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Remote injury assessment during natural disasters poses major challenges for healthcare providers due to the inaccessibility of disaster sites. This study aimed to explore the feasibility of using artificial intelligence (AI) techniques for rapid assessment of traumatic injuries based on gait analysis.
Methods
We conducted an AI-based investigation using a dataset of 4500 gait images across 3 species: humans, dogs, and rabbits. Each image was categorized as either normal or limping. A deep learning model, YOLOv5—a state-of-the-art object detection algorithm—was trained to identify and classify limping gait patterns from normal ones. Model performance was evaluated through repeated experiments and statistical validation.
Results
The YOLOv5 model demonstrated high accuracy in distinguishing between normal and limp gaits across species. Quantitative performance metrics confirmed the model’s reliability, and qualitative case studies highlighted its potential application in remote, fast traumatic assessment scenarios.
Conclusions
The use of AI, particularly deep convolutional neural networks like YOLOv5, shows promise in enabling fast, remote traumatic injury assessment during disaster response. This approach could assist healthcare professionals in identifying injury risks when physical access to patients is restricted, thereby improving triage efficiency and early intervention.
As cities like Beijing expand rapidly, green and blue spaces (GBS)—essential for ecosystem services (ESs) such as clean air, flood control, and recreation—are increasingly threatened. This 20-year study examines how urban expansion and policy interventions have shaped Beijing’s GBS. While green initiatives have increased natural areas, unchecked urban sprawl has fragmented these spaces, reducing their environmental benefits. Satellite data and urban planning analyses underscore a key lesson: maintaining well-connected natural zones is critical for urban resilience. These findings are broadly applicable for rapidly growing cities globally, urging urban planners to integrate ecological conservation with development, and to safeguard healthy environments and vibrant communities.
Technical Summary
This study quantifies the spatiotemporal dynamics of urban GBS in Beijing, evaluating their essential role in delivering ESs and strengthening urban resilience. Although China has achieved substantial progress in urban greening, the ecological impacts of rapid urbanization on GBS configuration and connectivity have not been comprehensively quantified. Using an integrated analytical framework combining principal component analysis and multiple linear regression, we reveal how urban development strategies have shaped GBS dynamics over two decades. A spatially explicit analysis, utilizing geographically weighted regression, further elucidates the heterogeneous relationships among the normalized difference vegetation index, human footprint index, and ESs delivery capacity. Notably, socioeconomic incentives and green infrastructure governance—especially objective indicators such as forest, garden, and greenspace area—have effectively driven GBS expansion. However, urban expansion has led to pronounced fragmentation of peri-urban GBS, suggesting potential degradation of their ecosystem service support functions. These findings emphasize the need for adaptive GBS management strategies that balance ecological conservation with sustainable urban growth in rapidly developing cities.
Social Media Summary
Urban growth fragments green and blue spaces, reducing vital ecosystem services. Balancing conservation with development is essential for sustainable cities.
A dual-beam platform is developed for all-optical Thomson/Compton scattering, with versatile parameter tuning capabilities including electron energy, radiation energy, radiation polarization, etc. By integrating this platform with a 200 TW Ti:sapphire laser system, we demonstrate the generation of inverse Compton scattering X-/gamma-rays with tunable energies ranging from tens of keV to MeV. The polarization of X-/gamma-rays is manipulated by adjusting the polarization of the scattering laser. In the near future, by combining this platform with multi-PW laser facilities, our goal is to explore the transition from nonlinear Thomson scattering to nonlinear Compton scattering, ultimately verifying theories related to strong-field quantum electrodynamics effects induced by extreme scattering.
