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In order to more accurately and quickly identify and count underwater fish targets, and to address the issues of excessive reliance on manual processes and low processing efficiency in the identification and counting of fish targets using sonar data, a method based on DIDSON and YOLOv5 for fish target identification and counting is proposed. This study is based on YOLOv5, which trains a recognition model by identifying fish targets in each frame of DIDSON images and uses the DeepSort algorithm to track and count fish targets. Field data collection was conducted at Chenhang Reservoir in Shanghai, and this method was used to process and verify the results. The accuracy of random sampling was 83.56%, and the average accuracy of survey line detection was 84.28%. Compared with the traditional method of using Echoview to process sonar data, the YOLOv5 based method replaces the step that requires manual participation, significantly reducing the time required for data processing while maintaining the same accuracy, providing faster and more effective technical support for monitoring and managing fish populations. [ABSTRACT FROM AUTHOR]

Hypothalamus is a crucial deep brain area that is responsible for the integration and coordination of various brain functions. The altered perfusion of hypothalamus during headache caused by medication-overuse headache (MOH) was previously unknown. In the current study, the altered perfusion of hypothalamic subregions in MOH patients was investigated using state-of-the-art 3D pseudo-continuous arterial spin labeling (PCASL) MR imaging. In this study, 29 normal controls subjects (NCs) and 29 MOH patients underwent 3D PCASL and brain structural MR imaging. The hypothalamus was automatically segmented into 10 subunits and the volume of each subunit was automatically determined using Freesurfer software (v7.4.1). All segmented hypothalamic subunits were converted to individual hypothalamic subunit masks. The cerebral blood flow (CBF) images were coregistered with the raw brain structural images and resliced. The CBF value of each hypothalamic subunit was extracted from the warped CBF images. The volume and CBF value of each hypothalamic subunit were analyzed using the independent sample T test and Mann–Whitney U test, receiver operating characteristic (ROC) curve analysis, and Pearson and Spearman correlation analysis. Hypothalamic subunits with significantly decreased perfusion were located in the left posterior, left tubular superior, right anterior–inferior, right tubular inferior, right tubular superior, right posterior subunit and the entire right hypothalamus [CBF value for MOH vs NC (mL/100 g·min): 48.41 ± 6.75 vs 54.08 ± 11.47, 44.44 ± 4.79 vs 48.11 ± 7.73, 41.49 (32.90, 61.46) vs 49.38 ± 10.47, 46.62 ± 7.04 vs 53.90 ± 11.75, 42.12 ± 5.74 vs 47.02 ± 9.99, 42.79 ± 5.15 vs 47.93 ± 10.48 and 43.58 ± 5.06 vs 48.65 ± 9.33, respectively] in MOH compared to NC (P < 0.05). ROC analysis for these positive subunits revealed that area under the curve was 0.658–0.693, and ROC curve for left posterior subunit had the highest specificity of 93.10% while the entire right hypothalamus had the highest sensitivity of 72.41%. Further correlation analysis showed that the CBF value of the left posterior, right anterior–inferior, right tubular superior, whole right hypothalamus presented significantly negative correlation with Hamilton Depression Scale (HAMD) score (P < 0.05). Hypoperfusion of hypothalamic subunits may contribute to the understanding of MOH pathogenesis, and the 3D PCASL could be considered as a potential diagnostic and assessment tool for MOH. [ABSTRACT FROM AUTHOR]

Globally, enhanced oil recovery (EOR) has become a pressing issue as the demand for crude oil continues to increase. This study investigates the flow and thermal-fluid–solid coupling of crude oil in a rod pump during hot water recovery and obtains the maximum recovery of crude oil in a vertical pipeline through numerical analysis. The pressure gradient in the pump barrel was first developed and deduced based on the ideal gas state equation and Bernoulli's equation. According to the rheological experiment results, it was proven that the light crude oil conforms to the Newtonian constitutive equation. Subsequently, the momentum equation of crude oil flowing in the pipeline and fluid–solid coupling heat transfer equations were established and solved using the finite difference method. The effects of the thermal recovery temperature Tw, wall thickness c, and stroke time n of the rod pump on flow Q are discussed. In particular, the flow Q within 1 min first increases and then slows down with the increase in stroke time n and reaches its maximum value at n = 7 r/min. Furthermore, flow Q decreases with an increase in c but increases as Tw increases; c = 1.2 cm, Tw = 363 K is the best oil recovery scheme. [ABSTRACT FROM AUTHOR]

Background: This study investigated clinical and laboratory characteristics of human bocavirus type 1 (HBoV1)‐plastic bronchiolitis (PB), Mycoplasma pneumoniae (MP)‐associated plastic bronchitis (PB) and MP‐NPB in children, highlighting inflammation, coagulation, and bronchoscopic needs. Methods: Data on preschool children with PB during HBoV1 or MP infection were collected, comparing MP‐PB to severe Mycoplasma pneumoniae pneumonia. Result: Compared with the MP‐PB group, the HBoV1‐PB group, with younger children, had significantly milder clinical symptoms but higher WBC counts (p =.028). The MP‐PB group exhibited notably elevated Fibrinogen (p =.045) and d‐dimer levels (p <.001). When contrasting the MP‐PB with the MP‐NPB group, children in MP‐PB group still had higher levels of d‐dimer and increased inflammatory indicators such as C‐reactive protein, procalcitonin, lactate dehydrogenase, and interleukin‐6, which were significantly elevated compared with the MP‐NPB group. MP‐PB showed a higher prevalence of plastic bronchial casts in lower lobes (p =.016) and a dominance of neutrophils in BALF cytology. Additionally, children in the MP‐PB group tended to undergo a greater number of bronchoscopies. Conclusion: This study identifies key differences in plastic bronchitis in children due to HBoV1 and MP, highlighting HBoV1's milder inflammation in younger kids and MP's link to severe inflammatory and coagulation responses, guiding clinical diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Traditional image classification usually relies on manual feature extraction; however, with the rapid development of artificial intelligence and intelligent vision technology, deep learning models such as CNNs can automatically extract key features from input images to achieve efficient classification. This study focuses on the application of lightweight separable convolutional neural networks in domain-specific image classification tasks. In this paper, we discuss how to use the SSDLite object detection algorithm combined with the MobileNetV2 lightweight convolutional architecture for puppet dynasty recognition from images—a novel and challenging task. By constructing a system that combines object detection and image classification, we aimed to solve the problem of automatic puppet dynasty recognition to reduce manual intervention and improve recognition efficiency and accuracy. We hope that this will have significant implications in the fields of cultural protection and art history research. [ABSTRACT FROM AUTHOR]

