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by Sergio Martínez-Vázquez, Rocío Adriana Peinado-Molina, Leticia Molina-García, Antonio Hernández-Martínez and Juan Miguel Martínez-Galiano

J. Clin. Med. 2026, 15(7), 2495; https://doi.org/10.3390/jcm15072495 (registering DOI) - 24 Mar 2026

Abstract

Background: Maternal control and the sense of support significantly influence a woman’s experience of birth. This study aimed to adapt and validate the Support and Control in Birth (SCIB) scale in Spanish women to assess maternal perceptions of support and control during birth, and to develop and validate an abbreviated version of the instrument. Methods: A cross-sectional study was conducted with a sample of 302 Spanish women who had given birth within the previous 6 months and were at least 1 week postpartum. Content, construct, and criterion validity, as well as reliability, were analysed using an expert panel, Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Cronbach’s Alpha Coefficient, and Intraclass Correlation Coefficient (ICC). Criterion validity was assessed using the Generalised Anxiety Disorder Screener (GAD-7) and the Birth Satisfaction Scale–Revised (BSS-R). Results: The KMO test yielded a value of 0.925, and Bartlett’s test of sphericity was significant (p < 0.001). EFA identified three factors (Support, External control, and Internal control) that explained 56.49% of the total variance. CFA showed good model fit for most of the evaluated indices. The SCIB scale correlated negatively with the GAD-7 and positively with the BSS-R (p < 0.001), as well as with several obstetric and neonatal variables (p < 0.05): planned pregnancy, high-risk pregnancy, onset and type of delivery, birth plan, use of epidural analgesia, maternal involvement, postpartum complications, and newborn characteristics. Cronbach’s alpha was 0.951, and the ICC indicated excellent consistency and agreement (0.995; 95% CI: 0.990–0.998). Based on expert panel consensus, a 24-item abbreviated version was developed that exhibited psychometric properties similar to those of the original version and a high correlation with it (r > 0.90). Conclusions: The Support and Control in Birth (SCIB) scale is a valid and reliable instrument for assessing perceptions of support and control during birth in Spanish women. The 24-item abbreviated version is recommended. Full article

(This article belongs to the Special Issue Psychological Affliction in Pregnancy, Delivery and Postpartum Period: A Multidisciplinary Approach)

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59 pages, 18674 KB

Open AccessArticle

Characterization and Predictive Modeling of Diatomite Mortar Performance: A Hybrid Framework Based on Experimental Analysis and Machine Learning Meta-Models

by Sihem Brahimi, Miloud Hamadache and Mhand Hifi

Buildings 2026, 16(7), 1281; https://doi.org/10.3390/buildings16071281 (registering DOI) - 24 Mar 2026

Abstract

Decarbonizing the construction sector requires high-volume replacement of Portland clinker with non-calcined supplementary cementitious materials (SCMs). This study investigates white cement pastes incorporating raw Algerian diatomite—a silica-rich biogenic mineral—at substitution levels from 40% to 95% (5% increments) and a fixed water-to-binder ratio of 0.5. The target application is ultra-lightweight, multifunctional composites for non-structural uses such as decorative panels and partition elements. Increasing diatomite content progressively reduced bulk density from 1.483 g/cm

^{3}

(D40) to 0.557 g/cm

^{3}

(D95) and increased porosity. 28-day compressive strength decreased monotonically from 16 MPa (D40) to 2.4 MPa (D95) as clinker dilution intensified. Ultrasonic pulse velocity dropped from 6205 m/s to 1495 m/s, reflecting progressive pore development and confirming the material’s lightweight potential. Statistically significant strength gains beyond 28 days were recorded (

+ 25.87 %

for compression, p-value

< 0.05

), evidencing delayed pozzolanic activity. These results confirm that raw, non-calcined diatomite is a viable SCM for eco-efficient, low-density construction systems. To overcome the extrapolation instability of purely data-driven approaches, a Meta-Avrami Hybrid Framework was developed. It anchors Gradient Boosting residual learning to a sigmoidal Avrami hydration kernel. The model achieved high predictive accuracy (

