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Urban parks, a core component of urban landscapes, play a crucial role in mitigating the negative effects of rapid urbanization and achieving sustainable urban development. In densely populated urban environments, providing urban parks fairly and efficiently, taking social preferences into account, is an important challenge. In this regard, we take Hangzhou, China, as an example and use a hedonic pricing model with a difference-in-differences estimator to test the effect of different types of urban parks on housing prices, quantify their respective economic values, and reflect homebuyers' preferences. The findings indicate that the construction of new urban parks leads to an overall increase in the value of the surrounding real estate to some extent. Specifically, the construction of comprehensive parks and large parks significantly enhances the value of nearby housing, while proximity to new medium-sized parks also results in a housing price premium, albeit to a lesser extent. In contrast, community parks and specialized parks have a less significant impact on housing prices. These findings provide valuable insights for equitable urban development and planning, optimizing the allocation of urban parks and determining investment priorities for different types of parks to enhance the sustainability of the urban environment and human well-being. [ABSTRACT FROM AUTHOR]

To address the challenges of high experimental costs, complexity, and time consumption associated with pre-mixed combustible gas deflagration experiments under semi-open space obstacle conditions, a rapid temporal prediction method for flame propagation velocity based on Ranger-GRU neural networks is proposed. The deflagration experiment data are employed as the training dataset for the neural network, with the coefficient of determination (R2) and mean squared error (MSE) used as evaluation metrics to assess the predictive performance of the network. First, 108 sets of pre-mixed methane gas deflagration experiments were conducted, varying obstacle parameters to investigate methane deflagration mechanisms under different conditions. The experimental results demonstrate that obstacle-to-ignition source distance, obstacle shape, obstacle length, obstacle quantity, and thick and fine wire mesh obstacles all significantly influence flame propagation velocity. Subsequently, the GRU neural network was trained, and different activation functions (Sigmoid, Relu, PReLU) and optimizers (Lookahead, RAdam, Adam, Ranger) were incorporated into the backpropagation updating process of the network. The training results show that the Ranger-GRU neural network based on the PReLU activation function achieves the highest mean R2 value of 0.96 and the lowest mean MSE value of 7.16759. Therefore, the Ranger-GRU neural network with PReLU activation function can be a viable rapid prediction method for flame propagation velocity in pre-mixed methane gas deflagration experiments under semi-open space obstacle conditions. [ABSTRACT FROM AUTHOR]

In recent years, there have been significant advancements in the research of Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV). However, several limitations and challenges still exist. For instance, researchers face constraints regarding experimental conditions and the feasibility of sample acquisition for studying SFTSV. To enhance the quality and comprehensiveness of SFTSV research, we opted to employ PMA-induced THP-1 cells as a model for SFTSV infection. Multiple time points of SFTSV infection were designed to capture the dynamic nature of the virus–host interaction. Through a comprehensive analysis utilizing various bioinformatics approaches, including diverse clustering methods, MUfzz analysis, and LASSO/Cox machine learning, we performed dynamic analysis and identified key genes associated with SFTSV infection at the host cell transcriptomic level. Notably, successful clustering was achieved for samples infected at different time points, leading to the identification of two important genes, PHGDH and NLRP12. And these findings may provide valuable insights into the pathogenesis of SFTSV and contribute to our understanding of host–virus interactions. [ABSTRACT FROM AUTHOR]

In laser scanning inspection systems for sheet metal parts, the rapid and accurate inspection of the high-precision holes is not only crucial but difficult. The accuracy of the circular holes, especially the locating datum holes on the parts, plays an important role in the assembly quality. However, accurately segmenting the circular hole boundary points required for circular hole fitting from large-scale scanning point cloud data remains one of the most difficult tasks for inspection accuracy improvement. To address this problem, a segmentation network called the circular hole boundary segmentation network (CHBS-Net) is proposed for boundary point cloud extraction. Firstly, an encoding–decoding–attention (EDA) fusion guidance mechanism is used to address the imbalance in data distribution due to the small proportion of boundary points in the overall point cloud. Secondly, a long short-term memory (LSTM) network parallel structure is used to capture the contour continuity and temporal relationships among boundary points. Finally, the interference of neighboring points and noise is reduced by extracting features in the multi-scale neighborhood. Experiments were performed using real cases from a sheet metal parts dataset to illustrate the procedures. The results showed that the proposed method achieves better performance than the benchmark state-of-the-art methods. The circular hole inspection accuracy is effectively improved by enhancing the segmentation accuracy of the scanning boundary points. [ABSTRACT FROM AUTHOR]

