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6 pages, 281 KB

Open AccessEditorial

Recent Advances in Wearable Biosensors for Human Health Monitoring

by Xiaojun Xian

Biosensors 2026, 16(1), 27; https://doi.org/10.3390/bios16010027 (registering DOI) - 1 Jan 2026

As the healthcare system transitions from traditional hospital-centered care to point-of-care and home-care systems, the demand for wearable sensors is increasing rapidly due to their ability to continuously monitor human health and support medical diagnostics [...] Full article

(This article belongs to the Special Issue Recent Advances in Wearable Biosensors for Human Health Monitoring)

23 pages, 1795 KB

Open AccessArticle

Permeability of Phospholipid Membranes to Divalent Cations: The Effect of Pulsed Electric Field

by Małgorzata Jurak, Monika Sujka, Agnieszka Ewa Wiącek and Urszula Pankiewicz

Molecules 2026, 31(1), 151; https://doi.org/10.3390/molecules31010151 (registering DOI) - 1 Jan 2026

Abstract

Achieving a high nutritional value of food often involves fortifying microorganisms (such as bacteria and yeast) used in baking and dairy industry with essential elements. The aim of this study was to investigate the effect of a pulsed electric field (PEF) on the [...] Read more.

Achieving a high nutritional value of food often involves fortifying microorganisms (such as bacteria and yeast) used in baking and dairy industry with essential elements. The aim of this study was to investigate the effect of a pulsed electric field (PEF) on the penetration and accumulation of Ca²⁺ and Mg²⁺ ions into model membranes of the food-grade yeast Saccharomyces cerevisiae. Simplified model membranes (monolayers and liposomes) were constructed using the phospholipid 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC). The Langmuir monolayer technique, dynamic light scattering (DLS) and microelectrophoresis were employed to characterize the physicochemical properties of the model membranes investigated. The results showed significant molecular-level differences in the interactions of the selected cations with lipid monolayers and bilayers in liposome structures. Both cations deeply penetrated the membrane’s hydrophilic region, yet two competing effects were evident: expansion induced by hydrated Mg²⁺ and condensation driven by Ca²⁺ bridging. Furthermore, the application of PEF increased the concentration of ions absorbed by the liposomes. Specifically, optimized PEF parameters resulted in cation accumulation within the model membranes, ranging from 6 to 13%. This finding correlates well with the increased Ca²⁺ and Mg²⁺ uptake observed in real yeast cells, providing a deeper understanding of the cell membrane-environment interface and the underlying processes. Full article

(This article belongs to the Special Issue Novel Membranes and Coatings for Biomedical and Food Applications)

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23 pages, 6554 KB

Open AccessArticle

BacT-Seq, a Nanopore-Based Whole-Genome Sequencing Workflow Prototype for Rapid and Accurate Pathogen Identification and Resistance Prediction from Positive Blood Cultures: A Feasibility Study

by Meriem El Azami, Véronique Lanet, Corinne Beaulieu, Aurélien Griffon, Stéphane Schicklin, Pierre Mahé, Marion Darnaud, Marion Helsmoortel, Erwin Sentausa, Adrien Saliou, Mallory Poncelet, Raphaël Fleury, Marine Ibranosyan, François Vandenesch and Emmanuelle Santiago-Allexant

Diagnostics 2026, 16(1), 133; https://doi.org/10.3390/diagnostics16010133 (registering DOI) - 1 Jan 2026

Abstract

Background/Objectives: Rapid and accurate pathogen identification and antimicrobial susceptibility testing (AST) are critical for the proper management of patients with bloodstream infection (BSI). Real-time whole-genome sequencing (WGS) represents an attractive opportunity for exhaustive pathogen identification and antimicrobial susceptibility prediction (ASP). This feasibility [...] Read more.

Background/Objectives: Rapid and accurate pathogen identification and antimicrobial susceptibility testing (AST) are critical for the proper management of patients with bloodstream infection (BSI). Real-time whole-genome sequencing (WGS) represents an attractive opportunity for exhaustive pathogen identification and antimicrobial susceptibility prediction (ASP). This feasibility study introduces BacT-Seq, a WGS-based prototype assay for the rapid and accurate identification of pathogens and the prediction of antimicrobial susceptibility from positive blood cultures using Oxford Nanopore Technologies (ONT) sequencing. Methods: A total of 200 positive blood culture samples from patients with a confirmed BSI were included in this study. DNA isolation from blood cultures was optimized prior to GridION (ONT) sequencing. Pathogen identification and several ASP methods were compared to conventional identification and phenotypic AST methods. Results: Most of the mono-microbial (89%) and poly-microbial (88%) samples were identified by BacT-Seq in less than 10 min of sequencing. While identification of poly-microbial samples remains challenging, identification of mono-microbial samples by sequencing was non-inferior to that of the conventional approach, even revealing an added value in terms of exhaustivity and/or taxonomic resolution. Machine-learning-based ASP models yielded 80% predictions in 2.5 h of sequencing. Their ability to predict resistance phenotypes varied with the microbial species evaluated, from 55/57 (96.5%) for Escherichia coli to 24/48 (50.0%) for Pseudomonas aeruginosa. Conclusions: This study demonstrates the feasibility of implementation of the BacT-Seq platform for the fast and accurate identification of pathogens from positive blood cultures. BacT-Seq performance of resistance predictions by bioinformatics tools is promising but requires further optimization and validation before clinical implementation. Full article

(This article belongs to the Special Issue New Diagnostic and Testing Strategies for Infectious Diseases)

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17 pages, 1346 KB

Open AccessArticle

Alginate-Based Beads Containing Artemisia absinthium L. Extract as Innovative Ingredients for Baked Products

by Alessandro Candiani, Giada Diana, Vincenzo Disca, Yassine Jaouhari, Margherita Stampini, Stefano Salamone, Federica Pollastro, Jessica Baima, Flavia Prodam, Sabrina Tini, Marta Bertolino, Lorella Giovannelli, Lorena Segale, Jean Daniel Coïsson and Marco Arlorio

Gels 2026, 12(1), 43; https://doi.org/10.3390/gels12010043 (registering DOI) - 1 Jan 2026

Abstract

Artemisia absinthium L. is a medicinal plant well known for the bitterness of its sesquiterpenoids. To mask its intense taste while preserving these active compounds, an ethanolic extract (AAE) was prepared, and two microencapsulation techniques (spray drying and ionotropic gelation) were investigated under [...] Read more.

