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The future pedagogical systems need anthropocentric inclusive educational programs in which the goal should be adjustable according to the knowledge requirements, intelligence, and learning objective of each student. Prioritizing these needs, innovative AI methods are required to assist and ensure the making of conscious educational decisions, in terms of clear identification and categorization with high accuracy of various forms of skills and knowledge of each student. This paper proposes a neuroevolution emerging technique that combines the searchability of evolutionary computation and the learning capability of a hybrid artificial neural networks method. Specifically, the proposed growing semiorganizing neural gas (GsONG) is a practical AI methodology utilizing advanced clustering techniques to enhance the learning experience by categorizing the true abilities, skills, and needs of learners, in an inclusive differentiated learning framework. It is a neural network architecture that includes competing and cooperating neurons with an unstructured mode whereby a cooperation-competition process delimits the topological neighborhood of neurons in a grid to identify patterns for which their classes are not known. To optimize the above process, a heuristic method was used that investigates the space of an objective function by regulating the optimal topologies of neurons that form pathway segments in a semi-contemplative manner. Based on the extensive experiments and results obtained from the GsONG clustering approach, the proposed algorithm can compensate with high accuracy for difficulties in multicriteria grouping and differentiation of uncertainty structures such as in small or tiny data sets.

For high dimensional gene expression data, one important goal is to identify a small number of genes that are associated with progression of the disease or survival of the patients. In this paper, we consider the problem of variable selection for multivariate survival data. We propose an estimation procedure for high dimensional accelerated failure time (AFT) models with bivariate censored data. The method extends the Buckley-James method by minimizing a penalized [Formula: see text] loss function with a penalty function induced from a bivariate spike-and-slab prior specification. In the proposed algorithm, censored observations are imputed using the Kaplan-Meier estimator, which avoids a parametric assumption on the error terms. Our empirical studies demonstrate that the proposed method provides better performance compared to the alternative procedures designed for univariate survival data regardless of whether the true events are correlated or not, and conceptualizes a formal way of handling bivariate survival data for AFT models. Findings from the analysis of a myeloma clinical trial using the proposed method are also presented.

Echocardiography is essential for evaluating cardiac anatomy and function during early recognition and screening for congenital heart disease (CHD), a widespread and complex congenital malformation. However, fetal CHD recognition still faces many difficulties due to instinctive fetal movements, artifacts in ultrasound images, and distinctive fetal cardiac structures. These factors hinder capturing robust and discriminative representations from ultrasound images, resulting in CHD's low prenatal detection rate. Hence, we propose a multi-scale gated axial-transformer network (MSGATNet) to capture fetal four-chamber semantic information. Then, we propose a SPReCHD: four-chamber semantic parsing network for recognizing fetal CHD in the clinical treatment of the medical metaverse, integrating MSGATNet to segment and locate four-chamber arbitrary contours, further capturing distinguished representations for the fetal heart. Comprehensive experiments indicate that our SPReCHD is sufficient in recognizing fetal CHD, achieving a precision of 95.92%, a recall of 94%, an accuracy of 95%, and a F

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods can now yield exceptionally accurate reconstructions of cells, but despite this accuracy, laborious post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons produced by these segmentations contain detailed morphological information, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting information about these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present “NEURD”, a software package that decomposes each meshed neuron into a compact and extensively-annotated graph representation. With these feature-rich graphs, we implement workflows for state of the art automated post-hoc proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other features that can enable many downstream analyses of neural morphology and connectivity. NEURD can make these new massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

To understand how the neocortex underlies our ability to perceive, think, and act, it is important to study the relationship between circuit connectivity and function. Previous research has shown that excitatory neurons in layer 2/3 of the primary visual cortex of mice with similar response properties are more likely to form connections. However, technical challenges of combining synaptic connectivity and functional measurements have limited these studies to few, highly local connections. Utilizing the millimeter scale and nanometer resolution of the MICrONS dataset, we studied the connectivity-function relationship in excitatory neurons of the mouse visual cortex across interlaminar and interarea projections, assessing connection selectivity at the coarse axon trajectory and fine synaptic formation levels. A digital twin model of this mouse, that accurately predicted responses to arbitrary video stimuli, enabled a comprehensive characterization of the function of neurons. We found that neurons with highly correlated responses to natural videos tended to be connected with each other, not only within the same cortical area but also across multiple layers and visual areas, including feedforward and feedback connections, whereas we did not find that orientation preference predicted connectivity. The digital twin model separated each neuron’s tuning into a feature component (what the neuron responds to) and a spatial component (where the neuron’s receptive field is located). We show that the feature, but not the spatial component, predicted which neurons were connected at the fine synaptic scale. Together, our results demonstrate the “like-to-like” connectivity rule generalizes to multiple connection types, and the rich MICrONS dataset is suitable to further refine a mechanistic understanding of circuit structure and function.

