Search Results (465)

Stroke survivors with upper-limb impairments often have difficulty using conventional computer interfaces, which limits their ability to perform daily computer-related activities independently. This study developed a wearable multimodal assistive interface that enables computer interaction through a virtual cursor. A lightweight headband equipped with electrooculography (EOG), electroencephalography (EEG), and an inertial measurement unit (IMU) was used to acquire multimodal signals for interaction control. EOG signals were processed to detect voluntary blinks to generate clicks, head movements were mapped to cursor movements through IMU-based control, and frontal EEG signals were used to estimate attention as an auxiliary mechanism for command verification. A rapid user-specific calibration procedure was introduced to adapt blink-detection thresholds to individual EOG characteristics without requiring extensive training. Thirty stroke patients with upper-limb impairments participated in experiments involving common computer tasks, including news reading, video playback, and character spelling. The system achieved an average operation accuracy of 87.53 ± 4.92%, an average operation time of 3.49 ± 0.49 s, and an information transfer rate of 62.04 ± 15.93 bits/min in the spelling task. The mean NASA-TLX score was 32.1 ± 5.4, indicating a moderate subjective workload during system use. These results demonstrate the feasibility of the proposed wearable multimodal assistive interface for supporting computer interaction in stroke survivors with upper-limb impairments. Full article

Background and Objectives: This methodology-focused narrative review synthesizes the eye-tracking literature in bipolar disorder (BD) to evaluate the utility of such technology in identifying potential state or trait biomarkers for BD. Methods: A PubMed and Scopus search was performed from database inception to August 2026. Eligible studies included adults with BD or individuals at high-risk for BD compared with healthy controls (HCs) that used at least one quantitative eye-tracking paradigm and reported extractable quantitative outcomes. Studies were grouped into eight paradigms: free-viewing task (FVT), antisaccade (AS), prosaccade (PS), memory-guided saccade (MGS), smooth pursuit eye movements (SPEM), vergence, binocular rivalry (BR), and eye-blink rate (EBR). Findings were synthesized narratively based on study designs and outcome measures. Results: 24 studies met inclusion criteria. FVT and PS were the most frequently represented paradigms (n = 8 each), followed by AS (n = 7), BR (n = 4), and SPEM (n = 3); MGS, vergence, and EBR were each represented by one report. Findings from FVT, AS, and PS were inconsistent; the study designs, stimulus types, mood states during the study, and outcome measures of studies with these paradigms were diverse. BR alternation rate was consistently slower in BD across three studies. SPEM deficits were more closely associated with psychotic features. Evidence from single studies of MGS, vergence, and EBR limits their interpretations. Conclusions: Eye-tracking paradigms are promising tools for studying cognitive, affective, perceptual, sensorimotor, and reward-related presentations of BD. However, the field needs standardized protocols that include eye-tracking paradigms, mood states, symptom severity, outcome measures, study samples, and comparison groups to examine the utility of eye-tracking technology in BD. Full article

Structural analysis using X-rays and electron beams has long provided the average arrangement of atoms and molecules—that is, “structural information”—with high precision. By contrast, static measurements cannot directly yield dynamic information on how a material changes over time; instead, information on motion is convolved into a single numerical value such as the B-factor (atomic displacement parameter). Taking this limitation as its starting point, this review surveys the recent trend of introducing a time axis into measurements to observe material dynamics directly. First, we outline the technological foundations that have made the transition from static to time-resolved measurement possible. It rests on the dramatic shortening of exposure times, enabled by the increased brilliance of X-ray and electron sources and by advances in detection technology such as direct photon-counting detectors. Next, we survey dynamic measurement techniques, including time-resolved X-ray crystallography, coherent X-ray scattering, neutron scattering, and time-resolved electron microscopy. We also point out the essential limitation that most of them still return ensemble or volume averages. Building on this, we systematically describe diffracted X-ray tracking (DXT), diffracted X-ray blinking (DXB), small-angle X-ray blinking (SAXB), transmitted X-ray blinking (TXB), and electron-beam molecular dynamics (EBMD), which use gold nanocrystals and gold nanoparticles as motion probes. We distinguish throughout between methods that follow individual objects—DXT and EBMD, which yield trajectories of single labeled molecules or single particles—and methods that analyze intensity fluctuations arising from many contributors within one pixel or illuminated volume—DXB, SAXB and TXB. The latter are not single-molecule measurements; rather, they replace a global ensemble average by a spatially localized statistical one, retaining local heterogeneity that a bulk measurement would average away. Finally, we discuss the implementation and prospects of the large-volume data analysis—principal component analysis, Bayesian inference, machine learning, and autonomous measurement—needed to handle the explosively increasing amount of information that the time axis introduces. We close with the outlook that time-resolved measurement incorporating AI and big-data analysis will become established as a new measurement platform that complements and extends conventional static structural analysis. Full article

