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Abstract Agile and adaptive maneuvers such as fall recovery, high-speed turning, and sprinting in the wild are challenging for legged systems. We propose a Curricular Hindsight Reinforcement Learning (CHRL) that learns an end-to-end tracking controller that achieves powerful agility and adaptation for the legged robot. The two key components are (i) a novel automatic curriculum strategy on task difficulty and (ii) a Hindsight Experience Replay strategy adapted to legged locomotion tasks. We demonstrated successful agile and adaptive locomotion on a real quadruped robot that performed fall recovery autonomously, coherent trotting, sustained outdoor running speeds up to 3.45 m/s, and a maximum yaw rate of 3.2 rad/s. This system produces adaptive behaviors responding to changing situations and unexpected disturbances on natural terrains like grass and dirt.

Biomass and its derivatives have broad applications in the fields of bio-catalysis, energy storage, environmental remediation. The structure and components of biomass, which are vital parameters affecting corresponding performances of derived products, need to be fully understood for further regulating the biomass and its derivatives. Herein, tobacco is taken as an example of biomass to introduce the typical characterization techniques in unraveling the structural information, chemical components, and properties of biomass and its derivatives. Firstly, the structural information, chemical components and application for biomass are summarized. Then the characterization techniques together with the resultant structural information and chemical components are introduced. Finally, to promote a wide and deep study in this field, the perspectives and challenges concerning structure and composition charaterization in biomass and its derivatives are put forward.

Falling is inevitable for legged robots when deployed in unstructured and unpredictable real-world scenarios, such as uneven terrain in the wild. Therefore, to recover dynamically from a fall without unintended termination of locomotion, the robot must possess the complex motor skills required for recovery maneuvers. However, this is exceptionally challenging for existing methods, since it involves multiple unspecified internal and external contacts. To go beyond the limitation of existing methods, we introduced a novel deep reinforcement learning framework to train a learning-based state estimator and a proprioceptive history policy for dynamic fall recovery under external disturbances. The proposed learning-based framework applies to different fall cases indoors and outdoors. Furthermore, we show that the learned fall recovery policies are hardware-feasible and can be implemented on real robots. The performance of the proposed approach is evaluated with extensive trials using a quadruped robot, which shows good effectiveness in recovering the robot after a fall on flat surfaces and grassland.

Underwater bionic-legged robots encounter significant challenges in attitude, velocity, and positional control due to lift and drag in water current environments, making it difficult to balance operational efficiency with motion stability. This study delves into the hydrodynamic properties of a bionic crab robot’s shell, drawing inspiration from the sea crab’s motion postures. It further refines the robot’s underwater locomotion strategy based on these insights. Initially, the research involved collecting attitude data from crabs during underwater movement through biological observation. Subsequently, hydrodynamic simulations and experimental validations of the bionic shell were conducted, examining the impact of attitude parameters on hydrodynamic performance. The findings reveal that the transverse angle predominantly influences lift and drag. Experiments in a test pool with a crab-like robot, altering transverse angles, demonstrated that increased transverse angles enhance the robot’s underwater walking efficiency, stability, and overall performance.

Bionic-legged robots draw inspiration from animal locomotion methods and structures, demonstrating the potential to traverse irregular and unstructured environments. The ability of Portunus trituberculatus (Portunus) to run flexibly and quickly in amphibious environments inspires the design of systems and locomotion methods for amphibious robots. This research describes an amphibious crab-like robot based on Portunus and designs a parallel leg mechanism for the robot based on biological observations. The research creates the group and sequential gait commonly used in multiped robots combined with the form of the robot’s leg mechanism arrangement. This research designed the parallel leg mechanism and modeled its dynamics. Utilizing the outcomes of the dynamics modeling, we calculate the force and torque exerted on each joint of the leg mechanism during group gait and sequential gait when the robot is moving with a load. This analysis aims to assess the performance of the robot’s motion. Finally, a series of performance evaluation experiments are conducted on land and underwater, which show that the amphibious crab-like robot has good walking performance. The crab-like robot can perform forward, backward, left, and right walking well using group and sequential gaits. Simultaneously, the crab-like robot showcases faster movement in group gaits and a more substantial load capacity in sequential gaits.

A model-based framework is presented to predict monoclonal antibody (mAb) pharmacokinetics (PK) in humans based on in vitro measures of antibody physiochemical properties. A physiologically based pharmacokinetic (PBPK) model is used to explore the predictive potential of 14 in vitro assays designed to measure various antibody physiochemical properties, including nonspecific cell-surface interactions, FcRn binding, thermal stability, hydrophobicity, and self-association. Based on the mean plasma PK time course data of 22 mAbs from humans reported in the literature, we found a significant positive correlation (R = 0.64, p = .0013) between the model parameter representing antibody-specific vascular to endothelial clearance and heparin relative retention time, an in vitro measure of nonspecific binding. We also found that antibody-specific differences in paracellular transport due to convection and diffusion could be partially explained by antibody heparin relative retention time (R = 0.52, p = .012). Other physiochemical properties, including antibody thermal stability, hydrophobicity, cross-interaction and self-association, in and of themselves were not predictive of model-based transport parameters. In contrast to other studies that have reported empirically derived expressions relating in vitro measures of antibody physiochemical properties directly to antibody clearance, the proposed PBPK model-based approach for predicting mAb PK incorporates fundamental mechanisms governing antibody transport and processing, informed by in vitro measures of antibody physiochemical properties, and can be expanded to include more descriptive representations of each of the antibody processing subsystems, as well as other antibody-specific information.

