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Full morphology of single neurons is indispensable to understand cell types, the basic building blocks in brains. Projecting trajectories are critical to extract biologically relevant information from neuron morphologies, as they provide valuable information of both connectivity and cell identity. We developed an artificial intelligence method, Deep Sequential Model (DSM), to extract concise, cell-type defining features from projections across brain regions. DSM achieves more than 90% accuracy in classifying twelve major neuron projection types, without compromising performance when spatial noise is present. Such remarkable robustness enabled us to efficiently manage and analyze several major full-morphology data sources, showcasing how characteristic long projections can define cell identities. We also succeeded in applying our model to both discovering previously unknown neuron subtypes and analyzing exceptional co-expressed genes involved in neuron projection circuits.

The surface plasmonic resonance (SPR) effect of Bi can effectively improve the light absorption abilities and photogenerated charge carrier separation rate. In this study, a novel ternary heterojunction of g-C3N4/Bi2MoO6/Bi (CN/BMO/Bi) hollow microsphere was successfully fabricated through solvothermal and in situ reduction methods. The results revealed that the optimal ternary 0.4CN/BMO/9Bi photocatalyst exhibited the highest photocatalytic efficiency toward rhodamine B (RhB) degradation with nine times that of pure BMO. The DRS and valence band of the X-ray photoelectron spectroscopy spectrum demonstrate that the band structure of 0.4CN/BMO/9Bi is a z-scheme structure. Quenching experiments also provided solid evidence that the •O2− (at −0.33 eV) is the main species during dye degradation, and the conduction band of g-C3N4 is only the reaction site, demonstrating that the transfer of photogenerated charge carriers of g-C3N4/Bi2MoO6/Bi is through an indirect z-scheme structure. Thus, the enhanced photocatalytic performance was mainly ascribed to the synergetic effect of heterojunction structures between g-C3N4 and Bi2MoO6 and the SPR effect of Bi doping, resulting in better optical absorption ability and a lower combination rate of photogenerated charge carriers. The findings in this work provide insight into the synergism of heterostructures and the SPR absorption ability in wastewater treatment.

A novel plasmonic photocatalysts of Ag-AgI/Bi3O4Cl was successfully synthesized via a simple and mild wet-chemical process. The 30 wt% Ag-AgI/Bi3O4Cl photocatalyst showed the highest photocatalytic activity for degradation of methyl orange (MO) under visible light (5 W LED lamp), which represents a 3.2 and 7.4 times enhancement in the photocatalytic degradation efficiency as compared to pure Bi3O4Cl and Ag-AgI, respectively. The surface plasmon resonance (SPR) effect of Ag nanoparticles (NPs) was detected by the UV–vis diffusion reflectance spectroscopy (DRS) and surface photovoltage (SPV) measurement, finding that the SPR effect of Ag extends the absorption and photo-response range in the Ag-AgI/Bi3O4Cl composite photocatalyst. Based on the analysis of electron spin resonance (ESR), linear sweeping voltammetry (LSV) characterization results, three electron transfer processes were proposed: AgICB → Bi3O4ClCB, AgICB → Ag and methyl orange → Ag. Such electron transfer paths can not only effectively improve the separation efficiency of photo-generated carriers, but also ensure the stability of the catalyst. This study can provide a novel insight for modification of other desirable semiconductor materials to achieve high photocatalytic activity.

Recent advances in neuroscience make the extraction of full neuronal morphology at whole brain dataset available. To produce quality morphometry at large scale, it is highly desirable but extremely challenging to efficiently handle petabyte-scale high-resolution whole brain imaging database. Here, we developed a multi-level method to produce high quality somatic, dendritic, axonal, and potential synaptic morphometry, which was made possible by utilizing necessary petabyte hardware and software platform to optimize both the data and workflow management. Our method also boosts data sharing and remote collaborative validation. We highlight a petabyte application dataset involving 62 whole mouse brains, from which we identified 50,233 somata of individual neurons, profiled the dendrites of 11,322 neurons, reconstructed the full 3-D morphology of more than one thousand neurons including their dendrites and full axons, and detected million scale putative synaptic sites derived from axonal boutons. Analysis and simulation of these data indicate the promise of this approach for modern large-scale morphology applications.

