Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel DOA Estimation of Coherent Signal based on Virtual Array

Conventional direction-of-arrival (DOA) estimations perform poorly in coherent signals due to the rank loss of spatial covariance matrix, and most of the existing methods solve the problem at the expense of Degree of Freedom (DOF) or accuracy. In this paper, a novel DOA estimation technique for coherent signal is presented based on virtual array. The method comprises three steps: Firstly, the covariance matrix is generated according to the output signals of the array. Then, the first row and first column are selected from the matrix according to the data model of each element of the covariance matrix, which can be regarded as a uniform and continuous single snapshot signal of virtual array. Finally, the forward and backward spatial smoothing is used to achieve decorrelation of the single snapshot signal of the virtual array element. The proposed method has no loss of DOF and maintains high accuracy for low signal-to-noise ratio (SNR) conditions. The feasibility of the proposed method is proved by theoretical derivation, and its effectiveness is also verified by numerical results.
Research on the Construction Method of Knowledge Ontology Facing the Field of Substation Maintenance

Starting from the definition and classification of knowledge, this paper gives the definition and classification of substation maintenance knowledge. Based on the “seven-step method”, it proposes a method of constructing knowledge ontology for narrow fields, including 9 steps, and establishes substation maintenance knowledge Ontology, including 13 concepts and 60 attributes, lists the concepts and attribute descriptions of the ontology, laying the foundation for the next step of building a knowledge navigation map.
A novel quantization method combined with knowledge distillation for deep neural networks

The massive parameters and intensive computations in neural networks always limit the deployment on embedded devices with poor storage and computing power. To solve this problem, a novel quantization algorithm combined with Knowledge Distillation (KD) is proposed to reduce the model size and speed up the inference of deep models. The proposed method consists of two phases, KD-Training and Quantization-Retraining. KD-Training attempts to train a compact student model with pre-quantized weights by the proposed pre-quantized constraint loss. In Quantization-Retraining, the pre-quantized weights are quantized to 2n and the first and last layers of the network are retained to make up for the accuracy loss caused by quantization. Experiments on the CIFAR-10 dataset show that the proposed method can obtain a low-precision (2-5bit) quantized student model with a compact structure, and the test accuracy even exceeds its full-precision(32bit) reference as the improvement of the generalization ability. It can get higher performance compared with that obtained by other quantization methods. Also, since the quantized weights are constrained in { ± 2n}, it is suitable for the acceleration of the network calculation in hardware.
The H2O2 treated agarose compositing with gelatin for skin repair

This paper presented that the H2O2 treated agarose (abbr. AG) was composited with gelatin (abbr.Gel) as gel-like polymeric mixture for skin cut repair. The low molecular weight AG was prepared by H2O2 treatment for certain intervals. The time of AG gelling might be tested by scattered light turbidimeter and its mechanical properties were evaluated. The degraded AG mixing with Gel was sprayed to cover rabbit lesion site. AG/Gel mixing gel had good biocomptability and could repair rabbit skin wound without liquid exudation and bacterium infection. H&E staining results disclosed that type I collagen and other extracelluar matrix in the repaired site have same with the original skin. The degraded AG mixing with Gel gels have potential as wound dressings.
Anonymous node location based on clustering

With the rapid development of network technology, the network’s scale is increasing and becoming more complex. It is imperative to understand the structure of the network for network management and network security. Therefore, the construction of the routing topology has become a top priority. Routing topology analysis is already a relatively mature technology, but anonymous nodes’ positioning has not received enough attention. Nowadays, the primary solutions to anonymous nodes are graph analysis and tomographic tree construction. Based on these two methods, this paper proposes a rough location of anonymous nodes based on the method of three-level clustering. They are the K-means clustering of data before anonymous identification, hierarchical clustering of feature values in anonymous identification, and central point calculation based on clustering ideas during anonymous positioning. Experiments have proved that performing the first-level K-means clustering before anonymous node identification can effectively improve anonymous positioning accuracy. And the three-layer clustering idea proposed in this paper can roughly get the location of anonymous nodes based on reducing the complexity of the original method.
Researching on mathematical computation and experimental bench design of high-pressure blowing system

