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Ship target detection faces the challenges of complex and changing environments combined with the varied characteristics of ship targets. In practical applications, the complexity of meteorological conditions, uncertainty of lighting, and the diversity of ship target characteristics can affect the accuracy and efficiency of ship target detection algorithms. Most existing target detection methods perform well in conditions of a general scenario but underperform in complex conditions. In this study, a collaborative network for target detection under foggy weather conditions is proposed, aiming to achieve improved accuracy while satisfying the need for real-time detection. First, a collaborative block was designed and SCConv and PCA modules were introduced to enhance the detection of low-quality images. Second, the PAN + FPN structure was adopted to take full advantage of its lightweight and efficient features. Finally, four detection heads were used to enhance the performance. In addition to this, a dataset for foggy ship detection was constructed based on ShipRSImageNet, and the mAP on the dataset reached 48.7%. The detection speed reached 33.3 frames per second (FPS), which is ultimately comparable to YOLOF. It shows that the model proposed has good detection effectiveness for remote sensing ship images during low-contrast foggy days.

The intense changes in glaciers in the southeastern Tibetan Plateau (SETP) have essential impacts on regional water resource management. In order to study the seasonal fluctuations of glaciers in this region and their relationship with climate change, we focus on the Yigong Zangbo River Basin in the SETP, extract the annual and seasonal variations of glaciers in the basin during 2018–2023, and analyze their spatio-temporal characteristics through the seasonal-trend decomposition using the LOESS (STL) method. Finally, combining the Extreme Gradient Boosting (XGBoost) model and the Shapley additive explanations (SHAP) model, we assess the comprehensive impact of meteorological factors such as temperature and snowfall on glacier changes. The results indicate that glaciers in the Yigong Zangbo River Basin experienced remarkable mass loss during 2018–2023, with an average annual melting rate of −0.83 ± 0.12 m w.e.∙yr−1. The glacier mass exhibits marked seasonal fluctuations, with increases in January–March (JFM) and April–June (AMJ) and noticeable melting in July–September (JAS) and October–December (OND). The changes over these four periods are 2.12 ± 0.04 m w.e., 0.93 ± 0.15 m w.e., −1.58 ± 0.19 m w.e., and −1.32 ± 0.17 m w.e., respectively. Temperature has been identified as the primary meteorological driver of glacier changes in the study area, surpassing the impact of snowfall. This study uses advanced altimetry data and meteorological data to monitor and analyze glacier changes, which provides valuable data for cryosphere research and also validates a set of replicable research methods, which provides support for future research in related fields.

Acute myeloid leukemia (AML) is a heterogeneous hematological malignancy that is often associated with relapse and drug resistance after standard chemotherapy or targeted therapy, particularly in older patients. Hematopoietic stem cell transplants are looked upon as the ultimate salvage option with curative intent. Adoptive cell therapy using chimeric antigen receptors (CAR) has shown promise in B cell malignancies and is now being investigated in AML. Initial clinical trials have been disappointing in AML, and we review current strategies to improve efficacy for CAR approaches. The extensive number of clinical trials targeting different antigens likely reflects the genetic heterogeneity of AML. The limited number of patients reported in multiple early clinical studies makes it difficult to draw conclusions about CAR safety, but it does suggest that the efficacy of this approach in AML lags behind the success observed in B cell malignancies. There is a clear need not only to improve CAR design but also to identify targets in AML that show limited expression in normal myeloid lineage cells.

(1) Background: Depression and anxiety are the most common and severe mental disorders. This research estimated the prevalence and disease burden of depression and anxiety from 1990 to 2044. (2) Methods: Data on disease burden, population, and risk factors were identified and gathered from the Global Health Data Exchange database. The time trends, sex and age differences, key factors, and regional variations in and predictions of depression and anxiety were analyzed based on the age-standardized incidence rate, prevalence rate, and DALY rate. (3) Results: Our findings revealed that the burden of depression and anxiety was heavy. Specifically, the age-standardized DALY rate of depression started to decrease compared with trends related to anxiety disorders. Meanwhile, females bear a heavier burden for both depression and anxiety. Seniors and the middle-aged population carry the highest burden regarding mental disorders. Both high- and low-socio-demographic-index countries were found to be high-risk regions for depressive disorders. The disease burden attributed to childhood sexual abuse, bullying victimization, and intimate partner violence has increased since 1990. Finally, projections regarding depression and anxiety revealed geographic and age variations. (4) Conclusions: Public health researchers, officers, and organizations should take effective age-, sex-, and location-oriented measures.

The intestinal microbiota and its metabolites are essential for the health and growth development of animals. Current research indicates that sex has a certain impact on the structure and function of the intestinal microbiota, but there are few reports on sex differences in intestinal microbiota metabolites, including those of castrated male animals. This study aimed to explore the impact of sex on the intestinal microbial metabolites of Hainan special wild boars (10 entire male pigs, 10 female pigs, and 10 castrated male pigs, denoted EM, FE, and CM, respectively) by employing non-targeted metabolomics and gas chromatography. A total of 1086 metabolites were detected, with the greatest number of differential metabolites observed between EM and FE (54 differential metabolites, including 18 upregulated and 36 downregulated metabolites), the fewest between CM and FE (7 differential metabolites, including 1 upregulated and 6 downregulated metabolites), and an intermediate number between CM and EM (47 differential metabolites, including 35 upregulated and 12 downregulated metabolites). Differential metabolites were involved in more pathways between EM and FE and between CM and EM, including amino acid metabolism and digestive system pathways, whereas differential metabolites were involved in the fewest pathways between CM and FE. Correlation analysis showed Ruminococcaceae UCG-009, uncultured_bacterium_o_SAR324_cladeMarine_group_B, and Candidatus Saccharimonas contributed to the production of metabolites such as trehalose, docosatrienoic acid, D(−)-beta-hydroxy butyric acid, and acetyl-DL-leucine. The levels of acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid, and isovaleric acid were significantly higher in EM than in FE, with CM falling between the two. Streptococcus, Lachnospiraceae_NK4A136_group and Rikenellaceae_RC9_gut_group showed a significant positive correlation with the production of short-chain fatty acids (SCFAs), while [Eubacterium]_coprostanoligenes_group, uncultured_bacterium_f_p–251–o5 and Ruminococcaceae_UCG–005 showed a significant negative correlation with the generation of SCFAs. This study provides foundational data and significant insights into precision feeding strategies for Hainan special wild boars of different sexes, as well as the study of sex differences in intestinal microbial metabolites in animals.