Recent advances in brain imaging allow producing large amounts of 3-D volumetric data from which morphometry data is reconstructed and measured. Fine detailed structural morphometry of individual neurons, including somata, dendrites, axons, and synaptic connectivity based on digitally reconstructed neurons, is essential for cataloging neuron types and their connectivity. To produce quality morphometry at large scale, it is highly desirable but extremely challenging to efficiently handle petabyte-scale high-resolution whole brain imaging database. Here, we developed MorphoHub to address this challenge by optimizing both the data and workflow management. In particular, this work presents a multi-level method to produce high quality somatic, dendritic, axonal, and potential synaptic morphometry. Our method also boosts data sharing and remote collaborative validation. We applied MorphoHub to a petabyte application dataset involving 62 whole mouse brains, and identified 50,233 somata of individual neurons, profiled the dendrites of 11,322 neurons, reconstructed the full 3-D morphology of 1,050 neurons including their dendrites and full axons, and detected 1.9 million putative synaptic sites derived from axonal boutons. Analysis and simulation of these data indicate the promise of this approach for modern large-scale morphology applications.

Ever since the seminal findings of Ramon y Cajal, dendritic and axonal morphology has been recognized as a defining feature of neuronal types. Yet our knowledge concerning the diversity of neuronal morphologies, in particular distal axonal projection patterns, is extremely limited. To systematically obtain single neuron full morphology on a brain-wide scale, we established a platform with five major components: sparse labeling, whole-brain imaging, reconstruction, registration, and classification. We achieved sparse, robust and consistent fluorescent labeling of a wide range of neuronal types by combining transgenic or viral Cre delivery with novel transgenic reporter lines. We acquired high-resolution whole-brain fluorescent images from a large set of sparsely labeled brains using fluorescence micro-optical sectioning tomography (fMOST). We developed a set of software tools for efficient large-volume image data processing, registration to the Allen Mouse Brain Common Coordinate Framework (CCF), and computer-assisted morphological reconstruction. We reconstructed and analyzed the complete morphologies of 1,708 neurons from the striatum, thalamus, cortex and claustrum. Finally, we classified these cells into multiple morphological and projection types and identified a set of region-specific organizational rules of long-range axonal projections at the single cell level. Specifically, different neuron types from different regions follow highly distinct rules in convergent or divergent projection, feedforward or feedback axon termination patterns, and between-cell homogeneity or heterogeneity. Major molecularly defined classes or types of neurons have correspondingly distinct morphological and projection patterns, however, we also identify further remarkably extensive morphological and projection diversity at more fine-grained levels within the major types that cannot presently be accounted for by preexisting transcriptomic subtypes. These insights reinforce the importance of full morphological characterization of brain cell types and suggest a plethora of ways different cell types and individual neurons may contribute to the function of their respective circuits.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits., Sparse labelling and whole-brain imaging are used to reconstruct and classify brain-wide complete morphologies of 1,741 individual neurons in the mouse brain, revealing a dependence on both brain region and transcriptomic profile.

The topic of the environmental Kuznets curve (EKC) was searched on Web of Science and 2, 747 documents were obtained from 2010 to 2020. Among them, 2616 documents were selected and analysed using the bibliometrix package in the R language. Results showed that Environmental Science and Pollution Research were the most literature sources, and the country with the most researches was China. Keywords analysis revealed that most researches were focused on the EKC, economic development, and carbon dioxide (CO2) emission, and the last item was the main environmental pollution problem. Most researches were focused on income distribution, benefits, ecological footprint, globalization, and degradation evidence. Dividing these documents into three stages with 2014 and 2018 as the nodes, economic growth was focused from 2010 to 2014, following was focused on emissions and then the international tourism from 2019 to 2020. EKC was easily visualized among the co-citation network of authors, the co-occurrence network of keywords and the cooperation network of countries. EKC historical graph showed that the global environment should be considered as a whole to research environmental pollution and economic development, and more research should be focused on the EKC related to clean energy and sustainable development. Therefore, by analysing a large number of documents and using scientific measurement methods, it is convenient for future research on the EKC hypothesis.