Artemisia absinthium L. is a medicinal plant well known for the bitterness of its sesquiterpenoids. To mask its intense taste while preserving these active compounds, an ethanolic extract (AAE) was prepared, and two microencapsulation techniques (spray drying and ionotropic gelation) were investigated under different process conditions. The best-performing formulation was selected for larger-scale production and a characterisation of the microparticles (MPs) was carried out. MPs were then incorporated into baked products (biscuits), which were subsequently characterised for proximate composition, total phenolic content (TPC) and antioxidant activity (AA). Bitter compounds were quantified through HPLC-DAD. A panel test was conducted on 50 volunteers, which compiled a satisfactory questionnaire. Ionotropic gelation proved to be the most suitable technique for producing AAE alginate-based MPs for incorporation into biscuit dough, yielding a product with a desirable particle size and flowability. The biscuits still retained a significant amount of TPC and AA, indicating that microencapsulation is a suitable strategy. Data from the acceptance questionnaire revealed that biscuits containing MPs loaded with absinthin-rich extract were comparable to the control ones regarding overall acceptance. In conclusion, a promising product was developed that effectively masks the bitterness of appetite-modulating bioactive compounds, with significant health-promoting potential. However, further investigation into the biological effects (e.g., hormonal responses, feelings of hunger, etc.) of these baked products is required. Full article

(This article belongs to the Special Issue Gels: Diversity of Structures and Applications in Food Science)

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28 pages, 15343 KB

Open AccessArticle

Model–Data Dual-Driven Method for Mode-Switching Radar Target Detection

by Boyu Wang and Gongjian Zhou

Remote Sens. 2026, 18(1), 144; https://doi.org/10.3390/rs18010144 (registering DOI) - 1 Jan 2026

Abstract

Maneuvering targets exhibit range migration (RM) and Doppler-frequency migration (DFM) during the coherent integration period. Most existing coherent integration methods model maneuvering target motion with a single motion mode. However, highly maneuvering targets often undergo mode-switching, which degrades the detection performance of conventional [...] Read more.

Maneuvering targets exhibit range migration (RM) and Doppler-frequency migration (DFM) during the coherent integration period. Most existing coherent integration methods model maneuvering target motion with a single motion mode. However, highly maneuvering targets often undergo mode-switching, which degrades the detection performance of conventional algorithms. To address this problem, this paper proposes a model–data dual-driven method for mode-switching radar targets. From the model-driven perspective, the range evolution over time is derived in the Cartesian coordinate system for transitions among constant-velocity (CV), constant-acceleration (CA), and constant-turn (CT) motions, thereby constructing multiple possible mode-switching scenarios. Subsequently, from the data-driven perspective, a hierarchical residual network and keypoint loss functions are designed to learn and capture the uncertainty associated with mode-switching, thereby accurately inferring the initial and switching points of the target. Furthermore, to enhance the interpretability of the network, probability heatmap visualization is employed to intuitively reveal the internal mechanisms of the network. Finally, by partitioning the Coherent Processing Interval (CPI) based on network-detected keypoints, the proposed method performs efficient piecewise coherent integration for different motion models by integrating along the slow-time echo-envelope migration path. Simulation results demonstrate that the proposed method not only effectively eliminates both RM and DFM but also achieves strong detection performance and favorable computational efficiency. Full article

(This article belongs to the Topic Radar Signal and Data Processing with Applications, 2nd Edition)

19 pages, 518 KB

Open AccessArticle

Maternal Antiretroviral Use and the Risk of Prematurity and Low Birth Weight in Perinatally HIV-Exposed Children—7 Years’ Experience in Two Romanian Centers

by Ana Maria Tudor, Simona Claudia Cambrea, Laurențiu Mihăiță Stratan, Constanța Angelica Vișan, Cătălin Tilișcan, Victoria Aramă and Simona Maria Ruță

Medicina 2026, 62(1), 93; https://doi.org/10.3390/medicina62010093 (registering DOI) - 1 Jan 2026

Abstract

Background and Objectives: Antiretroviral therapy used during pregnancy in HIV infected women effectively reduces vertical transmission, though concerns about potential adverse newborn outcomes persists. This study focused on prematurity and low birth weight in antiretroviral HIV-exposed children in two major Romanian centers, Bucharest [...] Read more.

Background and Objectives: Antiretroviral therapy used during pregnancy in HIV infected women effectively reduces vertical transmission, though concerns about potential adverse newborn outcomes persists. This study focused on prematurity and low birth weight in antiretroviral HIV-exposed children in two major Romanian centers, Bucharest and Constanța, in the context of free access to antiretroviral treatment for pregnant women in Romania since 2001. Materials and Methods: A retrospective observational study was performed including couples of HIV-infected women and their live singleton newborns from 2006 and 2012. Preterm delivery was defined as birth before week 37 and low birth weight was defined as birth weight less than 2500 g in full-term babies. Results: A total number of 352 children and 313 women were enrolled. Mean maternal age at delivery was 23.1 years. Mean newborn birth weight was 2726 g. In the children group, 191 (54.2%) were boys, and the rate of HIV transmission was 13.9%. The prematurity rate was 21.5% and low birth weight rate was 25.56%. Preterm birth was associated with high HIV RNA in the third trimester, HIV-positive final status in infants, and vaginal delivery. Low birth weight was associated with lack of antiretroviral treatment during pregnancy and HIV-positive status in infants. No association was found between prematurity and low birth weight in full-term newborns and exposure to any antiretroviral class, any specific antiviral drug, or with any number of maternal regimens, duration of antiretroviral treatment prior to conception, or maternal exposure during puberty. Conclusions: In our study, preterm birth was significantly associated with HIV vertical transmission in newborns and with exposure to high maternal viral replication during the last trimester of pregnancy. Low birth weight in full-term babies was significantly associated with lack of antiretroviral exposure in utero in our analysis. Full article

(This article belongs to the Section Infectious Disease)

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16 pages, 5401 KB

Open AccessArticle

Enhancing Astaxanthin Production in Paracoccus marcusii Using an Integrated Strategy: Breeding a Novel Mutant and Fermentation Optimization

by Yu Li, Shuyin Huang, Dong Wei and Siyu Pan

Mar. Drugs 2026, 24(1), 19; https://doi.org/10.3390/md24010019 (registering DOI) - 1 Jan 2026

Abstract

Astaxanthin, one of the most commercially valuable carotenoids, is renowned for its potent antioxidant and anti-inflammatory properties and is experiencing growing demand across diverse industries. To enhance astaxanthin production in Paracoccus marcusii, compound mutagenesis was performed using ethyl methanesulfonate (EMS), ultraviolet (UV) [...] Read more.