Severe Fever with thrombocytopenia syndrome (SFTS) is a highly fatal viral infectious disease that poses a significant threat to public health. Currently, the phase and pathogenesis of SFTS are not well understood, and there are no specific vaccines or effective treatment available. Therefore, it is crucial to identify biomarkers for diagnosing acute SFTS, which has a high mortality rate. In this study, we conducted differentially expressed genes (DEGs) analysis and WGCNA module analysis on the GSE144358 dataset, comparing the acute phase of SFTSV-infected patients with healthy individuals. Through the LASSO–Cox and random forest algorithms, a total of 2128 genes were analyzed, leading to the identification of four genes: ADIPOR1, CENPO, E2F2, and H2AC17. The GSEA analysis of these four genes demonstrated a significant correlation with immune cell function and cell cycle, aligning with the functional enrichment findings of DEGs. Furthermore, we also utilized CIBERSORT to analyze the immune cell infiltration and its correlation with characteristic genes. The results indicate that the combination of ADIPOR1, CENPO, E2F2, and H2AC17 genes has the potential as characteristic genes for diagnosing and studying the acute phase of SFTS virus (SFTSV) infection. [ABSTRACT FROM AUTHOR]

Farmland transfer is a crucial aspect of modernizing China's agriculture, which has a significant impact on farmers' income distribution. With rapid urbanization, farmers' livelihood has changed significantly, and the income effects of farmland transfer will differ among heterogeneous farmers. Based on the China Family Panel Studies (CFPS) data, this study examines the impact of farmland transfer on farmers' income growth and income disparity, as well as the income differences in farmland transfer among farmers with different types of livelihood capital. An endogenous switching regression model and unconditional quantile treatment effects are used to correct the selection bias and farmer heterogeneity. The results show that (1) farmland transfer increases farmers' income. Specifically, farmland transfer-in increases farmers' income by 21.15%, while transfer-out increases it by 43.33%. (2) The impact of farmland transfer on farmers' income has a "Matthew effect" and will widen the income gap between farmers. (3) Moreover, farmland transfer exhibits diverse income effects on heterogeneous farmers with livelihood capital. Capital-rich farmers experience the largest income-growth effect from farmland transfer-in, while capital-balanced farmers experience the largest income-growth effect from farmland transfer-out. The policy implications are to further improve the farmland transfer market and enable low-income farmers to participate by improving their qualifications and abilities. [ABSTRACT FROM AUTHOR]

A unique variety of wetlands known as coastal wetlands that connect terrestrial and marine ecosystems is crucial to reducing and adapting to climate change as well as the advancement of human culture. However, the coastal wetland ecosystem is currently in danger as a result of the increasing intensity of human activity, and wetland restoration and reconstruction have garnered a lot of interest. The differentiated ecological restoration strategies based on ecosystem service change analysis can provide a reference for the effective management and sustainability of coastal wetland ecosystems. The InVEST model and ArcGIS were used to analyze the spatiotemporal changes in ecosystem services before and after the implementation of coastal wetland restoration policies based on remote sensing image data, meteorological and soil data, etc. The ecological restoration pattern of coastal wetlands was divided, and the corresponding ecological restoration strategies were proposed in this study. The following are the results: (1) there are still many wetlands that have been converted to non-wetlands following the implementation of the wetland restoration policy, and the ecosystem services as a whole exhibit a rising and then falling trend, with a rise from 2005 to 2015, a fall in 2015 due to the creation of Hangzhou Bay New District, and a slight improvement to 2020. Among them, the water yield increased continuously, the carbon storage fluctuated, and the habitat quality did not improve significantly. (2) The hot spots of ecosystem services were concentrated in the south and southeast of the study area, with no obvious cold spots. (3) By comprehensively analyzing the changes and spatial patterns of ecosystem services, the coastal wetlands on the south bank of Hangzhou Bay were divided into an ecological conservation zone, a green development zone, and an ecological restoration zone at the township level, and corresponding optimization strategies were proposed. The results can provide a reference for the fine-grained and differentiated management of regional ecosystem services. [ABSTRACT FROM AUTHOR]