This paper designs a set of electromagnetic energy saving intelligent vehicle which can effectively save energy and ensure high speed running. The design includes the design of the mechanical structure of the vehicle model, the design of the circuit module, the design of the sensor signal processing, the design of the supercapacitor module, the preparation of the control algorithm five modules. The design of the mechanical structure of the car model is mainly about the design of the overall structure of the car and the selection of the car model materials, which can reduce the resistance and gravity of the car as much as possible, reduce energy consumption, improve the stability of the car and obtain a faster speed. The key point of circuit module design is to coordinate the work between each module, effectively reduce the total power consumption, and achieve energy saving. The sensor signal processing design focuses on the track information acquired according to the acquisition, so that the car can accurately and quickly adjust the attitude and smoothly pass through various tracks. The ultracapacitor module is the source of energy and power for the whole car. Giving full play to each joule is the key to energy saving. Control algorithm is the soul of the car, this paper is the incremental PID, to deal with a variety of tracks.

Due to the rarity of solitary bone plasmacytoma (SBP), few studies reported the prognosis and survival predictors of SBP, especially for patients with extremity SBP.A total of 552 patients with extremity SBP were identified from the Surveillance Epidemiology and Ends Results (SEER) database between 1973 and 2016. In order to obtain independent predictors of survival, we performed both univariate and multivariate analysis via Cox proportional hazards model. Additionally, we used the Kaplan-Meier method to construct survival curves.The mean and median age at diagnosis of all patients were 64 and 65 years, respectively. The ratio of male versus women was 1.3:1. Overall survival for this special population was 51.2% and 34.9% at 5 and 10 years, respectively. Cancer-specific survival (CSS) for this special population was 63.5% and 47.5% at 5 and 10 years, respectively. Age at diagnosis and radiotherapy treatment were found to be significant independent predictors of both overall survival and CSS. Additionally, multivariate analysis showed that year of diagnosis and marital status were significantly correlated with CSS.This is the first study to identify prognostic factors of extremity SBP by using the SEER database. Our findings highlight that radiotherapy is the mainstream treatment for extremity SBP. Additionally, age, year of diagnosis, and marital status were significant independent predictors of survival. Knowledge of these survival predictors may help clinicians provide appropriate management for extremity SBP patients.

Long noncoding RNAs (lncRNAs), a class of non-protein conding RNAs200 nt in length, were thought to play critical roles in regulating the expression of protein-coding genes. Here, we identified and characterized a novel lncRNA-000133 from the secondary hair follicle (SHF) of cashmere goat with its ceRNA network analysis, as well as, its potential effects on inductive property of dermal papilla cells were evaluated through overexpression analysis. Expression analysis indicated that lncRNA-000133 had a significantly higher expression at anagen than that at telogen in SHF of Cashmere goat, suggesting that lncRNA-000133 might be involved in the reconstruction of SHF with the formation and growth of cashmere fiber. Taken together with methylation analysis, we showed that 5' regulatory region methylation of the lncRNA-000133 gene might be involved in its expression suppression in SHF of Cashmere goat. The ceRNA regulatory network showed that a rich and complex regulatory relationship between lncRNA-000133 and related miRNAs with their target genes. The overexpression of lncRNA-000133 led to a significant increasing in the relative expression of ET-1, SCF, ALP and LEF1 in dermal papilla cells suggesting that lncRNA-000133 appears to contribute the inductive property of dermal papilla cells.

