A special type of homicide-suicide: A retrospective study of the characteristics of extended suicide.

Extended suicide, a specific type of homicide-suicide event, has severe social consequences yet remains lacking systematic research. This retrospective study investigated 51 cases of extended suicide involving mental disorders in central China with aim of better understanding risk factors for such events and guiding prevention strategies. Over an 8-year period from 2015 to 2022, cases were collected from forensic institutions, and demographic characteristics, case details, and psychiatric data were recorded. The 51 incidents involved 51 perpetrators and 79 victims, with more female perpetrators (58.8%) and more female victims (54.4%). The average age of the perpetrators was 36.1, and most were married (88.2%). Almost all of the victims were family members of the perpetrator, like the most numerous children (64.6%), followed by spouses (24.1%). The most common homicide mode of death was mechanical asphyxia (38.0%), followed by sharp devices (36.7%) and drug poisoning (16.5%). Depressive disorders (76.5%) were the most common diagnosis of mental disorder for perpetrators. The study analyzed the unique characteristics of extended suicide to enrich such data. These findings help strengthen the screening and identification of potential perpetrators and victims to prevent such cases from occurring.

The cardiovascular toxicity of clozapine in embryonic zebrafish and RNA sequencing-based transcriptome analysis.

Clozapine (CLZ) is the most prescribed medication for treating refractory schizophrenia but is associated with significant cardiovascular toxicity. This study aimed to investigate the cardiovascular toxicity induced by CLZ using zebrafish as a model animal. For this purpose, zebrafish developed to 80-h post-fertilization were exposed to different CLZ concentration solutions for 24 h followed by cardiac morphological observations in yolk sac edema, pericardial edema, and blood coagulation, in addition to increased SV-BA distance, functionally manifested as bradycardia, and decreased cardiac ejection fraction using the untreated embryos as control. At the same time, RNA sequencing was used to study the possible molecular mechanism of CLZ-induced cardiovascular toxicity. The results indicated that compared to the control group, the experimental groups possessed a total of 5888 differentially expressed genes (DEGs), where gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment of analysis indicated that DEGs were mainly enriched in the pathways related to ion channels. These findings may provide new insights and directions for the subsequent in-depth study of the molecular mechanism of CLZ-induced cardiovascular toxicity.

Assessment System for Child Head Injury from Falls Based on Neural Network Learning.

Toddlers face serious health hazards if they fall from relatively high places at home during everyday activities and are not swiftly rescued. Still, few effective, precise, and exhaustive solutions exist for such a task. This research aims to create a real-time assessment system for head injury from falls. Two phases are involved in processing the framework: In phase I, the data of joints is obtained by processing surveillance video with Open Pose. The long short-term memory (LSTM) network and 3D transform model are then used to integrate key spots' frame space and time information. In phase II, the head acceleration is derived and inserted into the HIC value calculation, and a classification model is developed to assess the injury. We collected 200 RGB-captured daily films of 13- to 30-month-old toddlers playing near furniture edges, guardrails, and upside-down falls. Five hundred video clips extracted from these are divided in an 8:2 ratio into a training and validation set. We prepared an additional collection of 300 video clips (test set) of toddlers' daily falling at home from their parents to evaluate the framework's performance. The experimental findings revealed a classification accuracy of 96.67%. The feasibility of a real-time AI technique for assessing head injuries in falls through monitoring was proven.

Synchronization stability of power-grid-tied converters.

Synchronization stability is one of central problems in power systems, and it is becoming much more complicated with the high penetration of renewable energy and power electronics devices. In this paper, we review recent work by several nonlinear models for renewable-dominated power systems in terms of multiple timescales, in particular, grid-tied converters within the DC voltage timescale. For the simplest model, a second-order differential equations called the generalized swing equation by considering only the phase-locked loop (PLL) is obtained, which shows a similar form with the well-known swing equation for a synchronous generator in the traditional power systems. With more outer controllers included, fourth-order and fifth-order models can be obtained. The fourth-order model is called the extended generalized swing equation, exhibiting the combined function of grid synchronization and active power balance on the DC capacitor. In addition, a nonlinear model for a two coupled converter system is given. Based on these studies, we find that the PLL plays a key role in synchronization stability. In summary, the value of this paper is to clarify the key concept of the synchronization stability in renewable-dominated power systems based on different nonlinear models, which still lacks systematic studies and is controversial in the field of electrical power engineering. Meanwhile, it clearly uncovers that the synchronization stability of converters has its root in the phase synchronization concept in nonlinear sciences.