Neurons in the neocortex exhibit astonishing morphological diversity which is critical for properly wiring neural circuits and giving neurons their functional properties. The extent to which the morphological diversity of excitatory neurons forms a continuum or is built from distinct clusters of cell types remains an open question. Here we took a data-driven approach using graph-based machine learning methods to obtain a low-dimensional morphological “bar code” describing more than 30,000 excitatory neurons in mouse visual areas V1, AL and RL that were reconstructed from a millimeter scale serial-section electron microscopy volume. We found a set of principles that captured the morphological diversity of the dendrites of excitatory neurons. First, their morphologies varied with respect to three major axes: soma depth, total apical and basal skeletal length. Second, neurons in layer 2/3 showed a strong trend of a decreasing width of their dendritic arbor and a smaller tuft with increasing cortical depth. Third, in layer 4, atufted neurons were primarily located in the primary visual cortex, while tufted neurons were more abundant in higher visual areas. Fourth, we discovered layer 4 neurons in V1 on the border to layer 5 which showed a tendency towards avoiding deeper layers with their dendrites. In summary, excitatory neurons exhibited a substantial degree of dendritic morphological variation, both within and across cortical layers, but this variation mostly formed a continuum, with only a few notable exceptions in deeper layers.

Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form. This physical transformation of neurons is facilitated by the engulfment and degradation of axonal branches and synapses by surrounding glial cells, including microglia and astrocytes. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia have made it difficult to define the contribution of these and other glial cell types to this crucial process. Here, we used large-scale, serial section transmission electron microscopy (TEM) with computational volume segmentation to reconstruct the complete 3D morphologies of distinct glial types in the mouse visual cortex, providing unprecedented resolution of their morphology and composition. Unexpectedly, we discovered that the fine processes of oligodendrocyte precursor cells (OPCs), a population of abundant, highly dynamic glial progenitors, frequently surrounded small branches of axons. Numerous phagosomes and phagolysosomes (PLs) containing fragments of axons and vesicular structures were present inside their processes, suggesting that OPCs engage in axon pruning. Single-nucleus RNA sequencing from the developing mouse cortex revealed that OPCs express key phagocytic genes at this stage, as well as neuronal transcripts, consistent with active axon engulfment. Although microglia are thought to be responsible for the majority of synaptic pruning and structural refinement, PLs were ten times more abundant in OPCs than in microglia at this stage, and these structures were markedly less abundant in newly generated oligodendrocytes, suggesting that OPCs contribute substantially to the refinement of neuronal circuits during cortical development.

Microbial signatures have emerged as promising biomarkers and targets for disease diagnosis, prognosis, and remission. However, these biomarkers exhibit contradictory results in different studies, necessitating the identification of universally robust microbial biomarkers. Therefore, we introduce xMarkerFinder, a four-stage computational framework for microbial biomarker identification with comprehensive validations from cross-cohort datasets, including differential signature identification, model construction, model validation, and biomarker interpretation. xMarkerFinder enables the identification and validation of reproducible biomarkers for cross-cohort studies, along with the establishment of classification models and potential microbiome-induced mechanisms. Although xMarkerFinder is initially developed for gut microbiome study, it is generalizable to different omics layers, as well as other habitats. Execution time varies depending on the sample size, selected algorithm, and computational resource. xMarkerFinder can be accessed at https://github.com/tjcadd2020/xMarkerFinder. FAQs, detailed tutorials, issue boards, and a ready-to-use Docker image are provided for users with no prior bioinformatics or statistics training.

