadotin analogues featuring a C-terminal tertiary amide functionalized with a variety of N-substituents, thus resulting in compounds occurring as a mixture of amide rotamers. Here we describe a comprehensive NMR and conformational study that provides new insights into the effect of the conformational equilibrium on the binding mode of the novel cemadotin analogues to the tubulin target. The conformational behavior of the isomer equilibrium of cemadotin’s terminal amide bond was investigated by TOCSY and ROESY NMR experiments, which allowed the identification and quantification of individual rotamer populations. A slow interconversion between the s-cis and s-trans amide rotamers was observed under standard NMR conditions (25 °C), indicating a significant energy barrier and conformational rigidity. Molecular docking and saturation transfer difference (STD) NMR experiments were performed with a representative analogue and tubulin to assess the binding mode. The results revealed that the s-trans rotamer is the predominant conformer in solution and exhibits a more favorable interaction with tubulin compared to the s-cis isomer, thus helping to understand the conformational requirements for an improved tubulin binding and the inhibition of the polymerization process. Full article

(This article belongs to the Special Issue 30th Anniversary of Molecules—Recent Advances in Bioorganic Chemistry)

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21 pages, 805 KB

Open AccessArticle

Multidimensional Impact Assessment of Social Welfare Incorporating Dynamic Cross Subsidy and Tiered Carbon Trading

by Ya-Juan Cao, Bin-Yang Qiu, Qiu-Jie Wang, Yi-Hui Luo and Yun-Xiang Zhang

Energies 2026, 19(5), 1225; https://doi.org/10.3390/en19051225 (registering DOI) - 28 Feb 2026

Abstract

In the context of advancing two pivotal national commitments, namely the “Dual Carbon” goals and the common prosperity strategy, energy policy formulation must move beyond purely economic or environmental considerations and adopt integrated social welfare assessments. This study develops an optimal dispatch model [...] Read more.

In the context of advancing two pivotal national commitments, namely the “Dual Carbon” goals and the common prosperity strategy, energy policy formulation must move beyond purely economic or environmental considerations and adopt integrated social welfare assessments. This study develops an optimal dispatch model for a multi-microgrid system that incorporates dynamic cross subsidy and tiered carbon trading. From the perspective of welfare economics, the socioeconomic impacts of the proposed model are then systematically evaluated. First, a unified operational framework is established, combining dynamic electricity tariff cross subsidy with a tiered carbon trading mechanism. Next, a quantitative model for electricity tariff cross subsidy is proposed, and a dynamic subsidy rate linked to renewable energy output is designed to guide electricity consumption behavior. Finally, a comparative simulation is conducted across three scenarios: no subsidy, traditional cross subsidy, and the proposed dynamic cross subsidy. The results demonstrate that the proposed dynamic mechanism reduces system carbon emissions by 17.05% compared to the non-subsidy baseline while significantly optimizing total costs. Full article

(This article belongs to the Special Issue Digital Modeling, Operation and Control of Sustainable Energy Systems)

28 pages, 954 KB

Open AccessArticle

Proactive Proctoring: A Critical Analysis of Machine Learning Architectures and Custom Temporal Data Sets for Moodle Fraud Detection

by Andrei-Nicolae Vacariu, Marian Bucos, Marius Otesteanu and Bogdan Dragulescu

Appl. Sci. 2026, 16(5), 2381; https://doi.org/10.3390/app16052381 (registering DOI) - 28 Feb 2026

Abstract

This paper examines the use of Machine Learning (ML) approaches in maintaining academic integrity using the information provided in the Moodle system logs. The paper focuses on data set construction, handling the issue of class imbalance, and the assessment of the performance of [...] Read more.