Astaxanthin, one of the most commercially valuable carotenoids, is renowned for its potent antioxidant and anti-inflammatory properties and is experiencing growing demand across diverse industries. To enhance astaxanthin production in Paracoccus marcusii, compound mutagenesis was performed using ethyl methanesulfonate (EMS), ultraviolet (UV) radiation, and atmospheric room temperature plasma (ARTP) treatment. Subsequently, a high-throughput microbial microdroplet culture (MMC) system was employed to select fast-growing microdroplet, followed by screening for high astaxanthin-producing mutants on dual-inhibitor plates. The mutant M21 was isolated and exhibited a significant increase of 16.86% in astaxanthin content (1.53 mg/g) and a 19.81% increase in astaxanthin production (11.71 mg/L) compared with the wild type (WT) (p < 0.05). Moreover, the enhanced phenotype of M21 was genetically stable. Response surface methodology (RSM)-based optimization of fermentation conditions further increased astaxanthin content and production to 1.72 mg/g and 12.92 mg/L, respectively, corresponding to improvements of 16.44% and 23.02% over the WT, while simultaneously reducing culture time, total nitrogen requirements, and sodium lactate consumption, thereby lowering production costs. This study achieved significant enhancement of astaxanthin production through novel mutant breeding and fermentation optimization, underscoring the effectiveness of this integrated strategy for application in industrial biotechnology. Full article

(This article belongs to the Section Marine Biotechnology Related to Drug Discovery or Production)

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27 pages, 1445 KB

Open AccessReview

Smart Healing for Wound Repair: Emerging Multifunctional Strategies in Personalized Regenerative Medicine and Their Relevance to Orthopedics

by Carla Renata Arciola, Veronica Panichi, Gloria Bua, Silvia Costantini, Giulia Bottau, Stefano Ravaioli, Eleonora Capponi and Davide Campoccia

Antibiotics 2026, 15(1), 36; https://doi.org/10.3390/antibiotics15010036 (registering DOI) - 1 Jan 2026

Abstract

To address the challenges in wound healing, clinical management increasingly demands targeted, adaptive, responsive, and patient-centered strategies. This is especially true for wounds characterized by delayed healing and a high risk of infection. Advances in regenerative medicine and biomaterial technologies are fostering the [...] Read more.

To address the challenges in wound healing, clinical management increasingly demands targeted, adaptive, responsive, and patient-centered strategies. This is especially true for wounds characterized by delayed healing and a high risk of infection. Advances in regenerative medicine and biomaterial technologies are fostering the development of multifunctional approaches that integrate tissue regeneration, antibacterial/antibiofilm activity, immunomodulation, and real-time monitoring. This paper surveys emerging platforms, including both natural and synthetic scaffolds, hydrogels enriched with platelet-derived growth factors, glycosaminoglycan mimetics, bioactive peptides (such as GHK-Cu and antimicrobial peptides), nanoscaffolds, and stimuli-responsive systems. The paper also explores cutting-edge technologies such as water-powered, electronics-free dressings that deliver localized electrical stimulation; biodegradable bioelectric sutures that produce self-sustained mechano-electrical signals; and sensory bandages that monitor pH, moisture, temperature, and bacterial contamination in real-time while enabling on-demand drug release with pro-regenerative, antibacterial, and other therapeutic functionalities. Further therapeutic approaches include natural matrices, exosomes, gene editing, 3D bioprinting, and AI-assisted design. Particular attention is paid to orthopedic applications and orthopedic implant infection. A brief section addresses the still unresolved challenge of articular cartilage regeneration. Interdisciplinary innovation, integrating insights from molecular biology through engineering, plays a central role in translating novel strategies into tailored, clinically effective wound management solutions. Full article

(This article belongs to the Special Issue Advances in the Field of Biofilm-Associated Musculoskeletal Infections)

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34 pages, 4301 KB

Open AccessArticle

Delay-Compensated EKF and Adaptive Delay Threshold Weighting for AUV–MDS Docking

by Han Yan and Shuxue Yan

J. Mar. Sci. Eng. 2026, 14(1), 86; https://doi.org/10.3390/jmse14010086 (registering DOI) - 1 Jan 2026

Abstract

This study tackles real-time state estimation for autonomous underwater vehicle (AUV)–mobile docking station (MDS) cooperation over low-bandwidth, high-latency, jitter-dominated acoustic links, with the goal of turning delayed/out-of-sequence measurements (OOSM) into consistent and informative constraints without sacrificing online operation. We propose an integrated scheme [...] Read more.

This study tackles real-time state estimation for autonomous underwater vehicle (AUV)–mobile docking station (MDS) cooperation over low-bandwidth, high-latency, jitter-dominated acoustic links, with the goal of turning delayed/out-of-sequence measurements (OOSM) into consistent and informative constraints without sacrificing online operation. We propose an integrated scheme centered on a delay-compensated extended Kalman filter (DC-EKF): a ring buffer enables backward updates and forward replay so that OOSM are absorbed strictly at their physical timestamps; a data-driven delay threshold is learned from “effective information gain” combined with normalized estimation error squared (NEES) filtering; and dynamic confidence, derived from innovation statistics, delay, and signal-to-noise ratio (SNR) proxies, scales the measurement noise to adapt fusion weights. Simulations show the learned delay threshold converges to about 6.4 s (final 6.35 s), error spikes are suppressed, and the overall position root-mean-square error (RMSE) is 5.751 m; across the full data stream, 1067 station measurements were accepted and 30 rejected, and the fusion weights shifted smoothly from inertial measurement unit (IMU)-dominant to station-dominant (≈0.16/0.84) over time. On this basis, a cooperative augmented EKF (Co-Aug-EKF) is added as a lightweight upper layer for unified-frame cooperative estimation, further improving relative consistency. The results indicate that the framework reliably maps delayed acoustic measurements into closed-loop useful information, significantly enhancing estimator stability and docking readiness, while remaining practical to deploy and readily extensible. Full article

(This article belongs to the Topic Advanced Technologies and Applications for Unmanned Systems)

26 pages, 1847 KB

Open AccessReview

Transcatheter Arterial Embolization (TAE) of Uterine Artery with Gelatin Sponge for Cesarean Scar Pregnancy: A Current State of the Art Review

by Roberto Minici, Francesco Tiralongo, Massimo Venturini, Federico Fontana, Filippo Piacentino, Melania Nicoletta, Andrea Coppola, Giuseppe Guzzardi, Francesco Giurazza, Fabio Corvino and Domenico Laganà

Gels 2026, 12(1), 44; https://doi.org/10.3390/gels12010044 (registering DOI) - 1 Jan 2026

Abstract

Cesarean scar pregnancy (CSP) carries a high risk of severe hemorrhage and potential loss of fertility. This narrative review summarizes current evidence on uterine artery embolization (UAE) using absorbable gelatin sponge (GS), focusing on GS preparation, procedural approaches, and reported outcomes. PubMed/MEDLINE, Scopus, [...] Read more.

