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To improve the drying efficiency and quality of hot air-dried apple slices with blanching pretreatment, this study systematically evaluated the effects of two blanching pretreatments, hot water blanching and vacuum steam pulsed blanching, on the macroscopic drying performance of apple slices. The results indicated that under the conditions of 0.07 MPa vacuum, two blanching cycles, and blanching time of 3 minutes, vacuum steam pulsed blanching significantly enhanced the rehydration rate and textural quality of apple slices while reducing the drying time. Paraffin sectioning, microscopic observation and image processing were used to compare the microstructural changes of apple slices in terms of cell cross-sectional area, perimeter, equivalent diameter, cell roundness, wall roughness factor, and porosity under different branching conditions (temperature and time for hot water blanching; vacuum level, number of cycles, and time for vacuum steam pulsed blanching). The results showed that with the increase in temperature, blanching time and number of blanching cycles, apple cells exhibited changes that accelerated water evaporation during subsequent drying, thus shortening the drying time. Additionally, the relationship between microstructural parameters and rehydration ratio was fitted to a polynomial regression model. The findings of this study provide a theoretical basis for understanding the mechanisms by which vacuum steam pulsed blanching affects the microstructure and quality of dried apple slices.

Volatile components in red orange essential oil extracted by two cold pressing processes (cup pressing and lime method) were analyzed by gas chromatography quadrupole time-of-flight mass spectrometry (GC-Q/TOF). A total of 93 components were identified, 89 and 84 compounds were identified for the two types of red orange essential oils, respectively. Among the 93 components, there were 29 terpenes, 20 alcohols, 20 aldehydes, 5 esters, 2 ketones, 12 hydrocarbons, and 5 other compounds. There were 80 compounds shared by the two essential oils. The total volatile component content of red orange essential oil by cup pressing method was significantly higher than that by lime method. The highest content of these compounds was terpenes which total content was over 80%. In addition, the compounds with higher content were D-limonene, γ-terpinene, β-myrcene, linalool and α-pinene. According to principal component analysis (PCA), there was a significant difference in the volatile components of the two types of red orange essential oils. The relative odor activity value (ROAV) method indicated that linalool was the most important aroma component of the two red orange essential oils. And the citrus aroma properties of red orange essential oil extracted by cup pressing method was significantly stronger than that extracted by lime method. Linalool, thymol, β-myrcene, D-limonene, citronellal, and γ-terpinene were confirmed to the key aroma components of the red orange essential oils.

Nowadays, the rapid development of hypersonic vehicles brings great challenges to the missile defense system. As achieving successful interception depends highly on terminal guidance laws, research on guidance laws for intercepting highly maneuvering targets has aroused increasing attention. Artificial intelligence technologies, such as deep reinforcement learning (DRL), have been widely applied to improve the performance of guidance laws. However, the existing DRL guidance laws rarely consider the partial observability problem of onboard sensors, resulting in the limitations of their engineering applications. In this paper, a deep recurrent reinforcement learning (DRRL)-based guidance method is investigated to address the intercept guidance problem against maneuvering targets under partial observability. The sequence consisting of previous state observations is utilized as the input of the policy network. A recurrent layer is introduced into the networks to extract hidden information behind the temporal sequence to support policy training. The guidance problem is formulated as a partially observable Markov decision process model, and then a range-weighted reward function that considers the line-of-sight rate and energy consumption is designed to guarantee convergence of policy training. The effectiveness of the proposed DRRL guidance law is validated by extensive numerical simulations.