With the widespread use of high-fat diets (HFD) in aquaculture, the adverse effects of HFD on farmed fish are becoming increasingly apparent. Creatine has shown potential as a green feed additive in farmed fish; however, the potential of dietary creatine to attenuate adverse effects caused by high-fat diets remains poorly understood. To address such gaps, this study was conducted to investigate the mitigating effect of dietary creatine on HFD-induced disturbance on growth performance, hepatic lipid metabolism, intestinal health and muscle quality of juvenile largemouth bass. Three diets were formulated: a control diet (10·20 % lipid), a high-fat diet (HFD, 18·31 % lipid) and HFD with 2 % creatine (HFD + creatine). Juvenile largemouth bass (3·73 (sem 0·01) g) were randomly assigned to three diets for 10 weeks. The key findings were as follows: (1) the expression of muscle growth-related genes and proteins was stimulated by dietary creatine, which contributes to ameliorate the adverse effects of HFD on growth performance; (2) dietary creatine alleviates HFD-induced adverse effects on intestinal health by improving intestinal health, which also enhances feed utilisation efficiency; (3) dietary creatine causes excessive lipid deposition, mainly via lipolysis and β-oxidation. Notably, this study also reveals a previously undisclosed effect of creatine supplementation on improving muscle quality. Together, for the first time from a comprehensive multiorgan or tissue perspective, our study provides a feasible approach for developing appropriate nutritional strategies to alleviate the adverse effects of HFD on farmed fish, based on creatine supplementation.
Thomassen’s chord conjecture from 1976 states that every longest cycle in a $3$-connected graph has a chord. The circumference $c(G)$ and induced circumference $c'(G)$ of a graph G are the length of its longest cycles and the length of its longest chordless cycles, respectively. Harvey [‘A cycle of maximum order in a graph of high minimum degree has a chord’, Electron. J. Combin.24(4) (2017), Article no. 4.33, 8 pages] proposed the stronger conjecture: every $2$-connected graph G with minimum degree at least $3$ has $c(G)\geq c'(G)+2$. This conjecture implies Thomassen’s chord conjecture. We observe that wheels are the unique Hamiltonian graphs for which the circumference and the induced circumference differ by exactly one. Thus, we need only consider non-Hamiltonian graphs for Harvey’s conjecture. We propose a conjecture involving wheels that is equivalent to Harvey’s conjecture on non-Hamiltonian graphs. A graph is $\ell $-holed if all its holes have length exactly $\ell $. We prove that Harvey’s conjecture and hence also Thomassen’s conjecture hold for $\ell $-holed graphs and graphs with a small induced circumference.
The betatron radiation source features a micrometer-scale source size, a femtosecond-scale pulse duration, milliradian-level divergence angles and a broad spectrum exceeding tens of keV. It is conducive to the high-contrast imaging of minute structures and for investigating interdisciplinary ultrafast processes. In this study, we present a betatron X-ray source derived from a high-charge, high-energy electron beam through a laser wakefield accelerator driven by the 1 PW/0.1 Hz laser system at the Shanghai Superintense Ultrafast Laser Facility (SULF). The critical energy of the betatron X-ray source is 22 ± 5 keV. The maximum X-ray flux reaches up to 4 × 109 photons for each shot in the spectral range of 5–30 keV. Correspondingly, the experiment demonstrates a peak brightness of 1.0 × 1023 photons·s−1·mm−2·mrad−2·0.1%BW−1, comparable to those demonstrated by third-generation synchrotron light sources. In addition, the imaging capability of the betatron X-ray source is validated. This study lays the foundation for future imaging applications.
The effect of the polarizations of two counter-propagating relativistic laser pulses interacting with subwavelength thin solid-density foil is investigated. Three-dimensional particle-in-cell simulations and analytical modelling show that the interaction and resulting transverse instability depend strongly on the polarization directions as well as the intensity distribution of the resultant light field in the foil. The left- and right-handed circularly polarized laser pair with the same phase at the common focal spot in the ultrathin foil leads to the strongest distortion of the foil. The fastest growing mode and maximum growth rate depend mainly on the laser intensity. For all polarization and phase-difference combinations, the instability is weakest when the two laser pulses are exactly out of phase at the common focusing point in the foil.