Utilized in sinking and surfacing of Autonomous Underwater Vehicle(AUV), the high-pressure blowing system(HPBS)had played an important role in maneuvering pilot of AUV and must be investigated thoroughly, by which the reserve buoyancy can be controlled. Because of the costliness of experiment on the real ship, an experimental bench of HPBS had been proposed and designed. After mathematical computations of sinking and surfacing processes of AUV, the pressure vessel prototype and it critical physical parameters selection were accomplished, which were used as ballast tank and sea environmental tank of the HPBS experimental bench. Based on those, the blueprint of the total experimental bench had been drawn and the working course of HPBS had been demonstrated.
Projectile wireless setting and Mechanical testing technology

This paper discusses the mechanical testing technology used in the wireless setting system of projectile, mainly including sensor, signal processing, system analysis, error analysis and data processing theory. The circuit simulation and system analysis are carried out by using Multisum, and the magnetic field simulation is carried out by using CST. The wireless setting scheme based on electromagnetic induction is designed, and the scheme is analyzed and improved. Finally, the data of range and firing angle of the projectile in high-speed motion can be set quickly.
Geographical distribution of liver cancer incidence based on big data analysis

The liver cancer has become the sixth most common cancer and the second leading cause of cancer deaths worldwide. The incidence of liver cancer has characteristics of the geographical distribution, which vary from region to region. Based on the data from Cancer Incidence in Five Continents, this study analyzed the spatial distribution of liver cancer globally and explored the effect of meteorological factors of surface temperature and wind field on incidence of liver cancer, to find the geographical distribution characteristics of liver cancer and the impact of geographical environmental factors on the incidence of liver cancer, which will be of great significance to the epidemiological study of liver cancer and the prevention of liver cancer. The results show that the humid and hot oceanic climate may be conducive to the development of liver cancer. The environmental factors play an important role in the occurrence of liver cancer.
Evaluation of a Physical Based Approach of Scattered Radiation Correction in Cone Beam CT for Non-Destructive Testing Applications

Cone Beam Computerized Tomography (CBCT) enables three-dimensional imaging with isotropic resolution. X-ray scatter management is a challenging task for quantitative CBCT imaging : scattered radiation level is signiﬁcantly high on cone beam systems compared to collimated fan beam systems. The effects of this scattered radiation are cupping artifacts, streaks, and quantiﬁcation inaccuracies. At CEA-LETI, an original scatter management process without additional on-line acquisition has been developed, the API (Analytical transformation Plus Indexation based) method. The proposed method is composed of two steps: a scatter calibration is ﬁrst performed through off-line acquisitions and is used to evaluate the level and a global shape of scattered radiation on on-line tomographic projections of the object. This global shape is adapted to the current acquisition with an analytical transformation issued from physical equations to evaluate the scattered radiation distribution on tomographic projections. This approach has been applied successfully in medical ﬁeld. This paper presents in detail the API method and evaluates it in CBCT for Non-Destructive Testing (NDT). To evaluate API method, experimental radiographic projections of simple geometry objects were performed with a Thales Flaschscan ﬂat panel detector and corrected from scatter by API method and by a beam stops method. Simulated projections of primary radiation were performed with the simulation software Sindbad, developed at CEA LETI. Reconstructions were then performed on experimental scatter corrected projections and on simulated projections. The API method provides results in good agreement with simulations, suppressing cupping artifact. The improvements due to the scatter correction by the API method have the same order of magnitude as those due to the correction by the beam stops method on experiments performed without antiscatter grid. The estimation of scatter is found to be more accurate with the API method than with the beam stops method on experiments performed with an antiscatter grid. API method improves NDT quantitatively and qualitatively without increasing on-line acquisition time
French CEOs compensation : what is the cost of a mandatroy upper limit ?