Feeding behavior is known to affect the welfare and fattening efficiency of yaks in feedlots. With the advancement of machine vision and sensor technologies, the monitoring of animal behavior is progressively shifting from manual observation towards automated and stress-free methodologies. In this study, a real-time detection model for individual yak feeding and picking behavior was developed using YOLO series model and StrongSORT tracking model. In this study, we used videos collected from 11 yaks raised in two pens to train the yak face classification with YOLO series models and tracked their individual behavior using the StrongSORT tracking model. The yak behavior patterns detected in trough range were defined as feeding and picking, and the overall detection performance of these two behavior patterns was described using indicators such as accuracy, precision, recall, and F1-score. The improved YOLOv8 and Strongsort model achieved the best performance, with detection accuracy, precision, recall, and F1-score of 98.76%, 98.77%, 98.68%, and 98.72%, respectively. Yaks which have similar facial features have a chance of being confused with one another. A few yaks were misidentified because their faces were obscured by another yak’s head or staff. The results showed that individual yak feeding behaviors can be accurately detected in real-time using the YOLO series and StrongSORT models, and this approach has the potential to be used for longer-term yak feeding monitoring. In the future, a dataset of yaks in various cultivate environments, group sizes, and lighting conditions will be included. Furthermore, the relationship between feeding time and yak weight gain will be investigated in order to predict livestock weight.

Abstract Pursuit of improved living quality has stimulated great demand for high-performance conformal healthcare devices in modern human society. However, manufacturing of efficient, comfortable and stretchable biomedical apparatus faces huge challenges using traditional materials. Liquid metals (LMs) show remarkable potential to solve this problem due to their extraordinary biocompatibility, stretchability, thermal and electrical conductivity. In recent years, tremendous explorations have attempted to make stretchable biomedical devices with LMs. Herein, we review the stretchable LM-based biomedical devices on the topics of disease treatment and human function augmenting. The representative and up-to-date neural interfaces, alloy cement, e-vessels, soft heaters, exoskeletons, and e-skins are summarized. The existing issues of LMs applied for biomedical devices are also discussed. This review can provide guidance for the follow-up research in LM-based biomedical devices.

Yak behavior is a valuable indicator of their welfare and health. Information about important statuses, including fattening, reproductive health, and diseases, can be reflected and monitored through several indicative behavior patterns. In this study, an improved YOLOv7-pose model was developed to detect six yak behavior patterns in real time using labeled yak key-point images. The model was trained using labeled key-point image data of six behavior patterns including walking, feeding, standing, lying, mounting, and eliminative behaviors collected from seventeen 18-month-old yaks for two weeks. There were another four YOLOv7-pose series models trained as comparison methods for yak behavior pattern detection. The improved YOLOv7-pose model achieved the best detection performance with precision, recall, mAP0.5, and mAP0.5:0.95 of 89.9%, 87.7%, 90.4%, and 76.7%, respectively. The limitation of this study is that the YOLOv7-pose model detected behaviors under complex conditions, such as scene variation, subtle leg postures, and different light conditions, with relatively lower precision, which impacts its detection performance. Future developments in yak behavior pattern detection will amplify the simple size of the dataset and will utilize data streams like optical and video streams for real-time yak monitoring. Additionally, the model will be deployed on edge computing devices for large-scale agricultural applications.

Abstract Background Peripheral nerve damage causes neuroinflammation, which plays a critical role in establishing and maintaining neuropathic pain (NeP). The mechanisms contributing to neuroinflammation remain poorly elucidated, and pharmacological strategies for NeP are limited. Thus, in this study, we planned to explore the possible link between astrocyte senescence and NeP disorders following chronic sciatic nerve injury. Methods An NeP animal model was established by inducing chronic constrictive injury (CCI) to the sciatic nerve in adult rats. A senolytic drug combination of dasatinib and quercetin was gavaged daily from the first postoperative day until the end of the study. Paw mechanical withdrawal threshold (PMWT) and paw thermal withdrawal latency (PTWL) were evaluated to assess behaviors in response to pain in the experimental rats. Senescence-associated β-galactosidase staining, western blot analysis, and immunofluorescence were applied to examine the levels of proinflammatory factors and severity of the senescence-like response in the spinal cord. Lipopolysaccharide (LPS) was administered to induce senescence of spinal astrocytes in primary cultures in vitro, to explore the potential impacts of senescence on the secretion of proinflammatory factors. Furthermore, single-cell RNA sequencing (scRNA-seq) was conducted to identify senescence-related molecular responses in spinal astrocytes under neuropathic pain. Results Following sciatic nerve CCI, rats exhibited reduced PMWT and PTWL, increased levels of spinal proinflammatory factors, and an enhanced degree of senescence in spinal astrocytes. Treatment with dasatinib and quercetin effectively attenuated spinal neuroinflammation and mitigated the hypersensitivities of the rats subjected to sciatic nerve CCI. Mechanistically, the dasatinib-quercetin combination reversed senescence in LPS-stimulated primary cultured astrocytes and decreased the levels of proinflammatory factors. The scRNA-seq data revealed four potential senescence-related genes in the spinal astrocyte population, and the expression of clusterin (CLU) protein was validated via in vitro experiments. Conclusion The findings indicate the potential role of astrocyte senescence in neuroinflammation following peripheral nerve injury, and suggest that targeting CLU activation in astrocytes might provide a novel therapeutic strategy to treat NeP. Graphical abstract

