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Recent Articles  

27 pages, 2831 KB  
Article
Effects of Flight and Processing Parameters on UAS Image-Based Point Clouds for Plant Height Estimation
by Chenghai Yang, Charles P.-C. Suh and Bradley K. Fritz
Remote Sens. 2026, 18(2), 360; https://doi.org/10.3390/rs18020360 (registering DOI) - 21 Jan 2026
Abstract
Point clouds and digital surface models (DSMs) derived from unmanned aircraft system (UAS) imagery are widely used for plant height estimation in plant phenotyping and precision agriculture. However, comprehensive evaluations across multiple crops, flight altitudes, and image overlaps are limited, restricting guidance for [...] Read more.
Point clouds and digital surface models (DSMs) derived from unmanned aircraft system (UAS) imagery are widely used for plant height estimation in plant phenotyping and precision agriculture. However, comprehensive evaluations across multiple crops, flight altitudes, and image overlaps are limited, restricting guidance for optimizing flight strategies. This study evaluated the effects of flight altitude, side and front overlap, and image processing parameters on point cloud generation and plant height estimation. UAS imagery was collected at four altitudes (30–120 m, corresponding to 0.5–2.0 cm ground sampling distance, GSD) with multiple side and front overlaps (67–94%) over a 2–ha field planted with corn, cotton, sorghum, and soybean on three dates across two growing seasons, producing 90 datasets. Orthomosaics, point clouds, and DSMs were generated using Pix4Dmapper, and plant height estimates were extracted from both DSMs and point clouds. Results showed that point clouds consistently outperformed DSMs across altitudes, overlaps, and crop types. Highest accuracy occurred at 60–90 m (1.0–1.5 cm GSD) with RMSE values of 0.06–0.10 m (R2 = 0.92–0.95) in 2019 and 0.07–0.08 m (R2 = 0.80–0.89) in 2022. Across multiple side and front overlap combinations at 60–120 m, reduced overlaps produced RMSE values comparable to full overlaps, indicating that optimized flight settings, particularly reduced side overlap with high front overlap, can shorten flight and processing time without compromising point cloud quality or height estimation accuracy. Pix4Dmapper processing parameters strongly affected 3D point cloud density (2–600 million points), processing time (1–16 h), and plant height accuracy (R2 = 0.67–0.95). These findings provide practical guidance for selecting UAS flight and processing parameters to achieve accurate, efficient 3D modeling and plant height estimation. By balancing flight altitude, image side and front overlap, and photogrammetric processing settings, users can improve operational efficiency while maintaining high-accuracy plant height measurements, supporting faster and more cost-effective phenotyping and precision agriculture applications. Full article
(This article belongs to the Special Issue Applications of Unmanned Aerial Remote Sensing in Precision Agriculture)
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24 pages, 3691 KB  
Article
Research on the Complex Network Structure and Spatiotemporal Evolution of Interprovincial Virtual Water Flows in China
by Qing Song, Hongyan Chen and Chuanming Yang
Sustainability 2026, 18(2), 1090; https://doi.org/10.3390/su18021090 (registering DOI) - 21 Jan 2026
Abstract
Water resources constitute a foundational strategic resource, and the efficiency of their spatial allocation profoundly impacts national sustainable development. This study integrates multi-regional input–output modeling, complex network analysis, and exploratory spatiotemporal data analysis methods to systematically examine the patterns, network structures, and spatiotemporal [...] Read more.
Water resources constitute a foundational strategic resource, and the efficiency of their spatial allocation profoundly impacts national sustainable development. This study integrates multi-regional input–output modeling, complex network analysis, and exploratory spatiotemporal data analysis methods to systematically examine the patterns, network structures, and spatiotemporal evolution characteristics of virtual water flows across 30 Chinese provinces from 2010 to 2023. Findings reveal the following: Virtual water flows underwent a three-stage evolution—“expansion–convergence–stabilization”—forming a “core–periphery” structure spatially: eastern coastal and North China urban clusters as input hubs, while East–Northeast–Northwest China served as primary output regions; The virtual water flow network progressively tightened and segmented, evidenced by increased network density, shorter average path lengths, and enhanced clustering coefficients and transitivity. PageRank analysis reveals significant Matthew effects and structural lock-in within the network; LISA time paths indicate stable spatial structures in most provinces, yet dynamic characteristics are prominent in node provinces like Guangdong and Jiangsu. Spatiotemporal transition analysis further demonstrates high overall system resilience (Type0 transitions accounting for 47%), while abrupt transitions in provinces like Hebei and Liaoning are closely associated with national strategies and industrial restructuring. This study provides theoretical and empirical support for establishing a coordinated allocation mechanism between physical and virtual water resources and formulating differentiated regional water governance policies. Full article
(This article belongs to the Section Sustainable Water Management)
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14 pages, 844 KB  
Article
Knowledge-Enhanced Time Series Anomaly Detection for Lithium Battery Cell Screening
by Zhenjie Liu, Yudong Wang and Jianjun He
Processes 2026, 14(2), 371; https://doi.org/10.3390/pr14020371 (registering DOI) - 21 Jan 2026
Abstract
The increasing application of lithium-ion batteries in manufacturing and energy storage systems necessitates high-precision screening of abnormal cells during manufacturing, so as to ensure safety and performance. Existing methods struggle to break down the barrier between prior knowledge and data, suffering from limitations [...] Read more.
The increasing application of lithium-ion batteries in manufacturing and energy storage systems necessitates high-precision screening of abnormal cells during manufacturing, so as to ensure safety and performance. Existing methods struggle to break down the barrier between prior knowledge and data, suffering from limitations such as insufficient detection accuracy and poor interpretability. This becomes even more prominent when facing distributional shifts in data. In this study, we propose a knowledge-enhanced anomaly detection framework for cell screening. This framework integrates domain knowledge, such as electrochemical principles, expert heuristic rules, and manufacturing constraints, into data-driven models. By combining features extracted from charging/discharging curves with rule-based prior knowledge, the proposed framework not only improves detection accuracy but also enables a traceable reasoning process behind anomaly identification. Experiments based on real-world battery production data demonstrate that the proposed framework outperforms baseline models in both precision and recall, making it a promising preferred solution for quality control in intelligent battery manufacturing. Full article
(This article belongs to the Special Issue Process Safety and Control Strategies for Urban Clean Energy Systems)
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24 pages, 9665 KB  
Article
Multi-Physics Based Optimal Design of an Axial-Flux Ferrite Consequent-Pole Motor for Permanent Magnet Reduction Using 3D Finite Element Analysis
by Hyeon-Jun Kim and Soo-Whang Baek
Appl. Sci. 2026, 16(2), 1094; https://doi.org/10.3390/app16021094 (registering DOI) - 21 Jan 2026
Abstract
This paper proposes a multiphysics-based optimal design process for a 750 W axial-flux ferrite consequent-pole (AFCP) pump motor aimed at reducing permanent magnet usage. To mitigate the high computational cost associated with repetitive numerical analyses, a metamodel (surrogate model)-based optimization framework is adopted. [...] Read more.
