搜索结果：Strikes

While state incarceration policies have received much attention in research on the causes of mass incarceration in the U.S., their roles in shaping population health and health disparities remain largely unknown. Merging data on state incarceration policies to vital statistics birth records from 1984-2004, we examine the impacts of two signature state incarceration policies adopted during the "tough on crime" era of the 1990s-three strikes and truth in sentencing-on Black and White birth outcomes. Using a difference-in-differences event study research design that models the dynamic impacts of these policies over time, we find that these policies had opposing effects on birth outcomes. Birth weight outcomes-including mean birth weight and low birth weight-for Black infants worsened markedly in the year three strikes policies were adopted. By contrast, birth outcomes for Black and White infants gradually improved after truth in sentencing policies were adopted. The discordant findings point to distinct, countervailing mechanisms by which sentencing policies can affect population health. We provide suggestive evidence that three strikes policies adversely impacted Black birth outcomes through affective mechanisms, by inducing highly racialized, stigmatizing, and criminalizing public discourse around the time of policy adoption. Our results indicate that truth in sentencing likely impacted birth outcomes via material mechanisms, by gradually reducing community incarceration and crime rates. Altogether, these findings point to the need to further interrogate state criminal legal system policies for their impacts on population health, considering whether, how, and for whom these policies result in health impacts.

An individual's chronotype reflects their intrinsic circadian rhythm preference and is closely associated with cognitive function and mental health. However, the relationship between chronotype and whole-brain morphological structural network organization remains unclear. This study aims to explore differences in the topological organization characteristics of morphometric similarity networks (MSNs) among healthy young adults of different chronotypes from a graph theory perspective. We employed a novel Morphometric INverse Divergence (MIND) method, which is more sensitive to subtle morphological differences, to construct individual-level brain MSNs. This method aggregates morphological metrics (cortical thickness, mean curvature, sulcal depth, surface area, gray matter volume) from all vertices within each cortical region to form a regional multivariate distribution. Subsequently, a k-nearest neighbor density algorithm constructs a pairwise distance matrix, and symmetric Kullback-Leibler divergence between regional multivariate distributions quantifies similarity among cortical regions. Using high-resolution Glasser atlas, medium-resolution Destrieux atlas, and low-resolution Desikan-Killiany atlas, MIND networks were constructed for 68 healthy young individuals with early chronotype (EC) and 68 with late chronotype (LC) patterns. We calculated the area under the curve (AUC) for multiple graph-theoretic metrics, including small-world properties, across varying sparsity levels in weighted networks, followed by intergroup comparisons and correlation analyses. Analysis based on the Destrieux atlas revealed that EC participants exhibited significantly higher AUC of Small-World Properties (AUC-SWP) compared to LC participants (P = 0.0045), and this metric showed a significant negative correlation with ChQ-ME scores (rs = -0.2114, P = 0.0135). When using the Desikan-Killiany atlas and the Glasser atlas, the aforementioned intergroup differences and correlations were not detected (P > 0.05). These findings suggest that an individual's chronotype correlates with the topological organization of brain MSNs. This association was detected specifically when using the medium-resolution Destrieux atlas, while was not found with either the lower-resolution Desikan-Killiany atlas or the higher-resolution Glasser atlas under the conditions of this study. This pattern indicates that chronotype-related brain differences may operate at an optimal spatial scale, where brain parcellation strikes a balance between signal integration and anatomical specificity. The results support a model of distributed, subtle morphological alterations that together form a detectable "weak signal" network. This study presented a novel spatial-scale perspective on the relationship between brain structure and circadian rhythms.