This paper examines the use of Machine Learning (ML) approaches in maintaining academic integrity using the information provided in the Moodle system logs. The paper focuses on data set construction, handling the issue of class imbalance, and the assessment of the performance of different ML models in uncovering academic fraud. Twelve different data sets were created by using the concept of temporal windows (e.g., one-day and three-day windows) during the feature extraction stage from the Moodle system logs. The manual labeling of the data sets was done based on a predefined set of rules that outline the fraudulent activities. The issue of class imbalance was treated using eleven different resampling approaches, such as SMOTE, ADASYN, Tomek Links, and NearMiss. We evaluated six classification algorithms, thus resulting in a total of 792 experiments based on the interactions between the data sets, resampling methods, and classification algorithms. The results from the experiment show that the Random Forest and AdaBoost models performed the best in the experiment. Furthermore, we observed a trade-off between fraud detection rates and model precision based on the temporal windows and resampling methods. The shortest temporal windows and hybrid undersampling approaches resulted in the maximum recall value in this study and could identify the greatest number of at-risk students. On the other hand, the longest temporal windows and hybrid oversampling approaches with data cleaning resulted in the best results in terms of F1-Score and Cohen’s Kappa statistics. The results provide conclusive evidence that the models can identify fraud; however, they should be used as predictive models for the improvement of proctoring approaches, such as random selection for verification or seating arrangement strategies, instead of judgment models. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

28 pages, 508 KB

Open AccessSystematic Review

Artificial Intelligence for Business Decision-Making in Latin America: A Systematic Review of Evidence, Contributing Countries, and Key Insights

by Luz Maribel Vásquez-Vásquez, Elena Jesús Alvarado-Cáceres and Víctor Hugo Fernández-Bedoya

Adm. Sci. 2026, 16(3), 121; https://doi.org/10.3390/admsci16030121 (registering DOI) - 28 Feb 2026

Abstract

In recent years, Latin America has experienced a growing incorporation of Artificial Intelligence (AI) into business and organizational environments, driven by digital transformation, data availability, and competitive pressures. Across multiple sectors, AI-based tools are increasingly used to support complex decision-making processes, raising both [...] Read more.

In recent years, Latin America has experienced a growing incorporation of Artificial Intelligence (AI) into business and organizational environments, driven by digital transformation, data availability, and competitive pressures. Across multiple sectors, AI-based tools are increasingly used to support complex decision-making processes, raising both opportunities and challenges related to efficiency, ethics, and organizational readiness. Within this context, this systematic review examines the scientific evidence on the implementation of AI in business decision-making in Latin America. Following PRISMA 2020 guidelines, a systematic search was conducted in the Scopus database for articles published between 2021 and 2025. The search strategy combined Boolean operators related to AI and decision-making. Inclusion criteria comprised original, open-access research articles conducted in Latin American countries and published in Spanish or Portuguese. After screening for temporality, geographic focus, language, document type, accessibility, duplication, and relevance, 27 studies were selected from an initial pool of 276,302 records. The studies originated mainly from Peru, Colombia, Chile, and Ecuador. The findings show that AI is applied across sectors such as industry, agriculture, finance, education, and public services, primarily to enhance predictive capacity, automate processes, and support data-driven decisions. While AI adoption improves efficiency, cost reduction, and strategic innovation, its effectiveness depends on staff training, ethical governance, and strategic alignment. Persistent challenges include resistance to change, data quality limitations, and concerns regarding transparency and algorithmic bias. Overall, AI emerges as a transformative but context-dependent tool for business decision-making in Latin America. Full article

(This article belongs to the Special Issue The Era of Technology: Impacts and Implications of Digital and Artificial Intelligence Transformation on Organizations)

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5 pages, 176 KB

Open AccessEditorial

Corrosion of Metals: Behaviors and Mechanisms

by Chao Liu, Zhongyu Cui and Tianliang Zhao

Metals 2026, 16(3), 277; https://doi.org/10.3390/met16030277 (registering DOI) - 28 Feb 2026

Abstract

Corrosion of metals and alloys represents one of the most persistent challenges in materials science and engineering [...] Full article

(This article belongs to the Special Issue Corrosion of Metals: Behaviors and Mechanisms)

36 pages, 2422 KB

Open AccessArticle

PDGV-DETR: Object Detection for Secure On-Site Weapon and Personnel Location Based on Dynamic Convolution and Cross-Scale Semantic Fusion

by Nianfeng Li, Peizeng Xin, Jia Tian, Xinlu Bai, Hongjie Ding, Zhiguo Xiao and Qian Liu

Sensors 2026, 26(5), 1542; https://doi.org/10.3390/s26051542 (registering DOI) - 28 Feb 2026

Abstract

In public safety scenarios, the precise detection and positioning of prohibited weapons such as firearms and knives along with the involved personnel are the core pre-requisite technologies for violent risk warning and emergency response. However, in security surveillance scenarios, there are common problems [...] Read more.

