Spatial relationships among offender, knife, and victim during slashing attacks: implications for crime scene reconstruction.

BACKGROUND: The offender-victim spatial relationship is crucial in reconstructing a crime scene. The study aims to evaluate the spatial relationship of performing slashing attacks on a dummy using a Chinese kitchen knife, and thus to establish a scientific basis for crime scene reconstruction. METHODS: Twenty-four participants (12 males and 12 females) slashed a dummy's neck or chest using a kitchen knife, and the kinematic data were obtained using a three-dimensional motion capture system. The spatial relationships among offender, knife, and victim during slashing attacks were analyzed. RESULTS: Slashing distance and occupancy area are significantly influenced by gender (all P < 0.05), with males having higher values than females. Body parts significantly influence bevel angle, offender and victim azimuth angles, slashing distance, relative slashing distance, and occupancy area (all P < 0.01), with slashing the chest resulting in larger values than slashing the neck. CONCLUSION: Gender and body position significantly influence the spatial relationships of slashing action. Our data indicate that males stand farther away and occupy a larger area during slashing attacks. When the chest is slashed, the wound orientation is more diagonal, the offender's standing position and slashing distance are farther, and the occupancy area is larger compared to the neck. The findings could help identify the spatial relationships among offender, knife, and victim, providing a scientific basis for criminal investigations and court trials.

The Neglected Role of Asphaltene in the Synthesis of Mesophase Pitch.

This study investigates the synthesis of mesophase pitch using low-cost fluid catalytic cracking (FCC) slurry and waste fluid asphaltene (WFA) as raw materials through the co-carbonization method. The resulting mesophase pitch product and its formation mechanism were thoroughly analyzed. Various characterization techniques, including polarizing microscopy, softening point measurement, Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), were employed to characterize and analyze the properties and structure of the mesophase pitch. The experimental results demonstrate that the optimal optical texture of the mesophase product is achieved under specific reaction conditions, including a temperature of 420 °C, pressure of 1 MPa, reaction time of 6 h, and the addition of 2% asphaltene. It was observed that a small amount of asphaltene contributes to the formation of mesophase pitch spheres, facilitating the development of the mesophase. However, excessive content of asphaltene may cover the surface of the mesophase spheres, impeding the contact between them and consequently compromising the optical texture of the mesophase pitch product. Furthermore, the inclusion of asphaltene promotes polymerization reactions in the system, leading to an increase in the average molecular weight of the mesophase pitch. Notably, when the amount of asphaltene added is 2%, the mesophase pitch demonstrates the lowest ID/IG value, indicating superior molecular orientation and larger graphite-like microcrystals. Additionally, researchers found that at this asphaltene concentration, the mesophase pitch exhibits the highest degree of order, as evidenced by the maximum diffraction angle (2θ) and stacking height (Lc) values, and the minimum d002 value. Moreover, the addition of asphaltene enhances the yield and aromaticity of the mesophase pitch and significantly improves the thermal stability of the resulting product.

The potential impact of polymorphisms in METTL3 gene on knee osteoarthritis susceptibility.

Objective: This study was aimed to explore the correlation between METTL3 polymorphisms and susceptibility to knee osteoarthritis (KOA). Methods: The relationship of five single nucleotide polymorphisms (SNPs) in the METTL3 gene with the susceptibility of KOA was analyzed through multinomial logistic regression analysis in this a case-control study. Genotyping was performed on 228 KOA patients and 252 unaffected individuals from South China based on the TaqMan method. The MDR software (version 3.0.2) was utilized for the analysis of SNP interactions. Results: Out of the five SNPs examined, the T > G change in the METTL3 gene at the rs1061026 locus increased the risk of KOA, while rs1139130 A > G and rs1263802 C > T variants were found to be linked with a reduced risk of developing KOA with statistical significance. The rs1061027 A > C and rs1263801 C > G variants did not show significant association (p＞0.05). The rs1061026 TG/GG genotype showed a significant correlation with an increased risk of KOA in the following subgroups: the males, individuals with a BMI ranging from 24 to 28, smokers, those who were not engaged in physical exercise (PE), patients who had experienced KOA symptoms for eight years or longer, and those without a family history of the disease or reported swelling. On the other hand, the rs1139130 AG/GG genotype demonstrated a protective effect against KOA among the females, individuals with a BMI greater than or equal to 24, a unilateral KOA, or a KOA duration of 8 years or less, non-smokers, non-alcohol drinkers, those who were not engaged in PE, and those who had no injury or family history, or no experience of knee swelling. Additionally, it was observed that the rs1263802 CT/TT genotypes showed a protective effect among patients without a history of injury. Furthermore, individuals with the haplotypes GAT, GGC, TAT, and TGC were found to have a significantly lower susceptibility to KOA compared to the reference haplotype TAC. Conclusions: The METTL3 gene variant rs1061026 could increase the risk of KOA, whereas the variants of rs1139130 as well as rs1263802 might exert a protective effect against KOA. These variants could potentially function as susceptibility markers for KOA among the population from South China.