A large amount of waste dust will be produced in the process of metal grinding, resulting in a waste of resources and environmental pollution. Therefore, we present a new method of inerting waste aluminum (Al) alloy dust for recycling purposes. Three natural high polymers—starch, pectin, and hydroxypropyl cellulose—were selected to inert waste metal dust in order to prevent the alloy from hydrolyzing and keep the dust pure enough for reuse. The particles of the Al base alloy before and after dust reaction were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infra-red (FTIR), and the relevant reaction mechanism was clarified. The hydrogen evolution test indicated that, across the temperature interval of 313–333 K, 0.75 wt% pectin inerted hydrogen evolution most efficiently (90.125%). XRD analysis indicated that the inerted product is composed of Al monomer and Al3Mg2, with no detectable content of Al hydroxide. The purity of the Al alloy dust was preserved. SEM and FTIR analyses indicated that the -OH, -COOH, and -COOCH3 functional groups in the high polymer participated in the coordination reaction by adsorbing on the surface of the waste Al alloy particles to produce a protective film, which conforms to Langmuir’s adsorption model. Verification of the inerted Al alloy dust in industrial production confirmed the possibility of reusing waste Al alloy dust. This study provides a simple and effective method for recycling waste Al alloy dust.

Hepatocellular carcinoma (HCC) is a major subtype of primary liver cancer with a high mortality rate. Pyroptosis and autophagy are crucial processes in the pathophysiology of HCC. Searching for efficient drugs targeting pyroptosis and autophagy with lower toxicity is useful for HCC treatment. Mallotucin D (MLD), a clerodane diterpenoid from

Serial-section electron microscopy (ssEM) is the method of choice for studying macroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so calledconnectomes. In order to use this data, consisting of up to 108individual EM images, it must be assembled into a volume, requiring seamless 2D stitching from each physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipelineASAP(Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of theRender[18] services used in the volume assembly of the brain of adultDrosophila melanogaster[2]. It achieves high throughput by operating on the meta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP is modular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous processing of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex [1, 25] at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

Mammalian neocortex contains a highly diverse set of cell types. These types have been mapped systematically using a variety of molecular, electrophysiological and morphological approaches. Each modality offers new perspectives on the variation of biological processes underlying cell type specialization. While many morphological surveys focus on branching patterns of individual cells, fewer have been devoted to sub-cellular structure of cells. Electron microscopy (EM) provides dense ultrastructural examination and an unbiased perspective into the subcellular organization of brain cells, including their synaptic connectivity and nanometer scale morphology. Here we present the first systematic survey of the somatic region of nearly 100,000 cortical cells, using quantitative features obtained from EM. This analysis demonstrates a surprising sufficiency of the perisomatic region to recapitulate many known aspects of cortical organization, while also revealing novel relationships. Parameters of cell size, nuclear infolding and somatic synaptic innervation co-vary with distinct patterns across depth and between types. Further, we describe how these subcellular features can be used to create highly accurate predictions of cell-types across large scale EM datasets. More generally, our results suggest that the shifts in cellular physiology and molecular programming seen across cell types accompany profound differences in the fine-scale structure of cells.

In order to alleviate the dust pollution in the fully mechanized mining face, the novel negative pressure entrainment dust collector was optimized by the method of orthogonal experimental design and numerical simulation. The influences of nozzle distance, throat diameter and diffusion angle on the atomization efficiency of the proposed dust collector was investigated. The obtained results showed that the optimum ejection dust removal performance of the developed negative pressure entrainment dust collector was obtained for throat diameter 80 mm, throat distance 60 mm and diffusion angle 20 degrees. Under these conditions, air suction rate at the entrance of contraction section was 17.48 m3/min and the average droplet size and mass concentration were 62.99 μm and 0.034 kg/m3, respectively. Here, we have proposed a local closed atomization control dust removal technology for hydraulic support areas based on the optimized negative pressure entrainment dust collector. After the application of the developed system in 2307 fully mechanized mining face in Tangkou Coal Mine, the average total dust of measuring points was decreased from 337.90 to 49.53 mg/m3 and average exhaust dust was decreased from 271.80 to 41.40 mg/m3. The average dust removal rates of total dust and exhaled dust were 85.17% and 84.74% respectively, and dust removal efficiency of the proposed system was obviously confirmed.