Genetic Ablation of GIGYF1, Associated With Autism, Causes Behavioral and Neurodevelopmental Defects in Zebrafish and Mice.

BACKGROUND: Autism spectrum disorder is characterized by deficits in social communication and restricted or repetitive behaviors. Due to the extremely high genetic and phenotypic heterogeneity, it is critical to pinpoint the genetic factors for understanding the pathology of these disorders. METHODS: We analyzed the exomes generated by the SPARK (Simons Powering Autism Research) project and performed a meta-analysis with previous data. We then generated 1 zebrafish knockout model and 3 mouse knockout models to examine the function of GIGYF1 in neurodevelopment and behavior. Finally, we performed whole tissue and single-nucleus transcriptome analysis to explore the molecular and cellular function of GIGYF1. RESULTS: GIGYF1 variants are significantly associated with various neurodevelopmental disorder phenotypes, including autism, global developmental delay, intellectual disability, and sleep disturbance. Loss of GIGYF1 causes similar behavioral effects in zebrafish and mice, including elevated levels of anxiety and reduced social engagement, which is reminiscent of the behavioral deficits in human patients carrying GIGYF1 variants. Moreover, excitatory neuron-specific Gigyf1 knockout mice recapitulate the increased repetitive behaviors and impaired social memory, suggesting a crucial role of Gigyf1 in excitatory neurons, which correlates with the observations in single-nucleus RNA sequencing. We also identified a series of downstream target genes of GIGYF1 that affect many aspects of the nervous system, especially synaptic transmission. CONCLUSIONS: De novo variants of GIGYF1 are associated with neurodevelopmental disorders, including autism spectrum disorder. GIGYF1 is involved in neurodevelopment and animal behavior, potentially through regulating hippocampal CA2 neuronal numbers and disturbing synaptic transmission.

Immersive Experience and Climate Change Monitoring in Digital Landscapes: Evidence from Somatosensory Sense and Comfort.

In this study, the virtual engine software (Unity 2019, Unity Software Inc., San Francisco, California, the U.S.) was used to generate a digital landscape model, forming a virtual immersive environment. Through field investigation and emotional preference experiments, the ancient tree ecological area and the sunlight-exposed area were respectively monitored, and the somatosensory comfort evaluation model was established. The subjects showed the highest degree of interest in the ancient tree ecological area after landscape roaming experience, and the mean variance in SC fluctuation was 13.23% in experiments. The subjects were in a low arousal state and had a significant degree of interest in the digital landscape roaming scene, and there was a significant correlation between positive emotion, somatosensory comfort and the Rating of Perceived Exertion index; moreover, the somatosensory comfort of the ancient tree ecological area was higher than that of the sunlight-exposed area. Meanwhile, it was found that somatosensory comfort level can effectively distinguish the comfort level between the ancient tree ecological area and the sunlight-exposed area, which provides an important basis for monitoring extreme heat. This study concludes that, in terms of the goal of harmonious coexistence between human and nature, the evaluation model of somatosensory comfort can contribute to reducing people's adverse views on extreme weather conditions.

Stable, long-term single-neuronal recording from the rat spinal cord with flexible carbon nanotube fiber electrodes.