This study investigates a supply chain comprising of a manufacturer and a retail platform, wherein the former decides the quality information transparency strategy of products and the latter determines whether or not to implement price parity clauses (PPCs). The manufacturer can directly sell the end-of-season product to the end-consumer market and indirectly via the retail platform. Specifically, this study considers two quality information transparency strategies (i.e. ex-ante blockchain-adoption and ex-post voluntary disclosure) that differ on whether the manufacturer's decision on quality information transparency strategy is made before or after observing the actual product quality. Results show that the manufacturer may prefer the ex-ante blockchain-adoption strategy in specific conditions but maintains the flexibility of information disclosure under ex-post voluntary disclosure strategy. Moreover, the implementation of PPCs significantly reduces the manufacturer's incentive to disclose a large extent of quality information transparency when the effort cost is high or the service effect coefficient is low. By contrast, the manufacturer is more likely to adopt information transparency strategies under PPCs when the effort cost is low and the service effect coefficient is high. More interestingly, contrary to theories of harm from PPCs, the implementation of PPCs may simultaneously benefit the manufacturer and retail platform, achieving a 'win-win' situation. [ABSTRACT FROM AUTHOR]

Single‐cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in‐depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single‐cell isolation, which is crucial for single‐cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high‐throughput single‐cell isolation and real‐time single‐cell analysis on‐ or off‐chip. Therefore, most current single‐cell isolation and analysis technologies are based on the single‐cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single‐cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single‐cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single‐cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single‐cell isolation and multiomic and exosome analyses. [ABSTRACT FROM AUTHOR]

An amphiphilic aza‐BODIPY dye (S)‐1 bearing two chiral hydrophilic side chains with S‐stereogenic centers was synthesized. This dye exhibited kinetic‐controlled self‐assembly pathways and supramolecular chiral polymorphism properties in MeOH/H2O (9/1, v/v) mixed solvent. The (S)‐1 monomers first aggregated into a kinetic controlled, off‐pathway species Agg. A, which was spontaneously transformed into an on‐pathway metastable aggregate (Agg. B) and subsequently into the thermodynamic Agg. C. The three aggregate polymorphs of dye (S)‐1 displayed distinct optical properties and nanomorphologies. In particular, chiral J‐aggregation characteristics were observed for both Agg. B and Agg. C, such as Davydov‐split absorption bands (Agg. B), extremely sharp and intense J‐band with large bathochromic shift (Agg. C), non‐diminished fluorescence upon aggregation, as well as strong bisignated Cotton effects. Moreover, the AFM and TEM studies revealed that Agg. A had the morphology of nanoparticle while fibril or rod‐like helical nanostructures with left‐handedness were observed respectively for Agg. B and Agg. C. By controlling the kinetic transformation process from Agg. B to Agg. C, thin films consisting of Agg. B and Agg. C with different ratios were prepared, which displayed tunable CPL with emission maxima at 788–805 nm and g‐factors between −4.2×10−2 and −5.1×10−2. [ABSTRACT FROM AUTHOR]

During weaning, piglets are susceptible to intestinal inflammation and impairment in barrier function. Dietary fiber (DF) plays an active role in alleviating weaning stress in piglets. However, the effects of different sources of dietary fiber on the performance of weaned piglets are inconsistent, and the mechanisms through which they affect intestinal health need to be explored. Therefore, in this study, sixty weaned piglets were randomly divided into three treatment groups: basal diet (control, CON), beet pulp (BP), and alfalfa meal (AM) according to the feed formulation for a 28-day trial. The results showed that both AM and BP groups significantly reduced diarrhea rate and serum inflammatory factors (IL-1β and TNF-α) and increased antioxidant markers (T-AOC and SOD), in addition to decreasing serum MDA and ROS concentrations in the AM group. At the same time, piglets in the AM group showed a significant reduction in serum intestinal permeability indices (LPS and DAO) and a substantial increase in serum immunoglobulin levels (IgA, IgG, and IgM) and expression of intestinal barrier-associated genes (Claudin1, Occludin, ZO-1, and MUC1), which resulted in an improved growth performance. Interestingly, the effect of DF on intestinal inflammation and barrier function can be attributed to its modulation of gut microbes. Fiber-degrading bacteria enriched in the AM group (Christensenellaceae_R-7_group, Pediococcus and Weissella) inhibited the production of TLR4- through the promotion of SCFAs (especially butyrate). MyD88-NF-κB signaling pathway activation reduces intestinal inflammation and repairs intestinal barrier function. In conclusion, it may provide some theoretical support and rationale for AM to alleviate weaning stress and improve early intestinal dysfunction, which may have implications for human infants. [ABSTRACT FROM AUTHOR]

Lipid homeostasis is crucial for growth and development of organisms. Several cytochrome P450 monooxygenases (CYPs) are involved in lipid metabolism. The function of Cyp311a1 in the anterior midgut as a regulator of phosphatidylethanolamine (PE) metabolism in Drosophila melanogaster has been demonstrated, as depletion of Cyp311a1 caused larval growth arrest that was partially rescued by supplying PE. In this study, we investigated the role of CYP311A1 in wing morphogenesis in Drosophila. Using the GAL4‐UAS system, Cyp311a1 was selectively knocked down in the wing disc. A deformed wing phenotype was observed in flies with reduced Cyp311a1 transcripts. BODIPY and oil red O staining revealed a reduction of neutral lipids in the wing disc after the depletion of Cyp311a1. In addition, we observed an enhanced sensitivity to Eosin Y penetration in the wings of Cyp311a1 knocked‐down flies. Moreover, the reduction of CYP311A1 function in developing wings does not affect cell proliferation and apoptosis, but entails disordered Phalloidin or Cadherin distribution, suggesting an abnormal cell morphology and cell cortex structure in wing epithelial cells. Taken together, our results suggest that Cyp311a1 is needed for wing morphogenesis by participating in lipid assembly and cell homeostasis. [ABSTRACT FROM AUTHOR]

Background: Nowadays, moderate gaming behaviors can be a pleasant and relaxing experiences among adolescents. However, excessive gaming behavior may lead to gaming disorder (GD) that disruption of normal daily life. Understanding the possible risk factors of this emerging problem would help to suggest effective at preventing and intervening. This study aimed to investigate the prevalence of GD and analyze its possible risk factors that adolescents with GD. Methods: Data were collected between October 2020 and January 2021. In total, a sample of 7901 students (4080 (52%) boys, 3742 (48%) girls; aged 12–18 years) completed questionnaires regarding the Gaming-Related Behaviors Survey, Gaming Disorder Symptom Questionnaire-21 (GDSQ-21); Behavioral Inhibition System and Behavioral Activation System Scale (BIS/BAS Scale); Emotion Regulation Questionnaire (ERQ); Short-form Egna Minnenav Barndoms Uppfostran for Chinese (s-EMBU-C); and Adolescent Self-Rating Life Events Checklist (ASLEC). Results: The prevalence of GD was 2.27% in this adolescent sample. The GD gamers were a little bit older (i.e., a higher proportion of senior grades), more boys, with more gaming hours per week in the last 12 months, with more reward responsiveness, maternal rejecting and occurrence of negative life events (e.g., interpersonal relationships, being punished and bereavement factors). Conclusion: These possible risk factors may influence the onset of GD. Future research in clinical, public health, education and other fields should focus on these aspects for provide target prevention and early intervention strategies. [ABSTRACT FROM AUTHOR]

