Search Results (5,363)

In the highly volatile cryptocurrency market, trading decision support based on price prediction remains a challenging task. Although machine learning and deep learning techniques have been widely applied to cryptocurrency price prediction, many existing approaches rely on correlation-based black-box models, which limits interpretability and robustness. In this study, we employed a NOTEARS-Linear-based Prediction Model (NLBPM) that directly incorporated causal structures inferred through a causal discovery method as structural constraints within the prediction model. Unlike conventional approaches that focus primarily on minimizing prediction error, the NLBPM emphasized return maximization as its objective function, thereby prioritizing practical economic value. Using Bitcoin as a case study, we constructed a model to predict the direction of price movement four hours ahead and evaluated its performance using a rolling-window scheme with a one-month sliding window. Analysis of the inferred causal structures showed that the returns improved when trades were executed only during rolling-window trials in which specific directed edges to the target variable were detected. Based on this finding, we proposed a causal filter strategy that restricts trading to periods in which specific directed edges to the target variable are detected. In the data period analyzed in this study, the selected edge was the one from the opening price (Open) to the target variable. Backtesting experiments incorporating a transaction fee of 0.1% demonstrated that, while the benchmark LSTM model achieved a negative monthly average return of −3.20% and the NLBPM without filtering yielded −7.20%, the NLBPM with the Open filter attained a higher monthly average return of 10.35%. This study supports the usefulness of using inferred causal structure for cryptocurrency trading decision support. Full article

South Africa has been receiving a high number of undocumented immigrants for years. As Africa’s second largest economy and the biggest in the South African Development Community region, it has witnessed a surge in illegal migration. Some undocumented immigrants marry local women, establishing spousal and familial relations. The government has taken a legal stand against undocumented immigrants. It deports thousands annually. A grassroots movement, Operation Dudula, has initiated efforts to locate undocumented immigrants. Its modus operandi has been condemned for lacking ubuntu. A void is left when undocumented immigrants are deported, leaving their families in South Africa. Some South African women have turned to TikTok to express their views on migration and familyhood. This study attempts to answer these questions: What are the TikTok discursive practices of South African women in spousal relations with African immigrants? In what ways do the women legitimise the relationships? How does TikTok function as a subaltern counter-public formation? Data were gathered through digital archival research and subjected to a multimodal critical discourse analysis. The findings show that the women celebrate the relations as an achievement. They construct them as pathways to prosperity. The women also invoked racial discourses to legitimise the relations. Through TikTok, they recontextualised discourses on migration by deconstructing dominant narratives that project African immigrants through lenses of criminality. Full article

This article offers a comparative reading of Ayla Kutlu’s Bir Göçmen Kuştu O and Zülfü Livaneli’s Huzursuzluk, examining how the two novels represent historical migration and contemporary displacement. It argues that, in both texts, migration cannot be reduced to physical movement from one place to another. Rather, it functions as a cultural rupture that reorders space, identity, belonging, memory, witnessing and alienation. Bir Göçmen Kuştu O frames forced migration from the Caucasus to Türkiye through homeland loss, family memory, genealogical continuity and the search for settlement. Huzursuzluk, by contrast, locates the Syrian war, the persecution of Yazidis, refugeehood, trauma and witnessing within the wider violence of the contemporary Middle East, tracing their effects on individual and cultural memory. Its central argument is that the two novels stage witnessing in two distinct modes. Read through Marianne Hirsch’s notion of postmemory, Kutlu’s novel renders witnessing as the intergenerational inheritance of homeland loss, whereas Livaneli’s stages the synchronic implication of a contemporary listener in another’s suffering; on this reading, migration fiction holds these two configurations together as simultaneous ethical possibilities rather than as successive literary phases. Full article

