Efficient design of piezoresitive sensors based on carbon black conductive composites

Flexible and stretchable sensors are widely investigated taking into account their potential for wearable electronics, such as electronic skin, healthcare monitoring, human-machine interfaces, and soft robotics. In this contribution, highly sensitive conductive polymer composites (CPCs) for piezoresistive sensing are summarized, considering a straightforward manufacturing process based on extrusion of thermoplastic polyurethane (TPU) and/or olefin block copolymer (OBC), carbon black (CB), and additionally polyethylene-octene elastomer (POE) grafted with maleic anhydride (POE-g-MA). The design of the formulation variables is successfully performed to enable both low and high strain sensing, as highlighted by both static and dynamic testing

Efficient design of piezoresistive sensors based on carbon black conductive composites

Flexible and stretchable sensors are widely investigated taking into account their potential for wearable electronics, such as electronic skin, healthcare monitoring, human-machine interfaces, and soft robotics. In this contribution, highly sensitive conductive polymer composites (CPCs) for piezoresistive sensing are summarized, considering a straightforward manufacturing process based on extrusion of thermoplastic polyurethane (TPU) and/or olefin block copolymer (OBC), carbon black (CB), and additionally polyethylene-octene elastomer (POE) grafted with maleic anhydride (POE-g-MA). The design of the formulation variables is successfully performed to enable both low and high strain sensing, as highlighted by both static and dynamic testing

AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation

Despite the considerable progress in automatic abdominal multi-organ segmentation from CT/MRI scans in recent years, a comprehensive evaluation of the models' capabilities is hampered by the lack of a large-scale benchmark from diverse clinical scenarios. Constraint by the high cost of collecting and labeling 3D medical data, most of the deep learning models to date are driven by datasets with a limited number of organs of interest or samples, which still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of various methods. To mitigate the limitations, we present AMOS, a large-scale, diverse, clinical dataset for abdominal organ segmentation. AMOS provides 500 CT and 100 MRI scans collected from multi-center, multi-vendor, multi-modality, multi-phase, multi-disease patients, each with voxel-level annotations of 15 abdominal organs, providing challenging examples and test-bed for studying robust segmentation algorithms under diverse targets and scenarios. We further benchmark several state-of-the-art medical segmentation models to evaluate the status of the existing methods on this new challenging dataset. We have made our datasets, benchmark servers, and baselines publicly available, and hope to inspire future research. Information can be found at https://amos22.grand-challenge.org

Different Chemotherapy Regimens in the Management of Advanced or Metastatic Urothelial Cancer: a Bayesian Network Meta-Analysis of Randomized Controlled Trials

Background/Aims: Urothelial cancer (UC) as a chemotherapy-sensitive tumor, has achieved remarkable progresses in therapeutic paradigm, particularly in the advanced/metastatic stages. However, both clinicians and patients are confused when it comes to choosing the optimal chemotherapy. Hence, this article was aimed to conduct a comprehensive comparison of different chemotherapy regimens for advanced or metastatic UC in terms of survival benefits or adverse events. Methods: The online databases PubMed, EMBASE and Web of Science were searched systematically and comprehensively for randomized controlled trials (RCTs) up to September 15, 2017. The pooled hazard ratios (HRs) or odds ratios (ORs) with 95% credible interval (CrI) were calculated by Markov chain Monte Carlo methods. The effectiveness and safety of included regimens were conducted to provide a hierarchy by means of rank probabilities with the help of “R-3.4.0” software and the “gemtc-0.8.2” package. The surface under the cumulative ranking curve (SUCRA) was also incorporated in our analysis for ranking the corresponding chemotherapy regimens. Results: Ten different chemotherapy regimens involved in this article were predominantly of trials in a first-line setting, and eight clinical outcomes were ultimately analyzed in this study. In terms of Overall response rate (ORR), Overall survival (OS) or Progression-free survival (PFS)/Time to progression (TTP), the rank probabilities and SUCRA indicated that Paclitaxel/cisplatin/gemcitabine (PCG) was superior to gemcitabine/cisplatin (GC) or methotrexate/vinblastine/doxorubicin/cisplatin (MVAC), the traditional first-line treatment for advanced/metastatic UC. In the case of ORR or PFS/TTP, GC+sorafenib also displayed its superiority in comparison with GC or MVAC. Despite their survival benefits, PCG or GC+sorafenib presented a relatively higher incidence of adverse events. Conclusion: Our results revealed that by adding a paclitaxel or sorafenib into the first-line GC, it could yield a better survival benefit, but also worsen adverse events for advanced/ metastatic UC. Clinically, physicians should weigh the merits of these approaches to maximize the survival benefits of eligible patients