In public safety scenarios, the precise detection and positioning of prohibited weapons such as firearms and knives along with the involved personnel are the core pre-requisite technologies for violent risk warning and emergency response. However, in security surveillance scenarios, there are common problems such as object occlusion, difficulty in capturing small-sized weapons, and complex background interference, which lead to the shortcomings of existing general object detection models in the tasks of detecting and locating security-related objects, including poor adaptability, low detection accuracy, and insufficient robustness in complex scenarios. Therefore, this paper proposes a threat object detection framework for security scenarios (PDGV-DETR) based on adaptive dynamic convolution and cross-scale semantic fusion, specifically optimized for the detection and positioning tasks of weapons and personnel objects in static security surveillance images. This research focuses on category recognition at the object level and pixel-level spatial positioning, and does not involve the classification and identification of violent behaviors based on temporal information. There are clear technical boundaries and scene limitations between the two. This framework is optimized through three core modules: designing a dynamic hierarchical channel interaction convolution module to reduce computational complexity while enhancing the ability to detect occluded and incomplete objects; constructing an improved bidirectional hybrid feature pyramid network, combining the cross-scale fusion module to strengthen multi-scale feature expression, and adapting to the simultaneous detection requirements of small weapon objects and large personnel objects; and introducing a global semantic weaving and elastic feature alignment network to solve the problem of low discrimination between objects and complex backgrounds. Under the same experimental configuration, the proposed model is verified against current mainstream models on typical datasets: on a dataset of 2421 conflict scene personnel violent images, the peak average precision mAP50 of PDGV-DETR reached 85.9%. Through statistical verification, compared with the baseline model RT-DETR with an average value ± standard deviation of 0.840 ± 0.007, the average value ± standard deviation of PDGV-DETR reached 0.858 ± 0.004, demonstrating statistically significant performance improvement, with a p-value less than 0.01. This model can accurately complete the task of locating the object area of personnel, and compared with the deformable DETR, the accuracy improvement rate reached 15.1%.; on the weapon-specific dataset OD-WeaponDetection, the mAP for gun and knife detection reached 93.0%, improving by 2.2% compared to RT-DETR. Compared to the performance fluctuations of other general object detection models in complex security scenarios, PDGV-DETR not only has better detection and positioning accuracy for security-related objects, but also significantly improves the generalization and stability of the model. The results show that PDGV-DETR effectively balances the accuracy of positioning, detection, and computational efficiency, accurately completing end-to-end detection and positioning of weapon and personnel objects in static security surveillance images, demonstrating highly competitive performance in the detection and positioning of security-related objects in security scenes, providing core object-level pre-processing technology support for scenarios such as public area monitoring, intelligent video monitoring, and early warning of violent risks, and providing basic data for subsequent violent behavior recognition based on temporal data. Full article

(This article belongs to the Special Issue Deep Learning for Perception and Recognition Based on Sensor Data: Methods and Applications, 2nd Edition)

38 pages, 778 KB

Open AccessSystematic Review

Transformational, Transactional, and Ethical Leadership in Sustainable Family Entrepreneurship: A Global Systematic Review

by Monica Elisa Meneses-La-Riva, Josefina Amanda Suyo-Vega, Hitler Giovanni Ocupa-Cabrera, Sofía Almendra Alvarado-Suyo and Víctor Hugo Fernández-Bedoya

Adm. Sci. 2026, 16(3), 120; https://doi.org/10.3390/admsci16030120 (registering DOI) - 28 Feb 2026

Abstract

Leadership plays a central role in the long-term sustainability of family enterprises, yet existing evidence is fragmented across contexts and methodologies. This systematic review synthesizes empirical findings on leadership practices that support sustainable family entrepreneurship. The objectives are to identify available evidence on [...] Read more.