The fresh-cut bulbs of the Lanzhou lily (Lilium davidii var. unicolor) experience browning problems during storage. To solve the problem of browning in the preservation of Lanzhou lily bulbs, we first investigated the optimal storage temperature and gas ratio of modified atmosphere packaging (MAP) of Lanzhou lily bulbs. Then, we tested the browning index (BD), activity of phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO) and peroxidase (POD), the content of malonaldehyde (MDA) and other physiological activity indicators related to browning. The results showed that the storage conditions of 10% O2 + 5% CO2 + 85% N2 and 4 °C were the best. To further explore the anti-browning mechanism of MAP in fresh-cut Lanzhou lily bulbs, the integration of metabolome and transcriptome analyses showed that MAP mainly retarded the unsaturated fatty acid/saturated fatty acid ratio in the cell membrane, inhibited the lipid peroxidation of the membrane and thus maintained the integrity of the cell membrane of Lanzhou lily bulbs. In addition, MAP inhibited the oxidation of phenolic substances and provided an anti-tanning effect. This study provided a preservation scheme to solve the problem of the browning of freshly cut Lanzhou lily bulbs, and discussed the mechanism of MAP in preventing browning during the storage of the bulbs. [ABSTRACT FROM AUTHOR]

Polymicrogyria is a brain malformation characterized by excessive folding of the cortex. To date, numerous causes of polymicrogyria have been identified, including variants in the genes associated with tubulinopathies. Herein, we present a child with severe intellectual disability, refractory to treatment seizures, microcephaly and MRI findings consistent with polymicrogyria, closed-lip schizencephaly, periventricular heterotopia and a dysplastic corpus callosum. Exome sequencing identified a de novo missense variant in TUBG2, a gene not associated with human disease. The variant, NM_016437.3 c.747G>A p.(Met249Ile), is absent from available control databases and is predicated to be deleterious by in silico prediction programs. Laboratory studies show that cultured lymphoblasts derived from the patient grew significantly faster than controls. Recombinant protein was expressed (recombinant wild type and mutant TUBG2-FLAG) in 293T cells and lower levels of TUBG2 mutant compared with controls were observed. Furthermore, co-immuno-precipitation in cells transfected demonstrated that the TUBG2–GCP2 interaction is increased due to the MUT recombinant protein versus WT recombinant protein. In closing, this work provides preliminary evidence that TUBG2 may represent a novel disease gene responsible for polymicrogyria. [ABSTRACT FROM AUTHOR]

Faced with problems such as unordered expansion, inefficient utilization, and the decay of old cities in the current urban development process, many scholars have considered introducing land use mix as a coping strategy. However, due to a lack of understanding of the evolution process and the theoretical connotation of land use mix, it fails to guide its role in practice. Therefore, this study summarizes the theoretical evolution of land use mix from four levels: ideological evolution, conceptual model, quantitative measurements, and influential factors and effects. It is found that after decades of evolution, although the land use mix theory initially formed a certain theoretical and methodological system, there are still some gaps or deficiencies that need to be filled or improved: (1) the theoretical framework lags behind the needs of practice; (2) in the process of evolution, the idea of modern land use mix has been given a deeper meaning; (3) the conceptual model still needs to be further improved; (4) the influencing mechanism is still unclear. [ABSTRACT FROM AUTHOR]