Human activity recognition (HAR) is a vital component of human–robot collaboration. Recognizing the operational elements involved in an operator’s task is essential for realizing this vision, and HAR plays a key role in achieving this. However, recognizing human activity in an industrial setting differs from recognizing daily living activities. An operator’s activity must be divided into fine elements to ensure efficient task completion. Despite this, there is relatively little related research in the literature. This study aims to develop machine learning models to classify the sequential movement elements of a task. To illustrate this, three logistic operations in an integrated circuit (IC) design house were studied, with participants wearing 13 inertial measurement units manufactured by XSENS to mimic the tasks. The kinematics data were collected to develop the machine learning models. The time series data preprocessing involved applying two normalization methods and three different window lengths. Eleven features were extracted from the processed data to train the classification models. Model validation was carried out using the subject-independent method, with data from three participants excluded from the training dataset. The results indicate that the developed model can efficiently classify operational elements when the operator performs the activity accurately. However, incorrect classifications occurred when the operator missed an operation or awkwardly performed the task. RGB video clips helped identify these misclassifications, which can be used by supervisors for training purposes or by industrial engineers for work improvement.
Mastitis in dairy cows is an important factor restricting the healthy development of dairy industry. Natural extracts have become a research hotspot to alleviate and prevent diseases because of their unique properties. The purpose of this study was to investigate the effects of resveratrol (RES) on the mitochondrial biosynthesis, antioxidation, and anti-inflammatory in bovine mammary epithelial cells (BMECs) and its mechanism involved. Blood samples were collected from six healthy cows and six mastitis affected cows, respectively, and lipopolysaccharide (LPS) was used to treat BMECs to construct inflammation models, gene interference is achieved by transfection. The results showed that messenger RNA (mRNA) expression of peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) was down-regulated and mitochondrial biogenesis-related gene expression was disrupted in the blood of mastitis cows and LPS-induced BMECs. RES is the best active substance to activate PGC-1α. The addition of RES can effectively alleviate the production of BMECs reactive oxygen species (ROS) and mitochondrial damage induced by LPS, and improve the antioxidation and anti-inflammatory ability, while the alleviation effect of RES is inhibited after interfering with protein kinase AMP-activated catalytic subunit α 1 (PRKAA1). In summary, our study emphasizes that PRKAA1 is a key gene mediating the activation of PGC-1α by RES, which regulates mitochondrial biosynthesis, inhibits ROS release, attenuates mitochondrial damage, and improves mitochondrial antioxidant capacity through the activation of PGC-1α by PRKAA1, thus attenuating the inflammatory response in BMECs.
While active back-support exoskeletons can reduce mechanical loading of the spine, current designs include only one pair of actuated hip joints combined with a rigid structure between the pelvis and trunk attachments, restricting lumbar flexion and consequently intended lifting behavior. This study presents a novel active exoskeleton including actuated lumbar and hip joints as well as subject-specific exoskeleton control based on a real-time active low-back moment estimation. We evaluated the effect of exoskeleton support with different lumbar-to-hip (L/H) support ratios on spine loading, lumbar kinematics, and back muscle electromyography (EMG). Eight healthy males lifted 15 kg loads using three techniques without exoskeleton (NOEXO) and with exoskeleton: minimal impedance mode (MINIMP), L/H support ratio in line with a typical L/H net moment ratio (R0.8), lower (R0.5) and higher (R2.0) L/H support ratio than R0.8, and a mechanically fixed lumbar joint (LF; simulating hip joint-only exoskeleton designs).
EMG-driven musculoskeletal model results indicated that R0.8 and R0.5 yielded significant reductions in spinal loading (4–11%, p < .004) across techniques when compared to MINIMP, through reducing active moments (14–30%) while not affecting lumbar flexion and passive moments. R2.0 and LF significantly reduced spinal loading (8–17%, p < .001; 22–26%, p < .001, respectively), however significantly restricted lumbar flexion (3–18%, 24–27%, respectively) and the associated passive moments.