Objective.Flexible implantable electrodes enable months-long stable recording of single-unit signals from rat brains. Despite extensive efforts in the development of flexible probes for brain recording, thus far there are no conclusions on their application in long-term single neuronal recording from the spinal cord which is more mechanically active. To this end, we realized the chronic recording of single-unit signals from the spinal cord of freely-moving rats using flexible carbon nanotube fiber (CNTF) electrodes.Approach.We developed flexible CNTF electrodes for intraspinal recording. Continuousin vivoimpedance monitoring and histology studies were conducted to explore the critical factors determining the longevity of the recording, as well as to illustrate the evolution of the electrode-tissue interface. Gait analysis were performed to evaluate the biosafety of the chronic intraspinal implantation of the CNTF electrodes.Main results.By increasing the insulation thickness of the CNTF electrodes, single-unit signals were continuously recorded from the spinal cord of freely-moving rats without electrode repositioning for 3-4 months. Single neuronal and local field potential activities in response to somatic mechanical stimulation were successfully recorded from the spinal dorsal horns. Histological data demonstrated the ability of the CNTF microelectrodes to form an improved intraspinal interfaces with greatly reduced gliosis compared to their stiff metal counterparts. Continuous impedance monitoring suggested that the longevity of the intraspinal recording with CNTF electrodes was determined by the insulation durability. Gait analysis showed that the chronic presence of the CNTF electrodes caused no noticeable locomotor deficits in rats.Significance.It was found that the chronic recording from the spinal cord faces more stringent requirements on the electrode structural durability than recording from the brain. The stable, long-term intraspinal recording provides unique capabilities for studying the physiological functions of the spinal cord relating to motor, sensation, and autonomic control in both health and disease.

Assessing Macro Disease Index of Wheat Stripe Rust Based on Segformer with Complex Background in the Field.

Wheat stripe rust (WSR) is a foliar disease that causes destructive damage in the wheat production context. Accurately estimating the severity of WSR in the autumn growing stage can help to objectively monitor the disease incidence level of WSR and predict the nationwide disease incidence in the following year, which have great significance for controlling its nationwide spread and ensuring the safety of grain production. In this study, to address the low accuracy and the efficiency of disease index estimation by traditional methods, WSR-diseased areas are segmented based on Segformer, and the macro disease index (MDI) is automatically calculated for the measurement of canopy-scale disease incidence. The results obtained with different semantic segmentation algorithms, loss functions, and data sets are compared for the segmentation effect, in order to address the severe class imbalance in disease region segmentation. We find that: (1) The results of the various models differed significantly, with Segformer being the best algorithm for WSR segmentation (rust class F1 score = 72.60%), based on the original data set; (2) the imbalanced nature of the data has a significant impact on the identification of the minority class (i.e., the rust class), for which solutions based on loss functions and re-weighting of the minority class are ineffective; (3) data augmentation of the minority class or under-sampling of the original data set to increase the proportion of the rust class greatly improved the F1-score of the model (rust class F1 score = 86.6%), revealing that re-sampling is a simple and effective approach to alleviating the class imbalance problem. Finally, the MDI was used to evaluate the models based on the different data sets, where the model based on the augmented data set presented the best performance (R2 = 0.992, RMSE = 0.008). In conclusion, the deep-learning-based semantic segmentation method, and the corresponding optimization measures, applied in this study allow us to achieve pixel-level accurate segmentation of WSR regions on wheat leaves, thus enabling accurate assessment of the degree of WSR disease under complex backgrounds in the field, consequently providing technical support for field surveys and calculation of the disease level.

Single-Atom Catalysts Supported on the Graphene/Graphdiyne Heterostructure for Effective CO2 Electroreduction.

Electrochemical reduction of CO2 to high-energy chemicals is a promising strategy for achieving carbon-neutral energy circulation. However, designing high-performance electrocatalysts for the CO2 reduction reaction (CO2RR) remains a great challenge. In this work, by means of density functional theory calculations, we systematically investigate the transition metal (TM) anchored on the nitrogen-doped graphene/graphdiyne heterostructure (TM-N4@GRA/GDY) as a single-atom catalyst for CO2 electroreduction applications. The computational results show that Co-N4@GRA/GDY exhibits remarkable activity with a low limiting potential of -0.567 V for the reduction of CO2 to CH4. When the charged Co-N4@GRA/GDY system is immersed in a continuum solvent, the reaction barrier decreases to 0.366 eV, which is ascribed to stronger electron transfer between GDY and transition metal atoms in the GRA/GDY heterostructure. In addition, the GRA/GDY heterostructure system significantly weakens the linear scaling relationship between the adsorption free energy of key CO2 reduction intermediates, which leads to a catalytic activity that is higher than that of the single-GRA system and thus greatly accelerates the CO2RR. The electronic structure analysis reveals that the appropriate d-π interaction will affect the d orbital electron distribution, which is directly relevant to the selectivity and activity of catalysis. We hope these computational results not only provide a potential electrocatalyst candidate but also open up an avenue for improving the catalytic performance for efficient electrochemical CO2RR.