Resisted sidestepping is widely implemented in rehabilitation and strength training, and exercise prescription is often guided by recommendations based on surface electromyography (EMG) patterns and intuitive assumptions about how elastic-band placement and posture influence hip loading. EMG provides valuable insight into neuromuscular strategies, but it does not, by itself, specify the direction or magnitude of joint-level mechanical demand. In this opinion article, we argue that exercise prescription is strengthened when EMG findings are interpreted within a joint-kinetic framework, in which the net external joint moment, calculated via inverse dynamics, defines the mechanical demand imposed by the task. Using resisted sidestepping as the central example and drawing on previously published three-dimensional inverse-dynamics findings, we address a common misconception that placing an elastic band around the forefeet necessarily imposes an external hip moment toward medial rotation that can help target “hip lateral rotator” muscles. Available inverse-dynamics evidence indicates that, under typical execution with slight hip and knee flexion, forefoot-band sidestepping imposes a resultant external hip moment toward lateral rotation, thereby requiring a net internal muscular moment toward medial rotation to maintain alignment and perform the task. We further highlight that posture and resistance configuration modulate how demand is distributed across joint movement planes. Specifically, band placement alters the moment arms of the elastic resistance relative to different hip joint axes and therefore influences how changes in band stiffness are translated into transverse- and frontal-plane hip loading. Thus, band placement, posture, and resistance magnitude should be selected according to the intended joint-level loading objective rather than inferred from EMG patterns alone. Although illustrated with sidestepping, this reasoning is relevant to many resistance and rehabilitation exercises in which EMG-only interpretations, without consideration of external forces and joint kinetics, may lead to incomplete or incorrect inferences about joint loading and musculoskeletal function. Full article

WPR (WEB1/PMI2-related) genes play a crucial role in regulating chloroplast movement and leaf coloration in plants. Previous studies have shown that these genes are implicated in leaf yellowing, both in Arabidopsis thaliana and in Paulownia fortunei following infection with Paulownia witches’ broom. To investigate the functions of the ZjWPR genes in jujube, bioinformatics methods were employed to identify the ZjWPR gene family in jujube, analyze their protein physicochemical properties, gene structure, evolutionary relationships, and cis-acting elements in this study. The results revealed that the ZjWPR gene family in jujube comprised 10 members. Phylogenetic analysis showed that WPR genes were divided into two classes, with ZjWPR genes distributed across three subgroups within Class II. Conserved motif analysis indicated that motif 2, motif 3, motif 7, and motif 8 were the most highly conserved and most genes exhibited similar structures. Cis-element analysis in their promoter suggested that ZjWPR genes were regulated by multiple hormones and were associated with stress responses such as low temperature and drought. Moreover, all ZjWPR genes contained light-responsive elements. Expression analysis of the ZjWPR gene family under Jujube Witches’ Broom (JWB) stress showed that ZjWPR4 and ZjWPR5 were significantly up-regulated in JWB-susceptible jujube cultivars following phytoplasma infection, whereas no significant changes were detected in JWB-resistant cultivars. Additionally, the expression levels of ZjWPR2, ZjWPR3, and ZjWPR6 were also altered in response to infection, suggesting their potential involvement in the response to JWB stress and the associated leaf chlorosis process. Moreover, transient overexpression of ZjWPR4 and ZjWPR5 in sour jujube leaves led to significant reductions, in critical photosynthetic parameters, including Fv/Fm, Fq′/Fm′, and ETR compared with WT, thereby reinforcing their functional contribution to JWB-associated leaf yellowing. This study provides valuable insights for further functional characterization of the ZjWPR gene family in mediating JWB-induced leaf yellowing and related metabolic pathways. Full article

Background/Objectives: Executive functions and motor performance develop rapidly during early childhood and may be closely interconnected. However, it remains unclear whether specific motor domains are more strongly associated with executive functioning than others. This study examined the relationships among executive functions, motor performance, physical activity, and waist circumference in preschool children using structural equation modeling (SEM). Methods: A cross-sectional study was conducted in 364 preschool children aged 4–7 years from Temuco, Chile. Executive functions were assessed using the Childhood Executive Functioning Inventory (CHEXI). Motor performance included postural stability and strength–coordination indicators derived from the PREFIT battery and the Movement Assessment Battery for Children-2. Physical activity was assessed using the Krece Plus questionnaire. SEM was used to examine direct and indirect statistical associations among variables while adjusting for age and sex. Results: The final SEM showed acceptable fit to the data (CFI = 0.915; TLI = 0.882; RMSEA = 0.054). Postural stability was significantly associated with executive functions (β = −0.268, p = 0.016), whereas strength–coordination was not. Physical activity positively predicted postural stability (β = 0.099, p = 0.024), while waist circumference negatively predicted postural stability (β = −0.095, p = 0.032). An indirect statistical association between waist circumference and executive functions through postural stability was observed. The model explained 9.6% of the variance in executive functions. Conclusions: In preschool children, executive functioning appeared to be more closely associated with postural stability than with broader strength–coordination performance. Although the observed associations were modest in magnitude, the findings suggest that balance-related motor processes may be relevant for understanding motor–executive function associations during early childhood. Longitudinal and experimental studies are needed to clarify the nature and direction of these associations. Full article