An L/H support ratio in line with a typical L/H net moment ratio reduces spinal loading, while allowing normal lifting behavior. High L/H support ratios (e.g., in hip joint-only exoskeleton designs) yield reductions in spinal loading, however, restrict lifting behavior, typically perceived as hindrance.
We consider the problem of parameter estimation for the superposition of square-root diffusions. We first derive the explicit formulas for the moments and auto-covariances based on which we develop our moment estimators. We then establish a central limit theorem for the estimators with the explicit formulas for the asymptotic covariance matrix. Finally, we conduct numerical experiments to validate our method.
Growing evidence indicates a link between diet and depression risk. We aimed to examine the association between an inflammatory diet index and depression utilising extensive data from UK biobank cohort. The energy-adjusted dietary inflammation index (E-DII) was calculated to quantify the potential of daily diet, with twenty-seven food parameters utilised. The E-DII scores were classified into two categories (low v. high) based on median value. To mitigate bias and ensure comparability of participant characteristics, propensity score matching was employed. To ascertain the robustness of these associations, sensitivity analyses were conducted. Subgroup analyses were performed to evaluate the consistency of these associations within different subpopulations. Totally, 152 853 participants entered the primary analyses with a mean age of 56·11 (sd 7·98) years. Employing both univariate and multivariate logistic regression models, adjustments were made for varying degrees of confounding factors (socio-demographics, lifestyle factors, common chronic medical conditions including type 2 diabetes and hypertension). Results consistently revealed a noteworthy positive correlation between E-DII and depression. In the context of propensity score matching, participants displaying higher E-DII scores exhibited an increased likelihood of experiencing incident depression (OR = 1·12, 95 % CI: 1·05, 1·19; P = 0·000316). Subgroup analysis results demonstrated variations in these associations across diverse subpopulations. The E-value for the point-estimate OR calculated from the propensity score matching dataset was 1·48. Excluding individuals diagnosed with type 2 diabetes or hypertension, the findings consistently aligned with the positive association in the primary analysis. These findings suggested that consumption of a diet with higher pro-inflammatory potential might associated with an increase of future depression risk.
The spatio-temporal scales, as well as a comprehensive self-sustained mechanism of the reattachment unsteadiness in shock wave/boundary layer interaction, are investigated in this study. Direct numerical simulations reveal that the reattachment unsteadiness of a Mach 7.7 laminar inflow causes over $26\,\%$ variation in wall friction and up to $20\,\%$ fluctuation in heat flux at the reattachment of the separation bubble. A statistical approach, based on the local reattachment upstream movement, is proposed to identify the spanwise and temporal scales of reattachment unsteadiness. It is found that two different types, i.e. self-induced and random processes, dominate different regions of reattachment. A self-sustained mechanism is proposed to comprehend the reattachment unsteadiness in the self-induced region. The intrinsic instability of the separation bubble transports vorticity downstream, resulting in an inhomogeneous reattachment line, which gives rise to baroclinic production of quasi-streamwise vortices. The pairing of these vortices initiates high-speed streaks and shifts the reattachment line upstream. Ultimately, viscosity dissipates the vortices, triggering instability and a new cycle of reattachment unsteadiness. The temporal scale and maximum vorticity are estimated with the self-sustained mechanism via order-of-magnitude analysis of the enstrophy. The advection speed of friction, derived from the assumption of coherent structures advecting with a Blasius-type boundary layer, aligns with the numerical findings.
China has been undergoing a rapid nutrition transition in the past few decades. This review aims to characterise commonly reported dietary patterns in Chinese populations and their associations with health outcomes.
Design:
We searched PubMed, Embase and CNKI from inception to June 2020 to identify observational studies reporting dietary patterns or the associations between dietary patterns and health outcomes. Information regarding dietary patterns, their association with health outcomes and other related items was collected.