The 5-axis Coordinate Measuring Machine (CMM) is widely used for quality data collection of the machining parts, such as cylinder blocks and heads of the engines. High efficient inspection path planning for multiple feature groups from different stations is one of the key tasks for CMM application. In engineering practice, the inspection planning of diverse feature groups accounts for large labor cost and process development cycle. To improve the efficiency of path generation for the complex machining part, a five-axis CMM inspection path planning method considering path length, probe rotation and path reusability is proposed. Firstly, the measuring points (MPs) are classified based on feasible inspection direction cone and accessibility of the MPs to achieve the minimum times of probe rotation. Then, the rapidly exploring random trees with multi-root node (RRT-MRNC) algorithm is proposed to implement local path planning considering inspection path reuse. Furthermore, intra-group and inter-group path is generated simultaneously based on the proposed enhanced Genetic Algorithm (GA) algorithm. In order to evaluate the effectiveness of the proposed method, the cylinder block path planning case is used. Compared with the benchmark methods, the total planning time based on the proposed planning method for the dynamic tasks was reduced by 55.2% and 54.9% respectively. [ABSTRACT FROM AUTHOR]

Lappaconitine (LA) is a C-18 diterpene alkaloid isolated from Aconitum sinomontanum Nakai that has been shown to relieve mild to moderate discomfort. Various researchers have tried to explain the underlying mechanism of LA's effects on chronic pain. This article uses metabolomics technology to investigate the metabolite alterations in the dorsal root ganglion (DRG) when lappaconitine hydrobromide (LAH) was injected in an inflammatory pain model, to explain the molecular mechanism of its analgesia from a metabolomics perspective. The pain model used in this study was a complete Freund's adjuvant (CFA)-induced inflammatory pain model in rats. There were two treatment groups receiving different dosages of LAH (4 mg/kg LAH and 8 mg/kg LAH). The analgesic mechanism of LAH was investigated with an analgesic behavioral test, tissue sections, and metabolomics. The results of the analgesic behavioral experiment showed that both 4 mg/kg LAH and 8 mg/kg LAH could significantly improve the paw withdrawal latency (PWL) of rats. The tissue section results showed that LAH could reduce the inflammatory response and enlargement of the paw and ankle of rats and that there was no significant difference in the tissue sections of the DRG. The metabolomics results showed that retinol metabolism and glycerophospholipid metabolism in the CFA-induced inflammatory pain model were significantly affected and may exacerbate the inflammatory reactions and initiate persistent pain; in addition, the linoleic acid metabolism, arachidonic acid metabolism, and alanine, aspartate, and glutamate metabolism were also slightly affected. Among them, the alpha-linolenic acid metabolism was up-regulated after LAH treatment, while the retinol metabolism was down-regulated. These results suggest that LAH could effectively reduce inflammatory pain and might achieve this by regulating the lipid metabolism in the rat DRG. [ABSTRACT FROM AUTHOR]

The application of legume green manure (LGM) is a traditional and valuable practice for agroecosystem management. In the present study, we conducted a meta-analysis to explore the effect of LGM on the yields of three major grain crops in China under different cropping systems and environmental conditions based on 315 field trial datasets. LGM application increased the yield of the three major grain crops significantly by 12.60% compared to those under no LGM application, with wheat, maize, and rice yields increasing significantly by 9.49%, 16.70%, and 19.22%, respectively. In addition, yield increases were significant under crop rotation with grain crops but not under intercropping. The amount of LGM returned to the field (dry weight) at only 2000–3000 kg/ha and 3000–4000 kg/ha increased yield significantly by 12.32% and 11.94%, respectively. The greatest yield increases were observed when annual precipitation was higher than 600 mm, while annual average temperature was higher than 10 °C, and when soil organic matter content was 0–10 g/kg, with 19.64%, 14.11%, and 32.63% increases, respectively. All regions in China, excluding North China, had significant yield increases, with the largest yield increase, 27.12%, observed in Northeast China. The results of the meta-analysis demonstrated that LGM increases yield of all the three major grain crops in China. Additionally, the benefits were also observed under appropriate planting system, green manure biomass, and environmental factors. [ABSTRACT FROM AUTHOR]