Cesarean scar pregnancy (CSP) carries a high risk of severe hemorrhage and potential loss of fertility. This narrative review summarizes current evidence on uterine artery embolization (UAE) using absorbable gelatin sponge (GS), focusing on GS preparation, procedural approaches, and reported outcomes. PubMed/MEDLINE, Scopus, and Google Scholar were searched from January 2015 to 31 December 2024 for peer-reviewed studies reporting UAE with GS for CSP (GS alone or combined with intra-arterial methotrexate and/or adjunct particles). Fifty studies (N = 3139) were included. Technical success was 3133/3139 (~99.8%) and clinical success was 2975/3139 (~94.8%), with most cohorts reporting high clinical control. Severe complications were infrequently reported (typically ~2–4% in most series). Menstrual function, when assessed, generally recovered within ~1–2 months. Subsequent pregnancy outcomes were inconsistently reported and follow-up durations were heterogeneous, predominantly in retrospective designs. Overall, UAE with GS appears effective for hemostasis in CSP and may reduce escalation to hysterectomy in appropriately selected patients. Standardized reporting of GS preparation and outcomes, as well as prospective multicenter registries/studies, are needed to refine best practices. Full article

(This article belongs to the Special Issue Design and Development of Gelatin-Based Materials (2nd Edition))

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18 pages, 2958 KB

Open AccessArticle

Targeting Arginase 1 but Not Arginase 2 Protects from Myocardial Ischemia–Reperfusion Injury via Nitric Oxide Signaling by Red Blood Cells in Type 2 Diabetes

by Jiangning Yang, Yahor Tratsiakovich, Renhai Cao, Ali Mahdi, Gianluigi Pironti, Tong Jiao, Rawan Humoud, Eftychia Kontidou, John Tengbom, Aida Collado, Zhichao Zhou, Yihai Cao, Eleonore Köhler, Adam E. Mullick and John Pernow

Antioxidants 2026, 15(1), 58; https://doi.org/10.3390/antiox15010058 (registering DOI) - 1 Jan 2026

Abstract

Background: Arginase influences cardiac tolerance to ischemia–reperfusion by modulating nitric oxide (NO) signaling. In type 2 diabetes (T2D), elevated arginase activity may worsen ischemic injury through red blood cells (RBCs), but the specific roles of arginase isoforms are unclear. Methods: C57BL/6 and db/db [...] Read more.

Background: Arginase influences cardiac tolerance to ischemia–reperfusion by modulating nitric oxide (NO) signaling. In type 2 diabetes (T2D), elevated arginase activity may worsen ischemic injury through red blood cells (RBCs), but the specific roles of arginase isoforms are unclear. Methods: C57BL/6 and db/db mice were pretreated with ARG1 or ARG2 antisense oligonucleotides (ASO) for six weeks. Conditional ARG1 knockout (ARG1^fl/fl/Tie2Cre^tg/−) and wild-type littermates were also studied. Mice underwent coronary artery ligation and reperfusion in vivo for infarct size assessment. In ex vivo experiments, buffer-perfused hearts were subjected to global ischemia–reperfusion with or without RBCs to evaluate recovery of left ventricular developed pressure (LVDP). Results: ARG1 knockdown, but not ARG2, improved post-ischemic recovery of LVDP in isolated hearts. RBCs from ARG1 ASO-treated mice enhanced recovery in wild-type hearts, while ARG1 knockout reduced infarct size compared with controls. Cardioprotection was abolished by NO synthase inhibition. RBCs from male and female ARG1 knockout mice improved LVDP recovery compared with RBCs from wild-type mice. In T2D mice, impaired recovery was restored by ARG1 ASO or RBCs from ARG1 ASO-treated T2D mice. Conclusions: Arginase 1, but not arginase 2, limits cardiac tolerance to ischemia–reperfusion and contributes to increased vulnerability in T2D. Full article

(This article belongs to the Special Issue Blood Cells and Redox Homeostasis in Health and Disease, 2nd Edition)

20 pages, 520 KB

Open AccessArticle

Active Compensation Fault-Tolerant Control for Uncertain Systems with Both Actuator and Sensor Faults

by Xufeng Ling, Haichuan Xu and Fanglai Zhu

Sensors 2026, 26(1), 267; https://doi.org/10.3390/s26010267 (registering DOI) - 1 Jan 2026

Abstract

This paper develops a novel fault reconstruction (FR) method and an FR-based fault-tolerant control (FTC) scheme for systems suffering from both sensor and actuator faults based on the combination of a Luenberger-like reduced-order observer and an interval observer. Firstly, by introducing an output [...] Read more.

This paper develops a novel fault reconstruction (FR) method and an FR-based fault-tolerant control (FTC) scheme for systems suffering from both sensor and actuator faults based on the combination of a Luenberger-like reduced-order observer and an interval observer. Firstly, by introducing an output transformation, an auxiliary output that is able to decouple the sensor fault is obtained. Secondly, for addressing the external disturbance and actuator fault, a multiple unknown input (MUI) is formed, and a reduced-order observer that is able to decouple the MUI is constructed. Consequently, asymptotic convergence estimations of the state and the sensor fault can be accomplished. Thirdly, in order to obtain the asymptotic convergence actual FR (AFR), an interval observer is designed. After this, an algebraic connection of the MUI and the state error estimation is given, and, based on the algebraic relationship, an algebraic MUI reconstruction (MUIR) method is proposed. Finally, an FTC scheme is developed by using the state estimation and MUIR. Under the FTC, the closed-loop system is asymptotically stable even if it suffers from sensor and actuator faults simultaneously. Theoretical analysis demonstrates that the observer-based FTC mechanism satisfies the separation principle. At last, two simulation examples are given to verify the effectiveness of the proposed methods. Full article

(This article belongs to the Special Issue Advances in Sensors for Online Condition Monitoring and Fault Diagnosis)

10 pages, 1080 KB

Open AccessArticle

Circulating miR-1246 as a Diagnostic and Prognostic Biomarker in Dengue Infection: A Case–Control Study

by Vishesh Rajbhandari, Frienson Pradhan, Kriti Rajbhandari, Rasika Ghulu, Ashna Dhakal and Amol Dahal

J. Mol. Pathol. 2026, 7(1), 1; https://doi.org/10.3390/jmp7010001 (registering DOI) - 1 Jan 2026

Abstract

Background: Dengue is a growing mosquito-borne viral infection of global concern. It remains a major public health challenge in Nepal, where reliable biomarkers for disease staging and prognosis are lacking. In this study, we investigated circulating microRNA-1246 (miR-1246) as a potential diagnostic and [...] Read more.