Burkitt lymphoma (BL) is an aggressive Epstein-Barr virus (EBV)-driven B-cell lymphoma characterized by the translocation and rearrangement of the c-Myc proto-oncogene. High-intensity multidrug chemotherapy regimens have a limited effect on the survival of refractory or relapsed BL patients, mainly owing to the high EBV load and drug resistance. l-asparaginase ( l-Asp) and etoposide (VP-16) play a beneficial role in EBV-related lymphoproliferative diseases; however, their roles and mechanisms in BL remain unclear. In this study, we found that VP-16 inhibited BL cell proliferation and arrested the cell cycle at the G

The diagnostic utility of poor body composition measures in sarcopenia remains unclear. We hypothesize that the skeletal muscle gauge [combination of skeletal muscle mass index (SMI) and skeletal muscle density (SMD); SMG = SMI × SMD] would have significant diagnostic and predictive value in certain regions and populations.Prospective cross-sectional study.We examined inpatients age ≥60 years with or without cancer and with gastrointestinal disorders.We used computed tomography (CT) image metrics in the 12th thoracic (T12), third lumbar (L3), erector spinae muscle (ESM), and psoas muscle (PM) regions to establish correlations with the 2019 Asian Working Group for Sarcopenia Consensus and used receiver operating characteristic area under the curve (AUC) to compare differences between metrics. Associations between CT metrics and mortality were reported as relative risk after adjustments.We evaluated 385 patients (median age, 69.0 years; 60.8% men) and found consistent trends in cancer (49.6%) and noncancer (50.4%) cohorts. SMG had a stronger correlation with muscle mass than SMD [mean rho: 0.68 (range, 0.59‒0.73) vs 0.39 (range, 0.28‒0.48); all P.05] in T12, L3, and PM regions and a stronger correlation with muscle function than SMI [mean rho: 0.60 (range, 0.50‒0.77) vs 0.36 (range, 0.22‒0.58); all P.05] in T12, ESM, and L3 regions. SMG outperformed SMI in diagnostic accuracy in all regions, particularly for L3 (AUC: 0.87‒0.88 vs 0.80‒0.82; both P.05). PM gauge and L3SMG did not differ, whereas EMG (ESM gauge) or T12SMG and L3SMG did (AUC: 0.80‒0.82 vs 0.87‒0.88; all P.05). L3SMI, L3SMD, T12SMG, EMG, and PM gauge showed no association with 1-year cancer-related mortality after adjusting for confounders; however, L3SMG [relative risk = 0.92 (0.85‒0.99); P = .023) was.L3SMG covers all features of sarcopenia with more diagnostic value than other metrics, allowing a complete sarcopenia assessment with CT alone and not just in populations with cancer.

Generally, the addition of exogenous stem cells and host-to-scaffold immune responses restricts the clinical applications of hydroxyapatite (HA)/chitosan (CS) scaffolds for bone regeneration. To achieve "facilitated endogenous tissue engineering", magnetic M-type hexagonal ferrite (SrFe12O19) nanoparticles were incorporated into bone scaffolds to recruit endogenous stem cells. Then, lanthanum incorporation was utilized to regulate host-to-scaffold immune responses and to provide a pro-regenerative environment for recruited endogenous stem cells. Here, we first fabricated and characterized magnetic lanthanum-doped HA/CS scaffolds. The MLaHA/CS scaffolds were demonstrated to be effective at recruiting rat bone marrow mesenchymal stem cells (rBMSCs) and modulating host-to-scaffold immune responses by promoting macrophage polarization into the anti-inflammatory phenotype (M2) in vitro. By further examining the underlying mechanism, we found that MLaHA/CS scaffolds could promote the osteogenic differentiation of rBMSCs by upregulating the phosphorylation of the Smad 1/5/9 pathway. When MLaHA/CS scaffolds were implanted into rat calvarial defects, the incorporation of magnetic nanoparticles and lanthanum significantly promoted the new bone regeneration, as revealed by micro-CT assays and histological staining. Our findings suggest that MLaHA/CS shows great potential for use as a cell-free and biocompatible scaffold for bone regeneration.

3D electron microscopy (EM) has been successful at mapping invertebrate nervous systems, but the approach has been limited to small chunks of mammalian brains. To scale up to larger volumes, we have built a computational pipeline for processing petascale image datasets acquired by serial section EM, a popular form of 3D EM. The pipeline employs convolutional nets to compute the nonsmooth transformations required to align images of serial sections containing numerous cracks and folds, detect neuronal boundaries, label voxels as axon, dendrite, soma, and other semantic categories, and detect synapses and assign them to presynaptic and postsynaptic segments. The output of neuronal boundary detection is segmented by mean affinity agglomeration with semantic and size constraints. Pipeline operations are implemented by leveraging distributed and cloud computing. Intermediate results of the pipeline are held in cloud storage, and can be effortlessly viewed as images, which aids debugging. We applied the pipeline to create an automated reconstruction of an EM image volume spanning four visual cortical areas of a mouse brain. Code for the pipeline is publicly available, as is the reconstructed volume.