Urban land-use efficiency (ULUE) has been increasingly recognized as an issue of land-use management across the world in the last century as the globe experienced unprecedented rapid urban expansion. However, although a large body of studies was dedicated to analyzing the driving forces of ULUE, literature was rarely focused on the impacts of regional cooperation on ULUE. To bridge the knowledge gap, we used the Chinese trailblazer of regional cooperation–Yangtze River delta (YRD)—as a case to reveal the impacts of regional cooperation on ULUE. Social network analysis and a super efficiency SBM model with undesirable outputs were used to measure regional cooperation and ULUE, respectively. Furthermore, the impacts of regional cooperation on ULUE were examined by using the geographically and temporally weighted regression model. The results show that regional cooperation in the YRD strengthened from 2009 to 2016, among which Shanghai was the core node city in the YRD. Only seven cities maintained good ULUE with a stable trend during 2009–2016. The regression results indicated the positive impacts of regional cooperation on ULUE, which was more evident in the southern cities of the YRD. The potential mechanism to explain the impacts of regional cooperation on ULUE includes co-building transportation facilities and joint development zones. These findings provide insightful implications for improving ULUE by strengthening regional cooperation in Chinese cities. [ABSTRACT FROM AUTHOR]

Farmers' protection behavior largely depends on their perceived value of cultivated land quality protection. However, existing research shows that the impact path of these perceived factors on farmers' cultivated land protection behavior is not clear. Based on the survey data of 288 farmers in Ningbo City, this study empirically analyzed the impact of farmers' perception on their cultivated land quality protection behavior through structural equation modeling (SEM). The results showed that farmers' cultivated land quality protection behavior largely depended on perceived value, and they followed the logic paradigm of "perceived tradeoff→perceived value→behavioral intention→behavioral response". Among them, farmers' perceived value comes from farmers' comprehensive tradeoff of benefits and risks in the process of cultivated land quality protection. In other words, improving farmers' perceived benefits and reducing perceived risks is conducive to improving farmers' perceived value of cultivated land quality protection. The above findings are helpful to improve farmers' behavior of farmland land quality protection and provide new ideas and empirical basis for the design and improvement of cultivated land quality protection policies. [ABSTRACT FROM AUTHOR]

All over the world, Industrial agglomeration has become a key to improve the efficiency of urban land use and regulate the process of urbanization. Industrial agglomeration, as a universal economic geographical phenomenon, has been extensively studied, but few scholars have discussed the relationship between industrial agglomeration and urban land use efficiency. Based on this, after classifying the type of agglomeration externalities, our study uses OLS and GTWR models to explore the complex mechanism of interaction between industrial agglomeration externalities and urban land use efficiency, especially the spatiotemporal non-stationary characteristics. We found that the impact of industrial agglomeration externalities on urban land use efficiency is significantly unstable in time and space, and the coexistence, substitution and aging mechanism of agglomeration externalities among different types were also observed. Our research can provide reference for city managers to formulate reasonable industrial policies and enterprises to choose the location. Meanwhile, our research has made some contributions to the academic research on urban land use efficiency. [ABSTRACT FROM AUTHOR]

As the most concentrated area of human activities, cities consume many natural resources and discharge a large amount of waste into the natural environment, which has a huge environmental impact. Most of the ecological and environmental problems, such as environmental pollution, global climate change, and loss of biodiversity, are related to urban systems. How to coordinate urban development with the urban ecological carrying capacity is related to the destiny of the city itself, and also to whether its surrounding areas can successfully achieve the goal of high environmental quality and sustainable development. At present, the theory and methods of urban ecological carrying capacity research are relatively new, which has caused problems for policy makers in practical applications. This paper proposes a theoretical framework for urban ecological carrying capacity assessment based on the analysis of ecosystem services supply and demand. Combined with multi-source spatial data and spatial model methods, the supply and demand of ecosystem services were spatially quantified. The capital city of China, Beijing, was the case study area for this research. The spatial differentiation of the supply–demand relationship of ecosystem services is formed. The priority areas for ecological carrying capacity improvement at pixel scale and at the administrative level are obtained, respectively. The results show that the first priority area is concentrated in the center of the urban area, accounting for 31.11% of the total area of Beijing. According to the secondary zone and the specific ecosystem service type, the ecological carrying capacity improvement strategy of different zones is proposed. This study provides a new perspective for investigating urban ecological carrying capacity and for identifying the priority areas for ecological carrying capacity improvement, and helps the policy-makers to design tailored policy actions. [ABSTRACT FROM AUTHOR]