Background: Dengue is a growing mosquito-borne viral infection of global concern. It remains a major public health challenge in Nepal, where reliable biomarkers for disease staging and prognosis are lacking. In this study, we investigated circulating microRNA-1246 (miR-1246) as a potential diagnostic and prognostic marker in dengue infection. Methods: Serum samples from 21 dengue-positive patients and 20 healthy controls were analyzed by quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR), with RNU6 as an internal control. Results: Dengue patients showed markedly elevated miR-1246 levels, with a mean 47-fold increase compared to controls (p = 0.001). Expression varied by disease stage, peaking in IgM positive cases, declining in weakly positive IgM patients, and reaching the lowest levels in IgG positive convalescent cases, a pattern consistent with clinical parameters such as platelet recovery. Receiver Operating Characteristic (ROC) analysis further highlighted diagnostic potential, yielding an Area Under the Curve (AUC) of 0.79, sensitivity of 95.24%, and specificity of 60.00%. Conclusions: These findings imply that miR-1246 is drastically dysregulated during dengue infection and could be a useful biomarker for tracking the intensity and course of the illness. Full article

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18 pages, 293 KB

Open AccessArticle

Adolescents and Transition-Age Youths with Intellectual Disabilities in Saudi Arabia: An Exploration of Parental Perspectives

by Mohaned G. Abed and Todd K. Shackelford

Behav. Sci. 2026, 16(1), 66; https://doi.org/10.3390/bs16010066 (registering DOI) - 1 Jan 2026

Abstract

The current study explores the social experiences of adolescent and transition-age youths with intellectual disabilities (IDs) and the support mechanisms available to these groups in Saudi Arabia. This study adopts a qualitative methodology with a semi-structured interview constituting the data collection method involving [...] Read more.

The current study explores the social experiences of adolescent and transition-age youths with intellectual disabilities (IDs) and the support mechanisms available to these groups in Saudi Arabia. This study adopts a qualitative methodology with a semi-structured interview constituting the data collection method involving 13 parents with children aged between 11 and 19 years, a critical adolescent period and transition to early adulthood. The results suggest that family, caregivers, community, friendships, and healthcare providers play important roles that impact the quality of life for these groups. The main challenges identified include health-related issues, employment challenges, educational barriers, insufficient services, inadequate community participation, and limited social relationships, with special emphasis on obstacles linked to transition during the 18 to 19-year period when youths must navigate transfers from pediatric to adult services and changes associated with legal rights. This study highlights several reasons it is important to increase awareness and education, while also continuing to improve support systems aimed at dealing with both transition challenges and adolescent needs. The results further illustrate that although support from family provides the foundation for care, systemic changes are needed to promote social inclusion and reduce stigma during critical development periods. The current study contributes to the limited research related to IDs in the context of the Middle East, with special reference to Saudi Arabia. Finally, the discussion highlights several insights that are culturally specific for the development of policy and provision of services associated with the transition from adolescence to early adulthood. Full article

26 pages, 635 KB

Open AccessArticle

Time-Weighted Result-Based Strength Indicators from Head-to-Head Outcomes: An Application to Trotter (Harness) Racing

by Manuel Ligero-Acosta, Juan M. Muñoz-Pichardo, María Dolores Gómez, María Ripollés-Lobo and Mercedes Valera

Mathematics 2026, 14(1), 167; https://doi.org/10.3390/math14010167 (registering DOI) - 1 Jan 2026

Abstract

We propose a general methodology for constructing dynamic performance indicators (or strength metrics) in any sport that relies on comparative outcomes among competitors, using chronological positional data. Specifically, we develop a family of strength indicators for harness trotting races based on time-weighted, head-to-head [...] Read more.

We propose a general methodology for constructing dynamic performance indicators (or strength metrics) in any sport that relies on comparative outcomes among competitors, using chronological positional data. Specifically, we develop a family of strength indicators for harness trotting races based on time-weighted, head-to-head results. Using the official Balearic trotting records (1990–2023), we construct win, draw, and confrontation matrices up to each event and apply a triweight kernel to reduce the influence of older results. From these matrices, we derive a family of five bounded, interpretable indicators on the interval

[0, 1]

: an overall average win rate, a category-adjusted version, and three distance-specific versions (short, medium, and long). Indicator validation is performed via predictive validation, employing regularized logistic regression models (Elastic Net) based on indicator differences between horse pairs. Standard metrics (accuracy, calibration, discrimination, and Brier score) are used for the validation analysis. The results confirm that the indicators are coherent, stable, and interpretable, demonstrating that the generic construction procedure yields robust outcomes. We conclude that these indicators establish a solid and easily updatable foundation for developing dynamic ranking systems and practical selection/handicap procedures in trotting. Full article

(This article belongs to the Special Issue Advances in Statistical Approaches with Applications for Multivariate Data Analysis)

11 pages, 677 KB

Open AccessArticle

The Significance of Sonication in the Detection of Peri-Implant Infections

by Christian Prangenberg, Alberto Alfieri Zellner, Jonas Roos, Lisa Fiona Roder, Soufian Ben Amar, Kristian Welle, Frank Sebastian Fröschen and Gunnar Thorben Rembert Hischebeth

Antibiotics 2026, 15(1), 35; https://doi.org/10.3390/antibiotics15010035 (registering DOI) - 1 Jan 2026

Abstract

Objective: The current gold standard for detection of implant-related infections is the intraoperative collection of tissue samples. However, false-negative results frequently occur, particularly in infections caused by biofilm-forming bacteria. As a complementary method, sonication has therefore been established for detecting implant-associated infections, [...] Read more.

Objective: The current gold standard for detection of implant-related infections is the intraoperative collection of tissue samples. However, false-negative results frequently occur, particularly in infections caused by biofilm-forming bacteria. As a complementary method, sonication has therefore been established for detecting implant-associated infections, especially in periprosthetic joint infections. In trauma surgery, this technique is still rarely used. The aim of this study is to evaluate the diagnostic significance of sonication after osteosynthesis. Methods: A retrospective single-center analysis was conducted on all patients who underwent plate osteosynthesis removal between 1 January 2019, and 1 May 2021, with both sonication and intraoperative tissue sampling performed. Patients with inlying arthroplasties or nail-less osteosynthesis systems were excluded. Pre- and postoperative infection parameters (leukocytes, CRP) were recorded, and preoperative clinical findings were used to classify suspected infection. Results: A total of 57 patients (30 men, 27 women; mean age 57.6 years, range 12–91) were included. The mean treatment duration was 20.1 days (range 1–152). Sonication was positive in 33 patients, tissue samples in 28, with 31 cases (54%) showing concordant results. In cases with preoperative suspicion of infection, sonication was positive in 21 of 26 cases (80.7%) and tissue samples in 18 of 26 (69.2%), whereas without suspicion, positivity rates were 38% and 31%, respectively. Sonication and tissue results matched in 14 of 26 cases; in the remainder, results were different or incomplete. Preoperative CRP elevation and the presence of an infection membrane influenced sensitivity: sonication generally detected more bacteria (59–81%) than tissue samples (49–73%), though discrepancies remained. Conclusions: Sonication represents a valuable complementary method for detecting implant-related infections. Due to its high sensitivity but limited specificity, it should not be used as a standalone diagnostic method. Full article