This paper proposes a multiphysics-based optimal design process for a 750 W axial-flux ferrite consequent-pole (AFCP) pump motor aimed at reducing permanent magnet usage. To mitigate the high computational cost associated with repetitive numerical analyses, a metamodel (surrogate model)-based optimization framework is adopted. A consequent-pole (CP) structure is applied to an initial ferrite axial-flux permanent magnet (AFPM) motor, and ten key design variables are selected for optimization. The electromagnetic performance corresponding to variations in these variables is evaluated using three-dimensional finite element analysis (3D FEA), and the resulting dataset is used to construct metamodels. In AFPM motors incorporating ferrite permanent magnets and a CP structure, electromagnetic performance, thermal saturation, and structural stability collectively limit reliable operation. Therefore, a multiphysics-based evaluation is essential. The optimal design is assessed through electromagnetic, thermal, and structural finite element analyses. According to the 3D FEA results, the optimal model achieves a 46.85% reduction in permanent magnet volume while improving efficiency by 0.75%, reaching 95.53%, compared to the initial model. The torque ripple and peak-to-peak cogging torque are reduced by 28.81% and 31.37%, reaching 0.08 Nm and 0.06 Nm, respectively. In addition, the total harmonic distortion (THD) of the back-electromotive force waveform decreases from 12.4% to 2.53%. Stable operating characteristics are confirmed through demagnetization, thermal, and structural analyses, demonstrating that the proposed optimal design process successfully achieves both permanent magnet reduction and overall performance improvement in ferrite-based AFCP motors. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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14 pages, 1033 KB  
Article
The Effect of Organic Production on the Sugar and Organic Acid Concentration in Different Sour Cherry Cultivars
by Alicja Ponder, Renata Kazimierczak, Małgorzata Żebrowska-Krasuska, Dominika Średnicka-Tober, Agnieszka Głowacka and Ewelina Hallmann
Appl. Sci. 2026, 16(2), 1092; https://doi.org/10.3390/app16021092 (registering DOI) - 21 Jan 2026
Abstract
Sour cherry is one of the most popular stone fruits in Poland. In the organic production system of sour cherries, no artificial pesticides and fertilizers are allowed, which is one of the organic production requirements increasingly appreciated by producers and consumers. The taste [...] Read more.
Sour cherry is one of the most popular stone fruits in Poland. In the organic production system of sour cherries, no artificial pesticides and fertilizers are allowed, which is one of the organic production requirements increasingly appreciated by producers and consumers. The taste of fruits is created by the sugar and organic acid content and their ratio. Vitamin C is known for its health-promoting properties. The aim of the present study was to analyze and compare the concentrations of vitamin C, sugars, and organic acids and their profiles in organic vs. conventional sour cherry fruits representing different cultivars, in a three-year experiment. In the presented experiment, four sour cherry cultivars, ‘Kelleris’ 16, ‘Oblacińska’, ‘Pandy 103’, and ‘Debreceni Bötermö’, were cultivated in two horticultural systems, organic and conventional, and the content of sugars and organic acids was analyzed in the fruit with HPLC methods. Organically cultivated sour cherry fruits were characterized by significantly higher concentrations of sugars and vitamin C only in the first year of the experiment, when the mean concentrations of fructose, glucose, and sucrose in these fruits reached 4.15 g/100 g F.W., 0.37 g/100 g F.W., and 0.27 g/100 g F.W., respectively, and the concentration of vitamin C reached 17.28 mg/100 g F.W. In the two subsequent years, conventional cherries were more abundant in these compounds. Among the tested sour cherry cultivars, ‘Oblačińska’ performed the best in terms of sugar content. The mean value for total sugars for ‘Oblačińska’ cv. was 5.53 g/100 g F.W. In the case of vitamin C, the highest levels (av. 28.13 mg/100 g F.W.) were noted in the fruits of ‘Pandy 103’ cv. The strong year-to-year variability underscores the need for multi-year experiments and, where possible, multi-site trials, to disentangle cultivar × system × environment interactions. Because the quality of sour cherry for fresh consumption and for processing depends mostly on sugar content, for organic production, ‘Oblačińska’ cv. is strongly recommended. Full article
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14 pages, 257 KB  
Article
Role Clarity Among Patient Care Technicians in Saudi Arabia: Outcomes of a Structured Educational Program
by Nashi Masnad Alreshidi, Afaf Mufadhi Alrimali, Wadida Darwiesh Alshammari, Kristine Angeles Gonzales, Maram Nasser Alawad, Eida Habeeb Alshammari, Mohmmad Khalf Al-Shammari, Ohoud Awadh Alreshidi, Fawziah Nasser Alrashedi, Asrar Eid Alrashidi and Lueife Ali Alrashedi
Healthcare 2026, 14(2), 269; https://doi.org/10.3390/healthcare14020269 (registering DOI) - 21 Jan 2026
Abstract
Background: Role clarity is a persistent challenge among Patient Care Technicians (PCTs), contributing to inconsistent task performance and safety risks. In Saudi Arabia, little is known about PCTs’ understanding of their responsibilities. This study evaluated the impact of a targeted educational program designed [...] Read more.
Background: Role clarity is a persistent challenge among Patient Care Technicians (PCTs), contributing to inconsistent task performance and safety risks. In Saudi Arabia, little is known about PCTs’ understanding of their responsibilities. This study evaluated the impact of a targeted educational program designed to improve PCTs’ role clarity, safety practices, and communication. Methods: A quasi-experimental pre-post study was conducted in September 2025 with 35 PCTs from the Hail Health Cluster. The one-day intervention included lectures, discussions, role-play, and case scenarios. Outcomes were measured using a validated instrument across four domains: role clarity; core clinical tasks and safety; communication and ethics; and objective knowledge. Pre-post changes were analyzed using paired t-tests (Cohen’s d), and subgroup differences in change scores were examined using one-way ANOVA (η2) in SPSS v29. Results: Baseline scores were lowest in objective knowledge (41.4%) and role clarity (62.8%). Post-training, total composite scores improved significantly (+10.88%, p < 0.001, d = 1.63), with the most significant gain in objective knowledge (+19.8%, p < 0.001, d = 0.99). Role clarity showed only a modest, non-significant increase (+3.98%, p = 0.088, d = 0.30). No demographic differences were found. Conclusions: Targeted training was effective in reducing knowledge gaps; however, improving role clarity may require organizational reinforcement beyond brief training. Full article
(This article belongs to the Special Issue Strategies and Interventions for Supporting the Holistic Well-Being of Clinicians and Nurses)
31 pages, 1500 KB  
Article
Communication-Efficient Asynchronous Fusion for Multi-Radar Systems via State and Covariance Projection
by Wenhui Xue, Peng Chen, Chunguo Li, Zhenxin Cao and Shuqin Zhang
Electronics 2026, 15(2), 458; https://doi.org/10.3390/electronics15020458 (registering DOI) - 21 Jan 2026
Abstract
Multi-radar systems can significantly improve tracking robustness and accuracy, but practical deployments are challenged by asynchronous sensing timestamps across distributed platforms and by limited communication bandwidth. This paper proposes a communication-efficient asynchronous track fusion framework based on state and covariance projection. Each radar [...] Read more.