Giant Magnon-Polaron Anomalies in Spin Seebeck Effect in Double Umbrella-Structured Tb_{3}Fe_{5}O_{12} Films.

We report a giant hysteretic spin Seebeck effect (SSE) anomaly with a sign reversal at magnetic fields much stronger than the coercive field in a (001)-oriented Tb_{3}Fe_{5}O_{12} film. The high-field SSE enhancement reaches 4200% at approximately 105 K over its weak-field value and presents a nonmonotonic dependence on temperature. The unexpected high-field hysteresis of SSE is found to be associated with a magnetic transition of double-umbrella spin texture in TbIG. Nearly parallel dispersion curves of magnons and acoustic phonons around this neoteric transition are supported by theoretical calculations, leading to a high density of field-tuned magnon polarons and consequently an extraordinarily large SSE. Our study provides insight into the evolution of magnon dispersions of double-umbrella TbIG and could potentially boost the efficiency of magnon-polarons SSE devices.

High-Performance Engineered Composites Biofabrication Using Fungi.

Various natural polymers offer sustainable alternatives to petroleum-based adhesives, enabling the creation of high-performance engineered materials. However, additional chemical modifications and complicated manufacturing procedures remain unavoidable. Here, a sustainable high-performance engineered composite that benefits from bonding strategies with multiple energy dissipation mechanisms dominated by chemical adhesion and mechanical interlocking is demonstrated via the fungal smart creative platform. Chemical adhesion is predominantly facilitated by the extracellular polymeric substrates and glycosylated proteins present in the fungal outer cell walls. The dynamic feature of non-covalent interactions represented by hydrogen bonding endows the composite with extensive unique properties including healing, recyclability, and scalable manufacturing. Mechanical interlocking involves multiple mycelial networks (elastic modulus of 2.8 GPa) binding substrates, and the fungal inner wall skeleton composed of chitin and ß-glucan imparts product stability. The physicochemical properties of composite (modulus of elasticity of 1455.3 MPa, internal bond strength of 0.55 MPa, hardness of 82.8, and contact angle of 110.2°) are comparable or even superior to those of engineered lignocellulosic materials created using petroleum-based polymers or bioadhesives. High-performance composite biofabrication using fungi may inspire the creation of other sustainable engineered materials with the assistance of the extraordinary capabilities of living organisms.

A multi-view convolutional neural network method combining attention mechanism for diagnosing autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition whose current psychiatric diagnostic process is subjective and behavior-based. In contrast, functional magnetic resonance imaging (fMRI) can objectively measure brain activity and is useful for identifying brain disorders. However, the ASD diagnostic models employed to date have not reached satisfactory levels of accuracy. This study proposes the use of MAACNN, a method that utilizes multi-view convolutional neural networks (CNNs) in conjunction with attention mechanisms for identifying ASD in multi-scale fMRI. The proposed algorithm effectively combines unsupervised and supervised learning. In the initial stage, we employ stacked denoising autoencoders, an unsupervised learning method for feature extraction, which provides different nodes to adapt to multi-scale data. In the subsequent stage, we perform supervised learning by employing multi-view CNNs for classification and obtain the final results. Finally, multi-scale data fusion is achieved by using the attention fusion mechanism. The ABIDE dataset is used to evaluate the model we proposed., and the experimental results show that MAACNN achieves superior performance with 75.12% accuracy and 0.79 AUC on ABIDE-I, and 72.88% accuracy and 0.76 AUC on ABIDE-II. The proposed method significantly contributes to the clinical diagnosis of ASD.