Unhealthy lifestyles (high-fat diet, smoking, alcohol consumption, too little exercise, etc.) in the current society are prone to cause lipid metabolism disorders affecting the health of the organism and inducing the occurrence of diseases. Saponins, as biologically active substances present in plants, have lipid-lowering, inflammation-reducing, and anti-atherosclerotic effects. Saponins are thought to be involved in the regulation of lipid metabolism in the body; it suppresses the appetite and, thus, reduces energy intake by modulating pro-opiomelanocortin/Cocaine amphetamine regulated transcript (POMC/CART) neurons and neuropeptide Y/agouti-related peptide (NPY/AGRP) neurons in the hypothalamus, the appetite control center. Saponins directly activate the AMP-activated protein kinase (AMPK) signaling pathway and related transcriptional regulators such as peroxisome-proliferator-activated-receptors (PPAR), CCAAT/enhancer-binding proteins (C/EBP), and sterol-regulatory element binding proteins (SREBP) increase fatty acid oxidation and inhibit lipid synthesis. It also modulates gut–liver interactions to improve lipid metabolism by regulating gut microbes and their metabolites and derivatives—short-chain fatty acids (SCFAs), bile acids (BAs), trimethylamine (TMA), lipopolysaccharide (LPS), et al. This paper reviews the positive effects of different saponins on lipid metabolism disorders, suggesting that the gut–liver axis plays a crucial role in improving lipid metabolism processes and may be used as a therapeutic target to provide new strategies for treating lipid metabolism disorders. [ABSTRACT FROM AUTHOR]

Thermal nanophotonics has undergone a revolution in recent decades, benefiting from in-depth studies in nano-optics and breakthroughs in nanotechnologies. The majority of thermal devices are constrained by Kirchhoff's law of thermal radiation, whereby spectral directional absorptivity and emissivity are identical according to Lorentz reciprocity. This restriction introduces an intrinsic loss in a plethora of energy technologies and prevents us from controlling emission and absorption independently. Recently, there has been considerable progress in realizing nonreciprocal radiation to overcome these limitations. Here we summarize the fundamental physics of nonreciprocal radiation, lay out different approaches to generalize Kirchhoff's law, and highlight several promising nonreciprocal thermal applications. This comprehensive overview of nonreciprocal thermal photonics may reveal new physics, unprecedented nonreciprocal effects and broader potential applications. This Review discusses the physics of nonreciprocal radiation and Kirchhoff's law generalization in the context of nanophotonics-enabled nonreciprocal thermal applications. [ABSTRACT FROM AUTHOR]

Numerical weather prediction (NWP), when accessible, is a crucial input to short-term solar power forecasting. WRF-Solar, the first NWP model specifically designed for solar energy applications, has shown promising predictive capability. Nevertheless, few attempts have been made to investigate its performance under high aerosol loading, which attenuates incoming radiation significantly. The North China Plain is a polluted region due to industrialization, which constitutes a proper testbed for such investigation. In this paper, aerosol direct radiative effect (DRE) on three surface shortwave radiation components (i.e., global, beam, and diffuse) during five heavy pollution episodes is studied within the WRF-Solar framework. Results show that WRF-Solar overestimates instantaneous beam radiation up to 795.3 W m−2 when the aerosol DRE is not considered. Although such overestimation can be partially offset by an underestimation of the diffuse radiation of about 194.5 W m−2, the overestimation of the global radiation still reaches 160.2 W m−2. This undesirable bias can be reduced when WRF-Solar is powered by Copernicus Atmosphere Monitoring Service (CAMS) aerosol forecasts, which then translates to accuracy improvements in photovoltaic (PV) power forecasts. This work also compares the forecast performance of the CAMS-powered WRF-Solar with that of the European Centre for Medium-Range Weather Forecasts model. Under high aerosol loading conditions, the irradiance forecast accuracy generated by WRF-Solar increased by 53.2% and the PV power forecast accuracy increased by 6.8%. Significance Statement: Numerical weather prediction (NWP) is the "go-to" approach for achieving high-performance day-ahead solar power forecasting. Integrating time-varying aerosol forecasts into NWP models effectively captures aerosol direct radiation effects, thereby enhancing the accuracy of solar irradiance forecasts in heavily polluted regions. This work not only quantifies the aerosol effects on global, beam, and diffuse irradiance but also reveals the physical mechanisms of irradiance-to-power conversion by constructing a model chain. Using the North China Plain as a testbed, the performance of WRF-Solar on solar power forecasting on five severe pollution days is analyzed. This version of WRF-Solar can outperform the European Centre for Medium-Range Weather Forecasts model, confirming the need for generating high spatial–temporal NWP. [ABSTRACT FROM AUTHOR]

Makeup transfer aims to transfer the makeup of the human face in the reference image to another face in the source image. Most mainstream makeup transfer methods directly learn the makeup, which often regard the interference information (posture, illumination, shadow and background) as part of makeup. We propose a novel Double Cycle Consistently constrained Multi-Feature Discrimination Generative Adversarial Networks (DCCMF-GAN) for makeup transfer, which is based on the separation of "makeup" and "content". DCCMF-GAN is nested by cycle reconstruction networks CycleI and CycleII, which are separately constrained by cycle consistency loss "cycle consistency1" and "cycle consistency2". Both cycle networks consist of two makeup-transfer generators G and two multi-feature discriminators, respectively. G first encodes to separate "makeup" and "content" of the source and the reference images. Then fuses the source content with reference makeup for makeup application, and merges the source makeup with reference content for makeup removal. Under the constraint of double cycle consistency loss and the adversarial learning of multi-feature discriminators in terms of identity, global makeup and focused local makeup ensure to generate pleasant makeup conversion results. Compared with several state-of-the-art makeup transfer methods, the proposed method is insensitive to pose, illumination, shadow, expression, aging and other interference, which achieves high-quality makeup transfer with strong robustness. [ABSTRACT FROM AUTHOR]

The importance of dietary fiber (DF) in animal diets is increasing with the advancement of nutritional research. DF is fermented by gut microbiota to produce metabolites, which are important in improving intestinal health. This review is a systematic review of DF in pig nutrition using in vitro and in vivo models. The fermentation characteristics of DF and the metabolic mechanisms of its metabolites were summarized in an in vitro model, and it was pointed out that SCFAs and gases are the important metabolites connecting DF, gut microbiota, and intestinal health, and they play a key role in intestinal health. At the same time, some information about host-microbe interactions could have been improved through traditional animal in vivo models, and the most direct feedback on nutrients was generated, confirming the beneficial effects of DF on sow reproductive performance, piglet intestinal health, and growing pork quality. Finally, the advantages and disadvantages of different fermentation models were compared. In future studies, it is necessary to flexibly combine in vivo and in vitro fermentation models to profoundly investigate the mechanism of DF on the organism in order to promote the development of precision nutrition tools and to provide a scientific basis for the in-depth and rational utilization of DF in animal husbandry. Key points: • The fermentation characteristics of dietary fiber in vitro models were reviewed. • Metabolic pathways of metabolites and their roles in the intestine were reviewed. • The role of dietary fiber in pigs at different stages was reviewed. [ABSTRACT FROM AUTHOR]