Multi-radar systems can significantly improve tracking robustness and accuracy, but practical deployments are challenged by asynchronous sensing timestamps across distributed platforms and by limited communication bandwidth. This paper proposes a communication-efficient asynchronous track fusion framework based on state and covariance projection. Each radar performs local Kalman filtering and transmits only a compact track message consisting of the posterior state estimate, the associated error covariance, and a timestamp. At the fusion center, a causal reference time is chosen as the latest received timestamp, and all tracks are projected to this common time using a hybrid constant-acceleration (CA)/constant-velocity (CV) motion model with appropriately discretized process noise, followed by information-form (inverse-covariance) fusion. Under standard linear-Gaussian assumptions, the fusion rule is minimum mean square error (MMSE)-optimal when the projected estimation errors are approximately independent. We also analyze the computational complexity and the communication payload of the proposed procedure. Monte Carlo simulations with five heterogeneous radars and random inter-radar time offsets up to 37.5 ms over 100 runs show that the proposed fusion reduces the steady-state range root mean square error (RMSE) by about 66% and the radial-velocity RMSE by about 31% relative to the average single-radar tracker, while maintaining statistical consistency as verified by the normalized estimation error squared (NEES). These results indicate that projection-based track fusion provides an effective accuracy–communication trade-off for asynchronous multi-radar tracking. Full article
(This article belongs to the Special Issue Challenges and Opportunities in the Internet of Vehicles)
14 pages, 761 KB  
Article
Clinical and Epidemiological Characteristics of an Oropouche Virus Outbreak in Loreto, Peru (October 2024–March 2025)
by Miguel Ángel Rojo-Pérez, Edgar A. Ramírez-García and Jara Llenas-García
Pathogens 2026, 15(1), 119; https://doi.org/10.3390/pathogens15010119 (registering DOI) - 21 Jan 2026
Abstract
Oropouche virus (OROV) has emerged as a significant arboviral pathogen in South America, responsible for recurrent outbreaks of febrile illness. In the Loreto region of Peru, more than 600 cases were reported in 2024, markedly exceeding expected incidence rates. We conducted a retrospective [...] Read more.
Oropouche virus (OROV) has emerged as a significant arboviral pathogen in South America, responsible for recurrent outbreaks of febrile illness. In the Loreto region of Peru, more than 600 cases were reported in 2024, markedly exceeding expected incidence rates. We conducted a retrospective observational study using clinical–epidemiological records of all RT-qPCR-confirmed cases of Oropouche fever from the Regional Health Directorate of Loreto between October 2024 and March 2025. A total of 100 confirmed cases were identified. The most frequent symptoms were fever (88%), headache (78%), and myalgia (72%). No atypical or neurological presentations were reported. No severe cases or deaths occurred. Eight patients required hospitalization, mainly due to severe abdominal pain, persistent vomiting, arthralgia, and pregnancy. Six pregnant women were identified; three experienced pregnancy complications, though no fetal malformations or miscarriages were observed. This outbreak represents a new OROV epidemic in the region, with fewer cases than in 2024 and predominantly mild clinical courses. Although outcomes were generally favorable, the occurrence of complications in pregnant women underscores the importance of continued molecular surveillance and targeted public health interventions. Full article
(This article belongs to the Special Issue Understanding Emerging and Re-Emerging Viral Infections)
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41 pages, 2850 KB  
Article
Automated Classification of Humpback Whale Calls Using Deep Learning: A Comparative Study of Neural Architectures and Acoustic Feature Representations
by Jack C. Johnson and Yue Rong
Sensors 2026, 26(2), 715; https://doi.org/10.3390/s26020715 (registering DOI) - 21 Jan 2026
Abstract
Passive acoustic monitoring (PAM) using hydrophones enables collecting acoustic data to be collected in large and diverse quantities, necessitating the need for a reliable automated classification system. This paper presents a data-processing pipeline and a set of neural networks designed for a humpback-whale-detection [...] Read more.
Passive acoustic monitoring (PAM) using hydrophones enables collecting acoustic data to be collected in large and diverse quantities, necessitating the need for a reliable automated classification system. This paper presents a data-processing pipeline and a set of neural networks designed for a humpback-whale-detection system. A collection of audio segments is compiled using publicly available audio repositories and extensively curated via manual methods, undertaking thorough examination, editing and clipping to produce a dataset minimizing bias or categorization errors. An array of standard data-augmentation techniques are applied to the collected audio, diversifying and expanding the original dataset. Multiple neural networks are designed and trained using TensorFlow 2.20.0 and Keras 3.13.1 frameworks, resulting in a custom curated architecture layout based on research and iterative improvements. The pre-trained model MobileNetV2 is also included for further analysis. Model performance demonstrates a strong dependence on both feature representation and network architecture. Mel spectrogram inputs consistently outperformed MFCC (Mel-Frequency Cepstral Coefficients) features across all model types. The highest performance was achieved by the pretrained MobileNetV2 using mel spectrograms without augmentation, reaching a test accuracy of 99.01% with balanced precision and recall of 99% and a Matthews correlation coefficient of 0.98. The custom CNN with mel spectrograms also achieved strong performance, with 98.92% accuracy and a false negative rate of only 0.75%. In contrast, models trained with MFCC representations exhibited consistently lower robustness and higher false negative rates. These results highlight the comparative strengths of the evaluated feature representations and network architectures for humpback whale detection. Full article
(This article belongs to the Section Sensor Networks)
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14 pages, 9051 KB  
Article
The Effect of Laser Surface Hardening on the Microstructural Characteristics and Wear Resistance of 9CrSi Steel
by Zhuldyz Sagdoldina, Daryn Baizhan, Dastan Buitkenov, Gulim Tleubergenova, Aibek Alibekov and Sanzhar Bolatov
Materials 2026, 19(2), 423; https://doi.org/10.3390/ma19020423 (registering DOI) - 21 Jan 2026
Abstract
This study presents a systematic investigation of laser surface hardening of 9CrSi tool steel with the aim of establishing the relationships between processing parameters, microstructural evolution, and resulting mechanical and tribological properties under the applied laser conditions. The influence of laser power, modulation [...] Read more.