R^{2} \approx 0.999

RMSE \approx 0.010

) under 10-fold cross-validation. Generalization was well-controlled, with a low overfitting gap (

Δ R^{2} = 0.0226

) and stable fold-to-fold performance (

Std = 0.0204

). These metrics confirm suitability for unseen mix designs. This is particularly relevant for service-life assessment of partition panels and lightweight façade elements, where long-term performance guarantees are required. The physics-informed architecture ensures asymptotic strength stabilization up to a 10-year horizon (amplification ratios 1.03–1.05). This prevents the non-physical divergence observed in polynomial and power-law hybrids (ratios 1.36–1.70). The framework provides a reliable and interpretable tool for service-life design of sustainable low-carbon cementitious systems. Full article

(This article belongs to the Section Building Materials, and Repair & Renovation)

27 pages, 3906 KB

Open AccessArticle

Theory-Based Interpretability in Deep Knowledge Tracing via Grounded Transformers

by Concepcion Labra and Olga C. Santos

Appl. Sci. 2026, 16(7), 3138; https://doi.org/10.3390/app16073138 (registering DOI) - 24 Mar 2026

Abstract

Knowledge Tracing, which estimates how students’ knowledge evolves during interactions with educational content, is a cornerstone of Intelligent Tutoring Systems. While deep learning models achieve superior predictive performance in this task, they lack interpretability, a limitation that is particularly critical in educational contexts. We introduce gTransformer, a new type of grounded Transformer model bridging deep learning performance with intrinsic interpretability through representational grounding. It adds theory-based parameters to input interaction sequences and uses attention mechanisms to transform them into latent representations. These are projected into enriched parameters that incorporate historical learning context while preserving semantics. Validation demonstrates: (1) structural encoding around theoretical concepts (probing selectivity

Δ R^{2} > 0.5

); (2) semantic alignment; and (3) functional alignment with quantified confidence. Results show that gTransformer achieves predictive performance competitive with state-of-the-art architectures while offering intrinsically interpretable predictions. The trade-off is characterised by a significant Area Under the Curve (AUC) gain over traditional theory-based models (+19.9%), with a minimal cost (3.9%) relative to non-interpretable configurations. Critically, gTransformer enables context-aware personalisation by differentiating students based on longitudinal learning trajectories rather than immediate responses, capturing patterns that traditional models cannot represent. This offers a practical path toward adaptive instruction driven by artificial intelligence that is both accurate and interpretable. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) in Educational Data Mining and Learning Analytics)

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20 pages, 3199 KB

Open AccessArticle

A Monitoring Method for In-Flight Droplet Flow Rate Based on Laser Imaging

by Yue Zhong, Zhonghua Miao, Yanlei Liu, Chuangxin He, Yanlong Zhang, Fan Feng, Wei Zou, Changyuan Zhai and Zhichong Wang

Agronomy 2026, 16(7), 684; https://doi.org/10.3390/agronomy16070684 (registering DOI) - 24 Mar 2026

Abstract

Efficient plant protection requires precise monitoring of spray droplets, yet current in situ methods for measuring in-flight droplet flow are limited. This study proposed a laser imaging-based method to quantify spray intensity without physical contact or tracers. An optimal imaging angle was determined via simulation by maximizing the linearity between the received optical feature and droplet volume density while satisfying geometric constraints. A compact acquisition device was then developed and tested with eight nozzle specifications under fixed pressure. Image processing algorithms—including cropping, RGB channel separation, and binarization—were employed to extract pixel area and cumulative intensity, with gravimetric measurements serving as the reference. Results showed that under optimized exposure and gain settings, features from the green and blue channels exhibited a strong linear correlation with flow rate (R² = 0.93–0.97). Based on these findings, this study demonstrates that in-flight droplet flow rate can be directly quantified from image features—a departure from conventional deposition-based approaches. The proposed method enables rapid, non-contact spray assessment using only a camera and laser module, offering a low-cost, simple-structured solution for spray system optimization and field monitoring. Full article