Setting:
Chinese population and Chinese immigrants.
Participants:
Not applicable.
Results:
Results from 130 studies with over 900 000 participants were included. Six dietary patterns were identified: traditional whole-grain diet (Traditional WG), traditional non-whole-grain diet (Traditional NWG), plant-based diet (Plant-based), animal food diet (Animal-food), Western energy-dense diet (Western) and other unclassified diets (Unclassified). The Plant-based diet was associated with a reduced risk of CVD and cancer from prospective studies, reduced risk of diabetes, hypertension, cognitive impairment and depressive symptoms from all study designs. The Traditional WG diet was associated with a reduced risk of diabetes and hypertension. Animal-food diet is associated with a range of metabolic diseases, and Western diet was associated with increased risks of obesity and depressive symptoms.
Conclusion:
Multiple dietary patterns identified reflect the diversity and transitioning of the Chinese diet. A healthy Chinese diet, comprising both the Traditional WG and Plant-based diets, was associated with reduced risks of specific undesirable health outcomes. Promoting this healthy diet will improve public health among the Chinese populations.
There is a clear demand for innovative therapeutics for bipolar disorder (BD).
Methods
We integrated the largest BD genome-wide association study (GWAS) dataset (NCase = 41 917, NControl = 371 549) with protein quantitative trait loci from brain, cerebrospinal fluid, and plasma. Using a range of integrative analyses, including Mendelian randomization (MR), Steiger filter analysis, Bayesian colocalization, and phenome-wide MR analysis, we prioritized novel drug targets for BD. Additionally, we incorporated data from the UK Biobank (NCase = 1064, NControl = 365 476) and the FinnGen study (NCase = 7006, NControl = 329 192) for robust biological validation.
Results
Through MR analysis, we found that in the brain, downregulation of DNM3, MCTP1, ABCB8 and elevation of DFNA5 and PDF were risk factors for BD. In cerebrospinal fluid, increased BD risk was associated with increased levels of FRZB, AGRP, and IL36A and decreased CTSF and LRP8. Plasma analysis revealed that decreased LMAN2L, CX3CL1, PI3, NCAM1, and TIMP4 correlated with increased BD risk, but ITIH1 did not. All these proteins passed Steiger filtering, and Bayesian colocalization confirmed that 12 proteins were colocalized with BD. Phenome-wide MR analysis revealed no significant side effects for potential drug targets, except for LRP8. External validation further underscored the concordance between the primary and validation cohorts, confirming MCTP1, DNM3, PDF, CTSF, AGRP, FRZB, LMAN2L, NCAM1, and TIMP4 are intriguing targets for BD.
Conclusions
Our study identified druggable proteins for BD, including MCTP1, DNM3, and PDF in the brain; CTSF, AGRP, and FRZB in cerebrospinal fluid; and LMAN2L, NCAM1, and TIMP4 in plasma, delineating promising avenues to development of novel therapies.
In view of the fact that the current research on active and passive rehabilitation training of lower limbs is mainly based on the analysis of exoskeleton prototype and the lack of analysis of the actual movement law of limbs, the human-machine coupling dynamic characteristics for active rehabilitation training of lower limbs are studied. In this paper, the forward and inverse kinematics are solved on the basis of innovatively integrating the lower limb and rehabilitation prototype into a human-machine integration system and equivalent to a five-bar mechanism. According to the constraint relationship of hip joint, knee joint and ankle joint, the Lagrange dynamic equation and simulation model of five-bar mechanism under the constraint of human physiological joint motion are constructed, and the simulation problem of closed-loop five-bar mechanism is solved. The joint angle experimental system was built to carry out rehabilitation training experiments to analyze the relationship between lower limb error and height, weight and BMI, and then, a personalized training planning method suitable for people with different lower limb sizes was proposed. The reliability of the method is proved by experiments. Therefore, we can obtain the law of limb movement on the basis of traditional rehabilitation training, appropriately reduce the training speed or reduce the man-machine position distance and reduce the training speed or increase the man-machine distance to reduce the error to obtain the range of motion angle closer to the theory of hip joint and knee joint respectively, so as to achieve better rehabilitation.