AbstractBackground An increasing number of studies show that the intestinal flora is closely related to spinal cord injury. Many researchers are exploring the changes in the richness, diversity, and evenness of intestinal flora in spinal cord injury animal models to identify the characteristic bacteria.Methods A comprehensive literature search was conducted using three databases: PubMed, Embase, and Web of Science. A meta-analysis was performed using R 4.3.1 to evaluate the comparison of microbiota diversity, richness, and evenness and the relative abundance of intestinal microbiota in animals with spinal cord injury and blank controls.Results Fifteen studies were included in the meta-analysis, of which 12 involved gut microbiota distribution indicators and 11 included intestinal microflora relative abundance indicators. Meta-analysis of high-dimensional indicators describing the distribution of the gut microbiota identified a substantial decline in the evenness and richness of the intestinal flora. In addition, the Actinobacteria phylum and Erysipelotrichales and Clostridiales orders were significantly different between the spinal cord injury and sham groups; therefore, they may be the characteristic bacteria in spinal cord injury models.Conclusion Our meta-analysis suggested that the gut microbiota in the spinal cord injury animal model group was altered compared with that in the control group, with varying degrees of changes in richness and evenness and potentially pathogenic characteristic flora. More rigorous methodological studies are needed because of the high heterogeneity and limited sample size. Further research is needed to clinically apply intestinal microbiota and potentially guide fecal microbiota transplantation therapy.

The escalating proliferation of space debris poses an increasing risk to spinning satellites, elevating the probability of hazardous collisions that can result in severe damage or total loss of functionality. To address this concern, a pioneering inflatable protective structure is employed to ensure the optimal functionality of spinning satellites. Additionally, a multi-body dynamic modeling method based on spring hinge unfolding/spring expansion is proposed to tackle the complex dynamics of spinning satellites with inflatable protective structures during flight. This method enables analysis of the motion parameters of spinning satellites. First, the structural composition of a spinning satellite with inflatable protective structures is introduced and its flight process is analyzed. Then, an articulated spring hinge unfolding model or a spring expansion model using the Newton–Euler method is established to describe the unfolding or expansion of the spinning satellite with inflatable protective structures during flight. Finally, the effects on the motion parameters of a spinning satellite are analyzed through simulation under various working conditions.

Al-Li alloy was prepared by electrodeposition on solid aluminum electrode in a urea-LiCl (77.5:22.5, mol%) molten salt system at 353–393 K. The results of cyclic voltammetry and chronopotentiometry show that underpotential deposition of Li occurs on the Al electrode and forms phases of Al(α) and AlLi(δ) which are confirmed by XRD measurements. Scanning electron microscopy observation of deposits indicates that Al-Li alloy with the thickness of 143 µm was obtained by potentiostatic electrolysis at −0.5 V vs. Li+/Li. The Li content in the alloy obtained at 373 K can reach 6.9 wt%. Galvanostatic electrolysis at 20 A demonstrated that Al-Li alloy coating on aluminum plate can be obtained from urea-LiCl electrolyte at 373 K in the atmosphere.