This study analyzed the applicability of five long-term precipitation datasets in the Hang-Jia-Hu Plain of eastern China based on meteorological observation data. The accuracy of each dataset at different time scales (yearly, monthly) was analyzed. Besides, their spatiotemporal distributions and differences in precipitation event frequency were also compared. The results indicate that the high-resolution (1 day, 1 km) and long-term (1961–2019) gridded dataset for temperature and precipitation across China (HRLT) exhibited the best overall performance at the annual scale, while the long-term, gauge-based gridded precipitation dataset for the Chinese mainland (CHM_PRE) performed the best at the monthly scale. The dataset of monthly precipitation with a resolution of 1 km in China from 1960 to 2020 (HHU) and the China Meteorological Forcing Dataset (CMFD) tend to overestimate the local precipitation amounts, while the other three products are characterized by an underestimation. The mean result of the five datasets indicates a slight, statistically insignificant rise in precipitation, by 4.19 mm annually, with an overall multi-year average of 1303.28 mm. The analysis of the five datasets successfully captures the spatial precipitation patterns across the Hang-Jia-Hu Plain, characterized by higher precipitation levels in the southwest and lower in the northeast. Although the interannual variability displays general consistency, there are significant discrepancies in the interannual growth rates and the spatial distribution of significance across different regions. This study can provide a reference for the accuracy of precipitation data in the fields of hydrology, meteorology, agriculture, and ecology, facilitating the analysis of uncertainties in related research.

Reinforced concrete structures play a pivotal role in island and reef engineering projects. Given the resource constraints typical of island regions, substituting traditional manufactured sand aggregate with reef limestone not only reduces reliance on river sand but also addresses the issue of disposing of waste reef limestone slag generated during excavation. However, the performance characteristics of reef limestone concrete, particularly its bond strength with reinforcing steel, warrant further investigation. This is particularly true for the bond–slip behavior of the reinforcement. This study aims to elucidate the effects of various parameters on the bond performance between steel and reef limestone concrete through central pullout tests. These parameters include the type and diameter of the reinforcement, bond length, and loading rate. The investigation encompasses the analysis of load–slip curves, bond failure modes, and variations in bond stress. Additionally, using the Abaqus software, a numerical simulation was conducted to analyze the mesoscopic stress characteristics, thereby revealing the mechanisms of bond formation and failure modes between steel reinforcement and reef limestone concrete. The results indicate that the bond–slip curve for reef limestone concrete reinforced with ribbed rebars and Glass Fiber-Reinforced Polymer (GFRP) rebars can be broadly categorized into four phases: minor slip, slip, decline, and residual, with the residual phase exhibiting a wave-like pattern. The predominant failure modes in reef limestone concrete are either pulling out or splitting. The bond stress in reef limestone concrete decreases with an increase in rebar diameter and bond length; conversely, it increases with the loading rate, although the ultimate slip decreases. The mesoscopic failure characteristics of reinforced reef limestone concrete, as simulated in Abaqus, are consistent with the experimental outcomes.

With the increase in the production of electric vehicles (EVs) globally, a significant volume of waste power battery modules (WPBM) will be generated accordingly, posing challenges for their disposal. An intelligent scrap power battery disassembly sequence planning method, integrated with operational risk perception, is proposed to automate the planning process. Taking into consideration the risk coefficients, energy consumption, and costs during disassembly, this method maximizes profits, minimizes energy usage, and ensures safety. Utilizing an extended part priority graph, an optimized model for integrated risk-aware disassembly sequence planning (IRA-DSP) is constructed. With the Guangqi Toyota LB7A-FX1 as a case study, and using real data from resource recovery enterprises, an improved MOPSO-GA algorithm is proposed to solve the model and generate disassembly plans. The results demonstrate the method’s ability to achieve unit-level disassembly of WPBM, avoid high-risk sequences, and optimize profit and energy consumption, exhibiting its practicality and feasibility.

Intensive increases in electrical energy storage are being driven by electric vehicles (EVs), smart grids, intermittent renewable energy, and decarbonization of the energy economy. Advanced lithium–sulfur batteries (LSBs) are among the most promising candidates, especially for EVs and grid-scale energy storage applications. In this topical review, the recent progress and perspectives of practical LSBs are reviewed and discussed; the challenges and solutions for these LSBs are analyzed and proposed for future practical and large-scale energy storage applications. Major challenges for the shuttle effect, reaction kinetics, and anodes are specifically addressed, and solutions are provided on the basis of recent progress in electrodes, electrolytes, binders, interlayers, conductivity, electrocatalysis, artificial SEI layers, etc. The characterization strategies (including in situ ones) and practical parameters (e.g., cost-effectiveness, battery management/modeling, environmental adaptability) are assessed for crucial automotive/stationary large-scale energy storage applications (i.e., EVs and grid energy storage). This topical review will give insights into the future development of promising Li–S batteries toward practical applications, including EVs and grid storage.

The length-biased lognormal distribution is a length-biased version of lognormal distribution, which is developed to model the length-biased lifetime data from, for example, biological investigation, medical research, and engineering fields. Owing to the existence of censoring phenomena in lifetime data, we study the change-point-testing problem of length-biased lognormal distribution under random censoring in this paper. A procedure based on the modified information criterion is developed to detect changes in parameters of this distribution. Under the sufficient condition of the Fisher information matrix being positive definite, it is proven that the null asymptotic distribution of the test statistic follows a chi-square distribution. In order to evaluate the uncertainty of change point location estimation, a way of calculating the coverage probabilities and average lengths of confidence sets of change point location based on the profile likelihood and deviation function is proposed. The simulations are conducted, under the scenarios of uniform censoring and exponential censoring, to investigate the validity of the proposed method. And the results indicate that the proposed approach performs better in terms of test power, coverage probabilities, and average lengths of confidence sets compared to the method based on the likelihood ratio test. Subsequently, the proposed approach is applied to the analysis of survival data from heart transplant patients, and the results show that there are differences in the median survival time post-heart transplantation among patients of different ages.

Burns and scarring are considered some of the greatest problems in public health because of their frequent occurrence. Today, photo-electric technology shows promising results in the treatment of burn scars. Over the years, more clinical trials and more technologies for scarring have emerged. The aim of this study was to determine better timing and methods of photo-electric therapy for burn scars. This study was registered in PROSPERO (CRD42023397244), following the PRISMA statement, and was carried out in concordance with the PRISMA checklist. In October 2022, we searched PubMed.gov, Embase, and the Cochrane library (1980–present) for published studies related to the photo-electric treatment of burn scars. Two review authors independently selected the studies, extracted the data, assessed the risk of bias among the studies included, and carried out NIH assessments to assess the certainty of the evidence. A third review author arbitrated any disagreements. Our research included 39 studies. We found evidence suggesting that photo-electric therapy between six months and one year offers significantly better outcomes than treatment of scarring after one year. The evidence also suggests the use of IPL for the treatment of early burn scarring. However, it is important to emphasize that the scientific evidence remains insufficient. We need more clinical trials of higher quality and with less heterogeneity to confirm our results.