To understand the brain we must relate neurons’ functional responses to the circuit architecture that shapes them. Here, we present a large functional connectomics dataset with dense calcium imaging of a millimeter scale volume. We recorded activity from approximately 75,000 neurons in primary visual cortex (VISp) and three higher visual areas (VISrl, VISal and VISlm) in an awake mouse viewing natural movies and synthetic stimuli. The functional data were co-registered with a volumetric electron microscopy (EM) reconstruction containing more than 200,000 cells and 0.5 billion synapses. Subsequent proofreading of a subset of neurons in this volume yielded reconstructions that include complete dendritic trees as well the local and inter-areal axonal projections that map up to thousands of cell-to-cell connections per neuron. Here, we release this dataset as an open-access resource to the scientific community including a set of tools that facilitate data retrieval and downstream analysis. In accompanying papers we describe our findings using the dataset to provide a comprehensive structural characterization of cortical cell types1–3and the most detailed synaptic level connectivity diagram of a cortical column to date2, uncovering unique cell-type specific inhibitory motifs that can be linked to gene expression data4. Functionally, we identify new computational principles of how information is integrated across visual space5, characterize novel types of neuronal invariances6and bring structure and function together to decipher a general principle that wires excitatory neurons within and across areas7, 8.

A q-rung orthopair fuzzy set (q-ROFS) is an effective tool for describing uncertainty and fuzziness, and is the promotion of intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs). This paper extends q-rung orthopair fuzzy environment to probabilistic q-rung orthopair hesitant fuzzy environment, and proposes the concept of probabilistic q-rung orthopair hesitant fuzzy sets (P-q-ROHFSs). Some desired operational laws and properties of P-q-ROHFSs are studied. And we develop the some aggregation operators for probabilistic q-rung orthopair hesitant fuzzy information. Then the relationship among these operators is discussed by comparing the score function. In order to measure the uncertain information, this paper proposes the four distance measures between two P-q-ROHFSs. Especially, ranking and expansion of P-q-ROHFSs are discussed in detail. Furthermore, we apply them to pattern recognition and multi-attribute group decision making (MAGDM) under probabilistic q-rung orthopair hesitant fuzzy environment. Finally, examples are given to show the rationality and practicability of the proposed method.

To improve the dust suppression efficiency of the external spray systems of shearers, a dust reduction method consisting of shearer external multi-stage atomization and dust removal fan was proposed. Computational fluid dynamics-based numerical simulation was combined with atomization experiments to analyze the migration and distribution of the cutting dust and multi-stage atomization field under airflow at the 2307 fully mechanized mining face of the Tangkou mine. The results show that with adding dust removal fan and multi-stage atomization points, the peak area of wind speed appeared on both sides of the shearer, and the wind speed was greater than 2.7 m/s, the dust concentration on the downside side of the shearer decreased, the spray coverage area increased significantly, and the droplet concentration at the shearer drum was the largest, exceeding 0.05 kg/m3. According to the research results, the multi-stage atomization arrangement of single-fluid water nozzles of shearer was put forward, and the field application was carried out. Compared with the engineering application results of the single-stage atomization dust suppression system, the total dust reduction rate of the synergistic effect of multi-stage atomization external spray with dust removal fan for the shearer is 87.12%, which is 38.59% higher than that of the conventional single-stage atomization dust suppression system.

A gas tank is an important storage facility in chemical enterprises. When an explosion occurs, it can easily cause mass injury and death. This paper takes a 50,000 m3 gas tank as an example to analyze the consequences of an accident. First, a TNT-equivalent explosion model, quantitative risk analysis and FLACS software are used to quantitatively analyze the explosion consequences. The range of casualties caused by the vapor cloud explosion is obtained. The simulation results are then compared with the actual damage range of a gas tank explosion, and the accuracy of the simulation results is verified. Next, the personal and social risks of a gas tank are identified according to China's national standards, and it is concluded that the individual risk can be tolerated, the social risk is within the tolerable range and its area has been reduced as far as possible, and it is necessary to minimize the overall risk as much as possible. Finally, a qualitative analysis of the gas tank explosion accident is carried out and the causes of the accident are analyzed. These analyses can be used to guide practices and effectively prevent the occurrence of similar accidents.

