Bias-Independent Subthreshold Swing in Nanoscale Cold-Source Field-Effect Transistors by Drain Density-of-States Engineering

We report a strategy to design nanoscale cold-source field-effect transistors (CS-FETs) with bias-independent sub-60 mV/dec subthreshold swing (SS). By first-principles calculations and quantum-transport simulations, we reveal that the energy alignment of density of states (DOS) between the drain and source electrodes is critical to achieving bias-independent SS. By defining "gate window", we propose a device model to demonstrate how similar slopes of the drain DOS falling into the gate window can stabilize the SS under different bias. This study underscores the significance of drain DOS engineering in the design of CS-FETs with bias-independent SS for portable electronic applications.Comment: currently under revie

The Review of Network Theory Applied to the Financial System

As the globalization is developing, financial interdependence has been increasing sharply among financial organizations, such as central banks, commercial banks, investment banks, etc.. And the relationships in this system can be perfectly explained as network structure. Many researchers have studied a lot in this intersection. In this paper, we select 158 literatures (2004-2016) from SSCI journals, and summarize the relative researches about network theory applied to the financial system in the western world. This research shows the development of financial network theory and four aspects of latest research results. In the future, IT will be the major driving force and the most popular solving method to analyze the financial network related problems

DNS SLAM: Dense Neural Semantic-Informed SLAM

In recent years, coordinate-based neural implicit representations have shown promising results for the task of Simultaneous Localization and Mapping (SLAM). While achieving impressive performance on small synthetic scenes, these methods often suffer from oversmoothed reconstructions, especially for complex real-world scenes. In this work, we introduce DNS SLAM, a novel neural RGB-D semantic SLAM approach featuring a hybrid representation. Relying only on 2D semantic priors, we propose the first semantic neural SLAM method that trains class-wise scene representations while providing stable camera tracking at the same time. Our method integrates multi-view geometry constraints with image-based feature extraction to improve appearance details and to output color, density, and semantic class information, enabling many downstream applications. To further enable real-time tracking, we introduce a lightweight coarse scene representation which is trained in a self-supervised manner in latent space. Our experimental results achieve state-of-the-art performance on both synthetic data and real-world data tracking while maintaining a commendable operational speed on off-the-shelf hardware. Further, our method outputs class-wise decomposed reconstructions with better texture capturing appearance and geometric details

Leakage control of water distribution system by drop-restore pressure based on viscoelastic mechanism

As a common method to control leakage of water distribution systems, pressure management has the advantages of reducing energy consumption, reducing the possibility of explosion, and avoiding the aggravation of leakage. With the popularization of plastic pipe in the world, it is necessary to study its leakage characteristic in recent years. Our research group carried out leakage experiments on high-density polyethylene (HDPE) pipe, and found that the correlation curve between leakage flow and pressure did not completely coincide in the phase of pressure boost and pressure reduction. The existing FAVAD and exponential leakage models could not explain this phenomenon, which challenges the pressure management theory dominated by a single depressing-pressure process, thus it’s necessary to explore pressure management strategies suitable for plastic pipes. Based on the viscoelastic properties of plastic pipe, we established the viscoelastic leakage model and proposed the leakage control method of drop-restore pressure, and verified its feasibility in practical engineering cases. The main research objectives of this paper will be first to describe the strain response of leakage area in the process of continuous stress application with the Boltzmann superposition principle for HDPE pipe; the Voigt-Kelvin model is used to simulate the creep behavior of viscoelastic material, and a suitable leakage model for viscoelastic pipe is proposed to provide accurate expression of the leakage under the regulation of drop-restore pressure. Secondly, the viscoelastic pipe leakage model is embedded into the pressure-driven analysis model based on non-iterative method and the pressure-driven viscoelastic leakage model is obtained. Finally, evaluating the proposed leakage model in the practical case. With the minimum leakage flow as the objective function, the leakage control model of drop-restore pressure is established and solved by a particle swarm optimization algorithm to obtain an accurate pressure regulation scheme. After applying the scheme from the optimization, the leakage rate decreases from 37.7% to 16.8% on weekdays, which is a great impact on leakage control