The application of green energy resources is gaining increasing attention in the field of engineering. In cold areas, the groundwater circulation temperature control system (GCTCS) can serve as an auxiliary structure to the bridge deck on highways, effectively preventing the pavement surface from freezing. In this study, a finite element simulation is conducted to establish a bridge structure model of the GCTCS, incorporating both steady-state and transient conditions to investigate its anti-icing performance. Additionally, the influences of various factors, such as wind speed, asphalt concrete layer thickness, groundwater temperature, pipe water flow rate, and pipe spacing, on the temperature of the water film on the pavement surface are investigated and validated through laboratory testing. The results demonstrate that wind speed has a significant influence, with the convective heat loss reaching 90% when the wind speed reaches 10 m/s. Groundwater temperature is the second most influential factor, showing a linear relationship with the water film temperature. Excessive pipe spacing can lead to an uneven temperature distribution on the pavement surface. The thickness of the asphalt concrete layer and the flow rate have minimal effects. However, a low flow rate can result in a significant decrease in the water film temperature. Furthermore, changes in the thermal conductivity of the surface layers also contribute to the anti-icing effect. The simulation analysis of the GCTCS provides valuable guidance for practical engineering in cooler regions where groundwater resources are abundant.

In this article, a novel cross-domain knowledge transfer method is implemented to optimize the tradeoff between energy consumption and information freshness for all pieces of equipment powered by heterogeneous energy sources within smart factory. Three distinct groups of use cases are considered, each utilizing a different energy source: grid power, green energy source, and mixed energy sources. Differing from mainstream algorithms that require consistency among groups, the proposed method enables knowledge transfer even across varying state and/or action spaces. With the advantage of multiple layers of knowledge extraction, a lightweight knowledge transfer is achieved without the need for neural networks. This facilitates broader applications in self-sustainable wireless networks. Simulation results reveal a notable improvement in the ’warm start’ policy for each equipment, manifesting as a 51.32% increase in initial reward compared to a random policy approach.

The development of global urbanization has brought about a significant amount of solid waste. These untreated wastes may be dumped in any corner, causing serious pollution to the environment. Thus, it is necessary to accurately obtain their distribution locations and detailed edge information. In this study, a practical deep learning network for recognizing solid waste piles over extensive areas using unmanned aerial vehicle (UAV) imagery has been proposed and verified. Firstly, a high-resolution dataset serving to solid waste detection was created based on UAV aerial data. Then, a dual-branch solid waste semantic segmentation model was constructed to address the characteristics of the integration of solid waste distribution with the environment and the irregular edge morphology. The Context feature branch is responsible for extracting high-level semantic features, while the Spatial feature branch is designed to capture fine-grained spatial details. After information fusion, the model obtained more comprehensive feature representation and segmentation ability. The effectiveness of the improvement was verified through ablation experiments and compared with 13 commonly used semantic segmentation models, demonstrating the advantages of the method in solid waste segmentation tasks, with an overall accuracy of over 94%, and a recall rate of 88.6%—much better than the best performing baselines. Finally, a spatial distribution map of solid waste over Jiaxing district, China was generated by the model inference, which assisted the environmental protection department in completing environmental management. The proposed method provides a feasible approach for the accurately monitoring of solid waste, so as to provide policy support for environmental protection.

Hainan yellow cattle are indigenous Zebu cattle from southern China known for their tolerance of heat and strong resistance to disease. Generations of adaptation to the tropical environment of southern China and decades of artificial breeding have left identifiable selection signals in their genomic makeup. However, information on the selection signatures of Hainan yellow cattle is scarce. Herein, we compared the genomes of Hainan yellow cattle with those of Zebu, Qinchuan, Nanyang, and Yanbian cattle breeds by the composite likelihood ratio method (CLR), Tajima’s D method, and identifying runs of homozygosity (ROHs), each of which may provide evidence of the genes responsible for heat tolerance in Hainan yellow cattle. The results showed that 5210, 1972, and 1290 single nucleotide polymorphisms (SNPs) were screened by the CLR method, Tajima’s D method, and ROH method, respectively. A total of 453, 450, and 325 genes, respectively, were identified near these SNPs. These genes were significantly enriched in 65 Gene Ontology (GO) functional terms and 11 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (corrected p < 0.05). Five genes—Adenosylhomocysteinase-like 2, DnaJ heat shock protein family (Hsp40) member C3, heat shock protein family A (Hsp70) member 1A, CD53 molecule, and zinc finger and BTB domain containing 12—were recognized as candidate genes associated with heat tolerance. After further functional verification of these genes, the research results may benefit the understanding of the genetic mechanism of the heat tolerance in Hainan yellow cattle, which lay the foundation for subsequent studies on heat stress in this breed.

Owing to their rich structural chemistry and unique electrochemical properties, vanadium-based materials, especially the low-dimensional ones, are showing promising applications in energy storage and conversion. In this invited review, low-dimensional vanadium-based materials (including 0D, 1D, and 2D nanostructures of vanadium-containing oxides, polyanions, and mixed-polyanions) and their emerging applications in advanced alkali-metal-ion batteries (e.g., Li-ion, Na-ion, and K-ion batteries) are systematically summarized. Future development trends, challenges, solutions, and perspectives are discussed and proposed. Mechanisms and new insights are also given for the development of advanced vanadium-based materials in high-performance energy storage and conversion.

Our skin is constantly exposed to blue light (BL), which is abundant in sunlight and emitted by digital devices. Prolonged exposure to BL can lead to oxidative stress-induced damages and skin hyperpigmentation. For this study, we used a cell line-based model to examine the protective effects of tocotrienol-rich fraction (TRF) on BL-induced oxidative stress and hyperpigmentation in B16-F1 melanocytes. Alpha-tocopherol (αTP) was used as a comparator. Molecular assays such as cell viability assay, flow cytometry, western blotting, fluorescence imaging, melanin and tyrosinase analysis were performed. Our results showed that TRF effectively suppressed the formation of reactive oxygen species and preserved the mitochondrial membrane potential. Additionally, TRF exhibited anti-apoptotic properties by reducing the activation of the p38 mitogen-activated protein kinase molecule and downregulating the expression of cleaved caspase-3. Moreover, TRF modulated tyrosinase activity, resulting in a lowered rate of melanogenesis and reduced melanin production. In contrast, αTP did not exhibit significant protective effects against skin damages and pigmentation in BL-induced B16-F1 cells. Therefore, this study indicates that TRF may offer superior protective effects over αTP against the effects of BL on melanocytes. These findings demonstrate the potential of TRF as a protective natural ingredient that acts against BL-induced skin damages and hyperpigmentation via its anti-oxidative and anti-melanogenic properties.

With the rapid development of modern technology and information systems, optical anti-counterfeiting and encryption have recently attracted considerable attention. The demand for optical materials is also constantly increasing, with new requirements proposed for performance and application fields. Currently, rare earth ion doped materials possess a unique electronic layer structure, underfilled 4f5d electronic configuration, rich electronic energy level, and long-life excited state, which can produce a variety of radiation absorption and emission. The distinctive properties of rare earth are beneficial for using in diverse optical output anti-counterfeiting. Design is essential for rare earth ion doped materials with multiple responsiveness and multi-channel optical information anti-counterfeiting in the field of information security. Therefore, this mini review summarizes the luminescent mechanisms, preparation methods, performance characteristics and anti-counterfeiting application of rare earth doped materials. In addition, we discuss some critical challenges in this field, and potential solutions that have been or are being developed to overcome these challenges.