Straw return is one of the main methods for protecting black soil. Efficient and accurate straw return detection is important for the sustainability of conservation tillage. In this study, a rapid straw return detection method is proposed for large areas. An optimized Sh-DeepLabv3+ model based on the aforementioned detection method and the characteristics of straw return in Jilin Province was then used to classify plots into different straw return cover types. The model used Mobilenetv2 as the backbone network to reduce the number of model parameters, and the channel-wise feature pyramid module based on channel attention (CA-CFP) and a low-level feature fusion module (LLFF) were used to enhance the segmentation of the plot details. In addition, a composite loss function was used to solve the problem of class imbalance in the dataset. The results show that the extraction accuracy is optimal when a 2048 × 2048-pixel scale image is used as the model input. The total parameters of the improved model are 3.79 M, and the mean intersection over union (MIoU) is 96.22%, which is better than other comparative models. After conducting a calculation of the form–grade mapping relationship, the error value of the area prediction was found to be less than 8%. The results show that the proposed rapid straw return detection method based on Sh-DeepLabv3+ can provide greater support for straw return detection. [ABSTRACT FROM AUTHOR]

The type and composition of food strongly affect the variation and enrichment of the gut microbiota. The gut–microbiota–spleen axis has been developed, incorporating the spleen's function and maturation. However, how short-chain fatty-acid-producing gut microbiota can be considered to recover spleen function, particularly in spleens damaged by changed gut microbiota, is unknown in geese. Therefore, the gut microbial composition of the caecal chyme of geese was assessed by 16S rRNA microbial genes, and a Tax4Fun analysis identified the enrichment of KEGG orthologues involved in lipopolysaccharide production. The concentrations of LPS, reactive oxygen species, antioxidant/oxidant enzymes, and immunoglobulins were measured from serum samples and spleen tissues using ELISA kits. Quantitative reverse transcription PCR was employed to detect the Kelch-like-ECH-associated protein 1–Nuclear factor erythroid 2-related factor 2 (Keap1-Nrf2), B cell and T cell targeting markers, and anti-inflammatory/inflammatory cytokines from the spleen tissues of geese. The SCFAs were determined from the caecal chyme of geese by using gas chromatography. In this study, ryegrass-enriched gut microbiota such as Eggerthellaceae, Oscillospiraceae, Rikenellaceae, and Lachnospiraceae attenuated commercial diet-induced gut microbial alterations and spleen dysfunctions in geese. Ryegrass significantly improved the SCFAs (acetic, butyric, propionic, isovaleric, and valeric acids), AMPK pathway-activated Nrf2 redox signaling cascades, B cells (B220, CD19, and IgD), and T cells (CD3, CD4, CD8, and IL-2, with an exception of IL-17 and TGF-β) to activate anti-inflammatory cytokines (IL-4 and IL-10) and immunoglobulins (IgA, IgG, and IgM) in geese. In conclusion, ryegrass-improved reprogramming of the gut microbiota restored the spleen functions by attenuating LPS-induced oxidative stress and systemic inflammation through the gut–microbiota–spleen axis in geese. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) and bipolar disorder (BD) share clinical features, which complicates their differentiation in clinical settings. This study proposes an innovative approach that integrates structural connectome analysis with machine learning models to discern individuals with MDD from individuals with BD. High-resolution MRI images were obtained from individuals diagnosed with MDD or BD and from HCs. Structural connectomes were constructed to represent the complex interplay of brain regions using advanced graph theory techniques. Machine learning models were employed to discern unique connectivity patterns associated with MDD and BD. At the global level, both BD and MDD patients exhibited increased small-worldness compared to the HC group. At the nodal level, patients with BD and MDD showed common differences in nodal parameters primarily in the right amygdala and the right parahippocampal gyrus when compared with HCs. Distinctive differences were found mainly in prefrontal regions for BD, whereas MDD was characterized by abnormalities in the left thalamus and default mode network. Additionally, the BD group demonstrated altered nodal parameters predominantly in the fronto-limbic network when compared with the MDD group. Moreover, the application of machine learning models utilizing structural brain parameters demonstrated an impressive 90.3% accuracy in distinguishing individuals with BD from individuals with MDD. These findings demonstrate that combined structural connectome and machine learning enhance diagnostic accuracy and may contribute valuable insights to the understanding of the distinctive neurobiological signatures of these psychiatric disorders. [ABSTRACT FROM AUTHOR]

Copy-move is a common image forgery operation, which copies and moves a block of an image from one position to another place. Image hashing refers to extracting a unique number sequence from the image by using various image features. In practical application, image hashing is used to replace the image itself, which effectively reduces the cost of image storage and computational complexity. In this paper, we propose a novel image hash extraction scheme: constructing image hashing by combining local feature based on Canny operator and global feature based on tensor. In addition, instead of using the traditional correlation coefficient or Hamming distance, a novel method is proposed to calculate the hash distances. A large number of experiments have proved that our image hashing can achieve a better balance between robustness and discrimination with a shorter hash length. What's more, we can directly locate the forgery areas from the hashing for copy-move forged images. [ABSTRACT FROM AUTHOR]

Background: The age-related heterogeneity in major depressive disorder (MDD) has received significant attention. However, the neural mechanisms underlying such heterogeneity still need further investigation. This study aimed to explore the common and distinct functional brain abnormalities across different age groups of MDD patients from a large-sample, multicenter analysis. Methods: The analyzed sample consisted of a total of 1238 individuals including 617 MDD patients (108 adolescents, 12–17 years old; 411 early-middle adults, 18–54 years old; and 98 late adults, > = 55 years old) and 621 demographically matched healthy controls (60 adolescents, 449 early-middle adults, and 112 late adults). MDD-related abnormalities in brain functional connectivity (FC) patterns were investigated in each age group separately and using the whole pooled sample, respectively. Results: We found shared FC reductions among the sensorimotor, visual, and auditory networks across all three age groups of MDD patients. Furthermore, adolescent patients uniquely exhibited increased sensorimotor-subcortical FC; early-middle adult patients uniquely exhibited decreased visual-subcortical FC; and late adult patients uniquely exhibited wide FC reductions within the subcortical, default-mode, cingulo-opercular, and attention networks. Analysis of covariance models using the whole pooled sample further revealed: (1) significant main effects of age group on FCs within most brain networks, suggesting that they are decreased with aging; and (2) a significant age group × MDD diagnosis interaction on FC within the default-mode network, which may be reflective of an accelerated aging-related decline in default-mode FCs. Conclusions: To summarize, these findings may deepen our understanding of the age-related biological and clinical heterogeneity in MDD. [ABSTRACT FROM AUTHOR]