In this study, apple pectin (AP) and tomato pectin (TP) were demonstrated to be a high-ester (74.8%) polysaccharide with the weight-average molecular weight (Mw) of ∼ 243 kDa and a low-ester (45.9%) polysaccharide with the Mw of ∼ 19 kDa, respectively. The semi-rigid chain conformations of pectic polysaccharides in NaNO3 aqueous solution were deduced according to the Smidsrød “B values” of AP (0.025) and TP (0.029), while AP and TP exhibited higher stiffness in water due to the electric repulsion of carboxyl groups, which was visually observed by AFM images. Under steady shear, the shear-thickening behaviors of AP and TP in NaNO3 aqueous solutions were observed in the shear rate range of

Bionic amphibious robots are the intersection of biology and robotics; they have the advantages of environmental adaptability and maneuverability. An amphibious robot that combines walking and swimming move modes inspired by a crab (Portunus) is presented in this article. The outstanding characteristic of the robot is that its environmental adaptability relies on the bionic multi-modal movement, which is based on two modular bionic swimming legs and six modular walking legs. We designed the biomimetic crab robot based on the biological observation results. The design, analysis, and simulation of its structure and motion parameters are introduced in this paper. The swimming propulsion capability and the walking performance are verified through indoor, pool, and seaside experiments. In conclusion, the designed bionic crab robot provides a platform with practical application capabilities in amphibious environment detection, concealed reconnaissance, and aquaculture.

Glucose effectiveness, defined as the ability of glucose itself to increase glucose utilization and inhibit hepatic glucose production, is an important mechanism maintaining normoglycemia. We conducted a minimal modeling analysis of glucose effectiveness at zero insulin (GEZI) using intravenous glucose tolerance test data from subjects with type 2 diabetes (T2D, n=154) and non-diabetic (ND) subjects (n=343). A hierarchical statistical analysis was performed, which provided a formal mechanism for pooling the data from all study subjects, to yield a single composite population model that quantifies the role of subject specific characteristics such as weight, height, age, sex, and glucose tolerance. Based on the resulting composite population model, GEZI was reduced from 0.021 min–1 (standard error – 0.00078 min–1) in the ND population to 0.011 min–1 (standard error – 0.00045 min–1) in T2D. The resulting model was also employed to calculate the proportion of the non–insulin-dependent net glucose uptake in each subject receiving an intravenous glucose load. Based on individual parameter estimates, the fraction of total glucose disposal independent of insulin was 72.8% ± 12.0% in the 238 ND subjects over the course of the experiment, indicating the major contribution to the whole-body glucose clearance under non-diabetic conditions. This fraction was significantly reduced to 48.8% ± 16.9% in the 30 T2D subjects, although still accounting for approximately half of the total in the T2D population based on our modeling analysis. Given the potential application of glucose effectiveness as a predictor of glucose intolerance and as a potential therapeutic target for treating diabetes, more investigations of glucose effectiveness in other disease conditions can be conducted using the hierarchical modeling framework reported herein.

A coordinated recovery strategy, based on MIESCR, is proposed for the converters Excessive dynamic reactive power demand and the low speed of power transmission recovery in multi-infeed HVDC system in this paper. Firstly, the article deduces the consistency of two type definition of MIESCR, and uses the respective advantages of the definition to improve the physical meaning of MIESCR; and then it elaborates the role of MIESCR played in in MIDC system voltage and power-angle stability Third, this pages put forward MIESCR as the fundamental to distinguish the strength of AC system, and use the size of MIESCR to arrange the recovery order of DC systems. Furthermore, the parameter of PI controller is used to realize the control of each DC system current. There is a great method to ensure coordinate control of PI controller. The last, a double infeed HVDC system simulation model, based on two actual DC system of China Southern Power Grid, is built on Electromagnetic transient simulation software of PSCAD/EMTDC to confirm the validity of this method proposed in this paper.

Abstract Drug addiction represents a multifaceted and recurrent brain disorder that possesses the capability to create persistent and ineradicable pathological memory. Deep brain stimulation (DBS) has shown a therapeutic potential for neuropsychological disorders, while the precise stimulation targets and therapeutic parameters for addiction remain deficient. Among the crucial brain regions implicated in drug addiction, the dorsal raphe nucleus (DRN) has been found to exert an essential role in the manifestation of addiction memory. Thus, we investigated the effects of DRN DBS in the treatment of addiction and whether it might produce side effects by a series of behavioral assessments, including methamphetamine priming-induced reinstatement of drug seeking behaviors, food-induced conditioned place preference (CPP), open field test and elevated plus-maze test, and examined brain activity and connectivity after DBS of DRN. We found that high-frequency DBS of the DRN significantly lowered the CPP scores and the number of active-nosepokes in the methamphetamine-primed CPP test and the self-administration model. Moreover, both high-frequency and sham DBS group rats were able to establish significant food-induced place preference, and no significant difference was observed in the open field test and in the elevated plus-maze test between the two groups. Immunofluorescence staining and functional magnetic resonance imaging revealed that high-frequency DBS of the DRN could alter the activity and functional connectivity of brain regions related to addiction. These results indicate that high-frequency DBS of the DRN effectively inhibits methamphetamine priming-induced relapse and seeking behaviors in rats and provides a new target for the treatment of drug addiction.

Pear trees must be artificially pollinated to ensure yield, and the efficiency of pollination and the quality of pollen germination affect the size, shape, taste, and nutritional value of the fruit. Detecting the pollen germination vigor of pear trees is important to improve the efficiency of artificial pollination and consequently the fruiting rate of pear trees. To overcome the limitations of traditional manual detection methods, such as low efficiency and accuracy and high cost, and to meet the requirements of screening high-quality pollen to promote the yield and production of fruit trees, we proposed a detection method for pear pollen germination vigor named YOLOv8-Pearpollen, an improved version of YOLOv8-n. A pear pollen germination dataset was constructed, and the image was enhanced using Blend Alpha to improve the robustness of the data. A combination of knowledge distillation and model pruning was used to reduce the complexity of the model and the difficulty of deployment in hardware facilities while ensuring that the model achieved or approached the detection effect of a large-volume model that can adapt to the actual requirements of agricultural production. Various ablation tests on knowledge distillation and model pruning were conducted to obtain a high-quality lightweighting method suitable for this model. Test results showed that the mAP of YOLOv8-Pearpollen reached 96.7%. The Params, FLOPs, and weights were only 1.5 M, 4.0 G, and 3.1 MB, respectively, and the detection speed was 147.1 FPS. A high degree of lightweighting and superior detection accuracy were simultaneously achieved.