Experiment Investigation of the Compression Behaviors of Nickel-Coated Hybrid Lattice Structure with Enhanced Mechanical Properties.

The lattice metamaterial has attracted extensive attention due to its excellent specific strength, energy absorption capacity, and strong designability of the cell structure. This paper aims to explore the functional nickel plating on the basis of biomimetic-designed lattice structures, in order to achieve higher stiffness, strength, and energy absorption characteristics. Two typical structures, the body-centered cubic (BCC) lattice and the bioinspired hierarchical circular lattice (HCirC), were considered. The BCC and HCirC lattice templates were prepared based on DLP (digital light processing) 3D printing. Based on this, chemical plating, as well as the composite plating of chemical plating followed by electroplating, was carried out to prepare the corresponding nickel-plated lattice structures. The mechanical properties and deformation failure mechanisms of the resin-based lattice, chemically plated lattice, and composite electroplated lattice structures were studied by using compression experiments. The results show that the metal coating can significantly improve the mechanical properties and energy absorption capacity of microlattices. For example, for the HCirC structure with the loading direction along the x-axis, the specific strength, specific stiffness, and specific energy absorption after composite electroplating increased by 546.9%, 120.7%, and 2113.8%, respectively. The shell-core structure formed through composite electroplating is the main factor for improving the mechanical properties of the lattice metamaterial. In addition, the functional nickel plating based on biomimetic structure design can further enhance the improvement space of mechanical performance. The research in this paper provides insights for exploring lighter and stronger lattice metamaterials and their multifunctional applications.

Multimodal Autism Spectrum Disorder Diagnosis Method Based on DeepGCN.

Multimodal data play an important role in the diagnosis of brain diseases. This study constructs a whole-brain functional connectivity network based on functional MRI data, uses non-imaging data with demographic information to complement the classification task for diagnosing subjects, and proposes a multimodal and across-site WL-DeepGCN-based method for classification to diagnose autism spectrum disorder (ASD). This method is used to resolve the existing problem that deep learning ASD identification cannot efficiently utilize multimodal data. In the WL-DeepGCN, a weight-learning network is used to represent the similarity of non-imaging data in the latent space, introducing a new approach for constructing population graph edge weights, and we find that it is beneficial and robust to define pairwise associations in the latent space rather than the input space. We propose a graph convolutional neural network residual connectivity approach to reduce the information loss due to convolution operations by introducing residual units to avoid gradient disappearance and gradient explosion. Furthermore, an EdgeDrop strategy makes the node connections sparser by randomly dropping edges in the raw graph, and its introduction can alleviate the overfitting and oversmoothing problems in the DeepGCN training process. We compare the WL-DeepGCN model with competitive models based on the same topics and nested 10-fold cross-validation show that our method achieves 77.27% accuracy and 0.83 AUC for ASD identification, bringing substantial performance gains.

Mycelium Composite with Hierarchical Porous Structure for Thermal Management.

High-performance porous materials with a low carbon footprint provide sustainable alternatives to petroleum-based lightweight foams and can help meet carbon neutrality goals. However, these materials generally face a trade-off between thermal management capabilities and structural strength. Here, a mycelium composite with a hierarchical porous structure, including both macro- and microscale pores, produced from multiple and advanced mycelial networks (elastic modulus of 1.2 GPa) binding loosely distributed sawdust is demonstrated. The morphological, biological, and physicochemical properties of the filamentous mycelium and composites are discussed in terms of how they are influenced by the mycelial system of the fungi and the way they interact with the substrate. The composite shows a porosity of 0.94, a noise reduction coefficient of 0.55 at a frequency range of 250-3000 Hz (for a 15 mm thick sample), a thermal conductivity of 0.042 W m-1  K-1 , and an energy absorption of 18 kJ m-3 at 50% strain. It is also hydrophobic, repairable, and recyclable. It is expected that the hierarchical porous structural composite with excellent thermal and mechanical properties can make a significant impact on the future development of highly sustainable alternatives to lightweight plastic foams.