Innovative Water Supply Network Pressure Management Method—The Establishment and Application of the Intelligent Pressure-Regulating Vehicle

The development of many intelligent technologies, such as artificial intelligence and the Internet of Things, has brought new opportunities for water industry intelligence. Based on intelligent pressure regulation technology, this paper built an intelligent management platform, designed an intelligent pressure-regulating device, and combined both to form an intelligent pressure-regulating vehicle (IPRV). The IPRV has the functions of developing a pressure-regulating scheme, equipment selection, pressure reduction potential analysis, etc. It can bring convenience to the field test of the water supply network. In the field test, an intelligent pressure-regulating device was used to obtain the network data in the pilot site called S-cell. After utilizing the intelligent management platform to analyze the measured data, the water usage pattern and pressure reduction potential of the S-cell were obtained, and an optimal pressure-regulating strategy was formulated. The water pressure at the critical node always met the water demand at the critical node during the field test. In addition, no complaints were received from other users. The results show that the IPRV is not only convenient for utility managers to make decisions on building pressure-reducing stations but also meets user needs, realizing a win–win situation for both users and companie

Comparison of fungal communities and nonvolatile flavor components in black Huangjiu formed using different inoculation fermentation methods

Black Huangjiu (BH) is a traditional alcoholic beverage in China, which is very popular among people. The different methods (simultaneous inoculation, sequential inoculation), were applied to ferment BH in this study, which were investigated the changes in the composition of fungal communities and non-volatile flavor compounds (nVFCs) by high-throughput sequencing (HTS) and ultraperformance liquid chromatography–tandem mass spectrometer (UPLC MS/MS). The results showed that Rhizopus and Saccharomyces were the predominant fungal genera throughout fermentation, and 471 nVFCs were detected in BH after fermentation. Compared to that observed simultaneous inoculation, Rhizopus increased at the end of sequential fermentation, and the contents of the organic acids and their derivatives increased significantly [variable importance in the projection (VIP) > 1.0, p < 0.05, fold change (FC) > 2], while that of lipids and lipid-like molecules decreased significantly (VIP > 1.0, p < 0.05, FC < 0.5). Through the correlation analysis of 32 nVFCs with significant differences (VIP > 1.0, p < 0.05, FC >32 or < 0.03) and the community, it was found that lipids and lipid-like molecules (12) and organic acids and their derivatives (10) were significantly (p < 0.05) negatively correlated with Saccharomyces, but they were significantly (p < 0.05) positively correlated with Rhizopus. Compared with simultaneous inoculation, BH fermented by sequential inoculation, the taste was stronger, sweeter, mellow, and softer. Our findings provide information on nVFC dynamics and will aid in the selection of beneficial strains to improve BH quality

Protective role for collectin‐11 in rheumatoid arthritis in mice

OBJECTIVE. Collectin-11 (CL-11) is a soluble C-type lectin, a mediator of innate immunity. Its role in autoimmune disorders is unknown. The goal of this study was to determine the role of CL-11 in a mouse model of rheumatoid arthritis (RA). METHODS. A murine collagen-induced arthritis (CIA) model, combining both gene deletion of Colec11 and recombinant (rCL-11) treatment approaches were employed. Joint inflammation and tissue destruction, circulating levels of inflammatory cytokines and adaptive immune responses were assessed in CIA mice. Splenic CD11c(+) cells were used to examine the influence of CL-11 on antigen presenting cell (APC) function. Serum levels of CL-11 in RA patients were also examined. RESULTS. Colec11(−/−) mice developed more severe arthritis than WT mice (as determined by disease incidence, clinical arthritis scores and histopathology; P<0.05). Disease severity is associated with significantly enhanced APC activation, Th1/Th17 responses, pathogenic IgG2a production and joint inflammation, as well as elevated circulating levels of inflammatory cytokines. In vitro analysis of CD11c(+) cells revealed that CL-11 is critical for suppression of APC activation and function. Pharmacological treatment of mice with rCL-11 reduced the severity of CIA in mice. Analysis of human blood samples revealed that serum levels of CL-11 was lower in RA patients (n=51) compared to healthy controls (n=53), a serum CL-11 reduction also displays a negative relationship with DAS28, ESR and CRP (P<0.05). CONCLUSION. Our findings demonstrate a novel role for CL-11 in protection against RA, suggesting the underlying mechanism involved suppression of APC activation and subsequent T cell responses