Objective: Major depressive disorder (MDD) and bipolar disorder (BD) are serious chronic disabling mental and emotional disorders, with symptoms that often manifest atypically in children and adolescents, making diagnosis difficult without objective physiological indicators. Therefore, we aimed to objectively identify MDD and BD in children and adolescents by exploring their voiceprint features. Methods: This study included a total of 150 participants, with 50 MDD patients, 50 BD patients, and 50 healthy controls aged between 6 and 16 years. After collecting voiceprint data, chi-square test was used to screen and extract voiceprint features specific to emotional disorders in children and adolescents. Then, selected characteristic voiceprint features were used to establish training and testing datasets with the ratio of 7:3. The performances of various machine learning and deep learning algorithms were compared using the training dataset, and the optimal algorithm was selected to classify the testing dataset and calculate the sensitivity, specificity, accuracy, and ROC curve. Results: The three groups showed differences in clustering centers for various voice features such as root mean square energy, power spectral slope, low-frequency percentile energy level, high-frequency spectral slope, spectral harmonic gain, and audio signal energy level. The model of linear SVM showed the best performance in the training dataset, achieving a total accuracy of 95.6% in classifying the three groups in the testing dataset, with sensitivity of 93.3% for MDD, 100% for BD, specificity of 93.3%, AUC of 1 for BD, and AUC of 0.967 for MDD. Conclusion: By exploring the characteristics of voice features in children and adolescents, machine learning can effectively differentiate between MDD and BD in a population, and voice features hold promise as an objective physiological indicator for the auxiliary diagnosis of mood disorder in clinical practice. [ABSTRACT FROM AUTHOR]

In the context of digitization, the insurance industry's value chain is undergoing significant shifts. However, the existing research on its comprehension and measurement remains relatively limited. This study constructs an index system for digital transformation in the insurance industry (DTII) on three components: digital infrastructure, digital platform, and digital applications. Utilizing data from 31 provinces in China, this study employs the entropy weight method, analytic hierarchy process method and minimum relative entropy method to measure the weights of indicators, empirically applying this index system. The results show that DTII in China experiences rapid advancement with an average annual growth rate of 20.46% from 2014 to 2020 and there exists strong regional convergence. In addition, the spatial agglomeration and spatial effects of DTII are mainly concentrated in the life insurance industry and the eastern region. This study provides an index system and empirical evidence for evaluating the DTII, providing policy insights for exploring the sustainable development path of the insurance industry in the digital era. [ABSTRACT FROM AUTHOR]

Aerosols play a crucial role in the surface radiative budget by absorbing and scattering both shortwave and longwave radiation. While most aerosol types exhibit a relatively minor longwave radiative forcing when compared to their shortwave counterparts, dust aerosols stand out for their substantial longwave radiative forcing. In this study, radiometers, a sun photometer, a microwave radiometer and the parameterization scheme for clear-sky radiation estimation were integrated to investigate the radiative properties of aerosols. During an event in Xianghe, North China Plain, from 25 April to 27 April 2018, both the composition (anthropogenic aerosol and dust) and the aerosol optical depth (AOD, ranging from 0.3 to 1.5) changed considerably. A notable shortwave aerosol radiative effect (SARE) was revealed by the integrated system (reaching its peak at −131.27 W·m−2 on 26 April 2018), which was primarily attributed to a reduction in direct irradiance caused by anthropogenic aerosols. The SARE became relatively consistent over the three days as the AODs approached similar levels. Conversely, the longwave aerosol radiative effect (LARE) on the dust days ranged from 8.94 to 32.93 W·m−2, significantly surpassing the values measured during the days of anthropogenic aerosol pollution, which ranged from 0.35 to 28.67 W·m−2, despite lower AOD values. The LARE increased with a higher AOD and a lower Ångström exponent (AE), with a lower AE having a more pronounced impact on the LARE than a higher AOD. It was estimated that, on a daily basis, the LARE will offset approximately 25% of the SARE during dust events and during periods of heavy anthropogenic pollution. [ABSTRACT FROM AUTHOR]

Background: There is no evidence supporting the feasibility of laparoscopic pancreaticoduodenectomy (LPD) compared to open pancreatoduodenectomy (OPD) following neoadjuvant chemotherapy (NACT) for pancreatic ductal adenocarcinoma (PDAC). Methods: The clinical data of consecutive patients with borderline resectable PDAC who received NACT and underwent either LPD or OPD between January 2020 and December 2022 at Fudan University Shanghai Cancer Center was prospectively collected and retrospectively analyzed. Results: The analysis included 57 patients in the OPD group and 20 in the LPD group. Following NACT, the LPD group exhibited a higher median CA19-9 decrease rate compared to the OPD group (85.3% vs. 66.9%, P = 0.042). Furthermore, 3 anatomically borderline PDACs in the LPD group and 5 in the OPD group were downstaged into resectable status (30.0% vs. 12.3%, P = 0.069). According to RECIST criteria, 51 (66.2%) patients in the entire cohort were evaluated as having stable disease. The median operation time for the LPD group was longer than the OPD group (419 vs. 325 min, P < 0.001), while the venous resection rate was 35.0% vs. 43.9%, respectively (P = 0.489). There was no difference in the number of retrieved lymph nodes, with a median number of 18.5 in the LPD group and 22 in the OPD group, and the R1 margin rate (15.0% vs. 12.3%) was also comparable. The incidence of Clavien-Dindo complications (35.0% vs. 66.7%, P = 0.018) was lower in the LPD group compared to the OPD group. Multivariable regression analysis revealed that a tumor diameter > 3 cm before NACT (HR 2.185) and poor tumor differentiation (HR 1.805) were independent risk factors for recurrence-free survival, and a decrease rate of CA19-9 > 70% (OR 0.309) was a protective factor for early tumor recurrence and overall survival. Conclusions: LPD for PDAC following NACT is feasible and oncologically equivalent to OPD. Effective control of CA19-9 levels is beneficial in reducing early tumor recurrence and improving overall survival. [ABSTRACT FROM AUTHOR]

Travel activity data mining is critical to numerous urban applications such as transportation and location‐based services. This article studies the spatial units ranking algorithm for uncovering spatial interaction patterns based on the flow properties of people's travel trajectories. For example, using a taxi origin–destination flow database, a user may want to rank the origin and destination with respect to their functional importance within the urban activity space. In the literature, such an importance concept is usually specified via the frequency function of trip flows. Considering the case that the less frequently visited place in reality may still be an important origin or an important destination, we propose a different method for the ranking of spatial units by introducing the structural property of trip network. The proposed method is inspired from the mutual reinforcing relationship between the trip origins and destinations: important destinations attract travel flows from important origins and at the same time important origins have many flows toward important destinations. Our experimental results show that the proposed method is effective in uncovering spatial interaction patterns of urban activities. [ABSTRACT FROM AUTHOR]