Is there any difference on cyanobacterial blooms patterns between Lake Chaohu and Lake Taihu over the last 20 years?

Serious cyanobacterial blooms (CBs) caused by lake eutrophication have become a global ecological and environmental problem and have adversely affected the production, life, and health of human beings. Lake Chaohu and Lake Taihu are two large closed shallow eutrophication lakes in the Yangtze River Delta in China with frequent CBs. In this study, the floating algae index (FAI) algorithm was applied to detect a long-time CBs sequence using Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2000 to 2019. The common characteristics and differences of the CBs patterns were further explored in both lakes over the last 20 years. The results showed that the severity of CBs in Lakes Chaohu and Taihu presented a similar trend of decreasing and then increasing during the period of 2000-2004 and 2005-2007, respectively. Although the severity of CBs in the two lakes was alleviated after 2008, CBs in Lake Taihu has gradually increased since 2011 and severe CBs broke out again in 2017 and 2019. Meanwhile, the CBs in Lake Chaohu have varied significantly in different years, and severe CBs were observed in 2012, 2014-2015, and 2018-2019, while in other years, CBs remained relatively low level. The high-frequency regions of CBs were mainly concentrated in the western part in Lake Chaohu and in Zhushan Bay and Meilian Bay in Lake Taihu in the initial years of 2000. However, since 2005, the CBs in Lake Chaohu gradually expanded to the central and eastern parts, and to the northwestern and western shore in Lake Taihu. Furthermore, the relationship between the monthly mean area of CBs (CBsmean) and environmental factors based on principal component analysis (PCA) indicated that temperature was the most important driving factor affecting CBs patterns. Compared to the period from 2001 to 2007, TP played a more important role in both lakes from 2008 to 2019. Various management measures have been adopted to reduce CBs in both lakes and these methods can effectively remove cyanobacteria in a short time, but they do not change CBs patterns in the long period.

[Comprehensive Classification Method of Urban Water by Remote Sensing Based on High-Resolution Images].

Urban water is a significant part of the urban ecosystem. Therefore, a comprehensive evaluation method of the water environment was proposed based on domestic high-resolution images. The relationships between the spectral characteristics and water quality parameters of urban water were analyzed based on sampling in Nanjing, Wuxi, Changzhou, and Yangzhou from 2017 to 2019. An index named the U-FUI (urban Forel-Ule index) suitable for urban water based on GF-2 images was proposed to achieve the classification of urban water on the basis of the international standard chroma conversion model and the Forel-Ule index. Independent verification data showed that the recognition accuracy of the classification model could reach 72%. The results indicated that urban water can be classified into six classes from Ⅰ to Ⅵ, which represent water colors of blue, light green, dark green, yellow, yellowish brown, and dark grey, respectively, according to the U-FUI. Among them, the water quality of U-FUI Ⅰ water is good, but is rarely distributed in urban water. The concentrations of chlorophyll-a in U-FUI Ⅱ-Ⅲ water are higher than those of the other classes; the concentrations of total suspended solids, particularly inorganic suspended solids, of U-FUI Ⅳ-Ⅴ water are higher than those of the other classes; and the water quality of U-FUI Ⅵ water is poor and the water quality parameters are different from those of the other classes. Meanwhile, the method was successfully applied to the GF-2 image of Nanjing on April 9, 2018. The results showed that the urban water in Nanjing is mainly composed of U-FUI Ⅱ-Ⅳ water, whereas the distribution of U-FUI Ⅰ, Ⅴ, and Ⅵ water is lower in the city. The spatial distribution characteristics were consistent with the results of in-situ sampling in the same period.

Carbon-Based Fiber Materials as Implantable Depth Neural Electrodes.