(This article belongs to the Special Issue Diagnostics and Antibiotic Therapy in Bone and Joint Infections)

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16 pages, 3451 KB

Open AccessArticle

An Enhanced Automatic Emergency Braking Control Method Based on Vehicle-to-Vehicle Communication

by Chaoqun Huang and Fei Lai

Algorithms 2026, 19(1), 34; https://doi.org/10.3390/a19010034 (registering DOI) - 1 Jan 2026

Abstract

The automatic emergency braking (AEB) system plays a crucial role in reducing rear-end collisions and is mandatory on certain heavy-duty vehicles, with future regulations extending to passenger cars. However, most current AEB systems are designed based on onboard sensors such as cameras and [...] Read more.

The automatic emergency braking (AEB) system plays a crucial role in reducing rear-end collisions and is mandatory on certain heavy-duty vehicles, with future regulations extending to passenger cars. However, most current AEB systems are designed based on onboard sensors such as cameras and radar, which may fail to prevent collisions in scenarios where the lead vehicle is already in a collision. To address this issue, this study proposes an enhanced AEB control method based on Vehicle-to-Vehicle (V2V) communication and onboard sensors. The method utilizes V2V communication and onboard sensors to predict obstacles ahead, applying effective braking when necessary. Simulation results in Matlab/Simulink R2022a show that the proposed V2V-based AEB control method reduces the risk of chain collisions, ensuring that the ego vehicle can avoid rear-end collisions even when the lead vehicle is involved in a crash. Three simulation scenarios were designed, where both the subject vehicle and the lead vehicle travel at 120 km/h. The following three distances between the subject vehicle and the lead vehicle were considered: 45 m, 70 m, and 30 m. When the lead vehicle detects an obstacle 30 m ahead and suddenly applies emergency braking, the lead vehicle fails to avoid a collision. In this case, the subject vehicle, equipped only with onboard sensors, is also unable to successfully avoid the crash. However, when the subject vehicle is equipped with both onboard sensors and vehicle-to-vehicle communication, it can prevent a rear-end collision with the lead vehicle, maintaining a vehicle-to-vehicle distance of 1 m, 6.8 m, and 3.1 m, respectively, during the stopping process. This control method contributes to advancing the active safety technologies of autonomous vehicles. Full article

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15 pages, 618 KB

Open AccessArticle

Exploring Greek Upper Primary School Students’ Perceptions of Artificial Intelligence: A Qualitative Study Across Cognitive, Emotional, Behavioral, and Ethical Dimensions

by Konstantinos Kotsidis, Georgios Chionas and Panagiotes Anastasiades

Computers 2026, 15(1), 14; https://doi.org/10.3390/computers15010014 (registering DOI) - 1 Jan 2026

Abstract

This study investigates the perceptions of Greek sixth-grade students regarding Artificial Intelligence (AI). Understanding students’ pre-instructional conceptions is essential for developing targeted interventions that build on existing knowledge rather than assuming conceptual deficits. A qualitative design was employed with 229 students from seven [...] Read more.

This study investigates the perceptions of Greek sixth-grade students regarding Artificial Intelligence (AI). Understanding students’ pre-instructional conceptions is essential for developing targeted interventions that build on existing knowledge rather than assuming conceptual deficits. A qualitative design was employed with 229 students from seven elementary schools in Athens, Greece. Data were collected through open-ended questions and word association tasks, then analyzed using Walan’s AI perceptions framework as an integrated set of analytical lenses (cognitive, affective, behavioral/use, and ethical considerations). Findings revealed that students hold multifaceted conceptions of AI. Cognitively, they described AI as robots, computational systems, software tools, and autonomous learning programs. Affectively, they expressed ambivalence, balancing appreciation of AI’s usefulness with concerns over potential risks. Behaviorally, they identified interactive question–answer functions, creative applications, and everyday assistance roles. Ethically, students raised issues of responsible use, societal implications, and human–AI relationships. This study contributes to international research, highlighting that primary students’ understandings of AI are more nuanced than is sometimes assumed, and offer empirical insights for designing culturally responsive, ethically informed AI literacy curricula. Full article

(This article belongs to the Special Issue Transformative Approaches in Education: Harnessing AI, Augmented Reality, and Virtual Reality for Innovative Teaching and Learning)

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16 pages, 316 KB

Open AccessArticle

Stability and Positivity Preservation in Conventional Methods for Space-Fractional Diffusion Problems: Analysis and Algorithms

by Menghis T. Bahlibi and Ferenc Izsák

Algorithms 2026, 19(1), 33; https://doi.org/10.3390/a19010033 (registering DOI) - 1 Jan 2026

Abstract

The numerical solution of space-fractional diffusion problems is investigated focusing on stability and non-negativity issues. The extension of classical schemes is analyzed for the case of the spectral fractional Dirichlet Laplacian operator. For the spatial discretization, both finite differences and finite elements are [...] Read more.

The numerical solution of space-fractional diffusion problems is investigated focusing on stability and non-negativity issues. The extension of classical schemes is analyzed for the case of the spectral fractional Dirichlet Laplacian operator. For the spatial discretization, both finite differences and finite elements are used. The finite element case needs special care and is discussed in detail. Both spatial discretizations are combined with the matrix transformation method, leading to fractional powers of matrices in the discretized problems. In the time stepping,

θ

-methods are utilized with

θ = 0, \frac{1}{2}

and 1. In the analysis, it is pointed out that the stability condition in the case of

θ = 0

depends on the fractional power

α \in (0, 1]

, which results in a weaker condition on the time discretization compared to the conventional diffusion. In this case, we also obtain non-negativity preservation. Also, unconditional stability is established for

θ = \frac{1}{2}

and

θ = 1

, where for the spatial discretization rather general conditions are posed. The results containing stability conditions are also confirmed in a series of numerical experiments. In the course of the corresponding algorithms, an efficient matrix power–vector product procedure is employed to keep simulation time at an affordable level. The associated computational algorithm is also described in detail. Full article

19 pages, 688 KB

Open AccessArticle

How Can Users Be Confident About Self-Disclosure in Mobile Payment? From Institutional Mechanism Perspective

by Haiqin Xu and Jian Li

J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 10; https://doi.org/10.3390/jtaer21010010 (registering DOI) - 1 Jan 2026

Abstract

Mobile payment platforms not only streamline users’ financial transactions but also encourage their participation in investment activities and additional services. To deliver personalized financial services, it is essential to collect users’ personal information. This study aims to investigate the factors influencing users’ willingness [...] Read more.