Leadership plays a central role in the long-term sustainability of family enterprises, yet existing evidence is fragmented across contexts and methodologies. This systematic review synthesizes empirical findings on leadership practices that support sustainable family entrepreneurship. The objectives are to identify available evidence on leadership in sustainable family enterprises, describe the methodologies employed, and examine how leadership is perceived and enacted across global contexts. The review followed PRISMA 2020 guidelines. Searches were conducted on 28 January 2025 on Scopus, Web of Science, EBSCOHost, and ProQuest. Eligibility criteria included empirical studies, full accessibility, publication in English, non-duplicated records, and relevance to leadership in sustainable family enterprises. Twenty-six studies met the inclusion criteria. Data extraction focused on context, methodology, leadership evidence, and key findings. Studies spanning Asia, Europe, Latin America, Africa, and the Middle East indicate that leadership strongly shapes sustainability outcomes in family firms. Three core leadership dimensions emerged: transformational leadership, which promotes innovation, engagement, affective commitment, and continuity; transactional leadership, which supports governance, succession planning, operational control, and performance; and ethical leadership, which fosters trust, shared values, and social responsibility. Cross-cutting themes include gendered leadership contributions, succession risk management, and cultural influences. Sustainable family enterprises rely on multidimensional leadership integrating these approaches, reinforced by structured succession processes, value alignment, and human capital investment. Full article

(This article belongs to the Special Issue Emerging Family Firms: Leadership and Entrepreneurship)

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29 pages, 4787 KB

Open AccessArticle

Genetic Activation of Locus Coeruleus Noradrenergic Neurons Modulates Cerebellar MF-GrC Synaptic Plasticity via Presynaptic α2-AR/PKA Signaling in Mice

by Ying-Han Xu, Xu-Dong Zhang, Yang Liu, Zhi-Zhi Zhao, Yuan Zheng, De-Lai Qiu and Chun-Ping Chu

Biology 2026, 15(5), 406; https://doi.org/10.3390/biology15050406 (registering DOI) - 28 Feb 2026

Abstract

Locus coeruleus (LC) noradrenergic neurons project their axons to the cerebellar cortex and modulate cerebellar circuit function via distinct adrenergic receptor (AR) subtypes. The present study investigated the mechanism by which optogenetic activation of LC noradrenergic neurons modulates facial stimulation-evoked long-term synaptic plasticity [...] Read more.

Locus coeruleus (LC) noradrenergic neurons project their axons to the cerebellar cortex and modulate cerebellar circuit function via distinct adrenergic receptor (AR) subtypes. The present study investigated the mechanism by which optogenetic activation of LC noradrenergic neurons modulates facial stimulation-evoked long-term synaptic plasticity at cerebellar mossy fiber-granule cell (MF-GrC) synapses in urethane-anesthetized DBH-Cre mice. Blockade of GABA_A receptors, 20 Hz facial stimulation induced MF-GrC long-term potentiation (LTP) in the control group, and this LTP was impaired by optogenetic activation of LC noradrenergic neurons via α2-ARs. Meanwhile, facial stimulation induced LTP of glutamate sensor fluorescence in the granular layer, which was abolished by chemogenetic activation of LC noradrenergic neurons. Following NMDA receptor blockade, optogenetic activation of LC noradrenergic neurons triggered facial stimulation-induced MF-GrC long-term depression (LTD) via α2A-ARs. Optogenetically activated LC noradrenergic neuron-induced MF-GrC LTD was abolished by protein kinase A (PKA) inhibition but not by protein kinase C inhibition. Immunofluorescence results revealed abundant α2A-AR expression in the granular layer, with particularly high levels in glomeruli, and no colocalization with the glutamate sensor. These results indicate that optogenetic activation of LC noradrenergic neurons impairs facial stimulation-induced MF-GrC LTP by triggering presynaptic LTD via the α2A-AR/PKA signaling cascade. Full article

(This article belongs to the Section Neuroscience)

21 pages, 1562 KB

Open AccessArticle

Development of Surveillance Robots Based on Face Recognition Using High-Order Statistical Features and Evidence Theory

by Slim Ben Chaabane, Rafika Harrabi, Anas Bushnag and Hassene Seddik

J. Imaging 2026, 12(3), 107; https://doi.org/10.3390/jimaging12030107 (registering DOI) - 28 Feb 2026

Abstract

The recent advancements in technologies such as artificial intelligence (AI), computer vision (CV), and Internet of Things (IoT) have significantly extended various fields, particularly in surveillance systems. These innovations enable real-time facial recognition processing, enhancing security and ensuring safety. However, mobile robots are [...] Read more.