(This article belongs to the Special Issue Advances in Precision Pesticide Spraying Technology and Equipment)

22 pages, 1290 KB

Open AccessArticle

In Silico-Identified miR-16-5p and miR-32-5p as a Shared Molecular Signature of Primary Gliomas and Parkinson’s Disease: Plasma Levels Are Increased Only in Glioma Patients

by Janusz Szyndler, Zofia Wicik, Anna Wierucka, Piotr Maciejak, Michał Sobstyl, Angelika Stapińska-Syniec, Piotr Glinka, Karol Piwowarski and Natalia Chmielewska

Brain Sci. 2026, 16(4), 347; https://doi.org/10.3390/brainsci16040347 (registering DOI) - 24 Mar 2026

Abstract

Objectives: In this study, we explore the molecular basis of the literature-reported inverse association between brain neoplasms and neurodegenerative disorders, including Parkinson’s disease (PD). As miRNAs are post-transcriptional regulators, we selected them as candidates underlying opposite processes of neurodegeneration and glioma development. Methods: We used bioinformatic analyses for disease-gene extraction, miRNA target prediction, enrichment analyses, and miRNA ranking. We identified 953 shared genes between PD and glioblastoma (GBM) in DisGeNET, then prioritized miRNAs predicted to regulate the largest number of shared targets. Next, we collected peripheral blood from patients with PD (n = 12), patients with gliomas (the most advanced—grade IV, n = 10 and grade III n = 3) and controls undergoing spinal surgery for disk pathology (n = 10). Blood samples were obtained pre-operatively in controls and glioma patients. Tumor and peritumoral tissues were obtained from glioma patients, whereas tissue sampling is not feasible in PD. Brain tissues and plasma were analyzed using RT-qPCR (miRNA) and ELISA (p53). Results: We observed increased levels of miR-16-5p (p < 0.05) and p53 protein (p < 0.05) in tumor tissues compared with peritumoral tissue. Additionally, miR-16-5p and miR-32-5p plasma levels were elevated in glioma patients compared with both PD patients (p < 0.01 and p < 0.001, respectively) and controls (p < 0.01 and p < 0.001, respectively). Plasma levels in PD did not differ from controls. Conclusions: Although these analyses highlight miR-16-5p and miR-32-5p as candidate biomarkers associated with glioma related pathways, the results did not provide evidence for the expected opposite regulation between PD and glioma. Future studies with a larger cohort of patients using high-throughput methods are needed to validate these findings and to elucidate the mechanisms driving neurodegeneration or excessive proliferation. Full article

(This article belongs to the Section Neuro-oncology)

20 pages, 3811 KB

Open AccessArticle

Development of a Mathematical Model to Determine the Stability of Osteosynthesis in Pertrochanteric Fractures

by Igor Merdzanoski, Milan Mitkovic, Ivan Mickoski, Ile Mircheski and Marko Spasov

Appl. Sci. 2026, 16(7), 3136; https://doi.org/10.3390/app16073136 (registering DOI) - 24 Mar 2026