In the middle of the 90s, the sharp increase in globalization and the last privatization wave have promoted the shaping of a market for executives in France. Characteristics of this market are estimated for France and a competitive model is simulated in order to assess to what extent such a model can reproduce the observed chief executive officer (CEO) compensations. The size elasticity of CEOs’ compensations in France is equal to 0.5 and justifies a large magnitude in compensations. To moderate these compensations, a wage cap is often called for not only by opinion and the European Left but also, more surprisingly, by representatives of shareholders. The cost of this policy is evaluated in this job assignement model and the lobbying of shareholders is investigated and explained above some thresholds. Classification JEL : J31, J33, D33, D41.
Nanofibrous rhPDGF-eluting PLGA–collagen hybrid scaffolds enhance healing of diabetic wounds

Patients with chronic, non-healing diabetic ulcers extend hospital stays and increase the financial burden more than non-diabetics. This investigation developed nanofibrous growth factor-eluting poly(lactic-co-glycolic acid) (PLGA)–collagen hybrid scaffolds that enabled the sustainable release of recombinant human platelet-derived growth factor (rhPDGF) to treat diabetic wounds. RhPDGF, collagen, and PLGA were dissolved in hexafluoroisopropanol, and then electrospun into nanofibrous scaffolds. An enzyme-linked immunosorbent assay kit and an elution method were utilized to evaluate the rates of in vivo and in vitro release of growth factors from the scaffolds. High concentrations and effectiveness of rhPDGF were documented for over three weeks. The water contact angles of nanofibrous rhPDGF-eluting PLGA–collagen hybrid scaffolds were less (97.2 ± 0.7°) than those of PLGA–collagen hybrid mesh (107.6 ± 1.0°) or virgin PLGA (113 ± 3.3°) (all post hoc p < 0.05). The nanofibers with rhPDGF-eluting PLGA–collagen hybrid scaffold also exhibited significantly higher water-retaining capacity than those in other groups (all post hoc p < 0.001). Furthermore, the scaffolds caused more re-epithelialization and contained more collagen I in rats with rhPDGF-eluting scaffolds than controls, as determined from the expressed matrix metalloproteinase 9 in the hair canals in developing hair follicles. These results revealed for the first time, the application of rhPDGF as a growth factor adjuvant, and developed a new collagen-based composite with potent cell infiltration and epithelialization properties.
This information is current as Homeostasis Cooperatively Modulate T Regulatory Cell TCR Signaling and CD 28 / CTLA-4 Signaling and

Print ISSN: 0022-1767 Online ISSN: 1550-6606. Immunologists, Inc. All rights reserved. Copyright © 2017 by The American Association of 9650 Rockville Pike, Bethesda, MD 20814-3994. The American Association of Immunologists, Inc., is published twice each month by The Journal of Immunology at U iv of C alifnia-San D igo Seials/B om ed L ib 0699 on Jauary 5, 2017 hp://w w w jim m unl.org/ D ow nladed from
Modeling the biodegradability and physicochemical properties of polycyclic aromatic hydrocarbons

Modeling the Biodegradability and Physicochemical Properties of Polycyclic Aromatic Hydrocarbons. (August 2005) Petros Dimitriou-Christidis, B.S., University of the Aegean; M.S., University of California, Berkeley Chair of Advisory Committee: Dr. Robin L. Autenrieth The biodegradability and physicochemical properties of unsubstituted and methylated polycyclic aromatic hydrocarbons (PAHs) were investigated. The focus was on the development of models expressing the influence of molecular structure and properties on observed behavior. Linear free energy relationships (LFERs) were developed for the estimation of aqueous solubilities, octanol/water partition coefficients, and vapor pressures as functions of chromatographic retention time. LFERs were tested in the estimation of physicochemical properties for twenty methylated naphthalenes containing up to four methyl substituents. It was determined that LFERs can accurately estimate physicochemical properties for methylated naphthalenes. Twenty unsubstituted and methylated PAHs containing up to four aromatic rings were biodegraded individually by Sphingomonas paucimobilis strain EPA505, and Monod-type kinetic coefficients were estimated for each PAH using the integral method. Estimated extant kinetic parameters included the maximal specific biodegradation rate, the affinity coefficient, and the inhibition coefficient. The generic Andrews model adequately simulated kinetic data. The ability of PAHs to serve as sole energy and carbon sources was also evaluated. Quantitative structure-biodegradability relationships (QSBRs) were developed based on the estimates of the kinetic and growth parameters. A genetic algorithm was used for QSBR development. Statistical analysis and validation demonstrated the
Technical Article: Security Incidents and Trends in Scada and Process Industries