Mobile payment platforms not only streamline users’ financial transactions but also encourage their participation in investment activities and additional services. To deliver personalized financial services, it is essential to collect users’ personal information. This study aims to investigate the factors influencing users’ willingness to engage in self-disclosure within mobile payment platforms, thereby assisting practitioners in efficiently allocating resources and maximizing returns on investments dedicated to promoting user self-disclosure. Consequently, this study focuses on examining how institutional mechanisms influence users’ self-disclosure behavior within these platforms. The authors developed a comprehensive framework that elucidates the influence of institutional mechanisms on users’ self-disclosure, mediated by trust and privacy concerns. To empirically validate our research model, we administered an online survey targeting Alipay users in China. Subsequently, we analyzed 559 valid survey responses utilizing partial least squares structural equation modeling (PLS-SEM). The results indicate that trust and privacy concerns jointly influence users’ self-disclosure behavior when utilizing mobile payment platforms. Moreover, key institutional mechanisms can effectively foster trust and alleviate privacy concerns, ultimately facilitating users’ willingness to self-disclose. Our research shifts scholarly focus from conventional adoption to users’ self-disclosure in the mobile payment field and enhances the existing self-disclosure research by identifying the impact of institutional mechanisms on users’ self-disclosure behavior. Full article

(This article belongs to the Section Digital Marketing and Consumer Experience)

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28 pages, 3848 KB

Open AccessArticle

When Deep Learning Meets Broad Learning: A Unified Framework for Change Detection with Synthetic Aperture Radar Images

by Shuchen Yu, Zhulian Wang, Jiayi Qu, Xinxin Liu, Licheng Liu, Bin Yang and Qiuhua He

Remote Sens. 2026, 18(1), 143; https://doi.org/10.3390/rs18010143 (registering DOI) - 1 Jan 2026

Abstract

Change detection (CD) with synthetic aperture radar (SAR) images remains pivotal for environmental monitoring and disaster management. Deep learning has powerful feature extraction capabilities for CD, but suffers from complex architectures and limited interpretability. While BLSs demonstrate advantages in structural simplicity and interpretability, [...] Read more.

Change detection (CD) with synthetic aperture radar (SAR) images remains pivotal for environmental monitoring and disaster management. Deep learning has powerful feature extraction capabilities for CD, but suffers from complex architectures and limited interpretability. While BLSs demonstrate advantages in structural simplicity and interpretability, their feature representation capacity remains constrained. In high-precision CD with SAR images, strong feature representation capability is required, along with an uncomplicated framework and high interpretability. Therefore, a novel paradigm named PC-BiBL is proposed which achieves seamless integration of deep learning and broad learning. On the one hand, it employs a hierarchical cross-convolutional encoding (HCCE) module that uses pseudo-random cross-convolution (PCConv) for hierarchical cross-feature representation, aggregating contextual information. PCConv is an untrained convolution layer, which can utilize specialized pseudo-random kernels to extract features from bitemporal SAR images. On the other hand, since back-propagation algorithms are not required, the features can be directly fed into the bifurcated broad learning (BiBL) module for node expansion and direct parameter computation. BiBL constructs dual-branch nodes and computes their difference nodes, explicitly fusing bitemporal features while highlighting change information—an advancement over traditional BLS. Experiments on five SAR datasets demonstrate the state-of-the-art performance of PC-BiBL, surpassing existing methods in accuracy and robustness. Quantitative metrics and visual analyses confirm its superiority in handling speckle noise and preserving boundary information. Full article

(This article belongs to the Special Issue Change Detection and Classification with Hyperspectral Imaging)

18 pages, 781 KB

Open AccessReview

Comparative Review of Cardioprotective Potential of Various Parts of Sambucus nigra L., Sambucus williamsii Hance, and Their Products

by Beata Olas

Int. J. Mol. Sci. 2026, 27(1), 460; https://doi.org/10.3390/ijms27010460 (registering DOI) - 1 Jan 2026

Abstract

The genus Sambucus L. consists of about 29 recognized species (including 7 different genera that have berry fruit) distributed in all regions of the world. The most popular species are Sambucus nigra L., Sambucus cerulean Raf., and Sambucus javanica Blume, of which the [...] Read more.

The genus Sambucus L. consists of about 29 recognized species (including 7 different genera that have berry fruit) distributed in all regions of the world. The most popular species are Sambucus nigra L., Sambucus cerulean Raf., and Sambucus javanica Blume, of which the European elderberry is widely used commercially. S. williamsii Hance (commonly known as Jiegumu) is endemic to China and is a valued variety of elderberry. S. nigra L. is one of the oldest medicinal plants. The herbal materials used in treatment and nutrition are its fruits, flowers, roots, leaves, and bark. Various parts of S. williamsii, including its fruit, flower, root, leaf, and stem, are also specifically used in Traditional Chinese Medicine. Additionally, berries and flowers of S. nigra L. have become a very popular inclusion in supplements, beverages, and foods in recent years. It is important that Sambucus plants are rich sources of various bioactive compounds, which determine their biological activities, such as antioxidant, antidiabetic, antimicrobial, and anti-inflammation. However, one of the most extensively studied species is S. nigra L. Among the different parts of this plant, the fruits and flowers are of particular interest due to their rich bioactive components. The aim of the present review is to provide and compare an overview of the cardioprotective potential of various parts not only of S. nigra L., but also of S. williamsii Hance, and their products in various models. Moreover, cardioprotective mechanisms of their main chemical constituents were demonstrated in this paper to provide a basis for further study and development. Full article

(This article belongs to the Section Bioactives and Nutraceuticals)

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20 pages, 6002 KB

Open AccessArticle

Design and Experimental Verification of a Compact Robot for Large-Curvature Surface Drilling

by Shaolei Ren, Xun Li, Daxi Geng, Zhefei Sun, Haiyang Xu, Jianchao Fu and Deyuan Zhang

Actuators 2026, 15(1), 24; https://doi.org/10.3390/act15010024 (registering DOI) - 1 Jan 2026

Abstract

Automated precision drilling is essential for aircraft skin manufacturing, yet current robotic systems face dual challenges: chatter-induced inaccuracies in hole quality and limited access to confined spaces such as air inlets. To overcome these limitations, this paper develops a compact drilling robot for [...] Read more.