Abstract

Background and Objectives: Determining the mechanical stability of osteosynthesis in pertrochanteric fractures remains a critical challenge in orthopedic biomechanics. The aim of this study was to develop a mathematical model for quantifying the stability of osteosynthesis and to establish criteria for its evaluation under physiological loading conditions. Materials and Methods: A mathematical model describing the biomechanical behavior of a proximal femur with a pertrochanteric fracture stabilized using a cephalomedullary nail (CMN) was developed. The model integrates force equilibrium, stress–strain relationships, and loading conditions representative of early functional rehabilitation. The theoretical framework was implemented in MATLAB/Simulink R2025b and complemented by finite element analysis to determine stress distribution, deformation patterns, and stability-related parameters of the bone–implant system. Results: The developed mathematical model enabled a quantitative assessment of osteosynthesis stability through the evaluation of key mechanical indicators, including displacement, stress distribution, and safety factor within the fixation system. Critical stress zones in the implant and surrounding bone were identified, allowing analysis of load transfer mechanisms. Finite element simulations showed that improved fixation mechanics reduced peak implant stresses, limited displacement at the fracture site, and increased the safety factor of the fixation construct, resulting in a more uniform load distribution in the surrounding bone and enhanced overall stability of the osteosynthesis system. Conclusions: The proposed mathematical model provides a systematic approach for determining the stability of osteosynthesis in pertrochanteric fractures. It offers a theoretical basis for optimizing implant design and fixation strategies, with potential applications in preclinical evaluation and surgical planning. Full article

(This article belongs to the Section Biomedical Engineering)

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18 pages, 19546 KB

Open AccessArticle

Characterization of Soil CO₂ Flux from an Active Volcano Through Visibility Graph Analysis

by Salvatore Scudero, Marco Liuzzo, Antonino D’Alessandro and Giovanni Bruno Giuffrida

Appl. Sci. 2026, 16(7), 3134; https://doi.org/10.3390/app16073134 (registering DOI) - 24 Mar 2026

Abstract

The comprehension of the complex dynamics of degassing is critical for volcano monitoring and assessing volcanic hazards. In this study, we apply visibility graph analysis (VGA) to a decadal, high-resolution time series of daily soil CO

_{2}

flux recorded by a standardized monitoring [...] Read more.

_{2}

flux recorded by a standardized monitoring network at Mt. Etna volcano (Italy). By mapping these time series into complex networks, we demonstrate that the connectivity degree distributions follow a power law described by the exponent

γ

, which reveals a self-similar behavior of gas emissions. We introduce the

γ

-deviation, namely the variation of the scaling exponent from its long-term site-specific baseline, as a novel proxy for degassing efficiency. The long-term baseline is interpreted as a site-specific measure of flux efficiency, while its variations are attributed to other factors, such as fluctuations in the sources or changes in the efficiency of fluids transport pathways. Our results identify a transition from a period of discordance across the monitoring sites (pre-2016) to a phase of network-wide concordance (after 2016). The striking correlation between topological

γ

-deviations and the established normalized network signal (

Φ_{n o r m}

) validates the methodology, suggesting that VGA is able to capture the same underlying magmatic drivers. This study establishes VGA as a robust and reliable tool for medium- and long-term monitoring, potentially capable of identifying the occurrence of large-scale magmatic processes and refining the characterization of fluid transport dynamics in active volcanic systems. Full article

(This article belongs to the Special Issue Advances in Geophysical Approaches in Volcanic and Geothermal Areas)

34 pages, 611 KB

Open AccessArticle

Nocturia Frequency and Its Association with Sleep Disturbance and Health-Related Quality of Life in a Urology Outpatient Population

by Theodore Voudoukis, Francesk Mulita, Vasileios Leivaditis, Ejona Shaska, Andreas Antzoulas, Dimitrios Litsas, Panagiotis Dimitrios Papadopoulos, Elias Liolis, Konstantinos Tasios, Paraskevi Katsakiori, George Theofanis, Ioannis Maroulis and Georgios Tsakaldimis