Background: Postoperative bowel dysfunction, including delayed gastrointestinal recovery and postoperative ileus, is a common complication that increases morbidity and prolongs hospitalization. In this systematic review and meta-analysis, we evaluated the effects of manual therapies on postoperative bowel function. Methods: MEDLINE/PubMed, Google Scholar, the Cochrane Library, Semantic Scholar, and ClinicalTrials.gov were searched from database inception up to 17 March 2026, and studies evaluating osteopathic manipulative treatment (OMT) or abdominal massage in postoperative patients were included in our analysis. Risk of bias and certainty were assessed using validated study design-specific tools, including the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework. Random-effects meta-analyses were performed for the prespecified outcomes of time to first bowel movement, time to first flatus, and hospital length of stay. Results: Seventeen studies met our inclusion criteria. Both OMT and abdominal massage were associated with a significantly shorter time to first bowel movement compared with controls (OMT: mean difference [MD] −0.57 days, 95% CI −0.96 to −0.18; abdominal massage: MD −0.91 days, 95% CI −1.47 to −0.35). OMT was also associated with reduced hospital length of stay (MD −2.46 days, 95% CI −4.52 to −0.41), while time to first flatus demonstrated favorable but non-significant trends, with substantial heterogeneity. Conclusions: Manual therapy may be associated with earlier postoperative bowel recovery, although heterogeneity and methodological limitations warrant cautious interpretation. Further high-quality multicenter studies are needed to clarify the clinical significance and reproducibility of these findings. Full article

Mangroves are widely promoted as coastal bio-shields, yet their capacity to stabilize shorelines in sediment-deprived, high-energy deltas remains poorly quantified at fine spatial scales. This study addresses whether sustained mangrove cover actively mitigates long-term shoreline erosion, or whether these ecosystems instead function as passive indicators of underlying geomorphic change, in the Muthupet wetland (1995–2025). Using Landsat imagery, the Digital Shoreline Analysis System (DSAS), and the Combined Mangrove Recognition Index (CMRI), shoreline movement was coupled with localized biological cover change through Thiessen polygon interpolation. Over three decades, the coastline was highly unstable and retreating, with over 76% of transects actively eroding under sediment deprivation. Contrary to the bio-shield assumption, segments supporting denser mangrove cover in 1995 underwent the greatest landward retreat, whereas sparsely vegetated transects remained comparatively stable, and sustained cover did not significantly reduce shoreline fluctuation. The strong synchronization between physical shoreline retreat and habitat contraction (rs = 0.611, p < 0.0001) is consistent with the Muthupet mangroves functioning as passive indicators of coastal instability rather than active stabilizers. Consistent with observations from other sediment-deprived deltas such as Mekong, these findings necessitate a shift in regional coastal management toward a geomorphology-first framework that prioritizes sediment–budget restoration over vegetation planting alone. Full article

Interpretability is essential for deploying deep learning (DL) models in electroencephalography (EEG)-based neurotechnology, particularly in brain–computer interfaces and clinical decision-support settings. Existing post hoc explainable artificial intelligence (XAI) methods often yield single-domain attribution maps, limiting their capacity to characterize the joint spatial, temporal, and spectral structure of EEG dynamics. In addition, perturbation-based strategies may disrupt physiological signal organization, whereas gradient-based methods require access to model internals and are therefore tied to specific classifier architectures. Here, we introduce space–time–frequency KernelSHAP (STF-KernelSHAP), a model-agnostic Shapley framework for physiologically coherent EEG explainability. The method comprises three stages. First, EEG trials are decomposed into structured channel–time–frequency cells using segment-wise spectral analysis. Second, coalitions are formed over complete channel–time–frequency cells and reconstructed in the signal domain to support physiologically informed perturbations. Third, class-conditional relevance is estimated with a KernelSHAP-based weighted surrogate model that uses only model outputs, enabling architecture-independent Shapley estimation. We evaluate STF-KernelSHAP on two prerecorded public datasets: the GIGA motor imagery/movement execution (MI-ME) dataset for motor imagery (MI) decoding and the IEEE DataPort EEG Data for Attention-Deficit/Hyperactivity Disorder (ADHD)/Control Children dataset for ADHD detection. For ADHD detection, the T-GARNet base classifier interpreted with STF-KernelSHAP achieved 73.33% accuracy and 79.86% area under the curve (AUC); these values characterize classifier performance rather than the explainer itself. We compare the framework against KernelSHAP, local interpretable model-agnostic explanations (LIME), Occlusion, Integrated Gradients, and gradient-weighted class activation mapping++ (Grad-CAM++). Fidelity is assessed with Deletion and remove and debias (ROAD), while qualitative analyses examine topographic and frequency-band attribution maps. Results show that STF-KernelSHAP remains functionally competitive with established XAI methods while providing window-dependent and frequency-specific explanations. Overall, STF-KernelSHAP offers a physiologically informed and model-agnostic alternative for multidomain EEG interpretability. Full article