Eye tracking is a valuable behavioral signal for human-centered AI, yet the reliability of feature-based machine-learning models for inferring task type and workload across users and tasks remains uncertain, because experimentally defined workload labels may reflect task type and visual structure as much as cognitive demand. The practical problem is that designers of gaze-adaptive systems need to know which inferences are dependable enough to act on, and reported accuracies alone do not answer this, because the choice of prediction target and validation split can determine the result. This study systematically evaluates feature-based machine-learning models with post hoc explainability across three prediction targets: task type, binary load-versus-rest, and three-level workload. Eye-movement features derived from fixations, saccades, pupils, and blinks were extracted from short temporal windows collected from 54 participants performing attention, visual-spatial, and memory tasks under rest, easy, and difficult conditions, and evaluated using leave-one-subject-out (LOSO) and leave-one-group-out (LOGO) validation. Task type was classified most reliably (85.9% LOSO, 83.4% LOGO), binary load-versus-rest showed moderate, validation-sensitive robustness (81.4% LOSO, 63.9% LOGO), and three-level workload classification was substantially more challenging (56.4% LOSO, 44.3% LOGO). SHAP and statistical analyses consistently identified fixation dispersion, pupil-related measures, and subject-normalized features as the strongest contributors across all three targets. These findings show that prediction target definition, validation strategy, and post hoc explainability jointly determine what can be reliably inferred from gaze-based machine-learning models. Eye tracking alone therefore appears promising for task-type recognition and may support coarse engagement-related inference when the deployment task family is represented during model development, whereas task-independent fine-grained workload estimation remains unsupported by the present evidence. Full article

The present study investigated whether retrieval practice facilitates memory retention and the rapid identification of newly learned French word components under attentional blink (AB) conditions. Specifically, a total of 107 native Chinese speakers participated in the study, and 103 were included in the final analyses after exclusions. In Experiment 1, participants studied novel, semantically opaque French compound words under two learning conditions: retrieval practice and repeated study. Experiment 2 was conducted 15 min after the completion of Experiment 1. Participants performed a two-target rapid serial visual presentation (RSVP) task in which the morphemic components of the learned compound words were presented as the first target (T1) and the second target (T2) at critical lags (Lag 3 and Lag 7). Experiment 1 confirmed the classical testing effect, with the retrieval practice condition showing higher accuracy and faster response times than the repeated study condition. Experiment 2 revealed that participants in the retrieval practice condition exhibited significantly higher T2 identification accuracy at Lag 7 and a numerical advantage at Lag 3 compared with those in the repeated study condition. These findings indicate that retrieval practice facilitates T2 identification, particularly when attentional resources are relatively recovered at Lag 7. Overall, retrieval-based learning appears to strengthen newly acquired lexico-semantic representations and support the rapid identification of newly learned word components under RSVP conditions. Full article

With the ever-evolving and constantly growing need for electric vehicles (EVs) in the automotive industry, the importance of reliable, efficient, and dynamic EV chargers is increasing. Power electronics is the enabler and forms the execution layer of any charging station. EV charging must now integrate fast control, wide adaptability, bidirectionality, and reliability. The existing literature provides overview studies on the EV charging system, its infrastructure, and necessary power electronics. However, the integration of 5G-enabled EV charging (i.e., data transmission/communication via the 5G network) has introduced new performance expectations that go beyond the capabilities of conventional power converters. This paper presents an in-depth overview of power electronics applications in a 5G-enabled EV charging system. Several key aspects such as advanced converter topologies, a resonant converter for 5G charging, the integration of power electronics with 5G communication, and anomaly and intrusion detection models for a 5G-enabled Blink-2-level EV charger are discussed. Moreover, the challenges and risks of integrating 5G into EV charging infrastructure are discussed. Some recommendations on future research opportunities are provided. This study provides a basic guideline on power electronics applications in a 5G-enabled EV charging system and is therefore valuable to the researchers, scientists, and engineers working in this interesting field. Full article