J. Clin. Med. 2026, 15(7), 2492; https://doi.org/10.3390/jcm15072492 (registering DOI) - 24 Mar 2026

Abstract

Objective: Nocturia, defined as waking from sleep to void, is a frequent lower urinary tract symptom associated with impaired sleep quality and reduced quality of life. This study aimed to evaluate the prevalence of nocturia episodes and their impact on sleep disturbance and health-related quality of life. Methods: A questionnaire-based cross-sectional study was conducted at the Urology Outpatient Clinic of the General Hospital of Eastern Achaia between November 2023 and May 2024. Participants reporting nocturia were assessed using the Nocturia Quality of Life (N-QOL) questionnaire, the Athens Insomnia Scale (AIS), and the EQ-5D questionnaire. Demographic data and comorbid conditions were also collected. Univariate analyses and multiple linear regression were applied to identify factors associated with nocturia-related outcomes. Results: A total of 89 participants (78 men and 11 women; mean age 68.9 years) were included. Most participants reported 2–3 nocturnal voids per night. The N-QOL score was significantly associated with the frequency of nocturia episodes (r = −0.55, p < 0.0001), and regression analysis confirmed this relationship (coefficient: −6.7; 95% CI: −10.4 to −3.1). Individuals scoring ≥ 8 on the OAB-V8 scale demonstrated significantly lower N-QOL performance. Conclusions: Increasing nocturia frequency is associated with impaired sleep, reduced vitality, and diminished quality of life, particularly among older adults. Nocturia should be recognized as a clinically relevant symptom requiring targeted evaluation and personalized management strategies. Full article

(This article belongs to the Section Nephrology & Urology)

18 pages, 375 KB

Open AccessReview

AI-Driven and Algorithm-Supported Decision Support Using Continuous, Remote, and Self-Monitoring Patient Data for Early Deterioration Detection and Escalation: A Scoping Review

by Kazumi Kubota and Anna Kubota

Appl. Sci. 2026, 16(7), 3131; https://doi.org/10.3390/app16073131 (registering DOI) - 24 Mar 2026

Abstract

Continuous ward monitoring, remote patient monitoring, and self-monitoring can generate high-frequency physiological data streams, yet clinical benefit depends on whether signals lead to timely escalation without excessive non-actionable alerts and workflow burden. This scoping review, reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR), mapped AI-driven and algorithm-supported decision support approaches using continuous, remote, or self-monitoring patient data for early deterioration detection or prediction and escalation support, with emphasis on nursing relevance, workflow integration, alert burden, and implementation outcomes. PubMed (MEDLINE), Ovid MEDLINE, Web of Science Core Collection, and Scopus were searched on 14 February 2026. The search identified 47 records; 12 duplicates were removed; 35 records were screened; 28 were excluded; and 7 full-text reports were included. The included evidence comprised two original studies, two protocol/design papers, and three reviews. Within these included sources, decision support was commonly described as linking monitoring inputs to interpretive outputs, such as tiered alerts or risk predictions, and then to escalation-related actions or response pathways. Because the evidence base was small and heterogeneous, the review should be interpreted as exploratory evidence mapping rather than as a basis for broad generalization. Within the included studies, key reporting gaps included inconsistent description of escalation endpoints, limited standardized reporting of alert burden and acknowledgment patterns, incomplete workflow descriptions in some remote monitoring evidence, and limited attention to maintenance risks such as dataset shift. Full article

(This article belongs to the Special Issue AI-Driven Health and Wellbeing: Self-Monitoring, Early Detection, and Multi-Criteria Personalized Decision Support)

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16 pages, 1696 KB

Open AccessArticle

Rapid Finger-Pump Microfluidic Paper-Based Assay Platform for Monitoring Calcium Ions in Human Biofluids

by Kuan-Hsun Huang, Chin-Chung Tseng, Chia-Chun Lee, Cheng-Xue Yu and Lung-Ming Fu

Biosensors 2026, 16(4), 183; https://doi.org/10.3390/bios16040183 (registering DOI) - 24 Mar 2026