Supervisory Control and Data Acquisition and industrial control systems, with their traditional reliance on proprietary networks and hardware, have long been considered immune to the cyber attacks suffered by corporate information systems. Unfortunately, both academic research and in-the-field experience indicate misplaced confidence.The move to open standards such as Ethernet,TCP/IP, and web technologies allows hackers and virus writers to take advantage of the control industry's ignorance.The result is a growing number of unpublicised cyber-based security events that are affecting critical infrastructure and manufacturing industries. Eric Byres,David Leversage and Nate Kube In making the case against complacency about control system security, this report summarises the incident information collected in the Industrial Security Incident Database (ISID). It describes a number of events that have directly affected process control systems indicating that the number of cyber incidents against SCADA and control systems worldwide has increased significantly since 2001. The majority of these incidents are coming from the Internet by way of opportunistic viruses, Trojan horses, and worms, but a surprisingly large number are directed acts of sabotage. In addition, the analysis indicates that many SCADA/process control networks (PCN) have poorly documented points of entry that provide secondary pathways into the system. Historically, the industrial control and SCADA systems that are responsible for monitoring and controlling our critical infrastructures and manufacturing processes have operated in isolated environments. These control systems and devices communicated with each other almost exclusively, and rarely shared information with systems outside their environment. As more components of control systems become interconnected with the outside world using IP-based standards, the probability and impact of a cyber attack will heighten. In fact, there is increasing concern among both government officials and control systems experts about potential cyber threats to the control systems that govern critical infrastructures. Even the flaws in SCADA specific technologies have become general knowledge – detailed presentations on how to exploit SCADA vulnerabilities have been given at black hat public gatherings1.What is lacking is good historical data to either back up or dismiss these concerns. Event data collected over the past five years by ISID could provide objective, relevant statistical data for security decisions. The Industrial Security Incident Database In early 2001 a security research team at the British Columbia Institute of Technology (BCIT) was asked by a major petroleum refining facility to investigate the possibility that their control systems could be impacted by cyber-related events such as hacking or …
Preparation,Characterization and Catalytic Properties of Sn-Containing MCM-41

The molecular sieve catalysis material of Si-MCM-41,Sn-MCM-41 were preparaed under the condition of low template concentration in weak base and the samples were characterized by XRD,N2 adsorption-desorption,FT-IR,ICP-AES and TEM techniques.Effect of the synthesis methods on the Sn-containing MCM-41 were studied.The results showed that Sn species were mainly incorporated into the framework of MCM-41 molecular sieves prepared by direct hydrothermal synthesis method(DHT),while Sn species were mainly existed on the wall surface of Sn-MCM-41 molecular sieves prepared by template-ion exchange method(TIE). The catalytic properties of Sn containing MCM-41 molecular sieves in Baeyer-Villiger oxidation of cyclohexanone were investigated.Catalytic activity results show that under the reaction condition of n(H2O2):n(Cyclohexanone)=3:1,30 g dioxane,at 70℃ for 6 h,the conversion of cyclohexanone and the selectivity of e-caprolactone reach 40.02% and 45.69%,respectively.
Random Signals