With the rapid growth of the Internet-of-Things (IoT), security issues for the IoT are becoming increasingly serious. Memory leaks are a common and harmful software defect for IoT programs running on resource-limited devices. Static analysis is an effective method for memory leak detection, however, because the existing methods cannot fully describe the memory state of IoT programs at run time, false positives and false negatives frequently occur. To improve the precision of memory leak detection, we propose an abstract memory model SeqMM to describe sequential storage structures. SeqMM differs from other abstract memory models in its ability to handle both points-to analysis and numerical analysis of pointers, which contributes to eliminating false positives in defect detection. In addition, based on the analysis of the sequential storage structure, we introduce the analysis of its operations in C programs, including transfer operations and predicate operations. Moreover, we present a memory leak detection algorithm by determining the state of the program points related to allocated memory blocks. The experimental results of five real projects indicate that the false positive rates of DTSC_SeqMM, Klocwork12 and DTSC_RSTVL are 29.0%, 15.0% and 40.6% respectively, and the corresponding false negative rates are 0%, 22.7% and 13.6%.

Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form1. This transformation is facilitated by the engulfment and degradation of excess axonal branches and inappropriate synapses by surrounding glial cells, including microglia and astrocytes2,3. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia has made it difficult to determine the contribution of these and other glial cell types to this process. Here, we used large scale, serial electron microscopy (ssEM) with computational volume segmentation to reconstruct the complete 3D morphologies of distinct glial types in the mouse visual cortex. Unexpectedly, we discovered that the fine processes of oligodendrocyte precursor cells (OPCs), a population of abundant, highly dynamic glial progenitors4, frequently surrounded terminal axon branches and included numerous phagolysosomes (PLs) containing fragments of axons and presynaptic terminals. Single- nucleus RNA sequencing indicated that cortical OPCs express key phagocytic genes, as well as neuronal transcripts, consistent with active axonal engulfment. PLs were ten times more abundant in OPCs than in microglia in P36 mice, and declined with age and lineage progression, suggesting that OPCs contribute very substantially to refinement of neuronal circuits during later phases of cortical development.

Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form1. This transformation is facilitated by the engulfment and degradation of excess axonal branches and inappropriate synapses by surrounding glial cells, including microglia and astrocytes2,3. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia has made it difficult to determine the contribution of these and other glial cell types to this process. Here, we used large scale, serial electron microscopy (ssEM) with computational volume segmentation to reconstruct the complete 3D morphologies of distinct glial types in the mouse visual cortex. Unexpectedly, we discovered that the fine processes of oligodendrocyte precursor cells (OPCs), a population of abundant, highly dynamic glial progenitors4, frequently surrounded terminal axon branches and included numerous phagolysosomes (PLs) containing fragments of axons and presynaptic terminals. Single- nucleus RNA sequencing indicated that cortical OPCs express key phagocytic genes, as well as neuronal transcripts, consistent with active axonal engulfment. PLs were ten times more abundant in OPCs than in microglia in P36 mice, and declined with age and lineage progression, suggesting that OPCs contribute very substantially to refinement of neuronal circuits during later phases of cortical development.

The alarms of the program-semantic defect-detection report based on static analysis include defects and false positives. The repair of defects and the elimination of false positives are time-consuming and laborious, and new defects may be introduced in the process. To solve these problems, the safe constraints interval of related variables and methods are proposed for the semantic defects in the program, and proposes a functionally equivalent no-side-effect program-semantic defect repair and false-positive elimination strategy based on the test-equivalence theory. This paper realizes the automatic repair of the typical semantic defects of Java programs and the automatic elimination of false positives by adding safe constraint patches. After the repair, the program functions are equivalent and the status of each program point is within the safety range, so that the functions before and after the defect repair are consistent, and the functions and semantics before and after the false positives are eliminated. We have evaluated our approach by repairing 5 projects, our results show that the repair strategy does not require manual confirmation of alarms, automated repair of the program effectively, shortened the repair time greatly, and ensured the correctness of the program after the repair.