Background: This study investigates the accuracy, stability, and safety of computer-assisted microcatheter shaping for intracranial aneurysm coiling. Methods: Using the solid model, a microcatheter was shaped using computer-assisted techniques or manually to investigate the accuracy and delivery of microcatheter-shaping techniques in aneurysm embolization. Then, forty-eight patients were randomly assigned to the computer-assisted microcatheter-shaping (CAMS) group or the manual microcatheter-shaping (MMS) group, and the accuracy, stability, and safety of microcatheter in the patients were compared between the CAMS and MMS groups. Results: The speed of the successful microcatheter position was significantly faster in the CAMS group than in the MMS group (114.4 ± 23.99 s vs. 201.9 ± 24.54 s, p = 0.015) in vitro. In particular for inexperienced operators, the speed of the microcatheter position with the assistance of computer software is much faster than manual microcatheter shaping (93.6 ± 29.23 s vs. 228.9 ± 31.27 s, p = 0.005). In vivo, the time of the microcatheter position in the MMS group was significantly longer than that in the CAMS group (5.16 ± 0.46 min vs. 2.48 ± 0.32 min, p = 0.0001). However, the mRS score at discharge, the 6-month follow-up, and aneurysm regrowth at the 6-month follow-up were all similar between the groups. Conclusions: Computer-assisted microcatheter shaping is a novel and safe method for microcatheter shaping that introduces higher accuracy in microcatheter shaping during the treatment of intracranial aneurysms. Significant: Endovascular coiling of intracranial aneurysms can be truly revolutionized through computer assistance, which could improve the endovascular treatment of aneurysms.

Berries are highly perishable and susceptible to spoilage, resulting in significant food and economic losses. The use of chemicals in traditional postharvest protection techniques can harm both human health and the environment. Consequently, there is an increasing interest in creating environmentally friendly solutions for postharvest protection. This article discusses various approaches, including the use of “green” chemical compounds such as ozone and peracetic acid, biocontrol agents, physical treatments, and modern technologies such as the use of nanostructures and molecular tools. The potential of these alternatives is evaluated in terms of their effect on microbial growth, nutritional value, and physicochemical and sensorial properties of the berries. Moreover, the development of nanotechnology, molecular biology, and artificial intelligence offers a wide range of opportunities to develop formulations using nanostructures, improving the functionality of the coatings by enhancing their physicochemical and antimicrobial properties and providing protection to bioactive compounds. Some challenges remain for their implementation into the food industry such as scale-up and regulatory policies. However, the use of sustainable postharvest protection methods can help to reduce the negative impacts of chemical treatments and improve the availability of safe and quality berries.

In scenarios of indoor localization of mobile robots, Global Positioning System (GPS) signals are prone to loss due to interference from urban building environments and cannot meet the needs of robot localization. On the other hand, traditional indoor localization methods based on wireless signals such as Bluetooth and WiFi often require the deployment of multiple devices in advance, and these methods can only obtain distance information and are unable to obtain the attitude of the positioning target in space. This paper proposes a method for the indoor localization of mobile robots based on a depth camera. Firstly, we extracted ORB feature points from images captured by a depth camera and performed homogenization processing. Then, we performed feature matching between adjacent two frames of images, and the mismatched points are eliminated to improve the accuracy of feature matching. Finally, we used the Iterative Closest Point (ICP) algorithm to estimate the camera’s pose, thus achieving the localization of mobile robots in indoor environments. In addition, an experimental evaluation was conducted on the TUM dataset of the Technical University of Munich to validate the feasibility of the proposed depth-camera-based indoor localization system for mobile robots. The experimental results show that the average localization accuracy of our algorithm on three datasets is 0.027 m, which can meet the needs of indoor localization for mobile robots.

The objective of this study was to investigate the effects of dietary supplemental chlorogenic acid and baicalin (CAB) on the growth performance and immunity of broilers challenged with lipopolysaccharide (LPS). This study was designed as a factorial arrangement of 2 dietary CAB treatments × 2 LPS treatments. Birds challenged with or without LPS were fed with a basic diet (CON) and (LPS), the level of CAB diet containing 500 mg/kg CAB(CAB) and (CAB + LPS). The feeding trial lasted for 42 days. Results showed that there was a negative effect on average daily weight gain (ADG) and average body weight of broilers during the animal trial with LPS challenge. The levels of diamine oxidase (DAO), lysozyme (LYZ), immunoglobulin G (IgG), and IgA in the serum, the contents of IL-1β and TNF-α in the spleen were elevated with LPS treated. Additionally, LPS treatment tended to reduce the jejunal villi height (VH) and total superoxide dismutase (T-SOD) in the serum. Dietary supplemental 500 mg/kg CAB increased the body weight and ADG and improved the feed conversion ratio (FCR) during the trial period. In addition, dietary 500 mg/kg CAB elevated the ratio of VH to crypt depth in the jejunum and reduced the content of protein carbonyl. Beyond that, the levels of IgG and IgA in the serum and transforming growth factor (TGF-β) in the spleen were up-regulated with 500 mg/kg CAB supplementation. In conclusion, dietary CAB was beneficial for growth performance and immunity of broilers challenged with lipopolysaccharide.

When added to mushroom growing substrates, edible and medicinal herbs affect the mushrooms’ nutritional and medicinal value. In this study, polysaccharides (P0OP-I and P15OP-I) were extracted and purified from oyster mushrooms grown on substrates supplemented with 0% and 15% Astragalus roots (P0 and P15), respectively, and their chemical structure and immunobiological activities were compared. P15OP-I and P0OP-I were extracted using ultrasound-assisted hot water and deproteinized with the Sevage method, depigmented with 30% H2O2, desalted with dialysis, and purified using DEAE-52 cellulose and Sephadex G-100 dextran column chromatography. The molecular weight of P0OP-I and P15OP-I was 21,706.96 and 20,172.65 Da, respectively. Both were composed of monosaccharides D-mannose, galacturonic acid, D-glucose, D-galactose, and L-arabinose but in different molar ratios, and both were connected by a pyranoside linkage. P15OP-I consisted of higher contents of mannose, glucose, galactose and arabinose and lower content of galacturonic acid as compared to P0OP-I. Both P0OP-I and P15OP-I induced NO and TNF-α production but did not show cytotoxic effect or induce ROS generation in RAW264.7 cells. P15OP-I showed a stronger ability to promote NO and TNF-α production relative to P0OP-I. In vitro experiments showed that the immunomodulatory activity of P0OP-I and P15OP-I in RAW264.7 macrophages were mediated by the JNK/MAPK, Erk/MAPK, and NF-κB signaling pathways. The results would be helpful for elucidation of the health promoting mechanism of Astragalus oyster mushrooms as a source of neutraceuticals.