This study presents a systematic investigation of laser surface hardening of 9CrSi tool steel with the aim of establishing the relationships between processing parameters, microstructural evolution, and resulting mechanical and tribological properties under the applied laser conditions. The influence of laser power, modulation frequency, and scanning speed on the hardened layer depth, microstructure, and surface properties was analyzed. Laser treatment produced a martensitic surface layer with varying fractions of retained austenite, while the transition zone consisted of martensite, granular pearlite, and carbide particles. X-ray diffraction identified the presence of α′-Fe, γ-Fe, and Fe3C phases, with peak broadening associated with increased lattice microstrain induced by rapid self-quenching. The surface microhardness increased from approximately 220 HV0.1 in the untreated state to 950–1000 HV0.1 after laser hardening, with hardened layer thicknesses ranging from about 500 to 750 µm depending on the processing regime. Instrumented indentation showed higher elastic modulus values for all hardened conditions. Tribological tests under dry sliding conditions revealed reduced coefficients of friction and more than an order-of-magnitude decrease in wear rate compared with untreated steel. The results provide a parameter–microstructure–performance map for laser-hardened 9CrSi steel, demonstrating how variations in laser processing conditions affect hardened layer characteristics and functional performance. Full article
(This article belongs to the Special Issue Laser, Plasma, and Radiation Processing of Advanced Functional Materials for Magnetic, Electrotechnical and Electrochemical Applications)
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76 pages, 15480 KB  
Review
Machine Learning in Climate Downscaling: A Critical Review of Methodologies, Physical Consistency, and Operational Applications
by Hamed Najafi, Gareth Lynton Lagerwall, Jayantha Obeysekera and Jason Liu
Water 2026, 18(2), 271; https://doi.org/10.3390/w18020271 (registering DOI) - 21 Jan 2026
Abstract
High-resolution climate projections are essential for regional risk assessment; however, Earth System Models (ESMs) operate at scales far too coarse for local impacts. This review examines how machine learning (ML) downscaling can bridge this divide and addresses a key knowledge gap: how to [...] Read more.
High-resolution climate projections are essential for regional risk assessment; however, Earth System Models (ESMs) operate at scales far too coarse for local impacts. This review examines how machine learning (ML) downscaling can bridge this divide and addresses a key knowledge gap: how to achieve reliable, physically consistent downscaling under future climate change. This article synthesizes ML downscaling developments from 2010 to 2025, spanning early statistical methods to modern deep learning (e.g., convolutional neural networks (CNNs), generative adversarial networks (GANs), diffusion models, and transformers). The analysis introduces a new taxonomy of model families and frames the discussion around the “performance paradox”—the tendency for models with excellent historical skill to falter under non-stationary climate shifts. Our analysis finds that convolutional approaches efficiently capture spatial structure but tend to smooth out extremes, whereas generative models better reproduce high-intensity events at the cost of greater complexity. The study also highlights emerging solutions like physics-informed models and improved uncertainty quantification to tackle persistent issues of physical consistency and trust. Finally, the synthesis outlines a practical roadmap for operational ML downscaling, emphasizing standardized evaluation, out-of-distribution stress tests, and hybrid physics–ML approaches to bolster confidence in future projections. Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
20 pages, 6046 KB  
Article
Genetic Diversity of SARS-CoV-2 in Kazakhstan from 2020 to 2022
by Altynay Gabiden, Andrey Komissarov, Aknur Mutaliyeva, Aidar Usserbayev, Kobey Karamendin, Alexander Perederiy, Artem Fadeev, Ainagul Kuatbaeva, Dariya Jussupova, Askar Abdaliyev, Manar Smagul, Yelizaveta Khan, Marat Kumar, Temirlan Sabyrzhan, Aigerim Abdimadiyeva and Aidyn Kydyrmanov
Viruses 2026, 18(1), 138; https://doi.org/10.3390/v18010138 (registering DOI) - 21 Jan 2026
Abstract
Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had major social and economic consequences worldwide. Whole genome sequencing (WGS) is essential for genomic monitoring, enabling tracking of viral evolution, detection of emerging variants, and identification of introductions and transmission chains to inform timely [...] Read more.
Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had major social and economic consequences worldwide. Whole genome sequencing (WGS) is essential for genomic monitoring, enabling tracking of viral evolution, detection of emerging variants, and identification of introductions and transmission chains to inform timely public health responses. Here, we compile and harmonize SARS-CoV-2 genomic data generated by multiple laboratories across Kazakhstan together with publicly available sequences to provide a national overview of genomic dynamics across successive epidemic waves from 2020 to 2022. We analyzed 4462 genomes deposited in GISAID (including 340 generated in this study), of which 3299 passed Nextclade quality filters, and summarized lineage turnover across major phases (pre-VOC, Alpha, Delta, Omicron BA.1/BA.2, Omicron BA.4/BA.5, and a later recombinant-dominant period). Sequencing intensity varied markedly over time (0.60‰ of confirmed cases during Delta vs. 11.57‰ during the Omicron BA.5 wave), suggesting that lineage diversity and persistence may be underestimated. Pre-VOC circulation included ≥12 Pango lineages with evidence of multiple introductions and sustained local transmission, including a Kazakhstan-restricted B.4.1 lineage that emerged in Nur-Sultan/Astana and disappeared after April 2020. The Tengizchevroil oilfield outbreak comprised B.1.1 viruses with phylogenetic support for ≥three independent introductions. Alpha and Omicron waves were characterized by repeated introductions and heterogeneous origins, whereas Delta was dominated by AY.122 with an additional distinct AY.122 cluster; a notable BF.7 local transmission event was observed during BA.5. We also highlight locally enriched non-lineage-defining mutations. Overall, recurrent importations and variable local amplification shaped SARS-CoV-2 dynamics in Kazakhstan, while interpretation is constrained by strongly time-skewed sequencing. Full article
(This article belongs to the Special Issue Molecular Epidemiology of SARS-CoV-2, 4th Edition)
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26 pages, 15029 KB  
Article
Exploring the Effects of Teas with Different Fermentation Levels and Black Coffee on the Body via the Urine Proteome
by Yuzhen Chen and Youhe Gao
Nutrients 2026, 18(2), 343; https://doi.org/10.3390/nu18020343 (registering DOI) - 21 Jan 2026
Abstract
Background/Objectives: Tea and coffee, two of the most widely consumed beverages worldwide, play important roles in supporting overall health. Changes in the urine proteome reflect the changes in the body influenced by beverage consumption, rather than beverage metabolites. In this study, the effects [...] Read more.