This chapter provides a summary of definitions and fundamental concepts of probability spaces, random variables, and random processes. References [1]—[8] provide more extensive background and examples. A probability space is a triple (Ω, F , P) where Ω is the sample space, F is a σ-field defined on Ω, and P is a probability measure defined on F. • The sample space Ω represents the set of outcomes of a random experiment, e.g., Ω = {Head, Tail} for a coin flip; or Ω = R + for the time to next child birth in Urbana, Illinois. • The sigma field F is a collection of subsets of Ω (viewed as events) such that
Analysis of Alkaloid from Cynanchum komanovii AL Iljinshi by GC-MS

Twelve alkaloids were isolated and identified from the whole plant of Cynanchum komanovii AL Iljinshi by GC MS.They are Pyridine,2,4,6 trimethyl ;2,6 Diethylpyridine ;2 Butanone,4 (1 piperidinyl) ;Benzothiazole;3 n Propyl 2,6 diphenylpyridine;Tylophorinidine;4 Piperidinone, 2,2,6,6 tetramethyl ;Diazen,butyl[1 [2,2 dimethylhydr)];5,10 Diethoxy 2,3,7,8 tetrahydro 1H, 6H dipyrrolo[1,2 a;1`,2` d]pyrazine;9 Azabicyclononane,9 methyl ;Piperidino2,3 dihtdroindene,1 methyl 4,4a diethyl 6 methyl ;7,14 Methano 4H,6H dipyrido[1,2 a:1`,2` E]diazocin 4 one,7,7a,8,9,10,11,13,14 octahydro ,[7R (7,alpha,7a,alpha,14,alpha)]. Last six compounds were obtained from this species for the first time
Automatic parallelization of sequential code for a cluster of multiprocessors

In recent years parallel architectures have rapidly evolved to solve increasingly large problems, mainly because single processor based systems have reached the limit of their physical capacity. The end of 90’s has seen the growth and evolution of parallel architectures towards a cluster of multiprocessors owing to scaling problems with shared memory machines. The eﬃcient use of such parallel architectures demands writing of parallel code by the programmer or automatic parallelization of sequential code by the compiler. We shall look at the latter approach in more detail since the former places too much responsibility on the individual. Our approach is based on SUIF, an automatic parallelizer for a symmetric memory architecture, developed by the Stanford University. We shall focus on extending SUIF to produce high level code with explicit calls to parallel libraries like MPI instead of calls to runtime libraries. This would allow us to produce parallel code for a cluster of multiprocessors instead of a shared memory machine.
Scalable Graph Neural Network Training

Graph Neural Networks (GNNs) are a new and increasingly popular family of deep neural network architectures to perform learning on graphs. Training them efficiently is challenging due to the irregular nature of graph data. The problem becomes even more challenging when scaling to large graphs that exceed the capacity of single devices. Standard approaches to distributed DNN training, like data and model parallelism, do not directly apply to GNNs. Instead, two different approaches have emerged in the literature: whole-graph and sample-based training. In this paper, we review and compare the two approaches. Scalability is challenging with both approaches, but we make a case that research should focus on sample-based training since it is a more promising approach. Finally, we review recent systems supporting sample-based training.
A pseudo-marginal sequential Monte Carlo online smoothing algorithm

: We consider online computation of expectations of additive state functionals under general path probability measures proportional to products of unnormalised transition densities. These transition densities are assumed to be intractable but possible to estimate, with or without bias. Using pseudo-marginalisation techniques we are able to extend the particle- based, rapid incremental smoother (PaRIS) algorithm proposed in [J. Olsson and J. Westerborn. Eﬃcient particle-based online smoothing in general hidden Markov models: The PaRIS algorithm. Bernoulli , 23(3):1951–1996, 2017] to this setting. The resulting algorithm, which has a linear complex- ity in the number of particles and constant memory requirements, applies to a wide range of challenging path-space Monte Carlo problems, includ- ing smoothing in partially observed diﬀusion processes and models with intractable likelihood. The algorithm is furnished with several theoretical results, including a central limit theorem, establishing its convergence and numerical stability. Moreover, under strong mixing assumptions we estab- lish a novel O ( nε ) bound on the asymptotic bias of the algorithm, where n is the path length and ε controls the bias of the density estimators.