The wide application of virtual reality technology has brought opportunities for teaching ideology and politics, breaking traditional education’s time and space limitations. This paper proposes an ...automatic three-dimensional modeling technology model, combined with computer vision camera imaging principles, to optimize the amount of data and improve optimization efficiency. And on this basis, it further proposes the Civics virtual scene construction technology, combined with the improved QEM grid simplification algorithm of edge segmentation, to optimize the virtual scene by simplifying the complex three-dimensional grid model. The experimental group’s students have shown good acceptance of this teaching method when teaching Civics in VR venues. In the cognitive and knowledge level of Civics learning, there is a significant difference between the experimental group and the control group in the dimensions of value identity and knowledge retention (P<0.05), and the mean value in the dimension of value identity is as high as 4.55, which is a very significant difference from the control class (P<0.01). And in the experiential feedback of Civics learning, the students in the experimental group have a greater sense of scene realism than the students in the control group (P<0.01), a stronger sense of realism of the interactive experience in learning (P<0.05), a higher degree of concentration in learning (P<0.01), and a more minor degree of interference by the external environment (P<0.01).
•Species of bacteria and fungi that dealt with PAHs and heavy metals were reviewed.•Factors affecting bioremediation of PAHs and heavy metals were discussed.•Bioremediation mechanisms of PAHs and ...heavy metals were elucidated.•Potential research needs for this field were discussed.
In recent years, knowledge in regard to bioremediation of combined pollution of polycyclic aromatic hydrocarbons (PAHs) and heavy metals by bacteria and fungi has been widely developed. This paper reviews the species of bacteria and fungi which can tackle with various types of PAHs and heavy metals entering into environment simultaneously or successively. Microbial activity, pollutants bioavailability and environmental factors (e.g. pH, temperature, low molecular weight organic acids and humic acids) can all affect the bioremediation of PAHs and heavy metals. Moreover, this paper summarizes the remediation mechanisms of PAHs and heavy metals by microbes via elucidating the interaction mechanisms of heavy metals with heavy metals, PAHs/PAHs metabolites with PAHs and PAHs with heavy metals. Based on the above reviews, this paper also discusses the potential research needs for this field.
Variants of TREM2 are associated with Alzheimer’s disease (AD). To study whether increasing TREM2 gene dosage could modify the disease pathogenesis, we developed BAC transgenic mice expressing human ...TREM2 (BAC-TREM2) in microglia. We found that elevated TREM2 expression reduced amyloid burden in the 5xFAD mouse model. Transcriptomic profiling demonstrated that increasing TREM2 levels conferred a rescuing effect, which includes dampening the expression of multiple disease-associated microglial genes and augmenting downregulated neuronal genes. Interestingly, 5xFAD/BAC-TREM2 mice showed further upregulation of several reactive microglial genes linked to phagocytosis and negative regulation of immune cell activation. Moreover, these mice showed enhanced process ramification and phagocytic marker expression in plaque-associated microglia and reduced neuritic dystrophy. Finally, elevated TREM2 gene dosage led to improved memory performance in AD models. In summary, our study shows that a genomic transgene-driven increase in TREM2 expression reprograms microglia responsivity and ameliorates neuropathological and behavioral deficits in AD mouse models.
•Elevating TREM2 gene dosage altered microglial morphology and interaction with Aβ•Increasing TREM2 gene dosage reprograms microglial responsivity in AD mouse brains•Transcriptomic profiling identified three groups of TREM2 gene-dosage-dependent genes•Extra TREM2 gene dosage ameliorates neuropathology and memory deficits in AD mice
Augmenting TREM2 gene dosage in AD mouse models leads to reduced amyloid burden and neuropathology and improved memory performance. Gene expression profiling reveals a reprogrammed disease-associated microglial response that may underlie the phenotypic improvement in AD models.
China's ties with Africa are evolving into a multi-faceted relationship of increasing complexity. After nearly two decades of debt-financed infrastructure development, Beijing's exposure to African ...debt is reaching disquieting proportions with an estimated US$132 billion owed to China in 2016. Managing this new role as Africa's creditor poses uncomfortable questions for creditor and debtor alike. Concurrently, the quiet surge of Chinese investment in manufacturing in Africa is transforming local economies in ways that are beginning to alter the continent's position within the global economy. Finally, the proliferation of Chinese businesses and migrants across Africa is inspiring greater Chinese involvement in UN peacekeeping and private security initiatives. This article examines how these structural changes are challenging core practices and principles which guided China–Africa relations in its formative decades. For instance, under the banner of an alternative to western policies China promoted the absence of conditionalities attached to its concessional loans and grants. Equally, promotion of industrialization of African economies marks a key shift away from China's resource-centric engagement with the continent. And, in the case of security, Beijing's commitment to avoid intervention in domestic affairs is being set aside with implications for its principles, and ultimately status, in Africa.