High-precision collaborative observation is urgently needed due to the increasing demands of space science missions. Based on a conventional DFP (disturbance-free-payload) configuration, this paper presents a novel DFP that has great potential to deal with collaborative observation missions. The novel DFP system is developed, in which two or more payloads are installed via a non-contact unit and installed parallel configuration. Thus, the novel design is a multibody dynamics system. With the incorporation of the dynamics of the flexible umbilical between the PMs (payload modules) and SM (support module), the six-degrees-of-freedom multibody rigid–flexible dynamics of the whole system are derived. To verify the effectiveness of the novel DFP design in a collaborative observation mission, a multi-loop controller is designed for an inertial Earth collaborative observation mission. Simulation studies are conducted, which indicate that the proposed design can complete collaborative observation and achieve high precision.

A hybrid energy storage system (HESS) consists of two or more types of energy storage components and the power electronics circuit to connect them. Therefore, the real-time capacity of this system highly depends on the state of the system and cannot be simply evaluated with traditional battery models. To tackle this challenge, an equivalent state of charge (ESOC) which reflects the remaining capacity of a HESS unit in a specific operation mode, is proposed in this paper. Furthermore, the proposed ESOC is applied to the control of the distributed HESS which contains several units with their own local targets. To optimally distribute the overall power target among these units, a sparse communication network-based hierarchical control framework is proposed. This framework considers the distributed control and optimal power distribution in the HESS from two aspects - the power output capability and the ESOC balance. Based on the primary droop control, the total power is allocated according to the maximum output capacity of each unit, and the secondary control is used to adjust the power from the perspective of ESOC balance. Therefore, each energy storage unit can be controlled to meet the local power demand of the microgrid. Simulation results based on MATLAB/Simulink verify the effectiveness of the application of the proposed equivalent SOC.

Interferon-induced transmembrane protein 3 (IFITM3) is an interferon-induced membrane protein, which has been identified as a functional gene in multiple human cancers. The role of IFITM3 in cancer has been preliminarily summarized, but its relationship to antitumor immunity is still unclear. A pancancer analysis was conducted to investigate the expression pattern and immunological role of IFITM3 based on transcriptomic data downloaded from The Cancer Genome Atlas (TCGA) database. Next, correlations between IFITM3 and immunological features in the bladder cancer (BLCA) tumor microenvironment (TME) were assessed. In addition, the role of IFITM3 in estimating the clinical characteristics and the response to various therapies in BLCA was also evaluated. These results were next confirmed in the IMvigor210 cohort and a recruited cohort. In addition, correlations between IFITM3 and emerging immunobiomarkers, such as microbiota and N6-methyladenosine (m6A) genes, were assessed. IFITM3 was enhanced in most tumor tissues in comparison with adjacent tissues. IFITM3 was positively correlated with immunomodulators, tumor-infiltrating immune cells (TIICs), cancer immunity cycles, and inhibitory immune checkpoints. In addition, IFITM3 was associated with an inflamed phenotype and several established molecular subtypes. IFITM3 expression also predicted a notably higher response to chemotherapy, anti-EGFR therapy, and immunotherapy but a low response to anti-ERBB2, anti-ERBB4, and antiangiogenic therapy. In addition, IFITM3 was correlated with immune-related microbiota and m6A genes. In addition to BLCA, IFITM3 is expected to be a marker of high immunogenicity in most human cancers. In conclusion, IFITM3 expression can be used to identify immuno-hot tumors in most cancers, and IFITM3 may be a promising pancancer biomarker to estimate the immunological features of tumors.

This article proposes a sliding mode observer based dynamic equivalent state of charge (ESOC) estimation method for hybrid energy storage system (HESS). Since different types of energy storage components and power electronics circuit are coupled in the HESS, the traditional SOC estimation method cannot reflect the real-time operation characteristics of the HESS. To tackle this problem, a sliding mode observer based on the model of the HESS is built in this article. By collecting the corresponding voltage and current signals, the internal parameters of energy storage elements can be observed accurately in real time. The dynamic ESOC is further defined with the idea of real-time charge balance to reflect the accurate available capacity of the HESS. Finally, the simulation results based on MATLAB/Simulink model are given to verify the feasibility of the proposed dynamic ESOC.