Abstract Background Verticillium wilt is the major disease of cotton, which would cause serious yield reduction and economic losses, and the identification of cotton verticillium wilt is of great significance to cotton research. However, the traditional method is still manual, which is subjective, inefficient, and labor-intensive, and therefore, this study has proposed a novel method for cotton verticillium wilt identification based on spectral and image feature fusion. The cotton hyper-spectral images have been collected, while the regions of interest (ROI) have been extracted as samples including 499 healthy leaves and 498 diseased leaves, and the average spectral information and RGB image of each sample were obtained. In spectral feature processing, the preprocessing methods including Savitzky-Golay smoothing (SG), multiplicative scatter correction (MSC), de-trending (DT) and mean normalization (MN) algorithms have been adopted, while the feature band extraction methods have adopted principal component analysis (PCA) and successive projections algorithm (SPA). In RGB image feature processing, the EfficientNet was applied to build classification model and 16 image features have been extracted from the last convolutional layer. And then, the obtained spectral and image features were fused, while the classification model was established by support vector machine (SVM) and back propagation neural network (BPNN). Additionally, the spectral full bands and feature bands were used as comparison for SVM and BPNN classification respectively. Result The results showed that the average accuracy of EfficientNet for cotton verticillium wilt identification was 93.00%. By spectral full bands, SG-MSC-BPNN model obtained the better performance with classification accuracy of 93.78%. By feature bands, SG-MN-SPA-BPNN model obtained the better performance with classification accuracy of 93.78%. By spectral and image fused features, SG-MN-SPA-FF-BPNN model obtained the best performance with classification accuracy of 98.99%. Conclusions The study demonstrated that it was feasible and effective to use fused spectral and image features based on hyper-spectral imaging to improve identification accuracy of cotton verticillium wilt. The study provided theoretical basis and methods for non-destructive and accurate identification of cotton verticillium wilt.

Objective: Post-traumatic stress disorder (PTSD) is a neuropsychiatric disorder that can develop after experiencing or witnessing a traumatic event. Exposure therapy is a common treatment for PTSD, but it has varying levels of efficacy depending on sex. In this study, we aimed to compare the sexual dimorphism in brain activation during the extinction of fear conditioning in male and female rats by detecting the c-fos levels in the whole brain. Methods: Thirty-two rats (Male: n = 16; Female: n = 16) were randomly separated into the extinction group as well as the non-extinction group, and fear conditioning was followed by extinction and non-extinction, respectively. Subsequently, brain sections from the sacrificed animal were performed immunofluorescence and the collected data were analyzed by repeated two-way ANOVAs as well as Pearson Correlation Coefficient. Results: Our findings showed that most brain areas activated during extinction were similar in both male and female rats, except for the reuniens thalamic nucleus and ventral hippocampi. Furthermore, we found differences in the correlation between c-fos activation levels and freezing behavior during extinction between male and female rats. Specifically, in male rats, c-fos activation in the anterior cingulate cortex was negatively correlated with the freezing level, while c-fos activation in the retrosplenial granular cortex was positively correlated with the freezing level; but in female rats did not exhibit any correlation between c-fos activation and freezing level. Finally, the functional connectivity analysis revealed differences in the neural networks involved in extinction learning between male and female rats. In male rats, the infralimbic cortex and insular cortex, anterior cingulate cortex and retrosplenial granular cortex, and dorsal dentate gyrus and dCA3 were strongly correlated after extinction. In female rats, prelimbic cortex and basolateral amygdala, insular cortex and dCA3, and anterior cingulate cortex and dCA1 were significantly correlated. Conclusion: These results suggest divergent neural networks involved in extinction learning in male and female rats and provide a clue for improving the clinical treatment of exposure therapy based on the sexual difference.

Sufficient soil moisture is required to ensure the successful transplantation of sweet potato seedlings. Thus, reasonable water management is essential for achieving high quality and yield in sweet potato production. We conducted field experiments in northern China, planted on 18 May and harvested on 18 October 2021, at the Nancun Experimental Base of Qingdao Agricultural University. Three water management treatments were tested for sweet potato seedlings after transplanting: hole irrigation (W1), optimized drip irrigation (W2), and traditional drip irrigation (W3). The variation characteristics of soil volumetric water content, soil temperature, and soil CO2 concentration in the root zone were monitored in situ for 0–50 days. The agronomy, root morphology, photosynthetic parameters, 13C accumulation, yield, and yield components of sweet potato were determined. The results showed that soil VWC was maintained at 22–25% and 27–32% in the hole irrigation and combined drip irrigation treatments, respectively, from 0 to 30 days after transplanting. However, there was no significant difference between the traditional (W3) and optimized (W2) drip irrigation systems. From 30 to 50 days after transplanting, the VWC decreased significantly in all treatments, with significant differences among all treatments. Soil CO2 concentrations were positively correlated with VWC from 0 to 30 days after transplanting but gradually increased from 30 to 50 days, with significant differences among treatments. Soil temperature varied with fluctuations in air temperature, with no significant differences among treatments. Sweet potato survival rates were significantly lower in the hole irrigation treatments than in the drip irrigation treatments, with no significant difference between W2 and W3. The aboveground biomass, photosynthetic parameters, and leaf area index were significantly higher under drip irrigation than under hole irrigation, and values were higher in W3 than in W2. However, the total root length, root volume, and 13C partitioning rate were higher in W2 than in W3. These findings suggest that excessive drip irrigation can lead to an imbalance in sweet potato reservoir sources. Compared with W1, the W2 and W3 treatments exhibited significant yield increases of 42.98% and 36.49%, respectively. The W2 treatment had the lowest sweet potato deformity rate.