Research progress in the preparation of mesophase pitch from fluid catalytic cracking slurry.

For the preparation of high-performance pitch-based carbon fibers and other carbon materials, mesophase pitch serves as a high-quality precursor. Since FCC (Fluid Catalytic Cracking) oil slurry is abundant in aromatic hydrocarbons and saturated hydrocarbons (about 95% in total), it has become an ideal choice for developing new carbon material products. This paper details the research progress of preparing mesophase asphalt with FCC oil slurry as a raw material from perspectives including the preparation method of synthesizing mesophase asphalt from FCC oil slurry, the impact factors of the formation process of mesophase asphalt and the industrial application of mesophase asphalt.

CeO2/Cu2O/Cu Tandem Interfaces for Efficient Water-Gas Shift Reaction Catalysis.

Metal-oxide interfaces on Cu-based catalysts play very important roles in the low-temperature water-gas shift reaction (LT-WGSR). However, developing catalysts with abundant, active, and robust Cu-metal oxide interfaces under LT-WGSR conditions remains challenging. Herein, we report the successful development of an inverse copper-ceria catalyst (Cu@CeO2), which exhibited very high efficiency for the LT-WGSR. At a reaction temperature of 250 °C, the LT-WGSR activity of the Cu@CeO2 catalyst was about three times higher than that of a pristine Cu catalyst without CeO2. Comprehensive quasi-in situ structural characterizations indicated that the Cu@CeO2 catalyst was rich in CeO2/Cu2O/Cu tandem interfaces. Reaction kinetics studies and density functional theory (DFT) calculations revealed that the Cu+/Cu0 interfaces were the active sites for the LT-WGSR, while adjacent CeO2 nanoparticles play a key role in activating H2O and stabilizing the Cu+/Cu0 interfaces. Our study highlights the role of the CeO2/Cu2O/Cu tandem interface in regulating catalyst activity and stability, thus contributing to the development of improved Cu-based catalysts for the LT-WGSR.

Biomechanical characteristics of slashing attack on different body parts of a dummy using a kitchen knife.

BACKGROUND: Slashing attack is one of the most common ways of committing a homicide. The purpose of this study was to evaluate the biomechanical characteristics of slashing different body parts of a dummy by young males and females using a Chinese kitchen knife and thus provide scientific evidence for criminal investigations and court trials. METHODS: A total of 12 male and 12 female college students participated in this study. Biomechanical parameters, including joint velocity, slashing velocity, slashing force, energy, and impulse, were evaluated when slashing the chest and the neck of a dummy using a Chinese kitchen knife. RESULTS: When slashing the neck or the chest of a dummy, male participants showed higher elbow and wrist velocities (21.2% and 28.5%, respectively) as well as higher knife velocity (33.6%), slashing velocity (25.3%), slashing force (23.3%), and energy (57.6%) compared to female participants (all p < 0.05). When slashing the chest, participants showed higher shoulder, elbow, and wrist velocities (31.9%, 12.7%, and 12.6%) as well as knife velocity (3.8%), slashing velocity (7.3%), and energy (23.2%) compared to slashing the neck (all p < 0.05), regardless of gender. CONCLUSION: Both gender and slashing position have great impact on biomechanical characteristics of the slashing movement. Our data indicate that when slashing using a Chinese kitchen knife, males may induce severer wounds than females, and slashing different body parts may generate different slashing velocity or energy. Compared to slashing position, gender may have greater influence on the biomechanical characteristics. Findings from this study may expand our knowledge about knife slashing attacks by Chinese kitchen knives as well as other knives with comparative heavy blades.

Multiscale Traffic Sign Detection Method in Complex Environment Based on YOLOv4.