Contemporary artificial intelligence systems present themselves through the aesthetic of openness: a clean interface, a blinking cursor, an implicit invitation to bring whatever one wishes. This essay argues that this appearance conceals a structural inversion. Drawing on phenomenological philosophy, particularly the work of Simone Weil, Jean-Luc Marion, Jacques Derrida, Henri Bergson, and Byung-Chul Han, alongside a technical account of transformer architecture and large language model training, the essay distinguishes two fundamentally different modes of openness, understood throughout as modes of relation to what arrives rather than as properties of objects: privative emptiness, defined by what it lacks and oriented toward resolution, and receptive openness, a positive capacity for availability toward what cannot be anticipated or controlled. At every structural level, from interface design through training objectives to core architecture, AI systems are constitutively oriented toward the former while producing a phenomenologically convincing simulation of the latter. Engaging Jean Baudrillard’s concept of the simulacrum, the essay argues that this simulation, at sufficient scale and ubiquity, risks eroding the human capacity to distinguish genuine receptive openness from its engineered appearance. The paper concludes by gesturing toward contemplative and institutional counter-practices, including the author’s work on Radical Pause: The UCCS Stillness Project, as responses to this formative challenge, and specifies the structural conditions under which such practices resist commodification by the very attention economy they oppose. Full article

The Jishen Black pig is a synthetic breed incorporating the genetic backgrounds of Chinese indigenous pigs and Western lean-type pigs. The objective of this study was to characterize phenotypic variation, estimate genetic parameters, and identify genomic loci associated with rib number (NR) and the total number of thoracolumbar vertebrae (NTLV) in Jishen Black pigs. NR, NTLV, and lumbar vertebra number (NLV) were measured in 389 pigs, and genotyping was performed using a 70K SNP chip. Genetic parameters were estimated using HIBLUP, and genome-wide association studies (GWAS) were conducted using the MLM and BLINK models in GAPIT v3.0. The mean values of NR, NTLV, and NLV were 14.88, 20.94, and 6.05, respectively, and their heritability estimates were 0.568, 0.493, and 0.140, respectively. GWAS identified a shared major association peak for NR and NTLV on SSC7 at 91.19–98.15 Mb, centered on VRTN and the adjacent ABCD4-LTBP2-AREL1-PGF linkage region, among which the loci at 96.12 Mb, 96.56 Mb and 97.79 Mb are NR-specific loci. Additional signals included MIB1 on SSC6 and MMRN2 on SSC14 for NTLV, together with NR-specific loci on SSC7 at 111.59 Mb and on SSC8. Database annotation indicated that several significant SNPs overlapped with records for rib number, carcass length, loin muscle area, backfat thickness, or teat number. This study identifies major genomic regions associated with vertebral-number traits in Jishen Black pigs and expands current knowledge of their genetic basis. Full article

Environmental stressors like low temperature, low relative humidity (RH), and particulate matter (PM2.5), promote tear film instability and dry eye disease. This study investigates how these conditions alter the interfacial behavior of meibomian gland secretion (MGS) films in vitro and evaluates the capacity of mucomimetic polymers (0.5% hyaluronic acid [HA], polyvinylpyrrolidone [PVP], and chondroitin sulfate [CHS]) to suppress these impacts. MGS films over polymer-containing aqueous subphases were analyzed using a Langmuir trough and Brewster angle microscopy under adverse conditions (20 °C subphase, 20% RH, PM2.5 exposure). A sophisticated analytical framework was developed to evaluate MGS duplex multilayers: (i) a Volmer equation-based 2D-VES model to probe interfacial molecular properties (limiting area, compressibility, cohesion pressure) and (ii) a combined Maxwell viscoelastic and diffusion-relaxation model to quantify the dilatational relaxation modulus. Results indicate that despite their distinct nature, environmental stressors similarly disrupt the multilayer structure, reorganization, and rheological properties of MGS layers during blink-like deformations. Polymer supplementation moderated these adverse effects, yielding partial recovery of film structure and isothermal reversibility. Distinct mechanisms of action for HA, PVP, and CHS at the film/aqueous interface are elucidated. Full article