In this work, we employ two Mach-Zehnder modulators (MZM) to achieve a novel six kinds of reconfigurable optical logic gate in millimeter wave over fiber, in which one MZM is used to generate millimeter wave (mm-wave) signal and the other is used to attain optical logic gate. By adjusting the direct current (DC) bias voltage of the first MZM, a frequency doubling mm-wave signal can be obtained and no filter is needed. By controlling the radio frequency (RF) drive voltage and DC bias voltage of the second MZM, the phase of between upper and lower arms can be converted. By adjusting the phase of the first channel RF signal to $(\pi /2,0)$ , setting the phase of the second channel RF signal to $(0,\pi /2)$ and controlling the bias voltage to let the phase of the upper and lower to be $\pi /2$ and $\pi /4$ , respectively, OR logic gate can be obtained. To obtain AND, NOR, NAND, XOR and NXOR logic gate, we just need to get proper phase by adjusting the RF drive voltage and DC bias voltage of the second MZM. According to the simulation, the millimeter wave signal with a frequency of 50 GHz can be obtained, which has completed the logic operation.

The role of eiptranscriptomic modifications in autophagy is unclear. Here, the authors show that the m6A reader YTHDF3 functions as a nutrient responder to recognize upregulated m6A modification, promoting FOXO3 translation to subsequently initiate autophagy.

Summary: Huddling behavior, a typical social interaction among animals, has the benefits of obtaining social support and adapting environment. Huddling behavior is determined by social (social hierarchy), environmental factors (stress events), and the neuroendocrine system. Nevertheless, the huddling behavior of different social hierarchies and the underlying mechanisms have not been fully elucidated. In the present study, acute 2-methyl-2-thiazoline (2 MT) can induce huddling behavior and significantly increase serum levels of testosterone (T) in mice; and the increased T level was positively correlated with huddling behavior. Further, the T treatment significantly increased the huddling behavior in mice under 2 MT exposure condition. More interestingly, T can quickly promote dominant individuals to occupy safe positions when huddling together under predator odor. Collectively, T can rapidly regulate the individual’s adaptive response to threats in a social rank-dependent manner, which provides a new perspective for the in-depth study of the influencing factors and underlying mechanisms of huddling behavior.

The occurrence of new vertebral fractures (NVFs) after vertebral augmentation (VA) procedures is common in patients with osteoporotic vertebral compression fractures (OVCFs), leading to painful experiences and financial burdens. We aim to develop a radiomics nomogram for the preoperative prediction of NVFs after VA. Data from center 1 (training set: n = 153; internal validation set: n = 66) and center 2 (external validation set: n = 44) were retrospectively collected. Radiomics features were extracted from MRI images and radiomics scores (radscores) were constructed for each level-specific vertebra based on least absolute shrinkage and selection operator (LASSO). The radiomics nomogram, integrating radiomics signature with presence of intravertebral cleft and number of previous vertebral fractures, was developed by multivariable logistic regression analysis. The predictive performance of the vertebrae was level-specific based on radscores and was generally superior to clinical variables. RadscoreL2 had the optimal discrimination (AUC ≥ 0.751). The nomogram provided good predictive performance (AUC ≥ 0.834), favorable calibration, and large clinical net benefits in each set. It was used successfully to categorize patients into high- or low-risk subgroups. As a noninvasive preoperative prediction tool, the MRI-based radiomics nomogram holds great promise for individualized prediction of NVFs following VA.

Abstract Introduction Several studies have linked inflammation and oxidative stress with the pathogenesis of depression. Artesunate is a commonly used medication to treat malaria and has been shown to produce antioxidant, anti‐inflammatory, and immunomodulatory effects. However, its prophylactic effects on depression and depression‐related brain pathology are unknown. Methods In Experiment 1, using a PC12 cell line, we investigated whether artesunate can prevent hydrogen peroxide (H2O2)‐induced oxidative injury that mimics oxidative stress commonly observed in the depressed brain. Next, using lipopolysaccharide (LPS)‐induced mouse model of depression, we investigated whether artesunate can prevent behavioral deficits observed in the open field test, novelty‐suppressed feeding test, sucrose preference test, forced swimming test, and tail suspension procedure. Results We found that artesunate significantly prevented a H2O2‐induced reduction in PC12 cell activity, suggesting its antioxidant potential. We also found that mice pretreated with artesunate (5, 15 mg/kg) intraperitoneally (i.p.) prior to the LPS (.8 mg/kg, i.p.) treatment showed fewer and less severe depression‐ and anxiety‐like behaviors than the LPS‐treated control mice. Conclusion Our findings indicate that artesunate produces antioxidant effect, as well as antidepressant and anxiolytic effects. Importantly, our findings first demonstrate that artesunate can prevent LPS‐induced depression‐ and anxiety‐like symptoms, strongly suggesting its prophylactic potential in the treatment of depression and, perhaps, other psychiatric disorders associated with inflammation and oxidative stress.

Summary: Peripheral neuroblastic tumors (PNTs) represent a spectrum of neural-crest-derived tumors, including neuroblastoma, ganglioneuroblastoma, and ganglioneuroma. Malignant cells in PNTs are theorized to interconvert between adrenergic/noradrenergic and mesenchymal/neural crest cell states. Here, single-cell RNA-sequencing analysis of 10 PNTs demonstrates extensive transcriptomic heterogeneity. Trajectory modeling suggests that malignant neuroblasts move between adrenergic and mesenchymal cell states via an intermediate state that we term “transitional.” Transitional cells express programs linked to a sympathoadrenal development and aggressive tumor phenotypes such as rapid proliferation and tumor dissemination. Among primary bulk tumor patient cohorts, high expression of the transitional gene signature is predictive of poor prognosis compared with adrenergic and mesenchymal expression patterns. High transitional gene expression in neuroblastoma cell lines identifies a similar transitional H3K27-acetylation super-enhancer landscape. Collectively, our study supports the concept that PNTs have phenotypic plasticity and uncovers potential biomarkers and therapeutic targets.