The recent advancements in technologies such as artificial intelligence (AI), computer vision (CV), and Internet of Things (IoT) have significantly extended various fields, particularly in surveillance systems. These innovations enable real-time facial recognition processing, enhancing security and ensuring safety. However, mobile robots are commonly employed in surveillance systems to handle risky tasks that are beyond human capability. In this paper, we present a prototype of a cost-effective mobile surveillance robot built on the Raspberry PI 4, designed for integration into various industrial environments. This smart robot detects intruders using IoT and face recognition technology. The proposed system is equipped with a passive infrared (PIR) sensor and a camera for capturing live-streaming video and photos, which are sent to the control room through IoT technology. Additionally, the system uses face recognition algorithms to differentiate between company staff and potential intruders. The face recognition method combines high-order statistical features and evidence theory to improve facial recognition accuracy and robustness. High-order statistical features are used to capture complex patterns in facial images, enhancing discrimination between individuals. Evidence theory is employed to integrate multiple information sources, allowing for better decision-making under uncertainty. This approach effectively addresses challenges such as variations in lighting, facial expressions, and occlusions, resulting in a more reliable and accurate face recognition system. When the system detects an unfamiliar individual, it sends out alert notifications and emails to the control room with the captured picture using IoT. A web interface has also been set up to control the robot from a distance through Wi-Fi connection. The proposed face recognition method is evaluated, and a comparative analysis with existing techniques is conducted. Experimental results with 400 test images of 40 individuals demonstrate the effectiveness of combining various attribute images in improving human face recognition performance. Experimental results indicate that the algorithm can identify human faces with an accuracy of 98.63%. Full article

(This article belongs to the Topic Applied Computer Vision and Pattern Recognition: 2nd Edition)

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13 pages, 1048 KB

Open AccessArticle

PD-L1 Negative Advanced Non-Small Cell Lung Cancer: Practice Patterns and Real-World Outcomes

by Audrey-Ann Bégin, Maude Dubé-Pelletier, Catherine Labbé, Vicky Mai, Michaël Maranda-Robitaille and Marie-Hélène Denault

Curr. Oncol. 2026, 33(3), 144; https://doi.org/10.3390/curroncol33030144 (registering DOI) - 28 Feb 2026

Abstract

The standard first-line treatment for metastatic non-small cell lung cancer (NSCLC) without oncogenic alterations and programmed death-ligand 1 (PD-L1) expression < 1% is a combination of chemotherapy (CT) and immunotherapy (IO). However, real-world overall survival (OS) appears more modest than in clinical trials, [...] Read more.

The standard first-line treatment for metastatic non-small cell lung cancer (NSCLC) without oncogenic alterations and programmed death-ligand 1 (PD-L1) expression < 1% is a combination of chemotherapy (CT) and immunotherapy (IO). However, real-world overall survival (OS) appears more modest than in clinical trials, averaging 10–13 months. This retrospective study aimed to assess treatment patterns and real-world outcomes at the Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ). Patients diagnosed between January 2019 and December 2023 with advanced PD-L1 <1% NSCLC and treated with palliative intent at IUCPQ were included and categorized by first-line treatment. Progression-free survival (PFS) and OS of the CT + IO and CT groups were compared using Kaplan–Meier curves and Cox regression analyses. Data regarding regimen selection, adverse events and subsequent treatment lines were collected. Among 217 eligible patients, 82 (37.8%) received CT + IO, 32 (14.7%) CT alone, 16 (7.4%) targeted therapy, and 87 (40.1%) supportive care. Median PFS was 5.3 vs. 4.7 months (p = 0.5) and OS 14.4 vs. 13.5 months (p = 0.2) for CT + IO and CT alone, respectively. In the CT + IO group, treatment discontinuation was mainly due to disease progression (59.4%) or adverse events (36.2%). Immune-related adverse events occurred in 29.3%, most frequently pneumonitis (8.5%). Therefore, in this cohort, no statistically significant survival difference was observed between CT + IO and CT alone. However, these findings should be interpreted cautiously given the non-randomized design, baseline imbalances between groups, and the limited sample size of the CT alone cohort. Tolerability of CT + IO was consistent with that observed in clinical trials. Full article