Genome wide prediction of protein function via a generic knowledge discovery approach based on evidence integration

BACKGROUND: The automation of many common molecular biology techniques has resulted in the accumulation of vast quantities of experimental data. One of the major challenges now facing researchers is how to process this data to yield useful information about a biological system (e.g. knowledge of genes and their products, and the biological roles of proteins, their molecular functions, localizations and interaction networks). We present a technique called Global Mapping of Unknown Proteins (GMUP) which uses the Gene Ontology Index to relate diverse sources of experimental data by creation of an abstraction layer of evidence data. This abstraction layer is used as input to a neural network which, once trained, can be used to predict function from the evidence data of unannotated proteins. The method allows us to include almost any experimental data set related to protein function, which incorporates the Gene Ontology, to our evidence data in order to seek relationships between the different sets. RESULTS: We have demonstrated the capabilities of this method in two ways. We first collected various experimental datasets associated with yeast (Saccharomyces cerevisiae) and applied the technique to a set of previously annotated open reading frames (ORFs). These ORFs were divided into training and test sets and were used to examine the accuracy of the predictions made by our method. Then we applied GMUP to previously un-annotated ORFs and made 1980, 836 and 1969 predictions corresponding to the GO Biological Process, Molecular Function and Cellular Component sub-categories respectively. We found that GMUP was particularly successful at predicting ORFs with functions associated with the ribonucleoprotein complex, protein metabolism and transportation. CONCLUSION: This study presents a global and generic gene knowledge discovery approach based on evidence integration of various genome-scale data. It can be used to provide insight as to how certain biological processes are implemented by interaction and coordination of proteins, which may serve as a guide for future analysis. New data can be readily incorporated as it becomes available to provide more reliable predictions or further insights into processes and interactions

A Variable-Weather-Parameter MPPT Method Based on Equation Solution for Photovoltaic System with DC Bus

The control signals of the variable-weather-parameter (VWP) methods need to be calculated by the real-time measured data of the irradiance and temperature (I&amp;T) sensors, which leads to the high hardware cost of the sensors. To solve this problem, the PV system with a DC bus is selected as the research subject and a novel maximum power point tracking (MPPT) method is proposed. It is named the VWP MPPT method based on the equation solution (ES-VWP method). Its control signal is directly calculated by the solution of an established equation set rather than data measured by the I&amp;T sensors. This equation set consists of two integrated mathematical equations, which represent two different operating points of the PV system. Meanwhile, when the bus voltage is varying or unknown, a calculation method that can estimate the real-time value of the DC bus voltage is proposed. In addition, an implementation method corresponding to the ES-VWP method is also designed. Finally, some simulation experiments are carried out to verify the availability and feasibility of the ES-VWP method. Meanwhile, some simulation experiments show that the error of the equation solution is less than 0.0001. In addition, some simulation experiments illustrate that the MPPT settling times of the ES-VWP method are always less than one-tenth of the P&amp;O method (or one-sixth of the FLC method). Compared with the existing VWP methods, it can be implemented without the use of I&amp;T sensors or external I&amp;T data. Meanwhile, compared with other existing MPPT methods, its better MPPT rapidity originating from the advantage of the VWP methods is inherited. This work is the first attempt to design a novel MPPT method by obtaining the real-time equation solutions of Voc and Isc. Meanwhile, this work is also the first attempt to solve the real-time equation of Vbus by the solved Voc and Isc. In addition, this work is also the first attempt to design an implementation method for establishing an equation set by sampling two operating points of a PV system at the same time