Bilayer graphene is a contender of interest for functional electronic applications because of its variable band gap due to interlayer interactions. Graphene growth on Cu is self-limiting, thus despite the fact that chemical vapor deposition (CVD) has made substantial strides in the production of monolayer and single-crystal graphene on Cu substrates, the direct synthesizing of high-quality, large-area bilayer graphene remains an enormous challenge. In order to tackle this issue, we present a simple technique using typical CVD graphene growth followed by a repetitive wrinkling-etching-regrowth procedure. The key element of our approach is the rapid cooling process that causes high-density wrinkles to form in the monolayer area rather than the bilayer area. Next, wrinkled sites are selectively etched with hydrogen, exposing a significant portion of the active Cu surface, and leaving the remaining bilayer areas, which enhance the nucleation and growth of the second graphene layer. A fully covered graphene with 78 ± 2.8% bilayer coverage and a bilayer transmittance of 95.6% at room temperature can be achieved by modifying the process settings. Bilayer graphene samples are examined using optical microscopy (OM), scanning electron microscopy (SEM), Raman spectroscopy, and an atomic force microscope (AFM) during this process. The outcomes of our research are beneficial in clarifying the growth processes and future commercial applications of bilayer graphene.

China is the largest producer and consumer of rice, and the classification of filled/unfilled rice grains is of great significance for rice breeding and genetic analysis. The traditional method for filled/unfilled rice grain identification was generally manual, which had the disadvantages of low efficiency, poor repeatability, and low precision. In this study, we have proposed a novel method for filled/unfilled grain classification based on structured light imaging and Improved PointNet++. Firstly, the 3D point cloud data of rice grains were obtained by structured light imaging. And then the specified processing algorithms were developed for the single grain segmentation, and data enhancement with normal vector. Finally, the PointNet++ network was improved by adding an additional Set Abstraction layer and combining the maximum pooling of normal vectors to realize filled/unfilled rice grain point cloud classification. To verify the model performance, the Improved PointNet++ was compared with six machine learning methods, PointNet and PointConv. The results showed that the optimal machine learning model is XGboost, with a classification accuracy of 91.99%, while the classification accuracy of Improved PointNet++ was 98.50% outperforming the PointNet 93.75% and PointConv 92.25%. In conclusion, this study has demonstrated a novel and effective method for filled/unfilled grain recognition.

Accumulating evidence has proved that aberrant methylation of enhancers plays regulatory roles in gene expression for various cancers including lung adenocarcinoma (LUAD). In this study, the transcriptome and methylation data of The Cancer Genome Atlas (TCGA)-LUAD cohort were comprehensively analyzed with a five-step Enhancer Linking by Methylation/Expression Relationships (ELMER) process. Step 1: 131,371 distal (2 kb upstream from the transcription start site) probes were obtained. Step 2: 10,665 distal hypomethylated probes were identified in an unsupervised mode with the get.diff.meth function. Step 3: 699 probe-gene pairs with negative correlations were screened using the get.pair function in an unsupervised mode. Step 4: After mapping with probes, 768 motifs were obtained and 24 of them were enriched. Step 5: 127 transcription factors (TFs) with differential expressions and negative correlations with methylation levels were screened, which were corresponding to 21 motifs. After the ELMER process, a prognostic “TFs-motifs-genes” regulatory network was constructed. The Least absolute shrinkage and selection operator (LASSO) and Stepwise regression analyses were further applied to identify variables in the TCGA-LUAD cohort and an eight-gene signature was constructed for calculating the risk score. The risk score was verified in two independent validation cohorts. The area under curve values of receiver operating characteristic curves predicting 1-, 3-, and 5-years survival ranged from 0.633 to 0.764. With the increase of the risk scores, both the survival statuses and clinical traits showed a worse tendency. There were significant differences in the degrees of immune cell infiltration, TMB values, and TIDE scores between the high-risk and low-risk groups. Finally, a better-performing prognostic nomogram was integrated with the risk score and other clinical traits. In short, this multi-omics analysis demonstrated the application of ELMER in analyzing enhancer-associated regulatory network in LUAD, which provided promising strategies for epigenetic therapy and prognostic biomarkers.

The persistence of drug memory contributes to relapse to drug seeking. The association between repeated drug exposure and drug-related cues leads to cravings triggered by drug-paired cues. The erasure of drug memories has been considered a promising way to inhibit cravings and prevent relapse. The re-exposure to drug-related cues destabilizes well-consolidated drug memories, during which a de novo protein synthesis-dependent process termed “reconsolidation” occurs to restabilize the reactivated drug memory. Disrupting reconsolidation of drug memories leads to the attenuation of drug-seeking behavior in both animal models and people with addictions. Additionally, epigenetic mechanisms regulated by DNA methyltransferase (DNMT) are involved in the reconsolidation of fear and cocaine reward memory. In the present study, we investigated the role of DNMT in the reconsolidation of heroin reward memory. In the heroin self-administration model in rats, we tested the effects of DNMT inhibition during the reconsolidation process on cue-induced reinstatement, heroin-priming-induced reinstatement, and spontaneous recovery of heroin-seeking behavior. We found that the bilateral infusion of 5-azacytidine (5-AZA) inhibiting DNMT into the basolateral amygdala (BLA) immediately after heroin reward memory retrieval, but not delayed 6 h after retrieval or without retrieval, decreased subsequent cue-induced and heroin-priming-induced reinstatement of heroin-seeking behavior. These findings demonstrate that inhibiting the activity of DNMT in BLA during the reconsolidation of heroin reward memory attenuates heroin-seeking behavior, which may provide a potential strategy for the therapeutic of heroin addiction.