To satisfy the design requirements for a hydropneumatic spring damper valve, the inlet–outlet pressure drop (ΔP) and the axial force on the spool (FZ) of a valve were investigated using fluid–solid coupling simulations and multi-objective optimization, along with the effects of the diameters of three internal holes (DA, DB, and DC) in the valve on the ΔP and the FZ. First, a meshed computational fluid dynamics model of a damper valve was established based on its geometric structure. Next, the effects of the flow rate (Q) and the diameter of the damping hole in the internal structure on the ΔP and the FZ of the damper valve were investigated. The results showed that the ΔP and the FZ varied nonlinearly with Q. For a given Q, the ΔP decreased as DA, DB, and DC increased. For a given Q, the FZ was not related to DA and DC, but it decreased as DB increased. Finally, the structure of the damper valve was optimized by defining the ΔP and the FZ as the response variables and DA, DB, and DC as the explanatory variables. The results showed that the best configuration of the hole diameters was DA = 8.8 mm, DB = 5.55 mm, and DC = 6 mm. In this configuration, ΔP = 0.704 MPa and FZ = 110.005 N. The ΔP of the optimized valve was closer to the middle value of the target range than that of the initial valve design. The difference between the simulated and target values of the FZ decreased from 0.28% to 0.0045%, satisfying application requirements.

The geometrical configuration is one of the main factors that affect the thermoelectric performance of a device. Research on the trapezoidal thermoelectric generator (TTEG) with varied cross section is mainly based on finite element simulation and experiment. In this paper, an explicit analytical solution of the maximum output power of annular thermoelectric generators (ATEG) is proposed, which has been proved to have high accuracy. Then, the maximum output power between ATEG and TTEG is compared. Results show that, for the appropriate geometric parameter δ, the relative error of maximum output power between explicit analytical ATEG and the simulated solution of TTEG can reach the order of 10−3. When the hot end is at the a side, the high temperature and θ is 510 K and 10°, respectively. For Bi2Te3 material and PbTe material, the relative error of maximum output power between the explicit analytical and simulated solution is 0.0261% and 0.074%, respectively. Under suitable working conditions, the explicit analytical results of ATEG can provide some reference for the performance optimization of TTEG.

A stable life support system in the spacecraft can greatly promote long-duration, far-distance, and multicrew manned space flight. Therefore, controlling the concentration of CO2 in the spacecraft is the main task in the regeneration system. The electrocatalytic CO2 reduction can effectively treat the CO2 generated by human metabolism. This technology has potential application value and good development prospect in the utilization of CO2 in the space station. In this paper, recent research progress for the electrocatalytic reduction of CO2 was reviewed. Although numerous promising accomplishments have been achieved in this field, substantial advances in electrocatalyst, electrolyte, and reactor design are yet needed for CO2 utilization via an electrochemical conversion route. Here, we summarize the related works in the fields to address the challenge technology that can help to promote the electrocatalytic CO2 reduction. Finally, we present the prospective opinions in the areas of the electrocatalytic CO2 reduction, especially for the space station and spacecraft life support system.

The rapid proliferation of the emerging yet promising notion of the Internet-of-Vehicles (IoV) has led to the development of a variety of conventional trust assessment schemes to tackle insider attackers. The primary reliance of these frameworks is on the accumulation of individual trust attributes. While aggregating these influential parameters, weights are often associated with each individual attribute to reflect its impact on the final trust score. It is of paramount importance that such weights be precise to lead to an accurate trust assessment. Moreover, the value of the minimum acceptable trust threshold employed for the identification of dishonest vehicles needs to be carefully defined to avoid delayed or erroneous detection. This paper employs an IoT data set from CRAWDAD by suitably transforming it into an IoV format. This data set encompasses information regarding 18,226 interactions among 76 nodes, both honest and dishonest. First, the influencing parameters (i.e., packet delivery ratio, familiarity, timeliness and interaction frequency) were computed, and two feature matrices were formed. The first matrix (FM1) takes into account all the pairwise individual parameters as individual features, whereas the second matrix (FM2) considers the average of all pairwise computations performed for each individual parameter as one feature. Subsequently, unsupervised learning is employed to achieve the ground truth prior to applying supervised machine learning algorithms for classification purposes. It is worth noting that Subspace KNN yielded a perfect precision, recall, and the F1-score equal to 1 for individual parametric scores, whereas Subspace Discriminant returned an ideal precision, recall, and the F1-score equal to 1 for mean parametric scores. It is also evident from extensive simulations that FM2 yielded more accurate classification results compared to FM1. Furthermore, decision boundaries among honest and dishonest vehicles have also been computed for respective feature matrices.

Gut microbiota and their metabolites play important roles in animal growth by influencing the host’s intake, storage, absorption, and utilization of nutrients. In addition to environmental factors, mainly diet, chicken breed and growth stage also affect changes in the gut microbiota. However, little research has been conducted on the development of gut microbiota and its metabolites in local chickens. In this study, the cecal microbiota and metabolites in different developmental stages of Hainan Wenchang chickens (a native breed of Bantam) were investigated using 16S rRNA sequencing and untargeted metabolomics. With aging, the structure of gut microbiota tended to be more stable. The relative proportions of dominant bacteria phyla Firmicutes, Bacteroidetes, and Proteobacteria showed stage changes with the development. With aging, gut microbiota and their metabolites may have structural and functional changes in response to nutrient metabolism and immune requirements in different physiological states. Several microbial and metabolic biomarkers with statistical differences were detected in different development stages. The bacteria that form networks with their significant related metabolites were different in various growth stages, including uncultured_bacterium_f_Ruminococcaceae, Ruminococcaceae_UCG-014, Faecalibacterium, uncultured_bacterium_o_Bacteroidales, and uncultured_bacterium_f_Lachnospiraceae. Partially differential bacteria were significantly correlated with short-chain fatty acids such as butyric acid. These findings may provide new insights into the physiological and molecular mechanisms of developmental changes of local chicken breeds, as well as resources for microbial and metabolic biomarker identification to improve growth efficiency.

The Kumaraswamy distribution is a common type of bounded distribution, which is widely used in agriculture, hydrology, and other fields. In this paper, we use the methods of the likelihood ratio test, modified information criterion, and Schwarz information criterion to analyze the change point of the Kumaraswamy distribution. Simulation experiments give the performance of the three methods. The application section illustrates the feasibility of the proposed method by applying it to a real dataset.

Controlled-release urea (CRU) is widely adopted to improve yields and nitrogen use efficiencies (NUEs) in rice. However, there are few studies on the effects of the mixed application of CRU and normal urea (at different N ratios) on rice yield, nitrogen efficiency, and grain quality. A series of simplified fertilization modes (SFMs) were set up in 2018–2019. CRU with release periods of 80 days and 120 days were mixed with urea at N ratios of 7:3, 6:4, 5:5, 4:6, and 3:7 and applied during the rice-growing season. We determined the rice yield, dry matter accumulation, NUEs, and grain quality. The yields of SFM_80_6/4 (CRU with release periods of 80 days were mixed with urea at N ratios of 6:4) and SFM_120_5/5 (CRU with release periods of 120 days were mixed with urea at N ratios of 5:5) were 3.69% and 4.39% higher than that of fractionated urea (FU), respectively, across 2018 and 2019. Combining the application of controlled-release urea and normal urea improved the dry matter accumulation, nitrogen accumulation, and nitrogen uptake rate when compared with FU. SFMs improved the processing quality and appearance quality of rice grains and did not reduce the cooking and eating quality. SFM_80_6/4 and SFM_120_5/5 are a one-time fertilization mode with high yield, high efficiency, and good grain quality, which is worthy of further promotion and application.