Traffic sign detection is a challenging problem in the field of unmanned driving, particularly important in complex environments. We propose a method, based on the improved You only look once (YOLO) v4, to detect and recognize multiscale traffic signs in complex environments. This method employs an image preprocessing module that can classify and denoize images of complex environments and then input the images into the improved YOLOv4. We also design an improved feature pyramid structure to replace the original feature pyramid of YOLOv4. This structure uses an adaptive feature fusion module and a multiscale feature transfer mechanism to reduce putative information loss in the feature map generation process and improve the information transfer between deep and shallow features, enhancing the representation ability of feature pyramids. Finally, we use EIOU LOSS and Cluster-NMS to further improve the model performance. The experimental results on the fusion of Tsinghua-Tencent 100 K and our collected dataset show that the proposed method achieves an mAP of 81.78%. Compared to existing methods, our method demonstrates its superiority with regard to traffic sign detection.

Characteristics of the Distance and Space Required for Knife Slashing Using a Motion Capture System.

OBJECTIVES: To investigate the relationship between the perpetrator's sex, victim's position and slashing location as well as anthropometric parameters on distance and space required for slashing, to provide the theoretical basis for the judgment of whether the crime scene was consistent with the criminal activity space. METHODS: The kinematics data of 12 male and 12 female subjects slashing the neck of standing and supine mannequins as well as the chest of the standing mannequins with a kitchen knife were obtained by using a 3D motion capture system. The relationship between the perpetrator's sex-victim's position, the perpetrator's sex-slashing location, and anthropometric parameters and the distance and space required for the slashing were analyzed by two-factor repeated measures ANOVA and Pearson correlation analysis respectively. RESULTS: Compared with slashing the neck of supine mannequins, the distance (L) and normalized L (l) of slashing the neck of standing mannequins were greater, while vertical distance (LVR) and normalized LVR (lVR) of the knife side were smaller. Compared with slashing the neck of standing mannequins, the L and l slashing the chest of standing mannequins were greater, while LVR and lVR were smaller. Horizontal distance (LHR) and normalized LHR (lHR) of the knife side in males were greater than that in females. Height and arm length were positively correlated with L, LHR, and LVR when striking the standing mannequins. CONCLUSIONS: When slashing the neck of supine or standing victims, the slashing distance is shorter and the slashing height is greater. Furthermore, the distance and space required for slashing are correlate with anthropometric parameters.

An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation.

In this paper, an inverse method is proposed for measuring the elastoplastic properties of metallic materials using a spherical indentation experiment. In the new method, the elastoplastic parameters are correlated with sub-space coordinates of indentation imprints using proper orthogonal decomposition (POD), and inverse identification of material properties is solved using a statistical Bayesian framework. The advantage of the method is that model parameters in the numerical optimization process are treated as the stochastic variables, and potential uncertainties can be considered. The posterior results obtained from the measuring method can provide valuable probabilistic information of the estimated elastoplastic properties. The proposed method is verified by the application on 2099-T83 Al-Li alloys. Results indicate that posterior distribution of material parameters exhibits more than one peak region when indentation load is not large enough. In addition, using the weighting imprints under different loads can facilitate the uniqueness in identification of elastoplastic parameters. The influence of the weighting coefficient on posterior identification results is analyzed. The elastoplastic properties identified by indentation and tensile experiment show good agreement. Results indicate that the established measuring method is effective and reliable.

Construction of a Phytic Acid-Silica System in Wood for Highly Efficient Flame Retardancy and Smoke Suppression.