High-intensity functional concurrent training (HIFCT) has emerged as a form of training characterized by constantly varied functional movements adapted to individual fitness levels. Previous studies have reported positive effects on muscular strength, cardiorespiratory fitness, body composition, and psychological well-being; however, evidence regarding HIFCT interventions in school-aged children remains limited. Therefore, the aim of the present study protocol is to evaluate the effects of an 8-week HIFCT programme on muscular strength, cardiorespiratory fitness, body composition, anxiety, stress, and self-esteem in children aged 10–12 years. Physical fitness, anthropometric variables, and psychological outcomes will be assessed before and after the intervention using validated field-based tests and questionnaires. This study may provide novel evidence regarding the feasibility, safety, and potential effects of HIFCT programmes in the school setting. The study protocol was registered at ClinicalTrials.gov (NCT07552844) and approved by the Córdoba Research Ethics Committee (IMIBIC, Córdoba, Spain; protocol code SICEIA-2025-000408). Full article

Honeybee (Apis mellifera) flight and vertical locomotion were investigated using high-speed imaging and schlieren flow visualization. Free-flight recordings were analyzed to extract wingbeat frequency, projected stroke amplitude, wingtip trajectories, and membrane deformation. The wingtip trajectory exhibited a pronounced asymmetry between upstroke and downstroke, suggesting a dominant role of the downstroke in thrust production. Significant membrane deformation was observed near stroke reversal, indicating strong wing flexibility and dynamic modulation of wing shape during flapping. A novel support-based framework was introduced to characterize vertical locomotion through the support polygon formed by leg contact points and the displacement of its centroid relative to the body. This movement function quantified changes in support distribution and revealed adaptive leg-contact strategies during wall climbing. Schlieren visualization provided qualitative evidence of wingtip vortex formation, although finer wake structures remained difficult to resolve. These findings provide new experimental observations of honeybee flight kinematics and introduce a quantitative framework for analyzing vertical locomotion using support redistribution metrics. Full article

Objective assessment of low back pain (LBP) is challenging due to subtle, task-dependent movement impairments that are poorly captured by existing sensing technologies. Motion Tape (MT), which is a self-adhesive elastic fabric skin strain sensor, enables skin-conforming measurement of localized biomechanical strain during functional movement, but its discriminative utility for LBP remains unclear. We examine this question in a multi-sensor, multi-movement setting and analyze whether MT signals encode discriminative structure that distinguishes individuals with LBP from healthy controls. Using data from 20 participants performing 19 functional movements with six sensors, we evaluate movement-specific classification under a leave-pair-out protocol and examine which movements, sensor placements, and features are most informative. Our analysis reveals that group separation is highly selective: only a small subset of movements, most notably forward flexion, consistently supports accurate classification, while many movements remain at near-chance level. We find that temporal dynamics features help in resolving difficult cases that global strain statistics fail to separate, and that informative signals are spatially localized to the lower lumbar spine. In contrast, pretrained time-series foundation models show negligible sensitivity to participant-level structure in MT signals. Overall, the findings from this exploratory study establish when and how MT sensing can effectively differentiate individuals with LBP from healthy controls, providing a principled foundation for larger-scale validation. Full article