Despite the rich nutritional content of okara, the majority remains underutilized and discarded as food waste. In this study, solid-state fermentation of okara with food-grade fungi was performed to extract and solubilize any remnant nutrients locked within the lignocellulosic matrix to produce a nutrient-rich okara fermentate. Fermented okara media (FOM) was used as the sole nutrient source for growing marine diatom, Phaeodactylum tricornutum. Results have shown a two-fold increase in biomass production when grown on FOM (0.52 g L−1) as compared with conventional Guillard’s F/2 media (0.25 g L−1). Furthermore, cellular fucoxanthin content was enhanced significantly by two-fold to reach a final concentration of 15.3 mg g−1 compared to 7.3 mg g−1. Additionally, a significantly higher amount of polyunsaturated fatty acid (PUFA) was produced, particularly eicosapentaenoic acid (EPA) which yield has increased by nearly three-fold. Metabolomics analysis of intracellular contents in fermented okara culture revealed a significantly enhanced accumulation of nitrogenous metabolites, alongside the decrease in sugar metabolites as compared to F/2 culture, thus indicating metabolic flux towards pathways involved in cellular growth. This study demonstrated an innovative and low-cost strategy of using fermented okara as a nutritious substrate for achieving a sustainable media replacement for high density algal growth with a simultaneous enhancement of production in highly valued nutraceuticals, including fucoxanthin and EPA.

The fluid inerter is a new mechanical element which has received great attention in the field of vibration reduction. However, due to the influence of secondary flow in the curved channel, the damping force is too large and the inertia force is relatively small, which limits the engineering applications of the single-cylinder fluid inerter. To eliminate the influence of secondary flow in the single-cylinder fluid inerter, this paper proposes a dual-cylinder fluid inerter that has a straight tube instead of the spiral pipe or spiral groove. We Analyze the working principle, derive conditions of free movement, establish the damping force and inertia force model, and prove the validity of the model through bench testing. Contrastingly, it is found that the maximum parasitic damping force is only 40.32% of the single-cylinder structure, but the inertia force increases to 180.96% of the single-cylinder structure. The proposed inerter greatly increases the proportion of inertia force, and provides a new scheme for engineering applications.

Helpful for human health, omega-3 (n-3)-enriched eggs are preferred by consumers. However, antioxidants should be added to the hen’s diet to prevent n-3 fatty acid oxidation due to their unsaturated bonds. A study was designed to investigate the effects of different antioxidants on performance, egg quality, fatty acid profile, oxidation parameters, gene expression, and magnum morphology. A total of 450 hens were divided into five dietary groups. Wheat–flaxseed was used for the basic diet (control) and supplemented with vitamin E (VE), chlorogenic acid (CA), polyphenol (PF), and lutein (L). The experiment lasted for 10 weeks. The eggs were collected on the 5th week and were analyzed for quality, oxidative stability, and fatty acid (FA) content, being stored for 0 d, 7 d, 14 d, 21 d, 28 d, 35 d, and 42 d. The results showed that supplemental VE, PF, CA, and L improved the egg weight and hen day egg production compared to the control group (p < 0.05). The VE, PF, and L groups significantly (p < 0.05) reduced the malondialdehyde (MDA) and maintained the superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and total antioxidant capacity (T-AOC) in the egg yolk. The albumen height and Haugh unit were maintained in the egg yolk till 35 days of storage by the VE, PF, and L groups, while the CA group reduced the albumen quality after 21 d storage. The VE, PF, CA, and lutein maintained the content of alpha-linolenic acid (ALA), during the whole storage period. The total n-3 FA and docosahexaenoic acid (DHA) were retained in the egg yolk till 35 and 28 days of storage, respectively, and slightly decreased after 35 and 28 days in the L groups. The total n-6 (Tn-6) FA was maintained in the yolk till 28 days of storage in the CA and PF groups, respectively. The VE, PF, and L groups upregulated the expression of Nrf-2, P38MAPK, HO-1, SOD-1, and GSH-Px as compared to the CA and control groups. The VE, PF, and L groups significantly increased the magnum primary folds and epithelium height as compared to CA and the control. Thus, it was concluded that the use of PF and L is better at preventing egg quality deterioration and lipid oxidation, maintaining more than 300 mg/egg n-3 FA during storage, by activating the Nrf-2 pathway through the phosphorylation of P38MAPK, and enhancing the phase-2 antioxidant defense enzymes, namely, SOD, GSH-Px, and HO-1.

The cow’s milk production characteristics are a significant economic indicator in the livestock industry. Serum cytokines such as interleukin-17 (IL-17) may be potential indicators for bovine mastitis concerning the milk somatic cell count (SCC) and somatic cell score (SCS). The current study aims to find previously undiscovered single nucleotide polymorphisms in the bovine (IL-17A) gene and further investigates their associations with milk production traits in Chinese Holstein cows. Twenty Chinese Holstein cows were randomly chosen from six farms in Jiangsu Province, China. The DNA was extracted from selected samples of bloods for PCR amplification Sequence analyses were used to find SNPs in the bovine (IL-17A) gene. The discovered five SNPs are g-1578A>G, g-1835G>A, and g-398T>A in the 5′UTR; g3164T>C and g3409G>C in the exon region. The genotyping of Holstein cows (n = 992) was performed based on Sequenom Mass ARRAY and SNP data. The connection between SNPs, milk production variables, and the somatic cell score was investigated using the least-squares method. Based on the results, SNP g-398T>A had a significant linkage disequilibrium with g3164T>C. SNPs were found to have significant (p < 0.05) correlations with the test-day milk yield. In conclusion, IL-17A affects cow’s milk production traits significantly.

Cadmium is one of the most toxic heavy metals and can be easily absorbed by plants, affecting root growth. Root border cells (RBCs), that are located in the periphery of the root cap and originate from the root cap meristem, represent a convenient tool to study the toxic effects of Cd on root performance. In this work, vegetables with contrasting types of root apical meristem (RAM) organizations were used. The open RAM organizations included pea and cucumber, and the closed RAM organizations included tomato, chili, and eggplant. The number of RBCs were significantly higher in the species possessing open RAM organization: pea (11,330 cells per root) > cucumber (8200) > tomato (2480) > eggplant (1830) > chili (1320). The same trend was observed for cell viability: pea (61%) > cucumber (59%) > tomato (49%) > eggplant (44%) > chili (42%). Pea and cucumber had higher relative radicle elongation rates and a lower increase in stress-induced accumulation of malondialdehyde (MDA), making them more resistant to Cd stress than the vegetables with close RAM organization. Under Cd treatment, the number and viability of RBCs in vegetables with both types of RAM organization were significantly decreased. However, the decreasing ratio of the number and viability of RBCs in pea and cucumber was higher than in tomato, chili, and eggplant. Taken together, the plants with the open-type RAM are more tolerant to Cd, and it can be speculated that the cadmium tolerance of the vegetables may be correlated with the number and viability of RBCs in response to cadmium stress.