Automated program repair is an effective way to ensure software quality and improve software development efficiency. At present, there are many methods and tools of automated program reapir in real world, but most of them have low repair accuracy, resulting in a large number of incorrect patches in the generated patches. To solve this problem, we propose a patch quality evaluation method based on semantic distance, which measures the semantic distance of patches by using features of interval distance, output coverage, and path matching. For each evaluation feature, we give a quantitative formula to obtain a specific distance value and use the distance to calculate the recommended patch value to measure the quality of the patch. Our quality evaluation method evaluated 279 patches from previous program repair tools, including Nopol, DynaMoth, ACS, jGenProg, and CapGen. This quality evaluation method successfully arranged the correct patches before the plausible but incorrect patches, and it recommended the higher-ranked patches to users first. On this basis, we compared our evaluation method with the existing evaluation methods and judged the evaluation ability of each feature. We showed that our proposed patch quality evaluation method can improve the repair accuracy of repair tools.

Repair and reconstruction of critical-sized bone defects has always been a difficult task in orthopedics. Hypoxia inducible factor-1α (HIF-1α) plays an important role in bone defect repair, it has the dual function of promoting osteogenesis and vascular regeneration, but it is quickly degraded by the body under normoxic conditions. Previously we prepared mutant HIF-1α, which has been shown to efficiently maintain cellular expression under normoxic conditions. In this study, we evaluated for the first time the role of exosomes of rat bone marrow mesenchymal stem cell carry mutant HIF-1α (BMSC-Exos-HIF1α) in repairing critical-sized bone defects. Evaluation of the effects of BMSC-Exos-HIF1α on bone marrow mesenchymal stem cells (BMSCs) proliferation and osteogenic differentiation by cell proliferation assay, alkaline phosphatase activity assay, alizarin red staining, real-time quantitative polymerase chain reaction. BMSC-Exos-HIF1α was loaded onto the β-TCP stent implanted in the bone defect area using a rat cranial critical-sized bone defect model, and new bone formation and neovascularization were detected in vivo by micro-CT, fluorescence labeling analysis, Microfil perfusion, histology and immunohistochemical analysis. In vitro results showed that BMSC-Exos-HIF1α stimulated the proliferation of BMSCs and up-regulated the expression level of bone-related genes, which was superior to bone marrow MSC exosomes (BMSC-Exos). In vivo results showed that BMSC-Exos-HIF1α combined with β-TCP scaffold promoted new bone regeneration and neovascularization in the bone defect area, and the effect was better than that of BMSC-Exos combined with β-TCP scaffold. In this study, the results showed that BMSC-Exos-HIF1α stimulated the proliferation and osteogenic differentiation of BMSCs and that BMSC-Exos-HIF1α combined with β-TCP scaffolds could repair critical-sized bone defects by promoting new bone regeneration and neovascularization.

Since the new century, with the changing and development of the times, cultural characteristics such as informatization, digitalization and consumerization have been continuously highlighted. New science and technology are rapidly flooding urban space, and people’s lifestyle and value orientation have undergone subversive changes. In the field of public art, the works of public art in the city are no longer the aesthetic expression of a single individual, but the reaction medium of the interactive relationships between people and things, person and person, people and natural world. Interactive, experiential and participatory design methods are increasingly valued and become the most direct manifestation of the “publicity” of art. This article will take interactive design in urban public art as the main research object, carry out a local investigation on the practice of urban public art in Shanghai area, relying on the case, focus on analyzing the presentation types, formal characteristics and connotation levels of interactive design, and discuss the construction way of emotional ties and cultural identity among artists, designers and the public. The purpose of this study is to explore the new trend of the development of interactive creative forms and design methods of urban public art, and to recognize that the future practices of urban public art is bound to grow dynamically and is an organic art that includes science and technology, experience and feedback, thoughts and expressions, aesthetic activities and the overall environment of life.

To eliminate the barrier among “designers (students)- virtual environment-users” in interior design teaching, as well as in response to the proposition of experience economy in this era, this study learns from relevant theories of embodied cognition, design thinking and drama theory to formulate the method of role immersion, which is applied in the general procedure of interior design. Through the application in the interior design course of “Regeneration of Old Built Space”, it is verified that “role immersion” can help students to wake up the “body”- a medium which is born to contact and interact with the environment. It can also help to cultivate students’ awareness and ability to carry out design from inside to outside and himself\herself to users to realize users’ positive perception and experience in continuous space and time. At last, the paper summarizes the problems of this method in teaching application and puts forward the developing points.