Background/Objectives: Tea and coffee, two of the most widely consumed beverages worldwide, play important roles in supporting overall health. Changes in the urine proteome reflect the changes in the body influenced by beverage consumption, rather than beverage metabolites. In this study, the effects of teas with different fermentation levels and black coffee on the body were explored via urine proteomics analysis. Methods: Urine samples were collected from rats before and after seven consecutive days of consuming green tea, oolong tea, black tea, Pu-erh tea, or black coffee. Both before-and-after comparisons and between-group comparisons were performed, and the samples were analyzed using liquid chromatography coupled with tandem mass spectrometry. Results: The urine proteome reflected the changes in rats after consumption of teas or black coffee for one week. Biological processes and pathways enriched with differential proteins included fat cell differentiation, lipid metabolism, glucose metabolism, fatty acid transport, and immune response. The effects of teas with different fermentation levels and black coffee on the body exhibited a high degree of specificity. Additionally, several identified differential proteins have been reported as biomarkers for diseases such as cancer and cardiovascular diseases. This suggests that beverage consumption, including tea and black coffee, should be considered in urine biomarker research. And the use of biomarker panels may be necessary to improve accuracy. Conclusions: The urine proteome provides a comprehensive and systematic reflection of the effects of all components in teas and black coffee on the body and allows for the distinction of changes in the body after consumption of teas with different fermentation levels and black coffee. Full article
(This article belongs to the Section Nutrition and Metabolism)
28 pages, 516 KB  
Article
Managing Archaeological Heritage Sites: A Comparative Analysis Across Cultural Contexts
by Mohamed Khater, Yehia Mahmoud, Nagwa Zouair, Mahmoud A. Saad and Manal Abdellatif
Heritage 2026, 9(1), 39; https://doi.org/10.3390/heritage9010039 (registering DOI) - 21 Jan 2026
Abstract
This study investigates and compares archaeological site management practices across diverse cultural contexts, focusing on how cultural factors influence preservation, stakeholder involvement, and management strategies. Employing a mixed-methods comparative design, the research integrates field observations, interviews with site managers and local stakeholders, and [...] Read more.
This study investigates and compares archaeological site management practices across diverse cultural contexts, focusing on how cultural factors influence preservation, stakeholder involvement, and management strategies. Employing a mixed-methods comparative design, the research integrates field observations, interviews with site managers and local stakeholders, and archival analysis. Three case studies, the Giza Necropolis in Egypt, Madain Saleh in Saudi Arabia, and the Al-Ain Archaeological Sites in the United Arab Emirates, form the empirical foundation for this analysis. Thematic and qualitative comparative analyses are used to identify cross-cultural patterns, challenges, and best practices. The findings reveal that management approaches are profoundly shaped by their respective cultural settings. Regions with strong traditions of community participation, such as Al-Ain, tend to integrate local knowledge and foster sustainable preservation outcomes. In contrast, state-dominated systems, as seen in Egypt and Saudi Arabia, often face constraints related to bureaucratic processes and limited local engagement. Across all contexts, factors such as governance structures, funding mechanisms, and cultural attitudes toward heritage emerge as decisive in shaping management effectiveness and sustainability. The results offer essential perspectives for the strategy of engaging local communities in the management of archaeological sites, and may be beneficial for implementation in other Arab countries. Full article
(This article belongs to the Section Archaeological Heritage)
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27 pages, 1706 KB  
Article
Cross-Modal Semantic Communication for Text-to-Video Retrieval in Internet of Vehicles
by Zhanping Liu, Chao Wu, Chengjun Feng, Zixiao Zhu and Puning Zhang
Electronics 2026, 15(2), 457; https://doi.org/10.3390/electronics15020457 (registering DOI) - 21 Jan 2026
Abstract
Text-to-video retrieval offers an intelligent solution for Internet of Vehicles (IoV) users to access desired content on demand. However, the constrained communication channels in IoV, characterized by low signal-to-noise ratios (SNR), pose significant obstacles to retrieval performance. To tackle these issues, this study [...] Read more.
Text-to-video retrieval offers an intelligent solution for Internet of Vehicles (IoV) users to access desired content on demand. However, the constrained communication channels in IoV, characterized by low signal-to-noise ratios (SNR), pose significant obstacles to retrieval performance. To tackle these issues, this study presents SemTVR, a semantic communication framework dedicated to achieving superior robustness in text-to-video retrieval tasks in low-SNR IoV environments. By integrating the semantic communication paradigm with edge–cloud collaboration, our architecture leverages roadside unit (RSU) features and cloud resources to enable collaborative retrieval. We introduce a multi-semantic interactive reliable transmission mechanism that utilizes historical search records to enhance semantic recovery accuracy under adverse channel conditions. Furthermore, we devise a cross-modal fine-grained matching strategy assigning differentiated weights to video content and query sentences. Experimental results conducted on authoritative datasets demonstrate that SemTVR significantly outperforms baseline methods in terms of search accuracy, particularly in low SNR scenarios, validating its effectiveness for future IoV applications. Full article
(This article belongs to the Special Issue Challenges and Opportunities in the Internet of Vehicles)
19 pages, 1516 KB  
Article
Energy-Dynamics Sensing for Health-Responsive Virtual Synchronous Generator in Battery Energy Storage Systems
by Yingying Chen, Xinghu Liu and Yongfeng Fu
Batteries 2026, 12(1), 36; https://doi.org/10.3390/batteries12010036 (registering DOI) - 21 Jan 2026
Abstract
Battery energy storage systems (BESSs) are increasingly required to provide grid-support services under weak-grid conditions, where the stability of virtual synchronous generator (VSG) control largely depends on the health status and dynamic characteristics of the battery unit. However, existing VSG strategies typically assume [...] Read more.
Battery energy storage systems (BESSs) are increasingly required to provide grid-support services under weak-grid conditions, where the stability of virtual synchronous generator (VSG) control largely depends on the health status and dynamic characteristics of the battery unit. However, existing VSG strategies typically assume fixed parameters and neglect the intrinsic coupling between battery aging, DC-link energy variations, and converter dynamic performance, resulting in reduced damping, degraded transient regulation, and accelerated lifetime degradation. This paper proposes a health-responsive VSG control strategy enabled by real-time energy-dynamics sensing. By reconstructing the DC-link energy state from voltage and current measurements, an intrinsic indicator of battery health and instantaneous power capability is established. This energy-dynamics indicator is then embedded into the VSG inertia and damping loops, allowing the control parameters to adapt to battery health evolution and operating conditions. The proposed method achieves coordinated enhancement of transient stability, weak-grid robustness, and lifetime management. Simulation studies on a multi-unit BESS demonstrate that the proposed strategy effectively suppresses low-frequency oscillations, accelerates transient convergence, and maintains stability across different aging stages. Full article
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22 pages, 1378 KB  
Systematic Review
Current Challenges and Long-Term Outcomes in Corneal Transplantation in Infectious Keratitis—A Systematic Review
by Ancuța-Georgiana Onofrei, Alina Gabriela Gheorghe, Ana Maria Dascalu, Bogdan Mihai Cristea, Sinziana Istrate, Ana Maria Arghirescu, Dragos Serban, Corneliu Tudor, Paul Lorin Stoica, Marina-Ionela Nedea and Dan Dumitrescu
J. Clin. Med. 2026, 15(2), 871; https://doi.org/10.3390/jcm15020871 (registering DOI) - 21 Jan 2026
Abstract
Background/Objectives: Infectious keratitis remains a major cause of blindness worldwide, and many cases progress to therapeutic keratoplasty despite advances in antimicrobial therapy. This systematic review aims to evaluate the outcomes of therapeutic keratoplasty in microbial keratitis and examine factors influencing anatomical success, graft [...] Read more.