Tactile sensors are essential for robots to interact with complex environment, but the precise perception of surface tackiness remains a critical challenge for robotic interactive intelligence. Quantitative adhesion analysis requires measuring both pressure and pulling forces at the exact same location. However, existing sensors struggle with signal crosstalk and baseline instability, failing to achieve this intrinsically decoupled measurement. Here, we report a surface-soft, magneto-mechanical coupling tactile sensor that achieves intrinsic signal decoupling within a single sensing element. By leveraging a skin-like bidirectional deformation design, inward pressure and outward pulling force generate baseline-separated magnetic signatures. This eliminates the need for complex post-processing and enables continuous, high-stability monitoring of the full adhesion cycle-from initial contact to final pull-off. The sensor exhibits only 0.25% force drift over 10 h and remains below 0.30% after hammer strikes and maintains 99.52% signal coincidence across repeated press-pull cycles. Such exceptional performance metrics grant the sensor a level of tackiness differentiation that rivals standard adhesion testing. When integrated with a neural network, the sensor yields 99.78% tackiness identification accuracy under diverse contact conditions, exceeding human precision (85.71%). This work pushes the boundaries of existing tactile sensing and lays a solid foundation for advanced robotic manipulation of tacky and lightweight objects.

Sharp force trauma (SFT) is a leading cause of homicide-related deaths, frequently involving kitchen knives as weapons. Offenders may attempt to eliminate forensic evidence by burning a corpse, complicating medicolegal investigation. While scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) has successfully detected metallic traces from sharp objects in skin and fresh bone, its efficacy in burned bone is currently unexplored. This study aimed to evaluate the potential of SEM-EDS to detect metallic residues transferred from sharp tools to bone that was subsequently burned, thereby contributing to the development of an identification procedure in forensic investigation. Ten knife strikes were inflicted on fleshed porcine ribs, which were then burned in an electric muffle furnace at 700 °C for two hours. Sharp lesions were analyzed using SEM-EDS to identify transferred chemical elements. Traces of iron and chromium were detected in seven lesions, with silicon identified in two samples. These elements, absent from the control samples, provided robust evidence of transfer from the blade to the bone. The residues appeared as bright spots with either undefined shapes or well-defined particles, located along the lesion edges. This study is the first to confirm the identification of metallic traces from SFT in bone subsequently exposed to heat using SEM-EDS. Despite thermal exposure, residues persist and remain detectable. SEM-EDS analysis is thus a non-destructive, valuable technique for distinguishing heat-induced bone damage from SFT. Further research with a larger sample and a broader range of implements is needed to validate and extend these findings for forensic applications.

Previous works have shown that increasing the window size for Transformer-based image super-resolution models (e.g., SwinIR) can significantly improve the model performance. Still, the computation overhead is also considerable when the window size gradually increases. In this paper, we present SRFormer, a simple but novel method that can enjoy the benefit of large window self-attention but introduces even less computational burden. The core of our SRFormer is the permuted self-attention (PSA), which strikes an appropriate balance between the channel and spatial information for self-attention. Without any bells and whistles, we show that our SRFormer achieves a 33.86dB PSNR score on the Urban100 dataset, which is 0.46dB higher than that of SwinIR but uses fewer parameters and computations. In addition, we also attempt to scale up the model by further enlarging the window size and channel numbers to explore the potential of Transformer-based models. Experiments show that our scaled model, named SRFormerV2, can further improve the results and achieves state-of-the-art. We hope our simple and effective approach could be useful for future research in super-resolution model design. The homepage is https://z-yupeng.github.io/SRFormer/.

High-throughput spatial transcriptomics (ST) now profiles hundreds of thousands of cells or locations per section, creating computational bottlenecks for routine analysis. Sketching, or intelligent sub-sampling, addresses scale by selecting small, representative subsets. While effective for single-cell RNA sequencing data, existing sketching methods, which optimize coverage in expression space but ignore physical location, can introduce spatial bias when applied to ST data. To explore the impact of sketching on ST analysis, we systematically benchmarked uniform sampling, leverage-score sampling, Geosketch (minimax/Hausdorff), and scSampler (maximin) across multiple real ST datasets (mouse ovary, MERFISH brain, human breast cancer, lung) and simulations, using three input representations: Principle Component Analysis (PCA) embeddings, spatial coordinates, and spatially smoothed embeddings. We show that expression-only designs capture global transcriptomic heterogeneity but distort tissue architecture by over-sampling high-variability regions and under-sampling homogeneous areas. Coordinate-only sampling restores tissue coverage but misses transcriptional extremes. A simple spatially aware extension, computing leverage scores from a randomized singular value decomposition (SVD) basis smoothed by a spatial weights matrix, strikes a favorable balance, recovering rare cell states while maintaining uniform tissue coverage and avoiding edge effects. Across robust Hausdorff distances, clustering stability (Adjusted Rand Index), PCA loading drift, and local cell-type mean squared error (MSE), spatially smoothed leverage scores match or outperform alternatives. These results motivate joint spatial-transcriptomic sketching objectives to enable fast, unbiased analyses of increasingly large ST datasets.