The asymptotic behavior of the Jaccard index in G(n, p), the classical Erdös–Rényi random graph model, is studied as n goes to infinity. We first derive the asymptotic distribution of the Jaccard index of any pair of distinct vertices, as well as the first two moments of this index. Then the average of the Jaccard indices over all vertex pairs in G(n, p) is shown to be asymptotically normal under an additional mild condition that $np\to\infty$ and $n^2(1-p)\to\infty$.
The laboratory generation and diagnosis of uniform near-critical-density (NCD) plasmas play critical roles in various studies and applications, such as fusion science, high energy density physics, astrophysics as well as relativistic electron beam generation. Here we successfully generated the quasistatic NCD plasma sample by heating a low-density tri-cellulose acetate (TCA) foam with the high-power-laser-driven hohlraum radiation. The temperature of the hohlraum is determined to be 20 eV by analyzing the spectra obtained with the transmission grating spectrometer. The single-order diffraction grating was employed to eliminate the high-order disturbance. The temperature of the heated foam is determined to be T = 16.8 ± 1.1 eV by analyzing the high-resolution spectra obtained with a flat-field grating spectrometer. The electron density of the heated foam is about under the reasonable assumption of constant mass density.
Sepiolite-based composites have great potential for application as flame-retardant and thermal-insulation material but their application and development are limited by poor mechanical properties. The objective of the present study was to combine polyvinyl alcohol (PVA) and 3-aminopropyltriethoxysilane (KH-550) with sepiolite (Sep) to improve its aerogel strength. A universal testing machine, thermogravimetry, and microcalorimetry were used to investigate the mechanical properties, thermal-stability, and flame-retardant properties, respectively, of aerogels. The results indicated that KH-550 can enhance effectively the mechanical properties and flame retardancy of aerogels. The compressive modulus of PVA/Sep vs KH-550/PVA/Sep aerogel was 209.28 vs. 474.43 kPa, the LOI index changed from 26.4 to 30.4%. The porosity of the aerogels was > 96% and the density was < 0.05 g/cm3. The thermal conductivity remained at between 0.0340 and 0.0390 W/(m·K), and the aerogel could recover to > 85% after a 50% compressive deformation. These data indicated that Sep-based aerogel would act as a flame retardant and a thermal insulating material with excellent mechanical properties.
The Lawson criterion for proton-boron (p-11B) thermonuclear fusion is substantially higher than that for deuterium-tritium (DT) because the fusion cross section is lower and peaks at higher ion energies. The Maxwellian averaged p-11B reactivity peaks at several hundred keV, where bremsstrahlung radiation emission may dominate over fusion reactions if electrons and ions are in thermal equilibrium and the losses are unrestricted. Nonequilibrium burn has often been suggested to realize the benefits of this aneutronic reaction, but the predominance of elastic scattering over fusion reactivity makes this difficult to achieve. The development of ultrashort pulse lasers (USPL) has opened new possibilities for initiating nonequilibrium thermonuclear burns and significant numbers of p-11B alpha particles have been reported from several experiments. We present an analysis that shows that these significant alpha yields are the result of beam fusion reactions that do not scale to net energy gain. We further find that the yields can be explained by experimental parameters and recently updated cross sections such that a postulated avalanche mechanism is not required. We use this analysis to understand the underlying physics of USPL-driven nonequilibrium fusion reactions and whether they can be used to initiate fusion burns. We conclude by outlining a path to increasing the p-11B reactivity towards the goal of achieving ignition and describing the design principles that we will use to develop a computational point design.