Background/Objectives: Infectious keratitis remains a major cause of blindness worldwide, and many cases progress to therapeutic keratoplasty despite advances in antimicrobial therapy. This systematic review aims to evaluate the outcomes of therapeutic keratoplasty in microbial keratitis and examine factors influencing anatomical success, graft survival, and visual rehabilitation. Methods: A systematic review was conducted following PRISMA guidelines, including English-language studies, published between 2000 and 2025. Studies with ≥10 eyes and ≥6 months follow-up were included. Data on infection control, graft clarity, anatomical success, visual acuity, and complications were extracted. Results: Fourteen studies encompassing 1527 eyes were analyzed. TPK accounted for 89% of procedures; DALK was used selectively for anterior or mid-stromal infections. Overall infection control ranged from 69 to 100%, with globe preservation in 85–100% of cases. Bacterial keratitis had higher cure rates and graft clarity than fungal or Acanthamoeba keratitis. Larger grafts (>8 mm) and deep stromal involvement were associated with increased graft rejection and postoperative complications. DALK offered higher graft survival and lower immunologic risk when the endothelium was spared. Visual outcomes were generally limited, reflecting preoperative disease severity, timing of surgery, and postoperative immunomodulation constraints. Early surgical intervention improved anatomical outcomes in severe fungal keratitis. Conclusions: Therapeutic keratoplasty is an effective globe-preserving intervention in advanced microbial keratitis, but with limited functional outcomes. Further prospective studies are needed to refine surgical indications, postoperative management, and long-term functional results. Full article
(This article belongs to the Special Issue New Insights in Ophthalmic Surgery)
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15 pages, 458 KB  
Article
Feedback Structures Generating Policy Exposure, Gatekeeping, and Care Disruption in Transgender and Gender Expansive Healthcare
by Braveheart Gillani, Rem Martin, Augustus Klein, Meagan Ray-Novak, Alyssa Roberts, Dana Prince, Laura Mintz and Scott Emory Moore
Systems 2026, 14(1), 112; https://doi.org/10.3390/systems14010112 (registering DOI) - 21 Jan 2026
Abstract
Transgender and gender-expansive (TGE) communities face persistent health inequities that are reproduced through everyday administrative and clinical encounters across care systems. A feedback-focused lens can clarify how those inequities are generated and sustained. Objective: To identify and validate feedback loops that create policy [...] Read more.
Transgender and gender-expansive (TGE) communities face persistent health inequities that are reproduced through everyday administrative and clinical encounters across care systems. A feedback-focused lens can clarify how those inequities are generated and sustained. Objective: To identify and validate feedback loops that create policy exposure and institutional gatekeeping in TGE healthcare and to surface leverage points to stabilize their continuity of care. Methods: Two facilitated, Zoom-based Group Model Building (GMB) sessions were conducted in March 2021 with eight TGE participants (mean age 38 years; range 22–63; transfeminine and transmasculine identities; multiracial, White, and SWANA racial identities) recruited through a Lesbian Gay Bisexual and Transgender (LGBT) community center, followed by a participant member-checking session to validate loop structure, causal direction, and interpretive accuracy. Analysis focused explicitly on identifying reinforcing and balancing feedback structures, rather than isolated barriers, to explain how policy exposure and institutional gatekeeping are generated over time. Results: Participants co-constructed a nine-variable Causal Loop Diagram (CLD) with six feedback structures, four reinforcing and two balancing that interact dynamically to amplify or dampen policy exposure, institutional gatekeeping, and continuity of care, which were organized across structural, institutional/clinical, and individual/community tiers. Reinforcing dynamics linked structural stigma, exclusion from formal employment, institutionalized provider bias, and enacted stigma to degraded care experience, increased trauma and distrust, and disrupted continuity, manifesting as policy exposure (e.g., coverage volatility, denials) and gatekeeping (e.g., discretionary documentation, referral hurdles). Community-based supports and peer/elder navigation functioned as balancing loops that reduced trauma, improved continuity and encounters, and, over time, dampened provider bias. A salient theme was the visibility/invisibility paradox: symbolic inclusion without workflow redesign can inadvertently increase exposure and reinforce harmful loops. Full article
(This article belongs to the Section Systems Practice in Social Science)
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20 pages, 5546 KB  
Article
Unexpected Encounter: A New Genus of Orthosiini (Noctuidae: Hadeninae) Revealed by Tit Predation in Late-Winter Baihuashan National Nature Reserve, Beijing
by Jun Wu, Nan Yang, László Ronkay and Hui-Lin Han
Insects 2026, 17(1), 121; https://doi.org/10.3390/insects17010121 (registering DOI) - 21 Jan 2026
Abstract
During a late-winter field survey in Baihuashan National Nature Reserve, Beijing, several noctuid moths were observed flying during the daytime at low temperatures and being actively preyed upon by Marsh tits, which removed the heads and wings of captured individuals. These observations indicate [...] Read more.
During a late-winter field survey in Baihuashan National Nature Reserve, Beijing, several noctuid moths were observed flying during the daytime at low temperatures and being actively preyed upon by Marsh tits, which removed the heads and wings of captured individuals. These observations indicate that adults of this noctuid lineage are active in late winter, providing a critical nutritional resource for insectivorous birds during the ecologically constrained, food-limited winter period. Here, we formally describe this lineage as a new genus, Shoudus gen. nov., based on a new species, S. baihuashanus sp. nov., collected from Baihuashan reserve, including three specimens retrieved during active interception of tit predation, along with detached wings and heads recovered from the snow. The new genus is placed in the tribe Orthosiini Guenée, 1837, primarily based on adult external morphology, including large compound eyes with long interfacetal hairs and bipectinate male antennae, as well as forewing patterning similar to certain orthosiine genera such as Perigrapha and Clavipalpula. Notably, the dark reddish-brown forewings with sharply contrasting pale markings, as seen in the new genus and these related genera, appear well adapted for camouflage against bark, leaf litter, and exposed soil in their habitats—potentially functioning as both background matching and disruptive coloration. To further assess its phylogenetic placement, we conducted a molecular analysis based on mitochondrial COI sequences (13 newly generated and 6 retrieved from BOLD/NCBI). The resulting maximum likelihood and Bayesian trees consistently support the monophyly of the new genus and reveal a close phylogenetic relationship with Orthosia, the type genus of Orthosiini. This integrative evidence strongly supports the recognition of Shoudus as a distinct lineage within Orthosiini. Full article
(This article belongs to the Special Issue Revival of a Prominent Taxonomy of Insects—2nd Edition)
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26 pages, 2126 KB  
Article
A Reinforcement Learning Approach for Automated Crawling and Testing of Android Apps
by Chien-Hung Liu, Shu-Ling Chen and Kun-Cheng Chan
Appl. Sci. 2026, 16(2), 1093; https://doi.org/10.3390/app16021093 (registering DOI) - 21 Jan 2026
Abstract
With the growing global popularity of Android apps, ensuring their quality and reliability has become increasingly important, as low-quality apps can lead to poor user experiences and potential business losses. A common approach to testing Android apps involves automatically generating event sequences that [...] Read more.