Dendritic and axonal morphology is a defining feature of neuronal types and their connectivity. Yet our knowledge concerning the diversity of neuronal morphology is extremely limited. To systematically obtain single neuron full morphology on a brain-wide scale in mice, we established a pipeline that encompasses five major components: sparse labeling, whole-brain imaging, reconstruction, registration, and classification. We achieved sparse, robust and consistent fluorescent labeling by combining transgenic or viral Cre delivery with novel transgenic reporter lines, and generated whole-brain fluorescent imaging datasets containing tens of thousands of reconstructable neurons. We developed software tools for large-volume image data processing and computer-assisted morphological reconstruction. For a proof-of-principle, we reconstructed the full morphologies of 96 neurons from the claustrum and cortex that belong to a single transcriptomically-defined subclass, and classified them into multiple morphological types, suggesting that they work in a targeted and coordinated manner to process cortical information over a large region.

Bi3O4Cl and Bi3O4Cl-OV nanosheets with oxygen vacancies were successfully synthesized and detected using UV–visible diffuse reflectance spectra (DRS), X-ray photoelectron spectrometry (XPS) and Kelvin probes to explore the impact of the oxygen vacancies on the energy band structure. It is suggested that the defect states will shorten the forbidden band, close the distance between the Fermi level and the conduction band, and reduce the work function. All of these effects were confirmed by density functional theory (DFT) calculations and provide a reasonable explanation for the improvement of the photocatalytic performance of Bi3O4Cl-OV nanosheets. At the same time, Bi3O4Cl-OV was further modified by loading with the metal halide AgBr and the photocatalytic degradation efficiency was significantly improved approximately 11.2-fold compared to that of pure Bi3O4Cl nanosheets. This work not only offers efficient guidance for ascertaining the energy band structure of a semiconducture but also provides tentative suggestions for improving photocatalytic performance via defect engineering.

Protecting user interests is one of the most important public sector responsibilities in PPP (public-private partnership) projects. However, user interests could be damaged by poor project performance. Therefore, this study focuses on the protection of user interests in PPP projects and analyzes the relationships among relational norms, project performance, and user interests in PPP projects. A questionnaire survey is conducted to collect the opinions of professionals from the public sector and private sector. Upon analyzing 109 valid questionnaires, the results demonstrate that the relational norms between the public sector and private sector have a positive effect on project performance, and project performance has a positive relationship on user interests. Moreover, project performance has a positive mediating effect on the relationships between relational norms and user interests. This finding can provide a theoretical foundation and suggest practical measures to help the public sector better protect user interests in PPP projects.

To investigate the genetic resources and to clarify the classification status of the Chinese yak, the Maiwa yak, Jiulong yak, Datong yak, and Tianzhu White yak were intensively studied using microsatellite DNA, RAPD (random amplified polymorphic DNA), and AFLP (Amplified Fragment Length Polymorphism) DNA markers on the basis of the previous study work of the authors' on chromosomes and blood protein polymorphisms of the Chinese yak. The overall results showed that: (1) the genetic distance based on allele frequencies at the microsatellite loci between the Maiwa yak and Jiulong yak was the largest (1.506), and as expected, the two populations of the Maiwa yak had the smallest genetic distance (1.062). The four yak breeds were clustered into two groups: the first group comprised the Jiulong yak, and the second group comprised the remaining three breeds; (2) the genetic distance between the Datong yak and Tianzhu White yak was the smallest (0.0336), whereas the genetic distance between the Jiulong yak and Maiwa yak was the largest (0.0414) based on the data from the RAPD and RFLP analyses. The four yak breeds were again clustered into two groups with the Datong yak and Tianzhu White yak grouped together first, followed by the Maiwa yak; (3) analyses of the chromosomes and blood protein polymorphisms showed a similar pattern of relationship among the breeds. Therefore, it was concluded that the Chinese yak could be considered to be of two types with the Jiulong yak and Maiwa yak as their representatives, respectively. This conclusion was in accordance with the classification proposed later by professor Cai L and his colleagues, according to which the Chinese yak was classified into two types, the ‘Qinghai-Tibetan Plateau yak’ and the ‘Hengduan Mountain Alpine yak’, although this conclusion differed from the other classifications. Considering the geographic distribution, ecological factors, history and development of the Chinese yak, it was believed that this classification is reasonable.