Fusarium wilt, caused by Fusarium oxysporum f. sp. melonis (FOM), is a main disease of melon (Cucumis melo L.). FOM 1.2 is the most widespread and detrimental variant of FOM, causing substantial economic losses under severe disease conditions. Current information suggests that resistance to race 1.2 (FOM 1.2) is controlled by multiple recessive genes and is strongly influenced by the environment. Therefore, identifying genetic polymorphisms within diverse melon populations is essential to elucidate the loci and putative candidate genes associated with resistance. The objective of this investigation was to identify single-nucleotide polymorphism (SNP) and structural variant (SV) markers associated with FOM 1.2 resistance utilizing a panel of 160 genotypes through a genome-wide association study (GWAS). Phenotypic evaluation was performed two weeks after sowing, at the first-true-leaf stage, on 2400 individual plants inoculated by the root dip method with a concentration of about 10⁶ spores/mL. Biochemical and disease-related traits, including area under disease progress curve (AUDPC), disease severity index (DSI), standardized AUDPC (SAUDPC), latent period (LP), catalase, peroxidase activity, and ascorbate peroxidase activity were measured 35 days after inoculation. PCA identified eighty-three individual melon plants with a broad range of disease-response variation. Genotyping-by-sequencing (GBS) was conducted on these plants, resulting in the identification of 737,435 SNPs and 75,133 SVs. Evaluation of the population structure outlined four genetic groups, including one associated with germplasm highly resistant to FOM 1.2. We used SNP data to describe linkage disequilibrium (LD), which was estimated to decay at 14 kb, on average. A GWAS was performed using the Bayesian information and linkage-disequilibrium iteratively nested keyway (BLINK) method, which revealed nine SNPs significantly associated with several disease indices, namely ascorbate peroxidase activity, AUDPC, catalase, peroxidase activity, rAUDPC, and SAUDPC. Also, eight SVs were associated with AUDPC and relative area under disease progress curve (rAUDPC), including translocation and deletion types. In addition, GWAS using the fixed and random model circulating probability unification (FarmCPU) method unveiled thirteen SVs associated with rAUDPC, peroxidase activity and ascorbate peroxidase activity, including translocation and inversion types. According to the performed models of GWAS, several significant SNPs and SVs, associated with putative candidate genes, including multidrug resistance-associated protein 6 (MRP6), LOB domain-containing protein 15 (LBD15), phosphomannomutase, and NADH-ubiquinone oxidoreductase B8 subunit, which may be involved in FOM 1.2 resistance. However, these findings represent a preliminary genome-wide survey and require further validation using high-coverage or long-read sequencing approaches. The results provide remarkable insights into the genetic control of FOM 1.2 resistance and valuable information for the implementation of the putative molecular markers identified in this study in melon breeding programs. Full article

Reproductive characteristics in pigs exhibit low heritability levels. Performing genome-wide association studies (GWAS) to pinpoint candidate genes for these characteristics is crucial for enhancing swine fertility. In this research, hair samples were gathered from 689 French Large White sows within the primary breeding population for DNA extraction purposes. Genotyping was carried out using a 50K liquid-phase SNP chip. Four statistical approaches—MLM, CMLM, FarmCPU, and BLINK—were utilized to perform GWAS on nine reproductive characteristics: total number born (TNB), litter birth weight (LBW), number born alive (NBA), number of healthy births (NHB), number of weak piglets (NWP), number of stillbirths (NSB), number of mummies (MUM), number of deformed fetuses (NDF), and adjusted 21-day litter weight (ALW). siRNAs targeting significantly associated genes were designed, and viral transfection was employed to introduce them into the ovarian granulosa cells of Large White sows to explore gene functions; transcriptome sequencing of granulosa cells treated with DNAH6 siRNA was conducted to investigate the gene’s action mechanism. The analysis indicated that both MLM and CMLM models identified a significant locus linked to the total number of piglets born, with the SNP positioned at 3-60064515, associated with the DNAH6 gene. Disruption of the DNAH6 gene notably reduced the proliferation of ovarian granulosa cells (p < 0.05). Transcriptome sequencing results suggest that DNAH6 may support the normal transcriptional activity of the cAMP signaling pathway by maintaining EP300 and CREBBP expression in porcine ovarian granulosa cells, while potentially inhibiting the anti-proliferative effects of the FoxO pathway. This potential mechanism may help sustain the proliferative ability of granulosa cells and promote normal follicular development, which may ultimately contribute to an increase in the total number of piglets born in sows. These results offer a potential candidate marker for enhancing the total number born of French Large White sows. Full article

Background: Lateral eye movements are part of natural ocular motility, and their effect on tear film behavior is largely unknown because they are usually not evaluated during tear film examinations, where patients are required to look straight ahead. This study aimed to determine what happens to the tear film during lateral eye movements in the absence of blinking. Methods: Tear film dynamics during a sequence of open-eye lateral gaze maneuvers were recorded using an infrared camera system (TearView). Results: The study included 15 healthy participants (5 female; median age 26) who had no ocular surface-related complaints. It was observed that lateral eye movements exposed new ocular surface areas not previously covered by the tear film. The tear film margins reacted to lateral eye movements by spreading towards the newly uncovered ocular surface areas, thereby recoating them. This response was asymmetrical, with a tear reservoir in the lacus lacrimalis of the medial canthus providing additional tear film spread only during ocular abduction. Conclusions: These findings expand our understanding of tear film physiology beyond static gaze. They might also bear implications for dry eye disease and oculoplastic surgical techniques affecting the medial canthus. Full article