Implantable brain electrophysiology electrodes are valuable tools in both fundamental and applied neuroscience due to their ability to record neural activity with high spatiotemporal resolution from shallow and deep brain regions. Their use has been hindered, however, by the challenges in achieving chronically stable operations. Furthermore, implantable depth neural electrodes can only carry out limited data sampling within predefined anatomical regions, making it challenging to perform large-area brain mapping. Minimizing inflammatory responses and associated gliosis formation, and improving the durability and stability of the electrode insulation layers are critical to achieve long-term stable neural recording and stimulation. Combining electrophysiological measurements with simultaneous whole-brain imaging techniques, such as magnetic resonance imaging (MRI), provides a useful solution to alleviate the challenge in scalability of implantable depth electrodes. In recent years, various carbon-based materials have been used to fabricate flexible neural depth electrodes with reduced inflammatory responses and MRI-compatible electrodes, which allows structural and functional MRI mapping of the whole brain without obstructing any brain regions around the electrodes. Here, we conducted a systematic comparative evaluation on the electrochemical properties, mechanical properties, and MRI compatibility of different kinds of carbon-based fiber materials, including carbon nanotube fibers, graphene fibers, and carbon fibers. We also developed a strategy to improve the stability of the electrode insulation without sacrificing the flexibility of the implantable depth electrodes by sandwiching an inorganic barrier layer inside the polymer insulation film. These studies provide us with important insights into choosing the most suitable materials for next-generation implantable depth electrodes with unique capabilities for applications in both fundamental and translational neuroscience research.

[Remote Sensing Classification of Urban Black-odor Water Based on Decision Tree].

Remote sensing monitoring of black-odor water is an important method for understanding the current status of urban water quality, and comprehensively evaluating the effect of urban water environment treatment. A total of 171 samples were collected in Nanjing, Changzhou, Wuxi, and Yangzhou cities and water quality parameters and optical parameters were measured simultaneously. Based on the analysis of the water color and optical characteristics of the black-odor water and non-black-odor water (denoted as general water), a decision tree was constructed to identify the severe, mild black-odor water, and general water as green and yellow water. The results found that:①According to the water color, the water bodies can be divided into six types. Among them, type 1 to 4 water bodies are black-odor water, which are gray black, dark gray, gray, and light gray water, respectively, and type 5 and 6 water bodies are general water, which are green and yellow water, respectively; ②Type 1 water body contains high contents of non-pigmented particulate matter and colored dissolved organic matter(CDOM), however, the absorption of pigmented particulate matter is not dominant. Type 2 and 5 water bodies are dominated by pigmented particulate matter. Type 3, 4, and 6 water bodies are dominated by non-pigmented particulate matter; ③After water color classification, and according to the differences of the reflection spectrums of the six types of water bodies, the difference of black-odorous water index (DBWI), green-red-nir area water index (G-R-NIR AWI), the green band reflectance and the normalized difference black-odorous water index (NDBWI) were used to construct a decision tree to identify the severe, mild black-odor water, and general water; ④The decision tree was applied to the PlanetScope satellite image of Yangzhou City on April 9, 2019, and 10 synchronous sampling points were used for verification. The overall recognition accuracy reached 80.00%, and the K value reached 0.67. The urban water classification model, after water color classification, can be applied to other similar water bodies, and provides a technical method for the supervision of black-odor water bodies.

Mapping spatio-temporal dynamics of main water parameters and understanding their relationships with driving factors using GF-1 images in a clear reservoir.

Due to eutrophication and water quality deterioration in clear reservoirs, it is necessary to monitor and manage the main water parameters: concentration of total phosphorus (CTP), chemical oxygen demand (CCOD), chlorophyll-a (CChla), total suspended matter (CTSM), and Secchi disk depth (SDD). Five random forest (RF) models are developed to estimate these parameters in Xin'anjiang Reservoir, which is a clear drinking water resource in Zhejiang, China. Then, the spatio-temporal distributions of the parameters over 7 years (2013-2019) are mapped using GaoFen-1 (GF-1) images and the relationships with driving factors are analyzed. Our study demonstrates that the parameters' distributions exhibited a significant spatio-temporal difference in Xin'anjiang Reservoir. Spatially, relatively high CTP, CCOD, CChla, and CTSM but low SDD appear in riverine areas, showing strong evidence of impact from the incoming rivers. Temporally, CChla and CTSM reached high values in summer and winter, whereas SDD and CTP were higher in the summer and autumn, respectively. In contrast, no significant seasonal variations of CCOD could be observed. This may be why CCOD is not sensitive to hydrological or meteorological factors. However, precipitation had a significant impact on CChla, CTP, SDD, and CTSM in riverine areas, though these parameters were less sensitive to meteorological factors. Moreover, the geomorphology of the reservoir and anthropogenic interference (e.g., tourism activities) also have a significant impact on the water quality parameters. This study demonstrates that coupling long-term GF-1 images and RF models could provide strong evidence and new insights to understand long-term dynamics in water quality and therefore support the development of corresponding management strategies for freshwater reservoirs.