The intrinsic flammability of wood restricts its application in various fields. In this study, we constructed a phytic acid (PA)-silica hybrid system in wood by a vacuum-pressure impregnation process to improve its flame retardancy and smoke suppression. The system was derived from a simple mixture of PA and silica sol. Fourier transform infrared spectroscopy (FTIR) indicated an incorporation of the PA molecules into the silica network. Thermogravimetric (TG) analysis showed that the system greatly enhanced the char yield of wood from 1.5% to 32.1% (in air) and the thermal degradation rates were decreased. The limiting oxygen index (LOI) of the PA/silica-nanosol-treated wood was 47.3%. Cone calorimetry test (CCT) was conducted, which revealed large reductions in the heat release rate and smoke production rate. The appearance of the second heat release peak was delayed, indicating the enhanced thermal stability of the char residue. The mechanism underlying flame retardancy was analyzed by field-emission scanning electron microscope coupled with energy-dispersive spectroscopy (SEM-EDS), FTIR, and TG-FTIR. The improved flame retardancy and smoke-suppression property of the wood are mainly attributed to the formation of an intact and coherent char residue with crosslinked structures, which can protect against the transfer of heat and mass (flammable gases, smoke) during burning. Moreover, the hybrid system did not significantly alter the mechanical properties of wood, such as compressive strength and hardness. This approach can be extended to fabricate other phosphorus and silicon materials for enhancing the fire safety of wood.

Assessing the influence of pore structure formation on heavy metal immobilization through image-based CFD.

Porous media are widely adopted as immobilization sorbents in environmental engineering. The microscale difference in pore structure formation causes significant deflection in a vast landscape. Computational fluid dynamics (CFD) offers a comparative approach to evaluate the individual influence from pore structure formation with strictly controlled surface and volume properties. This paper presents a comprehensive comparison between the performance of cylindrical media and spherical-media in heavy metal immobilization. Digital testing was performed to measure the surface area, specific surface area, density and porosity. Image-based input technique was developed to reconstruct the cylindrical media. It was found that although the surface area, specific surface area and porosity were the same, the spherical media still had an accelerated immobilization rate. Results further showed that the spherical media in floatation arrangement had an immobilization rate of 16% higher than the cylindrical media with the same surface properties. Non-floatation arrangement of the spherical media caused a reduction in immobilization capacity up to 32.8% lower than the cylindrical media. The cylindrical media demonstrated an advantage of being structurally stable under high porosity, the latter of which resulted in an increased immobilization capacity compared with the spherical-media. The results suggest that the cylindrical bio-microstructure is desirable for heavy metal immobilization in a non-flotational environment. The computational approach provides a digital solution to evaluate the immobilization in 3D architected media. The proposed testing methods are feasible for both experimentally obtained images and structures from algorithm-generation.

Restoration of the Antibiotic Susceptibility of Methicillin-Resistant Staphylococcus aureus and Extended-Spectrum ß-Lactamases Escherichia coli Through Combination with Chelerythrine.

Multidrug resistance poses a severe threat to public health and urgently requires new solutions. The natural product chelerythrine (CHE) is a benzophenanthridine alkaloid with antimicrobial potential. In this study, CHE was effective against seven gram-positive bacterial strains, and the minimum inhibitory concentrations (MICs) ranged from 2 to 4 µg/mL. By contrast, CHE showed inferior antibacterial activities against 11 gram-negative strains, and the MICs varied from 16 to 256 µg/mL. We also determined the synergistic/additive effects of combining CHE with nine currently used antibiotics. CHE restored the antibacterial efficacy of the antibiotics against methicillin-resistant Staphylococcus aureus and extended-spectrum ß-lactamases producing Escherichia coli. This study suggests that the combination of CHE with conventional antibiotics may be a promising strategy to combat infections caused by multidrug-resistant organisms.

Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution.

Computational analysis of virus dynamics provides a non-contact environment for the study of the vital object. Cluster modelling is an essential step to investigate the properties of a group of viruses, and an automatic approach is required for massive 3D data processing. The morphological complexity of individual virus limits the application of smooth function algorithms with a regular-shaped assumption. This paper proposed a voxel-based redistribution approach to generate the virus cluster with COVID-19 input automatically. Representative elementary volume analysis was performed to address the statistical influence from the digital sample size. Coordination number analysis and surface density measurement were conducted with COVID-19 input and spherical input for comparison. The proposed approach is in natural compatibility with the lattice Boltzmann method for fluid dynamics analysis. A virtual permeation simulation was performed with the COVID-19 cluster and spherical cluster to demonstrate the necessity to include spike protein structure in the cluster modelling.