The importance of dietary fiber (DF) in animal diets is increasing with the advancement of nutritional research. DF is fermented by gut microbiota to produce metabolites, which are important in improving intestinal health. This review is a systematic review of DF in pig nutrition using in vitro and in vivo models. The fermentation characteristics of DF and the metabolic mechanisms of its metabolites were summarized in an in vitro model, and it was pointed out that SCFAs and gases are the important metabolites connecting DF, gut microbiota, and intestinal health, and they play a key role in intestinal health. At the same time, some information about host-microbe interactions could have been improved through traditional animal in vivo models, and the most direct feedback on nutrients was generated, confirming the beneficial effects of DF on sow reproductive performance, piglet intestinal health, and growing pork quality. Finally, the advantages and disadvantages of different fermentation models were compared. In future studies, it is necessary to flexibly combine in vivo and in vitro fermentation models to profoundly investigate the mechanism of DF on the organism in order to promote the development of precision nutrition tools and to provide a scientific basis for the in-depth and rational utilization of DF in animal husbandry. Key points: • The fermentation characteristics of dietary fiber in vitro models were reviewed. • Metabolic pathways of metabolites and their roles in the intestine were reviewed. • The role of dietary fiber in pigs at different stages was reviewed. [ABSTRACT FROM AUTHOR]

Aim: The present study aimed to develop the Risk Perception Scale of Disease Aggravation for older patients with non‐communicable diseases and evaluate its psychometric properties. Design: Instrument development and cross‐sectional validation study were conducted. Methods: This study contained four phases. In phase I, a systematic literature review was conducted to identify the conception of disease aggravation and risk perception. In phase II, a draft scale was formulated from face‐to‐face semi‐structured in‐depth interviews by Colaizzi's seven‐step qualitative analysis method and group discussions among the researchers. In phase III, domains and items of the scale were revised in accordance with the suggestions from Delphi consultation and patient feedback. In phase IV, psychometric properties were evaluated. Findings: Exploratory and confirmatory factor analyses determined four structural factors. Convergent and discriminant validities were acceptable because the average variance extracted coefficients ranged from.622 to.725, and the square roots of the average variance extracted coefficients for the four domains were larger than those of bivariate correlations between domains. The scale also exhibited excellent internal consistency and test–retest reliability (Cronbach's alpha coefficient =.973, intraclass correlation coefficient =.840). Conclusions: Risk Perception Scale of Disease Aggravation is a new instrument that measures the risk perception of disease aggravation for older patients with non‐communicable diseases, including possible reason, serious outcome, behaviour control and affection experience. The scale contains 40 items that are scored on a 5‐point Likert scale, and it has acceptable validity and reliability. Impact: The scale is applied to identify different levels of risk perception of disease aggravation for older patients with non‐communicable diseases. Clinical nurses can provide targeted interventions to improve older patients' risk perception of disease aggravation based on levels of risk perception during hospitalization and the period before discharge. Patient or Public Contribution: Experts provided suggestions for revising the scale dimensions and items. Older patients participated in the scale revision process to improve the wording of the scale. [ABSTRACT FROM AUTHOR]

Uranium extraction through the in situ leaching method stands as a pivotal approach in uranium mining. In an effort to comprehensively assess the repercussions of in situ uranium leaching on groundwater quality, this study collected 12 representative groundwater samples within the Bayan-Uul mining area. The basic statistical characteristics of the water samples showed that the concentrations of SO42− and total dissolved solids (TDS) were relatively high. Through the use of cluster analysis, the water samples were categorized into two distinct clusters. Seven samples from wells W-d, W-u, N01, W10-2, W08-1, W10-1, and W13-1, situated at a considerable distance from the mining area, were grouped together. Conversely, five samples from wells W08-2, W13-2, W01-1, W02-2, and the pumping well located in closer proximity to the mining area, formed a separate cluster. A decision tree-based machine learning approach was employed to discern the influence of various hydrochemical indicators in forming these clusters, with results indicating that SO42− exerts the most substantial influence, followed by Ca2+. The mineral saturation indices from geochemical modeling indicated that, as the distance from the mining area increased, the trend of calcium minerals changed from dissolution to precipitation; iron minerals were in a precipitation state, and the precipitation trend was gradually weakening. In light of these findings, it is clear that in situ uranium leaching significantly impacted the groundwater in the vicinity of the mining area. The prolonged consumption of groundwater sourced near the study area, or its use for animal husbandry, poses potential health risks that demand heightened attention. [ABSTRACT FROM AUTHOR]

High blood pressure is a major risk factor for cardiovascular disease, and frequent use of blood pressure medications can have side effects. Therefore, safe and efficient food-borne antihypertensive peptides have become the focus of attention. In this study, a quantitative structure-activity relationship (QSAR) model of angiotensin-converting enzyme (ACE) inhibitory peptide was established to determine the relationship between the structure and activity of ACE inhibitory peptide. The model results were combined with computer virtual enzyme digestion to determine proteolytic sites accurately. Suitable proteases were selected to hydrolyze hemp seed protein to prepare ACE inhibitory peptide, and the inhibitory effect of the final hydrolysate was determined. The results showed that the SVM-AAindex model based on dipeptide had the best predictive performance (R² 0.81, RMSE 0.53), and had a strong ACE inhibition effect when the C-terminal amino acids of dipeptide were hydrophobic and aromatic amino acids. The analysis of protein components showed that hemp seed protein contains 34.60% hydrophobic amino acids and aromatic amino acids, which is a good source for preparing ACE inhibitory peptides. The alkaline and subtilisin, which produced more short peptides and bioac-tive peptides by virtual enzyme digestion, were selected for directed hydrolysis of hemp seed protein. The ACE inhibition values of the final hydrolysates were 1.89 and 2.30 mg/mL, respectively. In this study, an efficient and accurate method for preparing ACE inhibitory peptide from hemp seed protein was established, which has a good application prospect in antihypertensive drugs. [ABSTRACT FROM AUTHOR]