Coffee agro-waste is a potential source of polyphenols with antioxidant activity and application in the food and cosmetic trades. The usage of these byproducts persists as a challenge in the industrial landscape due to their high content of purported toxic substances hindering management. This study presents a green extractive process using pulsed electric field (PEF) and microwave assisted extraction (MAE) to recover polyphenols from coffee parchment and two varieties of pulp, posing quick processing times and the use of water as the only solvent. The performance of this process with regard to the bioactivity was assessed through the Folin-Ciocalteu assay, total flavonoid content, DPPH, ABTS and FRAP antioxidant tests. The phenolic composition of the extracts was also determined through HPLC-MS and quantified through HPLC-DAD. When compared to treatment controls, PEF + MAE treated samples presented enhanced yields of total phenolic content and radical scavenging activity in all analyzed residues (Tukey test significance: 95%). The chromatographic studies reveal the presence of caffeic acid on the three analyzed by-products. The HPLC-DAD caffeic acid quantification validated that a combination of MAE + PEF treatment in yellow coffee pulp had the highest caffeic acid concentration of all studied extraction methods.

Thermal inkjet printing can generate more than 300,000 droplets of picoliter scale within one second stably, and the image analysis workflow is used to quantify the positive and negative values of the droplets. In this paper, the SimpleBlobDetector detection algorithm is used to identify and localize droplets with a volume of 24 pL in bright field images and suppress bright spots and scratches when performing droplet location identification. The polynomial surface fitting of the pixel grayscale value of the fluorescence channel image can effectively compensate and correct the image vignetting caused by the optical path, and the compensated fluorescence image can accurately classify positive and negative droplets by the k-means clustering algorithm. 20 µL of the sample solution in the result reading chip can produce more than 100,000 effective droplets. The effective droplet identification correct rate of 20 images of random statistical samples can reach more than 99% and the classification accuracy of positive and negative droplets can reach more than 98% on average. This paper overcomes the problem of effectively classifying positive and negative droplets caused by the poor image quality of photographed picolitre ddPCR droplets caused by optical hardware limitations.

Bionanocomposites based on natural bioactive entities have gained importance due to their abundance; renewable and environmentally benign nature; and outstanding properties with applied perspective. Additionally, their formulation with biological molecules with antimicrobial, antioxidant, and anticancer activities has been produced nowadays. The present review details the state of the art and the importance of this pyrrolic compound produced by microorganisms, with interest towards Serratia marcescens, including production strategies at a laboratory level and scale-up to bioreactors. Promising results of its biological activity have been reported to date, and the advances and applications in bionanocomposites are the most recent strategy to potentiate and to obtain new carriers for the transport and controlled release of prodigiosin. Prodigiosin, a bioactive secondary metabolite, produced by Serratia marcescens, is an effective proapoptotic agent against bacterial and fungal strains as well as cancer cell lines. Furthermore, this molecule presents antioxidant activity, which makes it ideal for treating wounds and promoting the general improvement of the immune system. Likewise, some of the characteristics of prodigiosin, such as hydrophobicity, limit its use for medical and biotechnological applications; however, this can be overcome by using it as a component of a bionanocomposite. This review focuses on the chemistry and the structure of the bionanocomposites currently developed using biorenewable resources. Moreover, the work illuminates recent developments in pyrrole-based bionanocomposites, with special insight to its application in the medical area.

SET domain-containing 2 (SETD2) is a methyltransferase that can catalyze the di- and tri-methylation of lysine 36 on histone H3 (H3K36me2/me3). SETD2 frequently mediates H3K36me3 modification to regulate both oocyte maturation and preimplantation embryonic development in mice. However, the specific substrate and function of SETD2 in porcine early embryonic development are still unclear. In this study, SETD2 preferentially catalyzed H3K36me3 to regulate porcine early embryonic development. SETD2 mRNA is dynamically expressed during early embryonic development. Functional studies using an RNA interference (RNAi) approach revealed that the expression levels of SETD2 mRNA were effectively knocked down by siRNA microinjection. Immunofluorescence analysis indicated that SETD2 knockdown (KD) did not affect H3K36me2 modification but significantly reduced H3K36me3 levels, suggesting a preferential H3K36me3 recognition of SETD2 in porcine embryos. Furthermore, SETD2 KD significantly reduced blastocyst rate and disrupted allocation between inner cell mass (ICM) and trophectoderm (TE) lineage. The expression levels of key genes important for specification of the first two lineages apparently decreased in SETD2 KD blastocysts. SETD2 KD markedly increased the apoptotic percentage of cells within embryos and altered the expression of pro- and anti-apoptotic genes. Therefore, our data indicate that SETD2 is essential for porcine early embryonic development.

The bifurcation of limit cycles is an important part in the study of switching systems. The investigation of limit cycles includes the number and configuration, which are related to Hilbert’s 16th problem. Most researchers studied the number of limit cycles, and only few works focused on the configuration of limit cycles. In this paper, we develop a general method to determine the configuration of limit cycles based on the Lyapunov constants. To show our method by an example, we study a class of cubic switching systems, which has three equilibria: (0,0) and (±1,0), and compute the Lyapunov constants based on Poincaré return map, then find at least 10 small-amplitude limit cycles that bifurcate around (1,0) or (−1,0). Using our method, we determine the location distribution of these ten limit cycles.

This article first studies the stability conditions of a Chua system depending on six parameters. After, using the averaging method, as well as the methods of the Gröbner basis and real solution classification, we provide sufficient conditions for the existence of three limit cycles bifurcating from a zero-Hopf equilibrium of the Chua system. As we know, this last phenomena is first found. Some examples are presented to verify the established results.

With the boom in artificial intelligence (AI) and Internet-of-Things (IoT), thousands of smart devices are interconnected with each other and deeply applied into human society. This prosperity has significantly improved public service and management, which were traditionally based on manual work. As a notable scenario, librarianship has embraced an era of “Smart Libraries” enabled by AI and IoT. Unlike existing surveys, our work comprehensively overviews the AI- and IoT-based technologies in three fundamental aspects: smart service, smart sustainability, and smart security. We then further highlight the trend towards future smart libraries.

Ventilation velocity conditions may affect the smoke diffusion and evacuation environment in a tunnel fire, which should be fully considered in evacuation spacing designs of undersea tunnels. This study focuses on reasonable evacuation spacing under various possible velocity conditions of an undersea tunnel, providing a design method reference for calculating safe evacuation spacing. Fire Dynamic Simulator and Pathfinder software were used for numerical simulations of a 50 MW fire and evacuation process in a full-scale undersea tunnel with traffic congestion. The simulation cases contained velocity modes from zero to satisfying the critical velocity and evacuation spacings from 30 m to 80 m. The calculated distributions of the available safe escape time indicated that a low ventilation velocity, such as 1.0 m/s, is beneficial to the downstream evacuation, but turning off mechanical ventilation increased risk near the fire source. The required safe escape time is shortened with a reduction in slide spacings, but the shortened rate slowed down after spacing was less than 60 m. In addition, the slow evacuating areas from 100 m to 300 m from the fire source independent of spacing are identified. Ultimately, the reasonable evacuation spacings of 60 m, 50 m, and 30 m, corresponding to three possible ventilation velocity modes of low, medium, and high, are proposed through the comparisons of the distributions of available safe escape time and required safe escape time.