Increasing evidence has indicated that circular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs) regulatory network to regulate the expression of target genes by sponging microRNAs (miRNAs), and therefore play an essential role in many neuropsychiatric disorders, including cocaine use disorder. However, the functional roles and regulatory mechanisms of circRNAs as ceRNAs in dorsolateral prefrontal cortex (dlPFC) of patients with cocaine use disorder remain to be determined. In this study, an expression profiling for dlPFC in 19 patients with cocaine use disorder and 17 controls from Gene Expression Omnibus datasets was used for the differentially expressed circRNAs analysis and the differentially expressed mRNAs analysis. Several tools were used to predict the miRNAs targeted by the circRNAs and the miRNAs targeted mRNAs, which then overlapped with the cocaine-associated differentially expressed mRNAs to determine the functional roles of circRNAs. Functional analysis for the obtained mRNAs was performed via Gene Ontology (GO) in Metascape database. Integrated bioinformatics analysis was conducted to further characterize the circRNA–miRNA–mRNA regulatory network and identify the functions of distinct circRNAs. We found a total of 41 differentially expressed circRNAs, and 98 miRNAs were targeted by these circRNAs. The overlapped mRNAs targeted by the miRNAs and the differentially expressed mRNAs constructed a circRNA–miRNA–mRNA regulation network including 24 circRNAs, 43 miRNAs, and 82 mRNAs in the dlPFC of patients with cocaine use disorder. Functional analysis indicated the regulation network mainly participated in cell response-related, receptor signaling-related, protein modification-related and axonogenesis-related pathways, which might be involved with cocaine use disorder. Additionally, we determined four hub genes (HSP90AA1, HSPA1B, YWHAG, and RAB8A) from the protein–protein interaction network and constructed a circRNA–miRNA-hub gene subnetwork based on the four hub genes. In conclusion, our findings provide a deeper understanding of the circRNAs-related ceRNAs regulatory mechanisms in the pathogenesis of cocaine use disorder.

Tuning the level of oxygen vacancies in metal oxide materials is a promising approach to enhance resistive switching properties towards memory applications. To comprehensively understand the microstructure and oxygen vacancy migration mechanism of oxide materials, recent research in controlling the concentration of oxygen vacancies and the relationship between oxygen vacancy and resistive switching behavior as well as computational study have been reviewed in this work. In particular, the role of oxygen vacancies on the resistive switching properties of various metal oxides, including transition oxides, perovskite oxides and complex oxides are discussed in this review. Moreover, different types of processing methodologies of oxygen vacant oxide materials are reviewed and compared in detail. In the end, the future trends in fine tuning the level of oxygen vacancies are reviewed and discussed.

Diabetic retinopathy (DR) is an important complication with a high incidence of 34.6% in the diabetic populations. DR could finally lead to vision impairment without effective interventions, during which, diabetic macular edema (DME) is a key phase causing visual loss. Up to date, antivascular endothelial growth factor (anti-VEGF) therapy is the first-line treatment for DME which has achieved relatively better clinical outcomes than traditional treatments. However, there are several kinds of anti-VEGF medicines, and patients are sensitive to different anti-VEGF treatments. In addition, its effectiveness is unstable. Considering the patients’ need to accept continual anti-VEGF treatments and its price is comparatively high, it is clinically important to predict the prognosis after different anti-VEGF treatments. In our research, we used the demographic and clinical data of 254 DME patients and 2,763 optical coherence tomography (OCT) images from three countries to predict the fundus structural and functional parameters and treatment plan in 6 months after different anti-VEGF treatments. Eight baseline features combined with 11 models were applied to conduct seven prediction tasks. Accuracy (ACC), the area under curve (AUC), mean absolute error (MAE), and mean square error (MSE) were respectively used to evaluate the classification and regression tasks. The ACC and AUC of structural predictions of retinal pigment epithelial detachment were close to 1.000. The MAE and MSE of visual acuity predictions were nearly 0.3 to 0.4 logMAR. The ACC of treatment plan regarding continuous injection was approaching 70%. Our research has achieved great performance in the predictions of fundus structural and functional parameters as well as treatment plan, which can help ophthalmologists improve the treatment compliance of DME patients.

Exposure to a catastrophic event or intense stimulation can trigger fear memories, and the threatening memories persist even over a lifetime. Exposure therapy is based on extinction learning and is widely used to treat fear-related disorders, but its effect on remote fear memory is modest. Berberine, an isoquinoline alkaloid derived from Coptis chinensis or Berberis spp., has been recently reported to exert a diversity of pharmacological effects on the central nervous system, such as facilitating extinction of drug memory. Here, we explored the effect of berberine on extinction of fear memory using a classical contextual fear conditioning (CFC) paradigm, which is Pavlovian conditioning, can rapidly create fear memories related to contexts. Twenty-four hours or 30 days after CFC training, mice were subjected to context extinction (10 days) to extinguish their behaviors and treated with 12.5 or 25 mg/kg berberine intragastrically 1 or 6 h after each extinction session, followed by reinstatement and spontaneous recovery tests. The results showed that intragastric administration of 25 mg/kg berberine 1 h after extinction significantly promoted the extinction of recent and remote fear memories and prevented reinstatement and spontaneous recovery of extinguished fear in mice. These findings indicate that berberine combined with extinction training could serve as a promising novel avenue for the treatment of fear-related disorders.