Infrared UAV detection plays a crucial role in both security surveillance and military applications. However, under fast UAV movement or dynamic zooming scenarios, the rapid scale variation of targets poses severe challenges to existing detection models, especially on resource-constrained edge devices. To address this, a lightweight scale-adaptive multi-scale feature fusion model, termed LMF-IR, is proposed for efficient and accurate detection under sudden target size changes. The model integrates three key components: a Multi-Dilation Residual Block (MDRB) for enhanced multi-scale feature representation, an improved Channel Attention Model–Feature Fusion Pyramid Network (CAM-FPN) to boost adaptive feature fusion, and a modified P-WIoU loss function designed for precise bounding box regression under varying target sizes. The MDRB module effectively captures fine-grained features across multiple scales and reliably identifies targets of varying sizes. The CAM-FPN incorporates a channel attention mechanism, which can dynamically adjust the weights of features, enabling the model to focus on informative feature channels. The redesigned P-WIoU loss function is designed to account for the shape characteristics of UAV target bounding boxes. It includes centroid distance, overlap ratio, and aspect ratio, thereby improving localization accuracy under rapid scale changes. The experimental results on our self-built UAV–infrared dataset show that LMF-IR reduces 1.4 G in floating-point operations compared to the baseline model, and the parameter count is reduced to 62% of the baseline. At the same time, mAP@0.5:0.95 increases by 2.4%. Moreover, on the public ANTI-UAV dataset, our method increases mAP@0.5:0.95 by 4.8%, indicating that our method has excellent performance in real-time infrared UAV detection under rapid target scale changes. Full article

Background: Many individuals with traumatic brain injuries (TBIs) exhibit oculomotor dysfunctions that impact their daily functioning. As current clinical screening tools are limited, we have created and pilot-tested the Rehabilitation Oculomotor Screening Evaluation (ROSE) previously in a small sample of people with acquired brain injuries and neurotypical participants. The current study aims to validate ROSE in persons with TBI, focusing on mild TBI (mTBI). Methods: Participants with TBI (n = 25) completed different clinical scales, including ROSE, Sensory Organization Test (SOT) for standing balance, Reintegration to Normal Living Index (RNLI), Timed Up and Go (TUG) for mobility, and a visual analogue scale for the subjective perception of visual vertigo. Neurotypical individuals (n = 24) who were age- and sex-matched completed only ROSE. Results: The group with mTBI (n = 18) had significantly higher ROSE scores compared to the neurotypical group, with a large effect size. Significant correlation was found between ROSE and RNLI scores, but not with other clinical outcomes. Conclusions: Significant between-group difference in ROSE scores and their association with RNLI scores suggest that ROSE is a valid tool in detecting oculomotor dysfunction in TBI. Future studies should continue the validation of ROSE in other TBI and neurologic populations and in larger sample sizes. Full article

We investigate functional behavioural differentiation in genetically homogeneous animal collectives using the $ϵ$-machine and $ϵ$-transducer frameworks from symbolic dynamics. Long-term tracking of unmarked individuals in colonies of the clonally reproducing ant Pristomyrmex punctatus reveals two distinct movement modes—clustering within the group and solitary exploration outside it. Reconstructed individual $ϵ$-transducers expose a sharp asymmetry in computational structure between these modes: solitary explorers are described by a deterministic machine, whereas clustering ants require stochastic machines to capture their complex patterns of micro-movement. A population-level (universal) $ϵ$-transducer, inferred from pooled data, captures the shared behavioural repertoire across all individuals. Individual differences are parsimoniously explained as biased and partial traversals of a common state space rather than as distinct generative programs. We compare three predictive models: the $ϵ$-machine, which relies solely on an ant’s own output history; a memoryful $ϵ$-transducer, which additionally conditions on changes in the local neighbour count as social input; and a memoryless $ϵ$-transducer, which uses this social input alone. The memoryful transducer matches the $ϵ$-machine in prediction accuracy despite requiring ten times as many states, while the memoryless transducer performs substantially worse. This shows that an ant’s own behavioural history is the essential predictor of its future movement at the temporal resolution examined here. We argue, however, that this predictive redundancy does not entail the causal irrelevance of social input: the behavioural history itself accumulates the trace of past social encounters so that any role differentiation established through prior interactions is already inscribed in the output sequence that the $ϵ$-machine reads, and mode transitions—the moments at which social input most plausibly exerts causal influence—are rare events that contribute negligibly to aggregate one-step accuracy. Agent-based simulations driven by the universal $ϵ$-transducer reproduce basic motion statistics and transient aggregations but fail to generate the stable macroscopic clusters observed experimentally, pointing to the role of additional mechanisms such as longer-term memory or stigmergic coupling. Nevertheless, ants do respond to their social environment: an explorer encountering an increase in neighbours is absorbed into the cluster and ceases directed movement. Together, our results suggest a two-level organisation: within each behavioural mode, individual dynamics are self-sufficient for one-step prediction, while transitions between modes are environmentally triggered and represent switches between fundamentally different classes of dynamical organisation. Full article