Automated precision drilling is essential for aircraft skin manufacturing, yet current robotic systems face dual challenges: chatter-induced inaccuracies in hole quality and limited access to confined spaces such as air inlets. To overcome these limitations, this paper develops a compact drilling robot for drilling large-curvature skins of aircraft air inlets. Targeting the precision drilling requirements for complex-curvature aircraft air inlets, we present the robot’s overall design scheme, detailing each module’s composition to ensure precision drilling. In-depth analysis of the robot’s large-curvature adaptability precisely calculates the wheel assembly dimensions. To ensure high-precision drilling bit entry into guide mechanisms, a flexible drilling spindle mechanism is designed, with calculated and verified elastic ranges. An integrated intelligent control system is developed, combining vision recognition, real-time pose adjustment, and automated drilling workflow planning. Finally, traversability and drilling capabilities are validated using a simplified air inlet model. Test results confirm successful traversal on R200 mm curvature skins and automated drilling of Carbon Fiber-Reinforced Polymer (CFRP)/7075 aluminum stacks with a diameter of Φ4–Φ6 mm, achieving dimensional errors of less than 0.05 mm and normal direction errors of less than 0.65°. Full article

(This article belongs to the Special Issue AI, Designing, Sensing, Instrumentation, Diagnosis, Controlling, and Integration of Actuators in Digital Manufacturing—2nd Edition)

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19 pages, 2150 KB

Open AccessArticle

Towards Near-Real-Time Seismic Phase Recognition, Event Detection, and Location with Deep Neural Networks in Volcanic Area of Campi Flegrei

by Pasquale Cantiello, Roberta Esposito, Alessandro Di Filippoand and Rosario Peluso

Appl. Sci. 2026, 16(1), 458; https://doi.org/10.3390/app16010458 (registering DOI) - 1 Jan 2026

Abstract

The real-time phase picking, detection, and location of seismic events is a crucial challenge for monitoring in densely populated volcanic areas. In such contexts, low-magnitude events may escape traditional detection methods due to high levels of anthropogenic noise, which often masks weak seismic [...] Read more.

The real-time phase picking, detection, and location of seismic events is a crucial challenge for monitoring in densely populated volcanic areas. In such contexts, low-magnitude events may escape traditional detection methods due to high levels of anthropogenic noise, which often masks weak seismic signals. This study presents the implementation of a near-real-time automatic event detector with a seismic phase recognizer, pick associator, and localiser. The system is based on PhaseNet, a well-established deep neural network recognized for its effectiveness in seismology. The main innovation introduced in this work lies in the direct application of this method to real-time data streams. This integration allows for the enhanced identification and cataloguing of low-magnitude seismic events that would otherwise remain unobserved. The adoption of the system in a real-time operational context not only increases monitoring sensitivity and responsiveness but also contributes to a more detailed and comprehensive understanding of seismic activity in critical volcanic areas, providing essential data for risk assessment and prevention. Full article

(This article belongs to the Special Issue Artificial Intelligence Applications in Earthquake Science)

26 pages, 895 KB

Open AccessArticle

Optimization of Multi-User Secure Communication Rate Under Swarm Warden Detection in ISAC Networks

by Kuanhao Yu, Hang Hu, Yangchao Huang, Wei Li, Weiting Gao and Guobing Cheng

Drones 2026, 10(1), 23; https://doi.org/10.3390/drones10010023 (registering DOI) - 1 Jan 2026

Abstract

Unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) systems have been widely applied in various scenarios recently. This paper aims to maximize the total secure communication rate (SCR) of multiple users while ensuring the minimum beamforming gain towards sensing targets under the [...] Read more.

Unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) systems have been widely applied in various scenarios recently. This paper aims to maximize the total secure communication rate (SCR) of multiple users while ensuring the minimum beamforming gain towards sensing targets under the surveillance of multiple UAV warden swarms. To reduce the risk of detection, a novel type of artificial noise (AN) is introduced to interfere with swarm wardens. We conduct an analysis of the detection error probability (DEP) of these wardens and subsequently establish a mathematical model. In this model, the SCR is maximized subject to power, trajectory, sensing performance, and secure communication constraints. Since the problem is non-convex and the variables to be optimized are numerous and complex, we decompose the problem into three sub-problems. Then, an overall algorithm is proposed to solve these sub-problems separately. Simulation results demonstrate that the proposed scheme leads to a significant increase in the SCR. Moreover, the system exhibits highly stable performance in both communication and sensing tasks over time, indicating its robustness and reliability. Additionally, communication fairness among users is ensured, and energy efficiency is enhanced. Full article

20 pages, 3948 KB

Open AccessArticle

Integrated DEM–Experimental Framework for Multi-Objective Optimization of a Low-Disturbance Liquid Manure Injector Shank

by Zhiwei Zeng, Adewale Sedara and Matthew Digman

AgriEngineering 2026, 8(1), 10; https://doi.org/10.3390/agriengineering8010010 (registering DOI) - 1 Jan 2026

Abstract

Low-disturbance liquid manure injection is increasingly important for sustainable soil management because it reduces residue burial, minimizes surface disruption, and lowers energy demand during application. However, the performance of low-disturbance shanks has not been systematically optimized, and their interaction with soil remains poorly [...] Read more.

Low-disturbance liquid manure injection is increasingly important for sustainable soil management because it reduces residue burial, minimizes surface disruption, and lowers energy demand during application. However, the performance of low-disturbance shanks has not been systematically optimized, and their interaction with soil remains poorly quantified. This study developed an integrated discrete element method (DEM)–experimental framework to evaluate and optimize the performance of a purpose-built injector shank featuring a 45° rake angle, 25 mm thickness, and 110 mm width. The framework aimed to identify operating conditions that balance soil disturbance and energy efficiency. A DEM soil model was constructed using mechanical properties obtained from laboratory characterization tests and validated against soil bin experiments measuring draft force and soil rupture area across five working depths (100–250 mm) and three travel speeds (350–450 mm/s). The calibrated model showed strong agreement with experimental observations, yielding mean absolute relative errors of 1.7% for draft force and 6.2% for rupture area. Following validation, a multi-objective optimization was performed to minimize draft force while maximizing soil rupture, two key indicators of energy demand and injection effectiveness. Optimization results identified the most favorable operating parameters at a forward speed of 450 mm/s and an injection depth of 150 mm, achieving a desirability score of 0.884. The integrated DEM–experimental framework demonstrated reliable predictive capability and enables virtual testing of soil–tool interactions prior to field implementation. This study provides a scientifically grounded approach for improving injector shank operation and supports sustainable manure management by identifying settings that achieve adequate soil disruption while reducing energy consumption. Full article

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