(This article belongs to the Section Thoracic Oncology)

17 pages, 2405 KB

Open AccessArticle

A High-Affinity Nanobody Selectively Recognizing KPC-2/KPC-3: Biochemical and Structural Insights

by Emna Hamdi, Oussema Khamessi, Alessandra Piccirilli, Sayda Dhaouadi, Sinda Zarrouk, Fabrizia Brisdelli, Hafedh Dabbek, Mohamed Hedi Saihi, Balkiss Bouhaouala-Zahar, Rahma Ben Abderrazek and Mariagrazia Perilli

Biomolecules 2026, 16(3), 369; https://doi.org/10.3390/biom16030369 (registering DOI) - 28 Feb 2026

Abstract

Carbapenemase-producing bacteria, particularly those expressing the KPC-3 variant, pose a critical global health threat due to their resistance to nearly all β-lactam antibiotics, including carbapenems. Rapid and reliable detection tools are urgently needed to improve infection control and guide patient management. Nanobodies (VHHs) [...] Read more.

Carbapenemase-producing bacteria, particularly those expressing the KPC-3 variant, pose a critical global health threat due to their resistance to nearly all β-lactam antibiotics, including carbapenems. Rapid and reliable detection tools are urgently needed to improve infection control and guide patient management. Nanobodies (VHHs) present a promising alternative to conventional antibodies thanks to their high stability, small size, and capacity to access cryptic epitopes. Here, we report the generation and characterization of a nanobody specifically targeting KPC-3. An immune VHH phage display library was constructed, with over 90% of clones containing correctly sized inserts. After three rounds of biopanning, high-specificity binders were identified by ELISA screening. Sequencing identified a nanobody with hallmark VHH features, which was expressed and validated by ELISA and Western blot. Although kinetic assays showed no inhibition of KPC-3 enzymatic activity, interestingly, the nanobody demonstrated high-binding recognition of both KPC-2 and KPC-3 in periplasmic extracts from clinical strains. Structural modeling further supported these results, highlighting favorable interaction surfaces. This study provides the first evidence of a nanobody raised against KPC-3 that recognizes a conserved epitope shared by KPC-3 and KPC-2, underscoring its promising use as a molecular tool for detecting KPC variants and establishing a basis for future affinity maturation toward therapeutic applications. Full article

(This article belongs to the Section Molecular Biology)

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11 pages, 19603 KB

Open AccessArticle

First Record of Leiurus nigellus (Scorpiones: Buthidae) in Northern Saudi Arabia: Molecular and Morphological Insights from Ha’il Region, King Salman Bin Abdulaziz Royal Natural Reserve

by Abdulaziz M. Al-Amri, Mohammad A. Abdulhakeem, Abdulaziz R. Alqahtani, Ahmed M. Al-Malki and Wael M. Shohdi

Diversity 2026, 18(3), 149; https://doi.org/10.3390/d18030149 (registering DOI) - 28 Feb 2026

Abstract

This study documents the first confirmed record of the Buthid scorpion Leiurus nigellus from Jabal Arnan in the Ha’il region, located within the King Salman Bin Abdulaziz Royal Natural Reserve (KSRNR) in the northwestern Kingdom of Saudi Arabia (KSA). This species was originally [...] Read more.