Genome-Wide Identification and Immune Response Analysis of Serine Protease Inhibitor Genes in the Silkworm, Bombyx mori

In most insect species, a variety of serine protease inhibitors (SPIs) have been found in multiple tissues, including integument, gonad, salivary gland, and hemolymph, and are required for preventing unwanted proteolysis. These SPIs belong to different families and have distinct inhibitory mechanisms. Herein, we predicted and characterized potential SPI genes based on the genome sequences of silkworm, Bombyx mori. As a result, a total of eighty SPI genes were identified in B. mori. These SPI genes contain 10 kinds of SPI domains, including serpin, Kunitz_BPTI, Kazal, TIL, amfpi, Bowman-Birk, Antistasin, WAP, Pacifastin, and alpha-macroglobulin. Sixty-three SPIs contain single SPI domain while the others have at least two inhibitor units. Some SPIs also contain non-inhibitor domains for protein-protein interactions, including EGF, ADAM_spacer, spondin_N, reeler, TSP_1 and other modules. Microarray analysis showed that fourteen SPI genes from lineage-specific TIL family and Group F of serpin family had enriched expression in the silk gland. The roles of SPIs in resisting pathogens were investigated in silkworms when they were infected by four pathogens. Microarray and qRT-PCR experiments revealed obvious up-regulation of 8, 4, 3 and 3 SPI genes after infection with Escherichia coli, Bacillus bombysepticus, Beauveria bassiana or B. mori nuclear polyhedrosis virus (BmNPV), respectively. On the contrary, 4, 11, 7 and 9 SPI genes were down-regulated after infection with E. coli, B. bombysepticus, B. bassiana or BmNPV, respectively. These results suggested that these SPI genes may be involved in resistance to pathogenic microorganisms. These findings may provide valuable information for further clarifying the roles of SPIs in the development, immune defence, and efficient synthesis of silk gland protein

Fine-Scale Monitoring of Industrial Land and Its Intra-Structure Using Remote Sensing Images and POIs in the Hangzhou Bay Urban Agglomeration, China

China has experienced rapid industrial land growth over last three decades, which has brought about diverse social and environmental issues. Hence, it is extremely significant to monitor industrial land and intra-structure dynamics for industrial land management and industry transformation, but it is still a challenging task to effectively distinguish the internal structure of industrial land at a fine scale. In this study, we proposed a new framework for sensing the industrial land and intra-structure across the urban agglomeration around Hangzhou Bay (UAHB) during 2010–2015 through data on points of interest (POIs) and Google Earth (GE) images. The industrial intra-structure was identified via an analysis of industrial POI text information by employing natural language processing and four different machine learning algorithms, and the industrial parcels were photo-interpreted based on Google Earth. Moreover, the spatial pattern of the industrial land and intra-structure was characterized using kernel density estimation. The classification results showed that among the four models, the support vector machine (SVM) achieved the best predictive ability with an overall accuracy of 84.5%. It was found that the UAHB contains a huge amount of industrial land: the total area of industrial land rose from 112,766.9 ha in 2010 to 132,124.2 ha in 2015. Scores of industrial clusters have occurred in the urban-rural fringes and the coastal zone. The intra-structure was mostly traditional labor-intensive industry, and each city had formed own industrial characteristics. New industries such as the electronic information industry are highly encouraged to build in the core city of Hangzhou and the subcore city of Ningbo. Furthermore, the industrial renewal projects were also found particularly in the core area of each city in the UAHB. The integration of POIs and GE images enabled us to map industrial land use at high spatial resolution on a large scale. Our findings can provide a detailed industrial spatial layout and enable us to better understand the process of urban industrial dynamics, thus highlighting the implications for sustainable industrial land management and policy making at the urban-agglomeration level