With the growing global popularity of Android apps, ensuring their quality and reliability has become increasingly important, as low-quality apps can lead to poor user experiences and potential business losses. A common approach to testing Android apps involves automatically generating event sequences that interact with the app’s graphical user interface (GUI) to detect crashes. To support this, we developed ACE (Android Crawler), a tool that systematically generates events to test Android apps by automatically exploring their GUIs. However, ACE’s original heuristic-driven exploration can be inefficient in complex application states. To address this, we extend ACE with a deep reinforcement learning-based crawling strategy, called Reinforcement Learning Strategy (RLS), which tightly integrates with ACE’s GUI exploration process by learning to intelligently select GUI components and interaction actions. RLS leverages the Proximal Policy Optimization (PPO) algorithm for stable and efficient learning and incorporates an action mask to filter invalid actions, thereby reducing training time. We evaluate RLS on 15 real-world Android apps and compare its performance against the original ACE and three state-of-the-art Android testing tools. Results show that RLS improves code coverage by an average of 2.1% over ACE’s Nearest unvisited event First Search (NFS) strategy and outperforms all three baseline tools in terms of code coverage. Paired t-test analyses further confirm that these improvements are statistically significant, demonstrating its effectiveness in enhancing automated Android GUI testing. Full article
(This article belongs to the Topic Electronic Communications, IOT and Big Data, 2nd Volume)
15 pages, 4774 KB  
Article
Solid-State Fermentation of Jatropha curcas Cake by Pleurotus ostreatus or Ganoderma lucidum Mycelium to Determine Multi-Bioactivities
by Enrique Javier Olloqui, Emmanuel Pérez-Escalante, Raúl Velasco-Azorsa, Carlos Gutierrez, Juan Carlos Moreno-Seceña and Daniel Martínez-Carrera
Foods 2026, 15(2), 386; https://doi.org/10.3390/foods15020386 (registering DOI) - 21 Jan 2026
Abstract
Non-toxic Jatropha curcas cake is a by-product rich in protein that can be used in the food industry. Proteolytic kinetics were used to identify and quantify its antioxidant, antidiabetic, angiotensin-converting enzyme inhibitory, and hypocholesterolemic capacities. J. curcas cake was subjected to two systems [...] Read more.
Non-toxic Jatropha curcas cake is a by-product rich in protein that can be used in the food industry. Proteolytic kinetics were used to identify and quantify its antioxidant, antidiabetic, angiotensin-converting enzyme inhibitory, and hypocholesterolemic capacities. J. curcas cake was subjected to two systems of solid-state fermentation (SSF) hydrolysis by Pleurotus ostreatus (FPO) or Ganoderma lucidum (FGL), recording every 6 d until 24 d had passed. The maximum proteolytic capacity in FPO was reached on day 6 of the study, whereas FGL was achieved at 12 d. The FPO and FGL electrophoresis gels revealed the presence of 28 bands corresponding to peptides with molecular weights of less than 10 kDa in both systems analyzed. The highest FRAP values were obtained at 12 d for FPO and at the start of SSF for FGL. The highest antidiabetic capacity of FPO was obtained at 18 d and that of FGL at 24 d. The best antihypertensive activity obtained for FPO and FGL was observed at 6 d. FPO’s highest hypocholesterolemic activity was observed at the start of the SSF, while FGL’s was obtained at 24 d, which is the first report of the hypocholesterolemic activity of J. curcas. It should be noted that fermentation with G. lucidum outperformed fermentation with P. ostreatus, confirming its greater multi-bioactivity. The authors consider this method easy, practical, and generally recognized as safe (GRAS) for obtaining bioactive peptides. Full article
(This article belongs to the Special Issue Advances in Plant-Based Foods: From Sustainable Production to Functional Applications)
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14 pages, 3084 KB  
Article
Effect of Trans-Cinnamaldehyde on Moisture-Related Properties of Lime–Cement Plaster
by Adam Fišer, Miloš Jerman, Martin Böhm, Vojtěch Pommer, Jakub Vrzáň and Klára Kobetičová
Buildings 2026, 16(2), 443; https://doi.org/10.3390/buildings16020443 (registering DOI) - 21 Jan 2026
Abstract
In the present study, the effects of trans-cinnamaldehyde (TCA) addition on selected properties of lime–cement plaster were investigated. The algicidal effect of TCA on natural biofilm isolated from lime–cement plaster was investigated in the first experiment. Concentrations of 200 mg/L or higher caused [...] Read more.
In the present study, the effects of trans-cinnamaldehyde (TCA) addition on selected properties of lime–cement plaster were investigated. The algicidal effect of TCA on natural biofilm isolated from lime–cement plaster was investigated in the first experiment. Concentrations of 200 mg/L or higher caused complete inhibition of algal growth. Two TCA solutions (0.02% and 1.5% w/w relative to binders) were then used for the preparation of plaster according to the results of biological testing and previous research. The results did not indicate any practically relevant statistically significant effect of TCA on compressive and bending strength, while the total porosity increased with higher aldehyde concentration in the matrix and the matrix and bulk density decreased. Samples with 1.5% TCA showed reduced moisture uptake, indicating improved moisture-related behavior under high-humidity conditions. The occurrence of micropores in the structure compared to the reference was revealed by scanning electron microscopy. The main conclusions of the study are that TCA can be considered for the improvement of algicidal formulations in the form of protective coatings and as an additive influencing the moisture-related behavior of plaster, with beneficial effects observed at a TCA content of 1.5% w/w. Full article
(This article belongs to the Special Issue Advances in Environmentally-Friendly Building Materials in Construction)
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22 pages, 4099 KB  
Article
Diagenetic Characteristics and Evolution of Low-Permeability Clastic Reservoirs in the Mesozoic of the Tanhai Zone, Jiyang Depression
by Dongmou Huang, Shaochun Yang, Qunhu Wu, Yanjia Wu, Shilong Ma and Yifan Zhang
Minerals 2026, 16(1), 106; https://doi.org/10.3390/min16010106 (registering DOI) - 21 Jan 2026
Abstract
In multi-phase tectonic activity areas, complex stratigraphic uplift-subsidence cycles lead to multi-phase, superimposed diagenesis. This obscures the mechanisms of reservoir property evolution and makes predicting diagenetic sweet spots difficult. This study investigates the low-permeability clastic reservoirs in the Mesozoic of the Tanhai area, [...] Read more.