This study documents the first confirmed record of the Buthid scorpion Leiurus nigellus from Jabal Arnan in the Ha’il region, located within the King Salman Bin Abdulaziz Royal Natural Reserve (KSRNR) in the northwestern Kingdom of Saudi Arabia (KSA). This species was originally described by Abu Afifeh, Aloufi & Al-Saraireh (2023). This locality extends the known distribution range of L. nigellus by over 200 km southeast of the type locality in Al-Ula, Al Madinah province. A total of six specimens of L. nigellus were collected during fieldwork conducted between June 2024 and April 2025, including two adult males, one adult female, and three juveniles. The objective of this study was to confirm the taxonomic identity of Leiurus nigellus from a newly discovered locality using morphological examination and mitochondrial DNA analysis and documentation of its known geographic distribution. Adult specimens (one male and one female) were examined using comparative morphometric analysis following standard scorpion taxonomic protocols, confirming diagnostic traits consistent with the original species description. Meanwhile, habitat assessments indicated adaptation to semi-arid rocky and gravel substrates. Molecular analysis was conducted on one adult male using targeted mitochondrial 16S rRNA gene sequencing (Sanger method). Phylogenetic relationships were inferred using neighbor-joining and maximum-parsimony analyses, placing L. nigellus within the Arabian Leiurus clade with bootstrap-supported affinity to Arabian congeners and limited intraspecific divergence. The generated 16S rRNA sequence represents the first molecular record for L. nigellus and has been deposited in GenBank. Sexual dimorphism was evident in morphometric traits, but these differences reflect normal biological variation rather than taxonomic differentiation. The discovery of L. nigellus in northern Saudi Arabia emphasizes the importance of continued faunistic and genetic surveys in underexplored regions, both to refine species distributions and to inform conservation management of specialized desert arachnofauna. Full article

(This article belongs to the Topic Arthropod Biodiversity: Ecological and Functional Aspects, 2nd Edition)

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18 pages, 1714 KB

Open AccessArticle

A Novel Transformer Architecture for Scalable Perovskite Thin-Film Detection

by Mengke Li, Hongling Li, Yuyu Shi and Yanfang Meng

Micromachines 2026, 17(3), 314; https://doi.org/10.3390/mi17030314 (registering DOI) - 28 Feb 2026

Abstract

The further development of scalable fabrication for perovskite solar cells has been considerably constrained by strong process variability and the lack of a reliable real-time predictive mechanism during the thin-film formation process. Existing machine learning-based methods are incapable of capturing the inherent multi-stage [...] Read more.

The further development of scalable fabrication for perovskite solar cells has been considerably constrained by strong process variability and the lack of a reliable real-time predictive mechanism during the thin-film formation process. Existing machine learning-based methods are incapable of capturing the inherent multi-stage kinetic characteristics and uncertainties of the perovskite crystallization process, as they rely on deterministic point prediction models and flatten time-series signals into static features, which necessitates more advanced modeling strategies. To address these challenges, an in situ process monitoring and predictive modeling framework based on a lightweight probabilistic Transformer is proposed for the scalable preparation of perovskite thin films. The strategically designed inputs, consisting of time-resolved photoluminescence (PL) and diffuse reflectance imaging signals acquired during the vacuum quenching process, enable the model to directly learn the conditional probability distribution of the final device performance metrics. Rather than producing a single predicted value, this method enables the explicit quantification of prediction uncertainty, providing statistical support for uncertainty-aware process assessment. Leveraging its advantages over feed-forward neural networks and traditional tree-based machine learning methods, the proposed Transformer architecture effectively captures the staged and non-stationary kinetic features of thin-film formation. Consequently, it exhibits higher robustness and superior uncertainty calibration capability during the early-stage prediction phase. The results demonstrate that the probabilistic Transformer-based modeling paradigm provides a viable pathway toward uncertainty-aware, data-driven process evaluation in perovskite manufacturing. This framework extends its application beyond perovskite photovoltaic device fabrication, providing a generalizable modeling strategy for real-time predictive assessment in the preparation of other complex materials governed by irreversible stochastic dynamics. Full article

(This article belongs to the Special Issue Advanced Thin-Films: Design, Fabrication and Applications, Third Edition)

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15 pages, 1229 KB

Open AccessArticle

Xylem Hydraulic Conductance and Stomatal Aperture Ratio Are Key Factors in Enhancing Drought Tolerance in Cotton

by Yang Nan, Yunrui Chen, Ziliang Li, Fubin Liang, Dongsheng Sun, Qipeng Zhang, Wangfeng Zhang, Lan Zhu and Yali Zhang

Agronomy 2026, 16(5), 546; https://doi.org/10.3390/agronomy16050546 (registering DOI) - 28 Feb 2026

Abstract

Plant leaf drought tolerance is regulated by the coordinated effects of water transport efficiency, transpirational water loss, and hydraulic safety. Although cotton is considered drought-tolerant, the mechanisms that coordinate water transport and gas exchange to confer drought tolerance remain incompletely understood. In this [...] Read more.