Lightning strikes are a rare but potentially devastating cause of injury, particularly in children. Clinical manifestations range from transient neurological disturbances and cardiac arrhythmias to severe burns, auditory damage, and multisystem trauma. Early recognition and prompt resuscitative measures are essential for improving outcomes, as lightning victims often have a high potential for successful resuscitation if treated rapidly. While musculoskeletal, cardiac, and neurological complications are commonly reported, genitourinary injuries, especially bladder trauma, are exceedingly uncommon and, in fact, underreported. We report an unusual and extremely rare clinical case of a lightning strike victim who presented with an isolated bladder injury.

The transition from lipid flat disks to vesicles under shock waves is essential for producing nanosized vesicles during sonication. We perform non-equilibrium molecular dynamics simulations to examine how shock waves interact with a lipid flat disk. The lipid disk consists of coarse-grained saturated phospholipid models and is approximately 30 nm in diameter in the gel phase. Shock waves are simulated using a piston-driven method, with piston speeds limited to 1.0 km s-1 or less. When a planar shock wave strikes, the disk's structural changes depend on the impact angle and the shock intensity. A disk with its rotation axis parallel to the shock direction decreases in thickness while maintaining its circular shape. In contrast, a disk with its rotation axis perpendicular to the shock wave direction undergoes radial compression in the shock propagation direction, causing a temporary increase in ellipticity. Behind the shock front, lipid molecules become disordered, as indicated by a reduction in the average P2 order parameter of lipid chains and the gel fraction in the disk. This suggests that shock waves can trigger the phase transition of lipid disks from the gel to the liquid phase. The shock's intensity and the resulting structural changes influence subsequent vesicle formation. During recovery, vesicles often form from the disk after exposure to higher-intensity shock waves or after a temporary anisotropic disk induced by a side impact. This highlights the importance of impact angle. These structural changes in lipid flat disks caused by shock waves may help in understanding and controlling vesicle sizes through sonication.

Behavioral lateralization, a consistent directional asymmetry in behavior, has been documented across many vertebrates, yet population-level evidence in snakes remains limited and debated. We examined ambush-posture laterality in the Chinese green tree pit viper (Trimeresurus stejnegeri), a nocturnal sit-and-wait predator, using a large dataset compiled from nocturnal field surveys (2014-2025) and verified citizen-science records from iNaturalist (2013-2025). Ambush-posture direction was classified from photographs using a standardized, anatomically referenced procedure based on head-aligned reference lines, and ambiguous cases were excluded unless observer classifications were concordant. We tested for population-level bias among sites using chi-squared tests and binomial logistic regression, and evaluated effects of age class and perching height. Across 283 observations from three localities, snakes at Yangmingshan exhibited a significant rightward bias in ambush posture (36 of 55 individuals = 65.5%; χ 2 = 5.25, df = 1, p = 0.022), whereas no population-level bias was detected at the other two localities. Neither age class nor perching height significantly affected laterality. These results provide the first evidence for site-specific population-level ambush-posture laterality in a snake and suggest that local ecological or demographic contexts, potentially linked to prey community composition and availability, may modulate the expression of laterality. Future work across additional populations and taxa, together with performance-based tests comparing capture success between left- versus right-curved strikes, will be essential for evaluating the adaptive significance of this pattern.