In December 2019, coronavirus disease 2019 (COVID-19), which is caused by the new coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in Wuhan (Hubei province, ...China)
; it soon spread across the world. In this ongoing pandemic, public health concerns and the urgent need for effective therapeutic measures require a deep understanding of the epidemiology, transmissibility and pathogenesis of COVID-19. Here we analysed clinical, molecular and immunological data from 326 patients with confirmed SARS-CoV-2 infection in Shanghai. The genomic sequences of SARS-CoV-2, assembled from 112 high-quality samples together with sequences in the Global Initiative on Sharing All Influenza Data (GISAID) dataset, showed a stable evolution and suggested that there were two major lineages with differential exposure history during the early phase of the outbreak in Wuhan. Nevertheless, they exhibited similar virulence and clinical outcomes. Lymphocytopenia, especially reduced CD4
and CD8
T cell counts upon hospital admission, was predictive of disease progression. High levels of interleukin (IL)-6 and IL-8 during treatment were observed in patients with severe or critical disease and correlated with decreased lymphocyte count. The determinants of disease severity seemed to stem mostly from host factors such as age and lymphocytopenia (and its associated cytokine storm), whereas viral genetic variation did not significantly affect outcomes.
Unsupervised Domain Adaptation (UDA) makes predictions for the target domain data while manual annotations are only available in the source domain. Previous methods minimize the domain discrepancy ...neglecting the class information, which may lead to misalignment and poor generalization performance. To address this issue, this paper proposes Contrastive Adaptation Network (CAN) optimizing a new metric which explicitly models the intra-class domain discrepancy and the inter-class domain discrepancy. We design an alternating update strategy for training CAN in an end-to-end manner. Experiments on two real-world benchmarks Office-31 and VisDA-2017 demonstrate that CAN performs favorably against the state-of-the-art methods and produces more discriminative features.
Self-paced learning (SPL) is a recently proposed methodology designed by mimicking through the learning principle of humans/animals. A variety of SPL realization schemes have been designed for ...different computer vision and pattern recognition tasks, and empirically demonstrated to be effective in these applications. However, the literature is in lack of the theoretical understanding of SPL. Regarding this research gap, this study attempts to provide some new theoretical understanding of the SPL scheme. Specifically, we prove that the solution strategy on SPL accords with a majorization minimization algorithm implemented on an implicit objective function. Furthermore, we found that the loss function contained in this implicit objective has a similar configuration with the non-convex regularized penalty (NCRP) known in statistics and machine learning. Such connection inspires us to discover more intrinsic relationships between the SPL regimes and the NCRP forms, like smoothly clipped absolute deviation (SCAD), logarithmic penalty (LOG) and non-convex exponential penalty (EXP). The insight of the robustness under SPL can then be finely explained. We also analyze the capability of SPL regarding its easy loss-prior-embedding property, and provide an insightful interpretation of the effectiveness mechanism under current SPL variations. Moreover, we design a group-partial-order loss prior, which is especially useful for weakly labeled large-scale data processing tasks. By applying SPL with this loss prior to the FCVID dataset, which is currently one of the largest manually annotated video dataset, our method achieves state-of-the-art performance above existing methods, which further supports the proposed theoretical arguments.
Cholesterol is dynamically transported among membrane-bound organelles primarily by nonvesicular mechanisms. Sterol transfer proteins (STPs) bind cholesterol in their hydrophobic pockets and ...facilitate its transfer across the aqueous cytosol. However, STPs alone may not account for the specific and efficient movement of cholesterol between intracellular membranes. Accumulating evidence has shown that membrane contact sites (MCSs), regions where two distinct organelles are in close apposition to one another, can facilitate STP-mediated cholesterol trafficking in a cell. At some MCSs, cholesterol can move against its concentration by using phosphatidylinositol 4-phosphate (PI4P) metabolism as the driving force. Finally, the emergence of more MCSs and the discovery of a new STP family further highlight the crucial roles of MCSs and STPs in intracellular cholesterol transport.