Comparative transcriptome analysis reveals the genetic basis underlying the biosynthesis of polysaccharides in Hericium erinaceus.

BACKGROUND: Hericium erinaceus, also known as lion's mane mushroom, is a widely distributed edible and medicinal fungus in Asian countries. H. erinaceus harbors diverse bioactive metabolites with anticancer, immunomodulating, anti-inflammatory, antimicrobial, antihypertensive, antidiabetic and neuroprotective properties. Although the chemical synthesis processes of these bioactive metabolites are known, the biosynthetic processes remain unknown. RESULTS: In this study, we obtained the transcriptomes of six H. erinaceus strains using next-generation RNA sequencing and investigated the characteristics of the transcriptomes and biosynthesis of bioactive compounds, especially polysaccharides. The transcriptomes ranged in size from 46.58 to 58.14 Mb, with the number of unigenes ranging from 20,902 to 37,259 across the six H. erinaceus strains. Approximately 60% of the unigenes were successfully annotated by comparing sequences against different databases, including the nonredundant (NR), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), clusters of orthologous groups for eukaryotic complete genomes (KOG) and Swiss-Prot databases. Most of the transcripts were putatively involved in signal transduction, carbohydrate metabolism, translation, transport and catabolism, and amino acid metabolism. Genes involved in polysaccharide biosynthesis were identified, and these genes encoded phosphoglucomutase (PGM), glucose phosphate isomerase (PGI), UDP-glucose pyrophosphorylase (UGP), glycoside hydrolase family proteins, glycosyltransferase family proteins and other proteins. Moreover, the putative pathway for the intracellular polysaccharide biosynthesis of H. erinaceus was analyzed. Additionally, the open reading frames (ORFs) and simple sequence repeats (SSRs) were predicted from the transcriptome data of the six strains. CONCLUSIONS: Overall, the present study may facilitate the discovery of polysaccharide biosynthesis processes in H. erinaceus and provide useful information for exploring the secondary metabolites in other members of the Basidiomycetes genus.

Effects of Sulfuric Acid on the Curing Behavior and Bonding Performance of Tannin⁻Sucrose Adhesive.

The development of biomaterials-based adhesives is one of the main research directions for the wood-based material industry. In previous research, tannin and sucrose were used as adhesive to manufacture particleboard. However, the reaction conditions need to be optimized. In this study, sulfuric acid was added to the tannin⁻sucrose adhesive as a catalyst to improve the curing process. Thermal analysis, insoluble mass proportion, FT-IR, and solid state 13C NMR were used to investigate the effects of sulfuric acid on the curing behavior of tannin and sucrose. Thermal analysis showed weight loss and endotherm temperature reduced from 205 and 215 to 136 and 138 °C, respectively, by adding sulfuric acid. In case of the adhesive with pH = 1.0, the insoluble mass proportion achieved 81% at 160 °C, which was higher than the reference at 220 °C. FT-IR analysis of the uncured adhesives showed that adding sulfuric acid leads to hydrolysis of sucrose; then, glucose and fructose converted to 5-hydroxymehthylfurfural (HMF) and levulinic acid. Dimethylene ether bridges were observed by FT-IR analysis of the cured adhesives. The results of solid state 13C NMR spectrum indicated that 5-HMF participated in the curing process and formed methylene bridges with the C8 position of the resorcinol A-rings of tannin, whereas dimethylene ether bridges were detected as a major chemical chain of the polymer. Lab particleboards were produced using 20 wt % resin content at 180 °C and 10 min press time; the tannin⁻sucrose adhesive modified with sulfuric acid to pH = 1.0 exhibited better performance than the unmodified tannin⁻sucrose adhesive; the properties of the boards fulfilled the requirement of Japanese Industrial Standard (JIS) A5908 type 15.