Abstract

Chronic kidney disease (CKD) is a progressively worsening condition that erodes renal function over time, reduces quality of life, and can ultimately culminate in kidney failure with far-reaching systemic complications. In addition to reduced filtration, worsening kidney function disrupts mineral homeostasis and leads to CKD–mineral and bone disorder (CKD-MBD). Dysregulated calcium handling and maladaptive endocrine responses contribute to bone pathology and increase cardiovascular calcification risk; therefore, serial calcium monitoring remains clinically relevant for longitudinal CKD management. Conventional calcium measurements are typically obtained with centralized analyzers or laboratory assays (e.g., colorimetry and electrode/optical readouts). Despite high accuracy, the required instrumentation, controlled operating conditions, and pretreatment steps complicate rapid point-of-care deployment, especially when only microliter-scale biofluids are available. Accordingly, this study develops a finger-actuated microfluidic colorimetric platform capable of determining calcium ion concentrations in human biofluids, such as whole blood, serum, and urine. The platform integrates a three-dimensional PMMA/paper microchip with a compact reader that maintains stable temperature control while enabling CMOS-based optical detection. With just 6 μL of sample, a brief finger press propels the biofluid across an internal filtration layer, generating serum or cleaned urine that subsequently reacts with a pre-deposited murexide reagent. Under optimized conditions (1.6% reagent, 50 °C, 3 min), the signal follows a strong logarithmic relationship with calcium concentration (Y = 47.273 ln X + 28.890; R² = 0.9905), supporting quantification over 1–40 mg/dL and a detection limit of 0.2 mg/dL. Across 80 clinical CKD specimens spanning serum, whole blood, and urine, results aligned closely with the NM-BAPTA reference assay, with R² values exceeding 0.97. Full article

(This article belongs to the Special Issue Integrated Microfluidic Biosensing Systems: Designs and Applications)

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16 pages, 34225 KB

Open AccessArticle

Effects of Visible and UV Illumination on Dimensional Accuracy and Surface Roughness in Dual-Color Volumetric Additive Manufacturing (VAM)

by Seyyed Kaveh Hedayati, Hossein Safari Mozajin, Azar Najafi Tireh Shabankareh, Kristoffer Almdal, Yi Yang and Aminul Islam

Materials 2026, 19(7), 1285; https://doi.org/10.3390/ma19071285 - 24 Mar 2026

Abstract

Volumetric additive manufacturing (VAM) enables layerless and fast printing within seconds. However, print quality remains highly sensitive to the delivered energy. In this study, the effects of visible (460 nm) and ultraviolet (385 nm) projector power were evaluated in a dual-color VAM setup [...] Read more.

6 \times 6 \times 6.7 {mm}^{3}

) were printed under controlled visible and ultraviolet power and exposure times, then evaluated using in situ shadowgraphy, three-dimensional metrology, and confocal microscopy. Higher visible power reduced the polymerization initiation time, but increasing the visible dose rapidly led to over-polymerization, resulting in dimensional growth, corner rounding, and increased surface roughness (

R_{a}

). The lowest lateral variation was observed at the shortest exposure times, with a maximum error of 1.8%. Ultraviolet illumination did not significantly change initiation time or reduce over-polymerization within the tested intensities and inhibitor concentration ranges. Surface evaluations revealed a periodic line texture with a pattern pitch of approximately 25 μm. By shifting the focal plane and using a low-resolution projector, the pattern pitch increased to about 150 μm. These values were aligned with the

{MTF}_{50}

spatial frequencies of each projector at different defocus positions. This study provides useful guidelines for adjusting intensity to achieve high-fidelity VAM printed parts. Full article

(This article belongs to the Collection Manufacturing Engineering and Mechanical Properties of Composite Materials)

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31 pages, 16969 KB

Open AccessArticle

Research on Cooperative Vehicle–Infrastructure Perception Integrating Enhanced Point-Cloud Features and Spatial Attention

by Shiyang Yan, Yanfeng Wu, Zhennan Liu and Chengwei Xie

World Electr. Veh. J. 2026, 17(4), 164; https://doi.org/10.3390/wevj17040164 - 24 Mar 2026