For vehicle driving scenarios in complex backgrounds, road sign detection faces challenges such as multi-scale targets, long-distances, and low-resolution. To address these challenges, a detection method based on an improved YOLO11n network is proposed. Firstly, to accommodate the multi-scale characteristics of the targets and improve the network's ability to detect low-resolution objects and details, a Multi-path Gated Aggregation (MGA) Module is proposed, achieving these objectives via multi-dimensional feature extraction. Secondly, the Neck is improved by designing a network structure that incorporates high-resolution information from the Backbone, thereby enhancing the detection capabilities for small and blurry targets. Finally, an enhanced Spatial Pyramid Pooling-Fast (SPPF) module is proposed, wherein a Group Convolution-Layer Normalization-SiLU structure is integrated across various stages of information passing. By fusing adjacent channel information, it effectively suppresses complex background noise across multiple scales and amplifies road marking features, which consequently boosts the model's discriminability for distant and obscured targets. Experimental results on a multi-type road sign dataset show that the improved model achieves an mAP@0.5 of 96.96%, which is 1.42% higher than the original model. The mAP@0.5-0.95 and Recall rates are 83.94% and 92.94%, respectively, while the inference speed remains at 134 FPS. Research demonstrates that via targeted modular designs, the proposed approach strikes a superior balance between detection accuracy and real-time efficiency. Consequently, it provides robust technical support for the reliable operation of intelligent vehicle perception systems under complex conditions.

An unintended consequence of wind energy generation is bat fatalities caused by wind turbine blade strikes. One potential approach to reduce collision risk is to use ultrasound to create an uncomfortable or disorienting airspace around wind turbine blades. Ultrasonic deterrents (UDs) have produced mixed results in experimental field studies at commercial wind energy facilities, with effectiveness varying by species and location. It is possible that some species can alter their normal echolocation characteristics to counter the signal of UDs. Our broad objective was to maximize the effectiveness of a UD by comparing changes in echolocation characteristics during three UD frequency emissions among species, between seasons, and between sex. We hypothesized that UD emissions with frequencies most similar to each species' echolocation characteristics would be more likely to alter the bats' echolocation, and bat responses would vary between seasons and sex for each species. We released wild-captured bats into a 60 m × 10 m × 4.4 m (length × width × height) flight cage located in San Marcos, Texas, USA, from July to October 2020 and March to May 2021 and monitored echolocation frequencies with ultrasonic microphones. We conducted trials on Brazilian free-tailed bats (Tadarida brasiliensis; n = 54), cave myotis (Myotis velifer; n = 44), red bats (Lasiurus blossevilli, Lasiurus borealis; n = 41), evening bats (Nycticeius humeralis; n = 32), and tricolored bats (Perimyotis subflavus; n = 8). We found that species with high-frequency echolocation calls altered their echolocation signatures more commonly during high-frequency UD emissions, whereas low-frequency bats altered their echolocation signatures more commonly during low-frequency UD emissions. Additionally, echolocation responses varied between seasons and sexes for several species. Variations in responses may be dependent on species migratory status, differences in mating behavior and mating season, hormonal differences between sexes and seasons, and/or constraints on echolocation adaptability. Our results offer insights into the variable effectiveness of UDs at reducing bat fatalities at wind turbines and provide information for potential adjustments to UDs for improved success.

The aims of this study were to (1) quantitatively compare various k-space interpolation-based simultaneous multislice (SMS) reconstruction algorithms, including linear GRAPPA and nonlinear, data-driven RAKI methods, and (2) provide an open-source toolbox for GPU-accelerated SMS reconstructions. For a single phantom, fully sampled k-space reference data and SMS-accelerated, RSMS, data were collected for RSMS factors of 2 through 5, with in-plane acceleration, Rip, added retrospectively. Slice-GRAPPA, split-slice-GRAPPA, readout-SENSE-GRAPPA, and their hyperparameter-tuned analogous deep learning-based RAKI reconstructions were performed at different combinations of RSMS and Rip factors. Performance of the reconstruction methods were compared quantitatively by testing for significant differences in whole-image SSIM and regions of interest-based measurements of coefficient of variation (CV). The number of epochs, hidden layer size, and the interaction between the two were statistically significant factors for a Type II ANOVA test with SSIM performance (p=0.00005, p=0.00687, and p=0.000281, respectively) for RAKI reconstructions with post hoc tests suggesting that 500 epochs, 3 hidden layers, and 128 neurons per layer strike an ideal balance of speed and performance for this dataset. CV testing through Kruskal-Wallis tests did not yield any significant differences between reconstruction algorithms at any given RSMS×Rip. Limited testing indicated that a RAKI method generally resulted in larger SSIM values at any net acceleration factor, (Rnet=RSMS×Rip), and all RAKI methods had a larger SSIM value than their respective GRAPPA counterparts at Rnet>4, with the exception of ROSR at RSMS=5 and Rnet=10, and SPSR at RSMS=2,Rip=5. The difference between GRAPPA and RAKI was typically large enough (ΔSSIM of >0.02) to be obvious at Rnet≥8. Slice-GRAPPA, slice-RAKI, or readout-SENSE-GRAPPA performed well for net accelerations Rnet≤6, and readout SENSE-RAKI or split-slice-RAKI performed well for Rnet≥8. Caution should be taken when using these generalizations as observations were dataset-specific and collected on a single vendor, coil array, pulse sequence, and phantom. They may, however, serve as a useful starting point for hyperparameter tuning. More experiments need to be conducted before these results can be translated into in vivo observations.