In multi-phase tectonic activity areas, complex stratigraphic uplift-subsidence cycles lead to multi-phase, superimposed diagenesis. This obscures the mechanisms of reservoir property evolution and makes predicting diagenetic sweet spots difficult. This study investigates the low-permeability clastic reservoirs in the Mesozoic of the Tanhai area, Jiyang Depression. Integrating thin-section petrography, scanning electron microscopy (SEM), X-ray diffraction (XRD), high-pressure mercury injection, and burial history analysis, it reveals multi-phase diagenetic characteristics from a tectonic perspective and quantifies pore structure modification mechanisms. Results show the reservoirs underwent strong compaction and multi-phase carbonate-dominated cementation. Dissolution is further distinguished into meteoric water, organic acid, and volcanic material-related alkaline dissolution. Pore-throat evolution indicates that compaction and cementation shift pores towards micropores (<0.1 µm), while meteoric and alkaline dissolution enlarge mesopores (0.1–10 µm) crucial for permeability. Reservoir diagenesis is divided into five tectonic—diagenetic stages. A quantitative model identifies two diagenetic sweet spot types: (1) zones near unconformities intensely leached by meteoric water, and (2) relatively shallow intervals affected by alkaline dissolution related to volcanic rocks under deep burial. This study establishes a tectonic—diagenetic—pore structure framework. It provides a basis for predicting reservoir sweet spots in analogous multi-phase tectonic settings. Full article
(This article belongs to the Special Issue Natural and Induced Diagenesis in Clastic Rock)
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13 pages, 1797 KB  
Article
Enhanced Gas Classification in Electronic Nose Systems Using an SMOTE-Augmented Machine Learning Framework
by Minqiang Li, Chenxi Wu, Zhiyang Wang, Zhijian Wu, Wei Huang, Junru Chen, Kaibo Yu, Ting Wen, Hongbo Yin and Zhuqing Wang
Sensors 2026, 26(2), 714; https://doi.org/10.3390/s26020714 (registering DOI) - 21 Jan 2026
Abstract
Electronic nose systems are widely used in environmental monitoring and other related fields. In recent years, systems based on gas sensor arrays have attracted considerable attention. However, relying solely on improvements in gas-sensitive materials has struggled to break through the bottleneck in recognition [...] Read more.
Electronic nose systems are widely used in environmental monitoring and other related fields. In recent years, systems based on gas sensor arrays have attracted considerable attention. However, relying solely on improvements in gas-sensitive materials has struggled to break through the bottleneck in recognition accuracy. To address this challenge, this study designs and validates an integrated machine learning framework for enhanced gas identification in electronic nose systems. Specifically, (1) a Butterworth low-pass filter is combined with principal component analysis (PCA) to suppress sensor noise; (2) the synthetic minority over-sampling technique (SMOTE) is utilized for training set data augmentation to further enhance the classification accuracy of the support vector machine (SVM); and (3) the relationship between single-component and mixed-gas responses is analyzed to construct an artificial neural network (ANN) regression model. Experimental results demonstrate that the SMOTE-augmented, PCA-optimized SVM model achieves a recognition accuracy of 0.93 ± 0.08 for most target gases, representing improvements of 19% and 7% over decision tree and ANN classifiers, respectively, and that the ANN regression model attains a correlation coefficient of 99.55% between predicted and measured values in mixed-gas experiments. Overall, the construction and optimization of this system demonstrate significant practical value for intelligent gas identification and the development of advanced e-nose devices. Full article
(This article belongs to the Section Intelligent Sensors)
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48 pages, 4602 KB  
Article
Sequential Extraction Evaluation of Rock-Hosted Elements Using a pH Range Relevant to CO2 Geo-Sequestration
by Grant K. W. Dawson, Suzanne D. Golding, Dirk Kirste and Julie K. Pearce
Geosciences 2026, 16(1), 49; https://doi.org/10.3390/geosciences16010049 (registering DOI) - 21 Jan 2026
Abstract
Detailed geochemical modelling of the potential groundwater impacts of CO2 geo-sequestration requires site-specific knowledge of how mobile elements are hosted within rocks. We present a simple sequential extraction procedure analogous to pH conditions produced by different partial pressures of carbon dioxide (CO [...] Read more.
Detailed geochemical modelling of the potential groundwater impacts of CO2 geo-sequestration requires site-specific knowledge of how mobile elements are hosted within rocks. We present a simple sequential extraction procedure analogous to pH conditions produced by different partial pressures of carbon dioxide (CO2) in contact with water. The procedure consists of three sequential steps: water at pH 7; acetic acid–ammonium acetate at pH 5 and then at pH 3, with the amounts of specific elements extracted by each step considered with respect to the whole rock total element abundance. Our purpose in developing this procedure is three-fold: (1) identify readily mobilized suites of elements for groundwater baseline and monitor bore studies; (2) provide insights regarding the mode/s of occurrence of easily extracted elements within rock samples; and (3) suggest possible mechanisms for the mobilization of rock-sourced elements into groundwater under neutral to moderately acidic pH that can inform the reactive transport modelling of carbon storage sites. In our case study, the second step extracted most of the main mobile elements of interest. Full article
(This article belongs to the Topic New Advances in Carbon Capture and Storage (CCS) Geochemistry)
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15 pages, 3355 KB  
Article
Deleterious Mutations in the Mitogenomes of Cetacean Populations
by Matthew Freeman, Umayal Ramasamy and Sankar Subramanian
Biology 2026, 15(2), 199; https://doi.org/10.3390/biology15020199 (registering DOI) - 21 Jan 2026
Abstract
Cetaceans are artiodactyls adapted to live in the marine environment, and this group includes whales, dolphins, and porpoises. Although mitochondrial nucleotide diversity has been reported separately for many cetacean groups, the proportion of deleterious mutations in these populations is unknown. Furthermore, a comparison [...] Read more.
Cetaceans are artiodactyls adapted to live in the marine environment, and this group includes whales, dolphins, and porpoises. Although mitochondrial nucleotide diversity has been reported separately for many cetacean groups, the proportion of deleterious mutations in these populations is unknown. Furthermore, a comparison of mitogenomic diversities across all cetaceans is also lacking. To investigate this, we conducted a comparative genomic analysis of 2244 mitochondrial genomes from 65 populations across 32 cetacean species. We observed a 78-fold variation in mitogenomic diversity among cetacean populations, suggesting a large difference in genetic diversity. We used the ratio of nonsynonymous-to-synonymous diversities (dN/dS) to measure the proportion of deleterious mutations in the mitochondrial exomes. The dN/dS ratio showed a 22-fold difference between the cetacean population. Based on genetic theories, the large differences observed in the two measures could be attributed to differences in the effective sizes of the cetacean populations. Typically, small populations have low heterozygosity and a high dN/dS ratio, and the reverse is true for large populations. This was further confirmed by the negative correlation observed between heterozygosity and dN/dS ratios of cetacean populations. While our analysis revealed similarities in mitogenomic diversity between the endangered and least-concern cetacean species, the dN/dS ratio of the former was found to be higher than that of the latter. The findings of this study are useful for identifying the relative magnitude of reductions in the population sizes of different cetacean species. This will help conservation management efforts prioritise the use of limited resources, time, and effort to protect the cetacean populations that need immediate attention. Full article
(This article belongs to the Special Issue Genetic Variability within and between Populations)
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