Raspberry (Rubus idaeus L.), known as one of the famous healthy fruits an d are consumed fresh or processed products all over the world. The antioxidation activity of raspberry fruits as well as leaves have been widely investigated. To better understand the metabolite accumulation mechanisms and to develop different functional cultivars, we performed a non-targeted metabolomics analysis using LC-MS/MS to investigate the contents of existing components from three raspberry cultivars, Autumn Britten, Autumn Bliss, and Red Autumn leaves, respectively. The results show multiple differentially accumulated metabolites among three cultivars, especially for the lipids (α-linolenic acid and eicosatetraenoic acid), amino acids and their derivatives (L-cysteine, Phenylalanine), flavonoids (Kaempferol 3-O-rhamnoside-7-O-glucoside, Quercetin 3-glucoside), and vitamins (Biotin, Thiamine, Vitamin K2), etc. The in vitro cellular antioxidant activities of three raspberry cultivars leaves ethanol extracts (RLEE) were also characterized. Through comparison the superoxide dismutase (SOD), glutathione (GSH), catalase (CAT), and reactive oxygen species (ROS) levels before or after RLEE protection of L929 fibroblast cells upon excessive UVB exposure, we evaluated the antioxidation potentials for all three cultivar RLEEs. It turns out the raspberry Autumn Britten leaf extract holds the greatest potential for protecting the L929 fibroblast cells from UVB induced damage. Our study provides theoretical support for screening of active metabolites from three raspberry cultivars leaves, spanning metabolites' accumulation to cell damage protection, which could be used to refine bioactivity assessment for different raspberry cultivars suitable for antioxidant products extraction. [ABSTRACT FROM AUTHOR]

The root of Saposhnikovia divaricata (Fangfeng) is commonly used in traditional Chinese medicine (TCM) for headache and neuroinflammation-related disease treatment. The mRNA expression of IL-6 and IL-1β were significantly inhibited after Fangfeng extract (FFE) treatment in LPS-induced BV-2 cells. Metatolome profiling indicated that dopamine, palmitic acid, corticosterone, and eicosapentaenoic acid metabolites could be regulated by FFE for LPS stimulated inflammation responses in BV-2 cells. The disturbed metabolic pathways include caffeine metabolism, mannose type O-glycan biosynthesis, arachidonic acid metabolism, and steroid biosynthesis. This study will enable us to identify potential protein targets and metabolite intermediates for FFE exerting its protective function in BV-2 cells, and it also provided a potential application of Fangfeng in neuroinflammation-related disease treatment. [ABSTRACT FROM AUTHOR]

Using the daily precipitation and temperature data of 101 meteorological stations in four provinces of central China (Henan, Hubei, Hunan, Jiangxi) from 1988 to 2017, we analyzed the temporal and spatial dynamics and periodicity of nine extreme climate indices in central China, using the predefined methods for analyzing extreme climate events, such as a M-K test, a linear trend analysis, and a wavelet analysis. The extreme climate characteristics and changes in central China in the past 30 years were revealed. The results showed that the CSDI was significantly reduced linearly at a rate of −0.19 d/10a, and the WSDI and TXx increased significantly at rates of 0.25 d/10a and 0.30 °C/10a, respectively. The CDD decreased significantly at a rate of −1.67 d/10a. The duration of extreme low-temperature and drought events in central China showed a gradual shortening, while the duration of extreme high-temperature events and the high-temperature values increased. The results of the abrupt climate change test showed that some extreme climate indices in central China had significant abrupt climate changes after 2000. Analyzing the cyclicality of each index, it was determined that the extreme climate index in central China had a significant cyclical change every 2–4 years, and the change was more notable after 2000. Analyzing the spatial distribution of the extreme climate indices, it was determined that Jiangxi had the longest duration of all high-temperature events, and was the largest and longest of events of extreme precipitation. It was also determined that the Jiangxi region was at greater risk of extreme climate events in central China. The results of this study can provide a scientific basis for climate change trends, local disaster prevention, and mitigation management in central China. [ABSTRACT FROM AUTHOR]