Diabetic retinopathy (DR) is the largest cause of permanent vision loss in the working-age population, making automated grading critical for timely therapeutic intervention. While recent deep learning algorithms have improved feature discrimination, modern state-of-the-art systems have two fundamental drawbacks. First, most models rely on standard Convolutional Neural Networks, which struggle to capture long-range relationships and lack semantic reasoning, resulting in visual findings that do not correlate with clinical knowledge. Second, present approaches often consider grading as a nominal classification or a pure ordinal regression task, failing to strike a compromise between high classification accuracy and severity-consistent predictions (Quadratic Weighted Kappa). To address these challenges, we propose Dual-SwinOrd, a novel framework that integrates a hierarchical Vision Transformer with a semantically guided dual-head mechanism. Specifically, we use a Swin Transformer backbone to extract hierarchical features, effectively capturing global retinal structures. To handle diverse lesion scales, we incorporate a Progressive Lesion-aware Kernel Attention (PLKA) module and a Semantic Prior Modulation (SPM) module guided by PubMedCLIP, bridging the gap between visual features and medical linguistic priors. In addition, we propose a Dual-Head learning strategy that decouples the optimization objective into two parallel streams: a Classification Head to maximize diagnostic accuracy and an Ordinal Regression Head (DPE) to enforce rank-consistency. This design effectively mitigates the trade-off between precision and ordinality. Extensive experiments on the APTOS 2019 and DDR datasets demonstrate that Dual-SwinOrd achieves state-of-the-art performance, yielding an Accuracy of 87.98% and a Quadratic Weighted Kappa (QWK) of 0.9370 on the APTOS 2019 dataset, as well as an Accuracy of 86.54% and a QWK of 0.9040 on the DDR dataset.

This study presents a new high-resolution GNSS-derived velocity field and the first internally consistent, segment-resolved block model for the Havran-Balıkesir Fault Zone (HBFZ) in western Anatolia. Inversion of the GNSS velocity field was performed using a dense network of 77 sites within a 3D elastic half-space framework to estimate fault slip rates and interseismic coupling. The results reveal that the HBFZ behaves as a kinematically heterogeneous fault system, with deformation systematically partitioned along strike. Block-modeling results indicate pronounced along-strike variations in interseismic coupling and slip-deficit accumulation. While the westernmost Havran segment is weakly coupled and accommodates limited accumulation, the Turplu and Gökçeyazı segments emerge as major strain-accumulation zones with high and laterally continuous slip-deficit rates. In particular, the Gökçeyazı segment exhibits slip-deficit rates of ~4-6 mm/yr and nearly two millennia of seismic quiescence, implying the potential for a future large-magnitude earthquake (Mw ~7.1-7.3). The strong agreement between GNSS-derived deformation patterns and independent geological and paleoseismological constraints suggests that this segment is currently in an advanced stage of the seismic cycle. These findings highlight the importance of segment-scale geodetic observations for seismic hazard assessment in northwestern Anatolia.