Recently, with the rapid development of cloud storage, secure cloud computing and privacy protection have attracted widespread attention. Reversible data hiding in encrypted images (RDHEI) plays an important role in it and has been paid more and more attention. In this paper, an improved RHDEI is proposed. By combining adaptive Arithmetic coding and static Huffman coding, the image bit-plane is effectively compressed and a lot of space is made for data embedding. The security of image and embedded data is guaranteed by XOR-encryption and scrambling encryption. The data extractor can embed and extract data without decrypting the carrier image to protect the privacy of the image owner. Experimental results show that the scheme can achieve an average embedding capacity (EC) of up to 3 bpp while ensuring lossless recovery of carrier images and correct extraction of embedded data. Compared with state-of-the-art RDHEI methods, our scheme achieves higher EC and better security. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has resulted in significant global impacts on human society. With the evolution of cities during this period, urban facilities can rise and fall, showing different spatial patterns and function structures in local areas. Analyzing the change of urban facilities before and after the pandemic can assist to understand the impact of the COVID-19 on cities, which is especially important for the Wuhan city. In this paper, we first characterized the "birth", "death" and "retention" of urban facilities through matching POIs (Points of Interest) before and after the pandemic, and then examined their spatial distribution patterns across the city. In addition, spatial association patterns mining was applied to explore the interactions between the change of urban facilities and the environmental factors. The results revealed that the catering service has decreased the most in the wake of the pandemic, while accommodation service has grown the most. The state changes of catering service, living service and shopping service frequently appear together in the data mining results. During the pandemic, these types of urban facility changes are closely linked to each other. Many regional urban functions have also changed due to the epidemic, which are most obvious in the community. This update can facilitate the management of gated communities after the pandemic. [ABSTRACT FROM AUTHOR]

An unmanned aerial vehicle (UAV) observation platform obtained the first vertical profiles of particle number size distribution (PNSD) from 7 to 16 July 2022 on the eastern slope of the Tibetan Plateau (ESTP). The results were from two flanks at the Chuni (CN) and Tianquan (TQ) sites, which are alongside a mountain (Mt. Erlang). The observations revealed a significant negative correlation between the planetary boundary layer height (PBLH) and the particle number concentration (PNC), and the correlation coefficient was −0.19. During the morning, the rise in the PBLH at the CN and TQ sites caused decreases of 16.43% and 58.76%, respectively, in the PNC. Three distinct profile characteristics were classified: Type I, the explosive growth of fine particles with a size range of 130–272 nm under conditions of low humidity, strong wind shear, and northerly winds; Type II, the process of particles with a size range of 130–272 nm showing hygroscopic growth into larger particles (e.g., 226–272 nm) under high humidity conditions (RH > 85%), with a maximum vertical change rate of about −1653 # cm−3 km−1 for N130–272 and about 3098 # cm−3 km−1 for N272–570; and Type III, in which during the occurrence of a surface low-pressure center and an 850 hPa low-vortex circulation in the Sichuan Basin, polluting air masses originating from urban agglomeration were transported to the ESTP region, resulting in an observed increase in the PNC below 600 nm. Overall, this study sheds light on the various factors affecting the vertical profiles of PNSD in the ESTP region, including regional transport, meteorological conditions, and particle growth processes, helping us to further understand the various features of the aerosol and atmospheric physical character in this key region. [ABSTRACT FROM AUTHOR]

Background: Gaming disorder is a new disease, which is included in the disease unit of disorder caused by addiction in the 11th revision of the International Classification of Diseases. This study examined the symptom characteristics of gaming disorders in Chinese adolescents using the latent profile analysis. Methods: Totally, 5988 students (including 3285 boys and 2703 girls; aged 12–18 years) from junior high schools and senior high schools were enrolled. The Gaming Disorder Symptom Questionnaire-21 (GDSQ-21) was used to screen gaming disorder. A latent profile analysis was used for classifying the subgroups based on the extent of gaming usage. The relationship between adolescent gamers and demographic variables was analyzed by logistic regression. Results: The results of latent profile analysis supported the models of four latent profiles, which were defined as healthy gamers (Profile 1, 56.83%), impaired control gamers (Profile 2, 26.09%), impaired control-game priority gamers (Profile 3, 9.72%) and gamers with disorder (Profile 4, 7.36%), respectively. Logistic regression analysis found that, compared with girls, boys were more likely to be classified into the group dominated by the impaired gamers, the impaired control-game priority gamers, and the gamers with disorder. Conclusions: This study highlighted that the latent profile analysis identified four different groups of adolescent gamers, showing a clearer conceptualization of heterogeneous gamers. Gender and average weekly gaming time can predict the latent profile of adolescents. Our findings may facilitate the design of individualized assessment and early intervention programs for adolescent gamer users based on different gaming usage symptoms. [ABSTRACT FROM AUTHOR]

Peanut vine is a typical peanut by-product and can be used as a quality roughage resource. Whole-plant corn silage is a commonly used roughage. However, few studies have investigated the effects of diets combining peanut vine and whole-plant corn silage on growth performance, antioxidant capacity, meat quality, rumen fermentation and microbiota of beef cattle. To investigate these effects, eighty Simmental crossbred cattle (body weight, 451.27 ± 10.38 kg) approximately 14 months old were randomly divided into four treatments for a 90-day feeding experiment. A one-way design method was used in this experiment. According to the roughage composition, the cattle were divided into a control treatment of 45% wheat straw and 55% whole-plant corn silage (WG), and three treatments of 25% peanut vine and 75% whole-plant corn silage (LPG), 45% peanut vine and 55% whole-plant corn silage (MPG), and 65% peanut vine and 35% whole-plant corn silage (HPG), and the concentrate was the same for all four treatment diets. The results showed that compared to the WG group, the MPG group experienced an increase in their average daily feed intake of 14%, an average daily gain of 32%, and an increase in SOD activity in the spleen of 33%; in the meat, dry matter content increased by 11%, crude protein by 9%, and ether extract content by 40%; in the rumen, the NH3-N content was reduced by 36%, the relative abundance of Firmicutes increased, and the relative abundance of Bacteroidetes decreased (p < 0.05). These results showed the composition of 45% peanut vine and 55% whole-plant corn silage in the roughage improved growth performance, antioxidant capacity, meat quality, rumen fermentation, and microbiota of beef cattle. [ABSTRACT FROM AUTHOR]

As one of the world's major forestry countries, accurate forest-type maps in China are of great importance for the monitoring and management of forestry resources. Classifying and mapping forest types on a large scale across the country is challenging due to the complex composition of forest types, the similarity of spectral features among forest types, and the need to collect and process large amounts of data. In this study, we generated a medium-resolution (30 m) forest classification map of China using multi-source remote sensing images and local samples. A mapping framework based on Google Earth Engine (GEE) was constructed mainly using the spectral, textural, and structural features of Sentinel-1 and Sentinel-2 remote sensing images, while local acquisition data were utilized as the mapping channel for training. The proposed method includes the following steps. First, local data processing is performed to obtain training and validation samples. Second, Sentinel-1 and Sentinel-2 data are processed to improve the classification accuracy by using the enhanced vegetation index (EVI) and the red-edge position index (REPI) computed based on the S2A data. Third, to improve classification efficiency, useless bands are removed and important bands are retained through feature importance analysis. Finally, random forest (RF) is used as a classifier to train the above features, and the classification results are used for mapping and accuracy evaluation. The validation of the samples showed an accuracy of 82.37% and a Kappa value of 0.72. The results showed that the total forest area in China is 21,662,261.17 km 2 , of which 1,127,294.42 km 2 of coniferous forests account for 52% of the total area, 981,690.98 km 2 of broad-leaf forests account for 45.3 % of the total area, and 57,275.77 km 2 of mixed coniferous and broad-leaf forests account for 2.6% of the total area. Upon further evaluation, we found that textural and structural features play a greater role in classification compared to spectral features. Our study shows that combining multi-source high-resolution remote sensing imagery with locally collected samples can produce forest maps for large areas. Our maps can accurately reflect the distribution of forests in China, which is conducive to forest conservation and development. [ABSTRACT FROM AUTHOR]