Background: The silkworm (Bombyx mori) is an important lepidopteran model insect worldwide which undergoes a complete metamorphosis developmental process. Although genome sequencing has been long performed, no transcriptome data covering the complete life cycle are available. Methods: Herein, a total of 10 samples were collected consecutively at four different developmental stages, including eggs of 24 h after oviposition (Ed) and eggs of 24 h after artificial egg-hatching (E); larvae from fist to fifth instar (L1–L5); early and late pupa (P4 and P8); and adult moth (M), were subjected to Illumina RNA-Seq and time-course analysis. Results: The summations of the gene expression of the silkworm ten developmental stages show: at Ed stage, eggs develop towards diapause status, the total gene expression level is relatively low; at E stage, after artificial egg-hatching, the expression level improves rapidly; during larval stages from L1–L5, the expression level rises gradually and reaches a peak at L5 stage; during pupae and moth stages, the total gene expression decline stage by stage. The results revealed a dynamical gene expression profile exhibiting significant differential expressions throughout the silkworm life cycle. Moreover, stage-specific key genes were identified at different developmental stages, suggesting their functions mainly characterized in maintaining insect development and immunity homeostasis or driving metamorphosis. GO annotation and KEGG enrichment analysis further revealed the most significantly enriched and fundamentally biological processes during silkworm growth. Conclusion: Collectively, our omics data depicted the first comprehensive landscape of dynamic transcriptome throughout complete developmental processes of B. mori. Our findings also provide valuable references and novel insights into understanding the molecular developmental remodeling events for other Lepidoptera species. [ABSTRACT FROM AUTHOR]

The spatial pattern of music venues is one of the key decision-making factors for urban planning and development strategies. Understanding the current configurations and future demands of music venues is fundamental to scholars, planners, and designers. There is an urgent need to discover the spatial pattern of music venues nationwide with high precision. This paper aims at an open data solution to discover the hidden hierarchical structure of the for-profit music venues and their dynamic relationship with urban economies. Data collected from the largest two public ticketing websites are used for clustering-based ranking modeling and spatial pattern discovery of music venues in 28 cities as recorded. The model is based on a multi-stage hierarchical clustering algorithm to level those cities into four groups according to the website records which can be used to describe the total music industry scale and activity vitality of cities. Data collected from the 2018 China City Statistical Year Book, including the GDP per capita, disposable income per capita, the permanent population, and the number of patent applications, are used as socio-economic indicators for the city-level potential capability of music industry development ranking. The Spearman's rank correlation coefficient and the Kendall rank correlation coefficient are applied to test the consistency of the above city-level rankings. The results are 0.782 and 0.744 respectively, which means there is a relatively significant correlation between the scale level of current music venue configuration and the potential to develop the music industry. Average nearest neighbor index (ANNI), quadrate analysis, and Moran's I are used to identify the spatial patterns of music venues of individual cities. The results indicate that music venues in urban centers show more spatial aggregation, where the spatial accessibility of music activity services takes the lead significantly, while a certain amount of venues with high service capacity distribute in suburban areas. The findings can provide decision support for urban planners to formulate effective policies and rational site-selection schemes on urban cultural facilities, leading to smart city rational construction and sustainable economic benefit. [ABSTRACT FROM AUTHOR]

In recent years, there have been significant advancements in the research of Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV). However, several limitations and challenges still exist. For instance, researchers face constraints regarding experimental conditions and the feasibility of sample acquisition for studying SFTSV. To enhance the quality and comprehensiveness of SFTSV research, we opted to employ PMA-induced THP-1 cells as a model for SFTSV infection. Multiple time points of SFTSV infection were designed to capture the dynamic nature of the virus-host interaction. Through a comprehensive analysis utilizing various bioinformatics approaches, including diverse clustering methods, MUfzz analysis, and LASSO/Cox machine learning, we performed dynamic analysis and identified key genes associated with SFTSV infection at the host cell transcriptomic level. Notably, successful clustering was achieved for samples infected at different time points, leading to the identification of two important genes, PHGDH and NLRP12. And these findings may provide valuable insights into the pathogenesis of SFTSV and contribute to our understanding of host-virus interactions.