Carbon monoxide (CO), a byproduct of heme catalyzed by heme oxygenase (HO), has been reported to exert antioxidant and anti-inflammatory actions, and to produce significant neuroprotective effects. The potential effects of CO and even HO on depressive-like behaviors are still poorly understood. Utilizing several approaches including adeno-associated virus (AAV)-mediated overexpression of HO-1, systemic CO-releasing molecules (CO-RMs), CO-rich saline or CO gas treatment procedures in combination with hydrogen peroxide (H2O2)-induced PC12 cell injury model, and lipopolysaccharide (LPS)-induced depression mouse model, the present study aimed to investigate the potential antidepressant- and anxiolytic-like effects of endogenous and exogenous CO administration in vivo and in vitro. The results of in vitro experiments showed that both CO-RM-3 and CO-RM-A1 pretreatment blocked H2O2-induced cellular injuries by increasing cell survival and decreasing cell apoptosis and necrosis. Similar to the effects of CO-RM-3 and CO-RM-A1 pretreatment, AAV-mediated HO-1 overexpression in the dorsal hippocampus produced significant antidepressant-like activities in mice under normal conditions. Further investigation showed that the CO gas treatment significantly blocked LPS-induced depressive- and anxiety-like behaviors in mice. Taken together, our results suggest that the activation of HO-1 and/or exogenous CO administration produces protective effects and exerts antidepressant- and anxiolytic-like effects. These data uncover a novel function of the HO-1/CO system that appears to be a promising therapeutic target for the treatment of depression and anxiety.

Drug addiction can be seen as a disorder of maladaptive learning characterized by relapse. Therefore, disrupting drug-related memories could be an approach to improving therapies for addiction. Pioneering studies over the last two decades have revealed that consolidated memories are not static, but can be reconsolidated after retrieval, thereby providing candidate pathways for the treatment of addiction. The limbic–corticostriatal system is known to play a vital role in encoding the drug memory engram. Specific structures within this system contribute differently to the process of memory reconsolidation, making it a potential target for preventing relapse. In addition, as molecular processes are also active during memory reconsolidation, amnestic agents can be used to attenuate drug memory. In this review, we focus primarily on the brain structures involved in storing the drug memory engram, as well as the molecular processes involved in drug memory reconsolidation. Notably, we describe reports regarding boundary conditions constraining the therapeutic potential of memory reconsolidation. Furthermore, we discuss the principles that could be employed to modify stored memories. Finally, we emphasize the challenge of reconsolidation-based strategies, but end with an optimistic view on the development of reconsolidation theory for drug relapse prevention.

Persistent traces of drug reward memories contribute to intense craving and often trigger relapse. A number of pharmacological interventions on drug-associated memories have shown significant benefits in relapse prevention at a preclinical level but their translational potential is limited due to deleterious side effects. Propranolol, a non-specific β-adrenergic receptors antagonist, is known for its ability to erase maladaptive memories associated with nicotine or cocaine in rodents and humans. However, little is known about its effect on reconsolidation of heroin memory and heroin seeking. In the present study, rats with a history of intravenous heroin self-administration received the propranolol treatment (10 mg/kg; i.p.) at different time windows with or without CS (conditioned stimulus) exposure. Our results showed that propranolol, when administered immediately after CS exposure but not 6 h later, can significantly attenuate cue-induced and drug-primed reinstatement of heroin seeking, suggesting that propranolol has the ability to disrupt heroin memory and reduce relapse. The propranolol treatment without retrieval of drug memory had no effect on subsequent reinstatement of heroin seeking, suggesting that its interfering effects are retrieval-dependent. Importantly, the effects of propranolol were long lasting as rats showed diminished drug seeking even 28 days after the treatment. Altogether, our study suggests that propranolol can interfere with reconsolidation of heroin memory and reduce subsequent drug seeking, making it an attractive therapeutic candidate for the treatment of opioid addiction and relapse prevention.

Drug addiction is considered maladaptive learning, and drug-related memories aroused by the presence of drug related stimuli (drug context or drug-associated cues) promote recurring craving and reinstatement of drug seeking. The mammalian target of rapamycin signaling pathway is involved in reconsolidation of drug memories in conditioned place preference and alcohol self-administration (SA) paradigms. Here, we explored the effect of mTOR inhibition on reconsolidation of addiction memory using cocaine self-administration paradigm. Rats received intravenous cocaine self-administration training for 10 consecutive days, during which a light/tone conditioned stimulus was paired with each cocaine infusion. After acquisition of the stable cocaine self-administration behaviors, rats were subjected to nosepoke extinction (11 days) to extinguish their behaviors, and then received a 15 min retrieval trial with or without the cocaine-paired tone/light cue delivery or without. Immediately or 6 h after the retrieval trial, rapamycin (10 mg/kg) was administered intraperitoneally. Finally, cue-induced reinstatement, cocaine-priming-induced reinstatement and spontaneous recovery of cocaine-seeking behaviors were assessed in rapamycin previously treated animals, respectively. We found that rapamycin treatment immediately after a retrieval trial decreased subsequent reinstatement of cocaine seeking induced by cues or cocaine itself, and these effects lasted at least for 28 days. In contrast, delayed intraperitoneal injection of rapamycin 6 h after retrieval or rapamycin injection without retrieval had no effects on cocaine-seeking behaviors. These findings indicated that mTOR inhibition within the reconsolidation time-window impairs the reconsolidation of cocaine associated memory, reduces cocaine-seeking behavior and prevents relapse, and these effects are retrieval-dependent and temporal-specific.

Abstract The study of litter decomposition was often tightly linked to some hot topics such as global carbon balance and climate change, but the knowledge of microbes involved in litter decomposition remains limited especially in freshwater lake wetlands. An in situ experiment (278 d) was carried out to study the decomposition processes of two typical wetland plants—Carex cinerascens and Triarrhena lutarioriparia. The litter decay rate, extracellular enzyme, and microbial community composition were all observed. The decomposition rate of C. cinerascens was faster than T. lutarioriparia. Higher contents of TOC, TN, and TP conferred higher decomposition rate to C. cinerascens, as well as the higher activities of all tested enzymes and the lower content of lignin. The alpha diversity of bacterial and fungal communities changed separately over time, but their copy numbers of the rRNA gene (qPCR) increased collectively in both litters. Betaproteobacteria, Gammaproteobacteria, Bacteroidetes, and Basidiomycota were common in the primary stage (0–37 d) of decay in both litters, while Alphaproteobacteria, Chloroflexi, Nitrospirae, and Montagnulaceae were prevailing in the later stage (212–278 d). T. lutarioriparia also had higher proportions of Actinobacteria, Acidobacteria, and Firmicutes in the later stage. Pleosporales and Hypocreales were predominant during the whole decay processes of both litters. Our results showed that the microbial community composition was mainly regulated by litter stoichiometry (hemicellulose, lignin, and AFDM), thereby reflecting the niches differentiation caused by resource partitioning on litter decomposition. This work helps to the understanding of the microbial community involved in litter decomposition in wetland ecosystems.