Abstract

Vehicle–infrastructure cooperative perception (VICP) extends the sensing capability of single-vehicle systems by integrating multi-source information from onboard and roadside sensors, thereby alleviating limitations in sensing range and field-of-view coverage. However, in complex urban environments, the robustness of such systems—particularly in terms of blind-spot coverage and feature representation—is severely affected by both static and dynamic occlusions, as well as distance-induced sparsity in point cloud data. To address these challenges, a 3D object detection framework incorporating point cloud feature enhancement and spatially adaptive fusion is proposed. First, to mitigate feature degradation under sparse and occluded conditions, a Redefined Squeeze-and-Excitation Network (R-SENet) attention module is integrated into the feature encoding stage. This module employs a dual-dimensional squeeze-and-excitation mechanism operating across pillars and intra-pillar points, enabling adaptive recalibration of critical geometric features. In addition, a Feature Pyramid Backbone Network (FPB-Net) is designed to improve target representation across varying distances through multi-scale feature extraction and cross-layer aggregation. Second, to address feature heterogeneity and spatial misalignment between heterogeneous sensing agents, a Spatial Adaptive Feature Fusion (SAFF) module is introduced. By explicitly encoding the origin of features and leveraging spatial attention mechanisms, the SAFF module enables dynamic weighting and complementary fusion between fine-grained vehicle-side features and globally informative roadside semantics. Extensive experiments conducted on the DAIR-V2X benchmark and a custom dataset demonstrate that the proposed approach outperforms several state-of-the-art methods. Specifically, Average Precision (AP) scores of 0.762 and 0.694 are achieved at an IoU threshold of 0.5, while AP scores of 0.617 and 0.563 are obtained at an IoU threshold of 0.7 on the two datasets, respectively. Furthermore, the proposed framework maintains real-time inference performance, highlighting its effectiveness and practical potential for real-world deployment. Full article

(This article belongs to the Section Automated and Connected Vehicles)

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16 pages, 1687 KB

Open AccessArticle

Generation and Characterization of a Genetically Modified Zea mays Line with a Knockdown of Hypoxia-Dependent microRNA775A

by Dmitry N. Fedorin, Anna E. Khomutova, Alexander T. Eprintsev and Abir U. Igamberdiev

Int. J. Mol. Sci. 2026, 27(7), 2943; https://doi.org/10.3390/ijms27072943 - 24 Mar 2026

Abstract

Hypoxia-dependent microRNAs play an important role in orchestrating a plant’s response to low-oxygen stress. To assess the regulatory mechanisms of the adaptive response of maize (Zea mays L.) to hypoxia, an antisense sequence was developed, and the short tandem target mimic (STTM) system was used to induce the loss of function of the mature microRNA775A (miR775a) in maize. A recombinant binary vector pBI121 cloned in E. coli cells containing the antisense sequence anti-miR775A to maize miR775A was acquired to create a line of modified A. tumefaciens EHA105. Using the puncturing method on soaked seeds, maize plants with an active anti-miR775A construct were obtained, as evidenced by a decrease of more than 10-fold in mature miR775A content and by developmental changes in the seedlings. The size of seedlings of the maize knockdown line was almost twice smaller than that of the wild-type (WT) plants. An assessment of the effects of hypoxic conditions induced by flooding of 14-day-old maize plants revealed differences in the expression and activity of several enzymes between WT and knockdown plants. The reduced miR775A levels led to a 2.1-fold drop in pyruvate levels, which resulted in decreased pyruvate kinase, pyruvate dehydrogenase, and lactate dehydrogenase activities as compared to WT plants. A decrease in miR775A content in the maize knockdown cell line also affected the function of mitochondrial and extramitochondrial isoenzymes of citrate synthase, aconitase, and fumarase under hypoxic conditions. Full article

(This article belongs to the Special Issue Molecular Adaptation Mechanisms of Plants to Environmental Stress)