Plant leaf drought tolerance is regulated by the coordinated effects of water transport efficiency, transpirational water loss, and hydraulic safety. Although cotton is considered drought-tolerant, the mechanisms that coordinate water transport and gas exchange to confer drought tolerance remain incompletely understood. In this study, four soil moisture gradients were established under field conditions and maintained consistently throughout the growing season. The relationships among leaf turgor loss point (Ψ_tlp), gas exchange, and hydraulic traits were examined in two cotton cultivars at the peak flowering stage. With increasing drought treatments, Ψ_tlp, stomatal aperture ratio (g_ratio), leaf hydraulic conductance (K_leaf), leaf hydraulic conductance inside the xylem (K_x) and leaf hydraulic conductance outside the xylem (K_ox) declined significantly, with K_x showing the greatest reduction. Both K_x and g_ratio were strongly positively correlated with Ψ_tlp. Anatomically, vein density (D_v) and vessel number (Np) increased, whereas xylem vessel area (Ap) decreased. The reduction in Ap was the primary structural factor driving the decline in K_x and contributing to lower Ψ_tlp. We conclude that cotton enhances drought tolerance through a coordinated hydraulic and osmotic strategy, by modifying xylem anatomy (reducing Ap) to downregulate K_x and by adjusting osmotically to depress Ψ_tlp. The synergistic reduction in K_x and g_ratio slows the decline in leaf water potential, thereby delaying Ψ_tlp and enhancing leaf hydraulic safety during drought. This integration optimizes stomatal regulation and water transport while ensuring hydraulic safety. The findings provide a key theoretical basis and potential breeding targets for the targeted improvement of drought tolerance and water use efficiency in cotton. Full article

(This article belongs to the Special Issue Physiological and Anatomical Responses of Crops to Environmental Factors)

15 pages, 4855 KB

Open AccessArticle

Effect of Sodium Carbonate on Phosphorus Reaction Behavior and Iron Mineral Transformation During Direct Reduction

by Shichao Wu, Bo Li, Yonggang Wei, Haoyuan Xu and Tichang Sun

Minerals 2026, 16(3), 270; https://doi.org/10.3390/min16030270 (registering DOI) - 28 Feb 2026

Abstract

The coal-based direct reduction followed by magnetic separation (CDRMS) is an efficient iron extraction and dephosphorization process, which requires adding additives to improve the phosphorus removal rate. Compared with other additives, sodium carbonate has the advantages of good iron index, high phosphorus removal [...] Read more.

The coal-based direct reduction followed by magnetic separation (CDRMS) is an efficient iron extraction and dephosphorization process, which requires adding additives to improve the phosphorus removal rate. Compared with other additives, sodium carbonate has the advantages of good iron index, high phosphorus removal rate and less environmental pollution. Its role in phosphorus-rich oolitic iron ore (PROIO) where phosphorus exists in the form of apatite has been proved. However, the influence on the phosphorus transformation process in the lattice of iron minerals is not clear. In this paper, the effect of sodium carbonate on phosphorus removal in iron minerals and iron recovery during CDRMS was studied. Compared with not adding chemicals, the addition of sodium carbonate significantly reduced the phosphorus content of direct reduced iron (DRI) from 0.69% to 0.09%. The iron grade increased from 93.28% to 95.08%, and the iron recovery rate rose from 90.61% to 96.48%. The mechanism of sodium carbonate was revealed by using a synchronous thermal analyzer (TG–DSC), X-ray diffractometer (XRD), X-ray photoelectron spectrometer (XPS), scanning electron microscope and energy dispersive spectrometer (SEM–EDS), and vibrating sample magnetometer (VSM). The results show that sodium carbonate reacted with silicon and aluminum components to form nepheline, and the lattice substitution of phosphorus in iron minerals and silicon in nepheline prevents the reduction of phosphorus. In addition, sodium carbonate promotes the reduction of iron minerals, resulting in an increase in the magnetic properties of the reduction products. Full article

(This article belongs to the Section Mineral Processing and Extractive Metallurgy)

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