The close apposition between two cellular organelles allows efficient cholesterol transfer from one organelle to another.
Many STPs shuttle cholesterol between two adjacent organelles.
For some STPs, the metabolism of phosphoinositides drives cholesterol transport against its concentration gradient.
The list of membrane contacts is continuously expanding and a new STP family was recently identified.
The sludge in situ reduction process by inserting an anaerobic side-stream reactor (ASSR) in a sludge return line provides a cost-effective approach to reduce sludge production in activated sludge ...systems. In this study, four pilot-scale membrane bioreactors (MBRs), including an AO-MBR for control, ASSR coupled MBR (ASSR-MBR), a MBR with ASSR packed with carriers (AP-MBR) and an AP-MBR with part of sludge ultrasonicated before fed into ASSR (AUP-MBR) were operated in parallel to investigate enhancing effects of ultrasonication and packing carriers on sludge reduction and pollutants removal performance under both normal and low temperature. Low temperature showed negligible impact on COD removal, deteriorated NH4+N and TN removal from 98.3% to 69.7% at 21.6 °C to 92.5% and 48.8% at 2.6 °C, and decreased sludge reduction efficiency (SRE) in ASSR-MBR. Packing carriers and ultrasonication both enhanced sludge reduction, especially under low temperature with SRE values increased from 8.2% of ASSR-MBR to 17.1% of AP-MBR and 32.6% of AUP-MBR at 4.5 ± 2.5 °C. Packing carriers and ultrasonication increased cell rupture by 11.1% and 14.5% in aerobic MBR, enhanced protease activity in ASSR by 60.0% and 116.3%, and reduced ATP content for heterotrophic metabolism by 31.4% and 7.3%, respectively. MiSeq sequencing results showed that packing carriers enriched hydrolytic bacteria (Terrimonas, Dechloromonas and Woodsholea), slow growers (Sulfuritalea, Thauera and Azospira) and predatory bacteria (Bdellovibrio and norank_Saprospiraceae), while ultrasonication further enriched hydrolytic bacteria (norank_Saccharibacteria and Ferruginibacter). Packing carriers is more cost-effective than ultrasonication to enhance sludge reduction by partial damage to bacterial cells and promoting better interaction between bacteria, enzymes and substrates to favor particles hydrolysis.
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•Enhancement of sludge reduction in anaerobic side-stream reactor (ASSR) was studied.•Packing carriers enhanced sludge reduction from 8.2% to 17.1% at 1.0–9.0 °C.•Combining ultrasonication and packing carriers enhanced sludge reduction by 297%.•Combination enhanced cell rupture and protease activity, and reduced ATP content.
•An in-field automatic wheat disease diagnosis system (DMIL-WDDS) is firstly proposed.•DMIL-WDDS achieves identification and localization for wheat diseases.•DMIL-WDDS outperforms conventional ...CNN-based architectures on recognition accuracy.•A new in-field wheat disease dataset WDD2017 is collected.•DMIL-WDDS has been designed into a real-time mobile application.
Crop diseases are responsible for the major production reduction and economic losses in agricultural industry worldwide. Monitoring for health status of crops is critical to control the spread of diseases and implement effective management. This paper presents an in-field automatic wheat disease diagnosis system based on a weakly supervised deep learning framework, i.e. deep multiple instance learning, which achieves an integration of identification for wheat diseases and localization for disease areas with only image-level annotation for training images in wild conditions. Furthermore, a new in-field image dataset for wheat disease, Wheat Disease Database 2017 (WDD2017), is collected to verify the effectiveness of our system. Under two different architectures, i.e. VGG-FCN-VD16 and VGG-FCN-S, our system achieves the mean recognition accuracies of 97.95% and 95.12% respectively over 5-fold cross-validation on WDD2017, exceeding the results of 93.27% and 73.00% by two conventional CNN frameworks, i.e. VGG-CNN-VD16 and VGG-CNN-S. Experimental results demonstrate that the proposed system outperforms conventional CNN architectures on recognition accuracy under the same amount of parameters, meanwhile maintaining accurate localization for corresponding disease areas. Moreover, the proposed system has been packed into a real-time mobile app to provide support for agricultural disease diagnosis.
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