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18 pages, 625 KB

Open AccessArticle

Ketamine Use in Self-Described Therapeutic Contexts: A Thematic Analysis of Reddit Posts

by Jared Kendrick, Ghonwa Ahmad, Audrey Wood, Samuel Stumo, Aarav Sehgal, Douglas B. Matthews and Pravesh Sharma

Behav. Sci. 2026, 16(4), 480; https://doi.org/10.3390/bs16040480 (registering DOI) - 24 Mar 2026

Abstract

The use of ketamine for the management of neuropsychiatric conditions outside clinical settings has rapidly expanded, creating a critical need to understand diverse individual experiences. We conducted a qualitative content analysis of posts from the r/TherapeuticKetamine subreddit. From 3302 threads, the 500 highest-engagement threads (12,852 comments) were analyzed by independent coders across six domains: perceived positive effects, adverse effects, reasons for use, route of administration, polydrug use, and dose amounts. Mood-related concerns were the primary reason for use (53%). Users reported positive effects, most often improvements in emotional well-being (65%). Adverse effects were predominantly psychological or mood-related (56%). A total of 70% of reported doses exceeded 149 mg, suggesting a trend toward higher dose use. Intravenous administration (40%) and sublingual troches (23%) were the most frequently reported routes. Concurrent use of prescribed psychotropics, cannabis, and psychedelics was also reported. This analysis identified substantial heterogeneity in individual-reported experiences. Frequent high-dose use, dose escalation, and polydrug exposure underscores the importance of clinical monitoring and attention to addiction potential and drug–drug interactions. The findings should be interpreted with caution, as follow-up and clinical verification were not possible; however, the data provide an unfiltered view of individual experiences in relation to ketamine use outside the clinical setting. Full article

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12 pages, 449 KB

Open AccessArticle

An RXTE Search for the Sterile Neutrino Decay in Galaxy Clusters

by Mark Jeffrey Henriksen

Symmetry 2026, 18(4), 551; https://doi.org/10.3390/sym18040551 (registering DOI) - 24 Mar 2026

Abstract

We have used long observations of galaxy clusters obtained with the Rossi X-ray Timing Explorer to search for the 3.55 keV line from sterile neutrino decay. If a lepton-number asymmetry exists in one or more types of active neutrinos in the early Universe, sterile neutrinos can be produced via the Shi–Fuller mechanism. The data consist of 11 clusters observed for a total of 3.1 megaseconds using the Proportional Counter Array. A 2.5

σ

excess of emission over a thermal model is found over the energy span of the 3.55 keV line in the combined spectra of the eight clusters that individually have an excess. These residuals are added to increase the signal to noise ratio of the excess, which is then modeled with a Gaussian to simulate the instrumental spectral response. We find a significant correlation (r = 0.76) for a line centered at 3.6 keV with a model flux of 3.07 × 10⁻⁵ ph cm⁻² s⁻¹. Mixing angle for detected clusters ranges from 2.0 to 21.6 × 10⁻¹⁰. The decay rate inferred from the line flux is strongly correlated (r = 0.87) with cluster temperature, which is due to hotter, more massive clusters having a larger amount of dark matter. Approximately half of the total flux comes from the Coma cluster. The mixing angle for Coma is calculated to be 6.2 × 10⁻¹⁰. We fit the Coma cluster spectrum with two different three-component models. The first includes a Gaussian fixed at 3.55 keV to model soft emission. The flux of the Gaussian is 5.6 × 10⁻¹² ph cm⁻² s⁻¹ or 1.3% of the total flux. The second three-component model uses a second thermal component to model soft emission. This model gives a temperature of 0–17 keV for the second thermal component and a lower temperature for the hot component. This indicates that the second thermal component is modeling high-energy residuals rather than low ones, where the Gaussian is. Though our line fluxes exceed most reported detections and upper limits, they do not overproduce the dark matter. We conclude that some fraction of the marginally detected excess could be attributed to the decay line since low-temperature thermal emission and systematics fail to model it completely. Full article

(This article belongs to the Section Physics)

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