This paper reports on the effect of direct fluorination on interface discharge characteristics between isotactic polypropylene (PP) and silicone rubber under AC voltage. The influence of fluorination time on discharge initiation and propagation stages has been estimated by measuring phase resolved partial discharge pattern and relationship between discharge rate (N) and discharge magnitude (Q). Attenuated total reflection Fourier transform infrared spectrum, water contact angle and surface roughness were also measured to gain a better understanding of the fluorination effect on surface chemical and physical structures of sample. Obtained results showed that with the increase of fluorination time from 0 to 15 min, the average surface roughness of PP increased from 42 to 65 nm, whereas the water contact angle decreased from 88° to 58°. In addition, the discharge initiation time increased from 2 to 4 s but the discharge propagation time decreased from 14 to 2 s, leading to the reduction in overall time of interface breakdown from 16 to 6 s. It is suggested that at the initiation stage the C-F bond introduced by direct fluorination with higher bond energy and deeper trap depth should be responsible for the alleviation of polymer degradation, while at the propagation stage the formation of larger void at the surface tends to accelerate the degradation of polymer. It could be concluded that although the direct fluorination has positive effect by delaying the appearance of discharge channel, it possesses negative effect by shortening the propagation process.

In this paper, we report on electrical and mechanical properties of isotactic polypropylene (PP) blended with polyolefin elastomer (POE) and propylene-based elastomer (PBE). Carrier trap distribution of the samples was estimated by isothermal surface potential decay measurement, while dc breakdown strength was measured through a pair of semicircle electrodes. Elongation at break and tensile strength were obtained to examine the variation in mechanical property of PP caused by the addition of elastomers. Furthermore, scanning electron microscope (SEM), differential scanning calorimetry (DSC), and dynamic mechanical analysis (DMA) have been employed to assist the understanding of morphology of the blends, thermal properties, and mechanical properties. Obtained results have indicated that with the increase of the elastomer content from 0 to 30 wt%, the trap depth appeared to be shallower and the dc breakdown strength tended to be reduced for both PP/PBE and PP/POE samples. Compared with PP/POE blend, PP/PBE blend had deeper trap depth, which should be responsible for its higher dc breakdown strength. In addition, PP/PBE blend has presented a better performance in elongation at break and tensile strength measurement. With the growth of the elastomer content, the crystallinity of the blends appeared to decrease, whereas the melting and the crystallization temperatures did not change remarkably. The SEM inspections and DMA results revealed better compatibility between PP and PBE compared with that between PP and POE, which should be the reason for the better electrical and mechanical properties of PP/PBE blend. The blend of PBE with low content could result in remarkably improved flexibility of PP with acceptable electrical strength for dc cable insulation.

This paper describes the role of Ge as an enabler for light emitters on a Si platform. In spite of the large lattice mismatch of ~4.2% between Ge and Si, high-quality Ge layers can be epitaxially grown on Si by ultrahigh-vacuum chemical vapor deposition. Applications of the Ge layers to near-infrared light emitters with various structures are reviewed, including the tensile-strained Ge epilayer, the Ge epilayer with a delta-doping SiGe layer, and the Ge/SiGe multiple quantum wells on Si. The fundamentals of photoluminescence physics in the different Ge structures are discussed briefly.

Summary: Nature does nothing in vain. Through millions of years of revolution, living organisms have evolved hierarchical and anisotropic structures to maximize their survival in complex and dynamic environments. Many of these structures are intrinsically heterogeneous and often with functional gradient distributions. Understanding the convergent and divergent gradient designs in the natural material systems may lead to a new paradigm shift in the development of next-generation high-performance bio-/nano-materials and devices that are critically needed in energy, environmental remediation, and biomedical fields. Herein, we review the basic design principles and highlight some of the prominent examples of gradient biological materials/structures discovered over the past few decades. Interestingly, despite the anisotropic features in one direction (i.e., in terms of gradient compositions and properties), these natural structures retain certain levels of symmetry, including point symmetry, axial symmetry, mirror symmetry, and 3D symmetry. We further demonstrate the state-of-the-art fabrication techniques and procedures in making the biomimetic counterparts. Some prototypes showcase optimized properties surpassing those seen in the biological model systems. Finally, we summarize the latest applications of these synthetic functional gradient materials and structures in robotics, biomedical, energy, and environmental fields, along with their future perspectives. This review may stimulate scientists, engineers, and inventors to explore this emerging and disruptive research methodology and endeavors.

Hydraulic fracturing has become one of the most popular techniques for exploring sustainable energy sources. However, friction is associated with the entire fracturing process, presenting significant challenges for development. Facing the huge friction challenges, this review is elaborated in the following three aspects: (1) the fundamentals of hydraulic fracturing, including three aspects of rock fracture mechanism, fracturing fluid, and proppant; (2) the friction challenges in hydraulic fracturing, which mainly exist in friction along the path and friction near wellbore; (3) hydraulic fracturing drag reduction technologies, which are considered proppant segment plug, fracturing fluid viscosity enhancement, and proppant surface modification technologies. Therefore, we should not only understand the challenges in hydraulic fracturing but also know how to mitigate them. Additionally, we call for a strong focus on environmentally friendly, green friction-reducing technologies for oil and gas fields in the future development of the fracturing industry.