Spatial Load Prediction Considering Spatiotemporal Distribution of Electric Vehicle Charging Load

In view of the influence of large-scale electric vehicle access to the distribution network on spatial load prediction, this paper proposes a spatial load prediction method for urban distribution network considering the spatial and temporal distribution of electric vehicle charging load. Firstly, electric vehicles are classified according to charging mode and travel characteristics of various types of vehicles. Secondly, the probability distribution function is fitted to the travel rules of electric vehicles according to the travel survey and statistical data of residents. Then, the model of electric vehicle travel chain is constructed, and the charging load in different regions and different times is calculated by Monte Carlo method. Finally, based on the actual data of a certain area, the predicted spatial load values of different functional communities in one day are obtained, which can provide reference for future urban distribution network planning

Dynamic analysis of correlation patterns between urban population and construction land at different administrative levels: The case of Hangzhou megacity

Understanding the urban human-land interaction at multiple administrative levels comprehensively plays an important role in the refined governance and thus provides critical references for urban planning and management. This paper analyzes the relationship between urban population and urban construction land in Hangzhou from perspectives of equilibrium, intensification and coordination at the multi-level during 2010 and 2020. Meanwhile, the underlying mechanism among the urban construction land expansion, population flow and land utilization efficiency with different demographic migration pattern is defined by Kaya identity and further quantitatively deconstructed by the Logarithmic Mean Divisia Index (LMDI). Regraded with the multi-level evaluation of human-land interactions, the prefectural-level analysis reveals significant reduction in both internal difference and absolute value of per capita urban construction land area, and the growth rate of urban population is 2.24 times faster than that of the urban construction land. At the county-level, the proportion of balanced and intensive county-level units increase by 15.38% and 38.46% respectively. The proportion of the county-level units under coordinated status reaches up to 92.31%. At the township-level, the proportion of intensive township-level units increases by 16.84% and the proportion of the township-level units under coordinated status is up to 64.74%. Furthermore, analysis of the multidimensional combination characteristics of urban human-land interaction is performed with six combination types at the county-level and four combination types at the township-level, which are useful for managers to develop categorized and refined urban development guidance. The driving mechanisms demonstrated that 47% of the townships with net population inflow and 41% of the townships with net population outflow are mainly influenced by the increase of permanent resident population, while the deterioration degree of land utilization efficiency in the former is significantly lower than that in the latter. This result implies that the townships in the core urban areas present the better performance in the improvement of land utilization efficiency than those in the western areas of Hangzhou. The exploration will provide references for coordinating the rational allocation of land resources and optimizing the regional human-land relationship

AMP-Activated Protein Kinase Alleviates Extracellular Matrix Accumulation in High Glucose-Induced Renal Fibroblasts through mTOR Signaling Pathway

Background/Aims: Extracellular matrix accumulation contributes significantly to the pathogenesis of diabetic nephropathy. Although AMP-activated protein kinase (AMPK) has been found to inhibit extracellular matrix synthesis by experiments in vivo and vitro, its role in alleviating the deposition of extracellular matrix in renal interstitial fibroblasts has not been well defined. Methods: Currently, we conducted this study to investigate the effects of AMPK on high glucose-induced extracellular matrix synthesis and involved intracellular signaling pathway by using western blot in the kidney fibroblast cell line (NRK-49f). Results: Collagen IV protein levels were significantly increased by high glucose in a time-dependent manner. This was associated with a decrease in Thr72 phosphorylation of AMPK and an increase in phosphorylation of mTOR on Ser2448. High glucose-induced extracellular matrix accumulation and mTOR activation were significantly inhibited by the co-treatment of rAAV-AMPKα1312 (encoding constitutively active AMPKα1) whereas activated by r-AAV-AMPKα1D157A (encoding dominant negative AMPKα1). In cultured renal fibroblasts, overexpression of AMPKα1D157A upregulated mTOR signaling and matrix synthesis, which were ameliorated by co-treatment with the inhibitor of mTOR, rapamycin. Conclusion: Collectively, these findings indicate that AMPK exerts renoprotective effects by inhibiting the accumulation of extracellular matrix through mTOR signaling pathway