The present study plays a crucial role in enhancing the safety and perceived quality of life for users of bone-anchored prostheses. It focuses on developing an innovative protective component using various metallic materials to identify and mitigate potential risks during use, thereby reducing the likelihood of sudden fracture and maintaining the system's structural integrity. The protective element is manufactured from Ti6Al4V alloy, while the safety pin is made from ductile cast iron. This combination allows controlled fracture of the protective element without complete separation of the prosthesis, thereby reducing the risk of falls. To optimise the numerical analysis, a 3D model of the prosthesis and its protective component was created using SolidWorks software. Loading conditions were simulated to reflect two critical phases of the gait cycle: heel strike and toe-off. The analysis revealed that the highest stress occurred during the toe-off phase, reaching 248 MPa, with a safety factor of 1.6, demonstrating the design's ability to prevent sudden failure. Tensile testing showed that ductile cast iron is a suitable material for the safety component. Although Ti6Al4V alloy surpasses it in tensile strength, ductile cast iron's lower strength ensures a controlled and less catastrophic failure under excessive loading. Numerical results confirmed a high safety factor for the protective system, indicating improved reliability and mechanical load resistance. This study presents a novel approach aimed at improving the safety of bone-anchored prostheses by minimising injury risks due to mechanical overload, ultimately enhancing user comfort and confidence.

Systemic sclerosis (SSc) is a severe autoimmune disease characterised by progressive fibrosis driven by fibroblast activation. Primary cilia, key hubs for profibrotic signalling, are markedly shortened in SSc fibroblasts, but the mechanisms underlying this phenotype remain unclear. This study aimed to define the signalling pathways responsible for primary cilia shortening and fibroblast activation in SSc. Primary dermal fibroblasts from SSc patients and healthy controls were analysed for cilia incidence and length by immunofluorescence, profibrotic marker expression by qPCR, and contractility using gel contraction assays. Cells were treated with TGFβ1 and pharmacological inhibitors targeting AURKA, HDAC6, ROCK2, and Smad3 signalling. CAV1-silenced fibroblasts were used as an in vitro model of SSc. Maintenance of the constitutively short primary cilia phenotype in SSc fibroblasts did not require active TGFβ signalling. However, TGFβ1 induced reversible cilia shortening in healthy fibroblasts and further shortened cilia in SSc fibroblasts to a similar final length, mediated by Rho/ROCK2 rather than canonical Smad3-dependent signalling. Constitutive cilia shortening in SSc was driven by aberrant AURKA activity upstream of HDAC6, promoting ciliary disassembly. Pharmacological inhibition of AURKA or HDAC6 selectively elongated cilia in SSc fibroblasts, reduced profibrotic marker expression, and abrogated fibroblast contractility, but it did not affect healthy control cells. CAV1-silenced fibroblasts similarly exhibited constitutive cilia shortening that was reversed by AURKA inhibition without affecting healthy cells. The AURKA/HDAC6 axis maintains short primary cilia and promotes fibroblast activation in SSc. These findings reveal a mechanistic link between cilia morphology and fibrosis and identify AURKA as a potential therapeutic target for SSc-associated tissue remodelling.

Flatfeet involve a collapse of the medial longitudinal arch, hindfoot valgus, and forefoot abduction. Flexible flatfoot is the most common type and can often be corrected with physiotherapy or orthotics. While some individuals remain asymptomatic, others develop symptoms for reasons that are not fully understood. This cross-sectional study compared plantar pressure distributions in 16 adults with asymptomatic and 16 with symptomatic flexible flatfeet (FPI-6 > 6; navicular drop > 5 mm), using a resistive-sensor-equipped pressure plate during walking and heel-strike running. During walking, symptomatic participants showed significantly higher total and peak forces at metatarsal 5 (p ≤ 0.003), and the midfoot (p ≤ 0.02146). The medial heel had significantly lower peak force (p = 0.00147), and metatarsal 4 showed higher peak force (p = 0.02539). Force ratios indicated a more lateralized pressure distribution in the symptomatic group. During heel-strike running, the symptomatic group exhibited higher total and peak forces at the fifth metatarsal, the midfoot, and the first metatarsal, with shorter time to peak force in the midfoot and the medial part of the heel. No significant ratio differences were found during running. Symptomatic individuals adopted a lateralized pressure distribution pattern, contrasting the traditional expectation of medial overload in flatfoot conditions.