Acute lung injury is the most common type of organ damage with high incidence and mortality in sepsis, which is a poorly understood syndrome of disordered inflammation. The aims of this study are to explore whether heat shock protein 70 (HSP70), as a molecular chaperone, attenuates the septic lung injury, and to understand the underlying mechanisms. In our study, treatment with HSP70 ameliorated the survival rate, dysfunction of lung, inflammation, and apoptosis in cecal ligation and puncture (CLP)-treated mice as well as in LPS-treated human alveolar epithelial cells. Furthermore, HSP70 interacted with KANK2, leading to reversed cell viability and reduced apoptosis-inducing factor (AIF) and apoptosis. Additionally, knockdown of KANK2 in epithelial cells and deletion of hsp70.1 gene in CLP mice aggravated apoptosis and tissue damage, suggesting that interaction of KANK2 and HSP70 is critical for protecting lung injury induced by sepsis. HSP70 plays an important role in protection of acute lung injury caused by sepsis through interaction with KANK2 to reduce AIF release and apoptotic cell. HSP70 is a novel potential therapeutic approach for attenuation of septic lung injury.

Temperature field calculation is an important step in infrared image simulation. However, the existing solutions, such as heat conduction modelling and pre-generated lookup tables based on temperature calculation tools, are difficult to meet the requirements of high-performance simulation of infrared images based on three-dimensional scenes under multi-environmental conditions in terms of accuracy, timeliness, and flexibility. In recent years, machine learning-based temperature field prediction methods have been proposed, but these methods only consider the influence of meteorological parameters on the temperature value, while not considering the geometric structure and the thermophysical parameters of the object, which results in the low accuracy. In this paper, a multivariate temperature field prediction network based on heterogeneous data (MTPHNet) is proposed. The network fuses geometry structure, meteorological, and thermophysical parameters to predict temperature. First, a Point Cloud Feature Extraction Module and Environmental Data Mapping Module are used to extract geometric information, thermophysical, and meteorological features. The extracted features are fused by the Data Fusion Module for temperature field prediction. Experiment results show that MTPHNet significantly improves the prediction accuracy of the temperature field. Compared with the v-Support Vector Regression and the combined back-propagation neural network, the mean absolute error and root mean square error of MTPHNet are reduced by at least 23.4% and 27.7%, respectively, while the R-square is increased by at least 5.85%. MTPHNet also achieves good results in multi-target and complex target temperature field prediction tasks. These results validate the effectiveness of the proposed method.

As a southwestern province of China, Sichuan is confronted with geographical disparities in access to healthcare professionals because of its complex terrain, uneven population distribution and huge economic gaps between regions. With 10-year data, this study aims to explore the county-level spatial disparities in access to different types of healthcare professionals (licensed doctors, registered nurses, pharmacists, technologists and interns) in Sichuan using temporal and spatial analysis methods. The time-series results showed that the quantity of all types of healthcare professionals increased, especially the registered nurses, while huge spatial disparities exist in the distribution of healthcare professionals in Sichuan. The local Moran’s I calculations showed that high–high clusters (significantly high healthcare professional quantity in a group of counties) were detected in Chengdu (capital of Sichuan) and relatively rich areas, while low–low clusters (significantly low healthcare professional quantity in a group of counties) were usually found near the mountain areas, namely, Tsinling Mountains and Hengduan Mountains. The findings may deserve considerations in making region-oriented policies in educating and attracting more healthcare professionals to the disadvantaged areas.

To address the problem of intelligent recognition of optical ship targets under low-altitude squint detection, we propose an intelligent recognition method based on simulation samples. This method comprehensively considers geometric and spectral characteristics of ship targets and ocean background and performs full link modeling combined with the squint detection atmospheric transmission model. It also generates and expands squint multi-angle imaging simulation samples of ship targets in the visible light band using the expanded sample type to perform feature analysis and modification on SqueezeNet. Shallow and deeper features are combined to improve the accuracy of feature recognition. The experimental results demonstrate that using simulation samples to expand the training set can improve the performance of the traditional k-nearest neighbors algorithm and modified SqueezeNet. For the classification of specific ship target types, a mixed-scene dataset expanded with simulation samples was used for training. The classification accuracy of the modified SqueezeNet was 91.85%. These results verify the effectiveness of the proposed method.

Testicular development is critical for male animals’ reproduction and is tightly regulated by epigenetic factors. Circular RNAs (circRNAs) were recently identified in the testes of humans and bulls. However, the expression profile of circRNAs and their potential biological functions in boar testicular development remain unclear. We identified 34,521 and 31,803 circRNAs in piglet (30 d) and adult (210 d) boar testes by high-throughput sequencing, respectively. Bioinformatics analysis revealed that these circRNAs are widely distributed on autosomes and sex chromosomes. Some of the host genes can generate multiple circRNAs. A total of 2326 differentially expressed circRNAs (DECs) derived from 1526 host genes was found in testicular development, of which 1003 circRNAs were up-regulated in adult boar testes and 1323 circRNAs were down-regulated. Furthermore, gene ontology analysis of host genes of DECs revealed that these circRNAs are mainly involved in regulating spermatogenesis, cilia motility, and hormone biosynthesis. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that the DECs are markedly enriched to stem cell pluripotency regulation, tight junctions, adhesion junctions, and cAMP signaling pathway. These results indicate that circRNAs are abundantly expressed in boar testes and exhibit dynamic changes during testicular development.

Understanding social behaviour in livestock groups requires accurate geo-spatial localisation data over time which is difficult to obtain in the field. Automated on-animal devices may provide a solution. This study introduced an Real-Time-Kinematic Global Navigation Satellite System (RTK-GNSS) localisation device (RTK rover) based on an RTK module manufactured by the company u-blox (Thalwil, Switzerland) that was assembled in a box and harnessed to sheep backs. Testing with 7 sheep across 4 days confirmed RTK rover tracking of sheep movement continuously with accuracy of approximately 20 cm. Individual sheep geo-spatial data were used to observe the sheep that first moved during a grazing period (movement leaders) in the one-hectare test paddock as well as construct social networks. Analysis of the optimum location update rate, with a threshold distance of 20 cm or 30 cm, showed that location sampling at a rate of 1 sample per second for 1 min followed by no samples for 4 min or 9 min, detected social networks as accurately as continuous location measurements at 1 sample every 5 s. The RTK rover acquired precise data on social networks in one sheep flock in an outdoor field environment with sampling strategies identified to extend battery life.