In order to achieve effective dust suppression during coal cutting process in a fully-mechanized coal mining face by using coal cutter dust removal fans, this study first conducted numerical simulations on the airflow-dustmigration rules. Then, by combining simulation results with experimental measurements and field tests, a novel hydraulic axial-flow dust coal cutter removal fan was developed. Simulation results demonstrated that, during the coal cutting process, high-concentration dust clusters exceeding 1000 mg/m3 were produced 0–20 m away from the coal cutter on the leeward side, which then spread to the operating space along the footway. After using dust removal fans, the concentration of the dust clusters on the leeward side of the coal cutter was reduced to below 500 mg/m3. The dust removal fans were then applied to the 3up705 fully-mechanized coal mining face at seven-five Coal Mine for field measurements. According to the measured results, the use of these dust removal fans can effectively reduce the dust concentration in the operating region around the coal cutter, and the dust removal rates of total dust and respirable dust reached up to 66.5% and 61.8%, respectively. Therefore, the dust removal fans performed well in terms of dust suppression in fully-mechanized coal mining faces.

Background. Platelet-rich plasma (PRP) has been shown to be a promising therapeutic agent against osteoarthritis (OA), whereas its chondroprotection mechanism is not fully elucidated. Autophagy is considered an important biological process throughout the development of OA. Therefore, the objective of the present study is to investigate the role of autophagy in the chondroprotection and compare the effects of releasate between L-PRP and P-PRP. Methods. PRP were prepared from rat blood. Rat chondrocytes pretreated in the presence or absence of interleukin-1 beta (IL-1β) were incubated with PRP releasate. The expressions of OA-related genes and autophagy-related genes were determined by RT-PCR and western blot, respectively. Autophagic bodies were assessed by transmission electron microscopy and the autophagy flux was monitored under the confocal microscopy. The effect of PRP on autophagy was further investigated in the milieu of autophagy activator, rapamycin, or autophagy inhibition by downregulation of Atg5. The effect of PRP on cartilage repair and autophagy was also evaluated in an OA rat model. Results. In vitro, PRP releasate increased the expression of the anabolic genes, COL2 and Aggrecan, and decreased the expression of the catabolic genes, whereas the expression of autophage markers, Atg5 and Beclin-1, as well as the ratio of LC3 II/LC3 I, was not significantly altered in normal or IL-1β-treated chondrocytes. Similar expression pattern was found following the activation (rapamycin) or inhibition (Atg5 silencing) of autophagy. In vivo, PRP releasate ameliorated posttraumatic cartilage degeneration while the expression of LC3 was comparable to that in the vehicle treatment group. Conclusions. PRP releasate promoted the anabolic gene expression, relieved inflammatory stress in chondrocytes, and ameliorated cartilage degeneration, but autophagy was independent of these processes.

CoS nanoplates and nanoparticles films were successfully grown on carbon fibers (CF) via one-step process and used in fiber-shaped dye sensitized solar cells as counter electrodes. The electrocatalytic ability of CF accompanied with CoS nanoplates electrode was comparable with the expensive Pt wire, and obviously superior to the CF covered by CoS nanoparticles film. The results were believed to originate from: (1) the enough void space among CoS nanoplates allows easier redox ion diffusion; (2) the two-dimensional nanoplates favor the longer distance electron transport with less diffusive hindrance than the randomly depositing nanoparticles film, where the electrons have to cross many tiny particle boundaries that can trap electrons.

Resveratrol (trans-3,5,4′-trihydroxystilbene, RSV), a naturally occurring biologically active polyphenol has been observed to induce numerous beneficial effects in diabetic animals and humans. However, its protective effects are somewhat controversial due to low bioavailability and rapid clearance rate. Therefore, we in this study have tried to investigate if its main metabolites, RSV-3-O-glucuronide (R3G) and RSV-4-O-glucuronide (R4G) could ameliorate insulin resistance, similar to RSV in insulin-resistant HepG2 cells. Herein, we first established an insulin-resistant cell model by treating HepG2 cells with 1 × 10−6 mol L−1 insulin for 24 h. Subsequently, the effects of R3G and R4G on insulin resistance inhibition were evaluated in HepG2 cells. Interestingly, our data indicated that R3G and R4G treatment improved cellular glucose uptake and glycogen synthesis contents, and blocked generation of intracellular reactive oxygen species (ROS). Additionally, R3G and R4G also modulated insulin signaling and improved insulin sensitivity by modulating the IRS-1/AMPK signaling pathway. Taken together, our data provided a significant new insight into the effects and molecular mechanism of R3G and R4G on ameliorating insulin resistance in HepG2 cells. Overall, our data supported the hypothesis that despite low bioavailability in vivo, RSV biological effects could be mediated through its metabolites.