Vision-based driver fatigue detection remains challenging because facial signals associated with fatigue are often ambiguous, while geometric indicators such as Eye Aspect Ratio (EAR) and Percentage of Eye Closure (PERCLOS) are prone to false positives caused by normal facial activity, including smiling or speaking. This paper proposes a context-aware framework that integrates behavioural, geometric, and emotional information for robust fatigue assessment. Facial landmarks are extracted using MediaPipe Face Mesh, while adaptive eye-closure detection is performed through multi-stage validation combining EAR trajectories, mouth activity, head-pose analysis, and event-level filtering. Emotion recognition is achieved using an EfficientNet-B0 convolutional neural network trained on the AffectNet dataset, enabling frame-level estimation of facial expression probabilities. These predictions are aggregated into descriptors representing emotional variability and fatigue-related emotional relevance over time. Behavioural information obtained from blinking, yawning, head nodding, and validated PERCLOS is fused with emotional context to construct a multi-level fatigue assessment model. The final Driver Fatigue Risk Index combines physiological eye-closure information with contextual behavioural–emotional analysis, providing an interpretable estimation of driver state rather than a binary classification alone. Experimental evaluation on the NTHU-DDD dataset achieved 94% accuracy and demonstrated improved robustness under non-frontal head poses and expressive facial behaviour. Full article

Essential blepharospasm (BEB) is a focal dystonia characterized by abnormal brainstem excitability and impaired inhibitory control within trigeminal–facial circuits. Botulinum toxin type A (BoNT-A) is the established first-line treatment, primarily acting at the neuromuscular junction. However, whether BoNT-A also modulates central brainstem circuits in BEB patients remains unclear, and dedicated neurophysiological studies have yielded conflicting results. To investigate whether BoNT-A modulates brainstem interneuronal excitability in BEB using the blink reflex recovery cycle and to correlate clinical outcomes with neurophysiological results. Thirteen patients with BEB underwent neurophysiological and clinical evaluation before (T0) and one month after (T1) BoNT-A treatment. The blink reflex recovery cycle was assessed at interstimulus intervals (ISIs) of 200, 300, 500, and 1000 ms. Clinical severity was assessed using the BSPSS, JRS, and BDS scales. The R2 amplitude ratio showed a statistically significant decrease after treatment across all ISIs (all p ≤ 0.001), indicating reduced brainstem interneuronal excitability. All clinical scales demonstrated statistically significant improvement after treatment (BSPSS, JRS, BDS; all p < 0.001). This pilot study provides preliminary evidence that BoNT-A treatment may reduce brainstem interneuronal excitability in BEB patients, as evidenced by a substantial and consistent decrease in R2 amplitude ratios of the blink reflex recovery cycle. These findings are consistent with a central modulatory effect of BoNT-A beyond its established peripheral action. Larger controlled studies are warranted to confirm these results. Full article

Adaptive Sidelobe Cancellation (ASLC) is a core technology for modern radar systems to suppress active sidelobe jamming. From the perspective of disrupting the ASLC system’s ability to stably track the jamming direction, this paper proposes a distributed jamming method based on random phase perturbation. The method employs two spatially separated jamming sources that simultaneously transmit coherent signals. By actively applying controllable random jumps to the relative phase between the two sources, the equivalent wavefront direction of the synthesized signal at the radar receiver changes rapidly, forming a non-stationary jamming that destroys the null-tracking capability of ASLC. An analytical model of the ASLC cancellation ratio (CR) under random phase perturbation is established, with a focus on analyzing the effects of time synchronization accuracy and phase synchronization accuracy on jamming performance. Monte Carlo simulation results show that the proposed method can reduce the average ASLC CR from 26.80 dB to 20.29 dB (a decrease of 6.51 dB). Under identical conditions, this performance is comparable to asynchronous blinking jamming while requiring no precise timing matching, and outperforms multi-source saturation jamming in resource efficiency (two vs. four jammers). This study provides promising simulation-level evidence for the effectiveness of the proposed jamming method. The quantitative results and sensitivity analyses offer a simulation-level theoretical reference for parameter design of distributed cooperative jamming. Further validation in semi-physical simulations or field trials is necessary before claiming engineering readiness. Full article