Smilax glabra Roxb (S. glabra) is a conventional Chinese medicine that is mainly used for the reliability of inflammation. However, bioactive polysaccharides from S. glabra (SGPs) have not been thoroughly investigated. Here, we demonstrate for the first time that SGPs preserve the integrity of the gut epithelial layer and protect against intestinal mucosal injury induced by dextran sulfate sodium. Mechanistically, SGPs mitigated colonic mucosal injury by restoring the association between the gut flora and innate immune functions. In particular, SGPs increased the number of goblet cells, reduced the proportion of apoptotic cells, improved the differentiation of gut tight junction proteins, and enhanced mucin production in the gut epithelial layer. Moreover, SGPs endorsed the propagation of probiotic bacteria, including Lachnospiraceae bacterium, which strongly correlated with decreased pro-inflammatory cytokines via the blocking of the TLR-4 NF-κB and MyD88 pathways. Overall, our study establishes a novel use of SGPs for the treatment of inflammatory bowel disease (IBD)-associated mucosal injury and provides a basis for understanding the therapeutic effects of natural polysaccharides from the perspective of symbiotic associations between host innate immune mechanisms and the gut microbiome. [ABSTRACT FROM AUTHOR]

We study a two-echelon supply chain with two homogeneous manufacturers and one common retailer who has full knowledge about his own value-added service cost structure that is unknown to the manufacturers. The retailer may choose to disclose his cost information to the manufacturers. Using a three-stage game-theoretic model, we derive optimal pricing strategies for each participant, and optimal information sharing strategies, and the optimal level of the value-added services for the retailer. Our study also reveals when the manufacturers should accept the disclosed information by the retailer. It is shown that information sharing does not always create a win–win situation among the partners in the supply chain. When the value-added service cost efficiency is low, the retailer is willing to share complete information with the manufacturers; however, information sharing harms the manufacturers' profits if they accept the shared information. In contrast, when the value-added service cost efficiency is high, the common retailer has no incentive to share information with the manufacturers and the unique equilibrium is no information sharing. Finally, we utilize a revenue-sharing contract to achieve supply chain coordination and induce information sharing under asymmetric information. [ABSTRACT FROM AUTHOR]

Mobile robot path planning involves designing optimal routes from starting points to destinations within specific environmental conditions. Even though there are well-established autonomous navigation solutions, it is worth noting that comprehensive, systematically differentiated examinations of the critical technologies underpinning both single-robot and multi-robot path planning are notably scarce. These technologies encompass aspects such as environmental modeling, criteria for evaluating path quality, the techniques employed in path planning and so on. This paper presents a thorough exploration of techniques within the realm of mobile robot path planning. Initially, we provide an overview of eight diverse methods for mapping, each mirroring the varying levels of abstraction that robots employ to interpret their surroundings. Furthermore, we furnish open-source map datasets suited for both Single-Agent Path Planning (SAPF) and Multi-Agent Path Planning (MAPF) scenarios, accompanied by an analysis of prevalent evaluation metrics for path planning. Subsequently, focusing on the distinctive features of SAPF algorithms, we categorize them into three classes: classical algorithms, intelligent optimization algorithms, and artificial intelligence algorithms. Within the classical algorithms category, we introduce graph search algorithms, random sampling algorithms, and potential field algorithms. In the intelligent optimization algorithms domain, we introduce ant colony optimization, particle swarm optimization, and genetic algorithms. Within the domain of artificial intelligence algorithms, we discuss neural network algorithms and fuzzy logic algorithms. Following this, we delve into the different approaches to MAPF planning, examining centralized planning which emphasizes decoupling conflicts, and distributed planning which prioritizes task execution. Based on these categorizations, we comprehensively compare the characteristics and applicability of both SAPF and MAPF algorithms, while highlighting the challenges that this field is currently grappling with. [ABSTRACT FROM AUTHOR]

The Cauchy problems of Keller-Segel system with logistic source seem much less throughly understood than associated initial-boundary problems in bounded domains. This paper is concerned with the Cauchy problem of Keller-Segel system with generalized logistic source given by$ \begin{eqnarray*} \left\{ \begin{array}{llc} \label{188} u_t = \Delta u - \nabla \cdot (u\nabla v)+\lambda u-\mu u^{k}, \\ 0 = \Delta v+u, \end{array} \right. \end{eqnarray*} $in $ \mathbb{R}^{n} $ for $ n\ge 3 $, where $ \lambda\in \mathbb{R} $, $ \mu >0 $, $ k>1 $.Under the assumption $ k<\frac{3}{2}-\frac{1}{n} $, it is shown that there exists $ m_{*}>0 $ such that if the radially symmetric initial data satisfies $ \int_ {B_{\frac{1}{2}}(0)}u_{0}\geq m_{*} $, then the problem admits a finite-time blowup solution. [ABSTRACT FROM AUTHOR]

A poor quality of life (QoL) in patients with pulmonary hypertension (PH) is often associated with emotional disturbances and the ability to cope. Little is known, however, about the intrinsic links among the QoL, fear of disease progression (FoP), and coping styles in patients with PH. The purpose of this study was to elucidate the relationships among QoL, FoP, and coping styles in patients with PH. We conducted a cross‐sectional survey of 247 patients from a tertiary hospital in Jinan, China and analyzed the relationships using network analysis. Participants completed the World Health Organization's Quality of Life Questionnaire, Fear of Disease Progression Questionnaire and Simple Coping Style Questionnaire during the survey period. The total QoL, positive coping, and negative coping scores were 46.55 ± 10.46, 31.75 ± 6.85, and 18.75 ± 4.66, respectively. The QoL psychological domain had the strongest centrality, deserving more attention than other domains. The coping styles were bridge nodes that connected the whole network, where negative coping and social family FoP, and positive coping and both social and psychological QoL had the strongest positive correlations. There were no significant sex‐based or age‐based differences in the networks. To improve QoL and psychological well‐being in people with PH, healthcare professionals must focus on issues beyond the patient's physical health. Specifically, they should focus on positive coping styles, while developing interventions to promote positive coping and reduce negative coping styles. [ABSTRACT FROM AUTHOR]