Miracle-dz/UniFAR-FTUs huggingface dataset:
IN VIVO STUDIES OF CELL-FREE DNA AND DNASE IN A MURINE MODEL OF POLYMICROBIAL SEPSIS

III Acknowledgements.VIII List of figures.XVI List of tables.XX List of abbreviations.XX Chapter 1: General introduction.1 1.1 Overview of hemostasis.1 1.1.1 Platelet adhesion and aggregation.1 1.2 Blood coagulation.3 1.2.1 Extrinsic pathway of coagulation.3 1.2. 2 In vivo studies of the extrinsic pathway: blood-borne tissue factor.7 1.2. 3 Intrinsic pathway of coagulation.8 1.2. 4 Activators of the intrinsic pathway of coagulation: platelet polyphosphates and nucleic acids.9 1.2. 5 Common pathway of coagulation.11 1.2. 6 Formation of the fibrin clot.11 1.2. 7 Fibrinolysis.12 1.2. 7.1 Inhibitors of fibrinolysis.13 1.3 Inhibitors of coagulation.14 1.3. 1 Antithrombin.14 1.3. 2 Tissue factor pathway inhibitor.15 1.3. 3 Protein C.18 1.4 Sepsis.19 1.4. 1 Pro-inflammatory response in sepsis.19 1.4. 2 Crosstalk between inflammation and coagulation in sepsis.21 1.5 Neutrophil extracellular traps (NETs). 22 1.5. 1 NETosis, a unique form of cell death.23 1.5. 2 NETosis in infection.26 1.5. 2.1 NETs in sepsis: circulating cf-NETs and anchored NETs.30 1.5. 3 Effects of NETs and NET components on hemostasis.31 1.5. 4 Pro-inflammatory effects of NETs and NET components.33 1.5. 5 Inhibitors of NETosis and NET components.35 1.5. 6 Modulation of fibrinolysis by DNA and histones.37 1.6 Historical development of animal models of sepsis.38 1.6. 1 Cecal ligation and puncture (CLP) model of sepsis.40
A learning algorithm for the Whittle index policy for scheduling web crawlers

We revisit the Whittle index policy for scheduling web crawlers for ephemeral content proposed in Avrachenkov and Borkar, IEEE Trans. Control of Network Systems 5(1), 2016, and develop a reinforcement learning scheme for it based on LSPE(0). The scheme leverages the known structural properties of the Whittle index policy.
Using SDN Strategies to Improve Resource Management On a NoC

The dynamic resource allocation has a significant impact on the performance of Network-on-Chip (NoC). In this work, we propose to use Software-Defined Network (SDN) paradigm together with IPNoSys, a non-conventional architecture with a specific execution model. The SDNoC proposed can use SDN to provide flexibility and reliability, with the same performance as others SDNoCs in literature and can be more efficient because of IPNoSys execution model features. The SDNoC use IPNoSys compilers to cluster tasks and the IPNoSys processor element to manage the communication and migrate tasks if necessary.
Towards a mm-Sized Free-Floating Wireless Implantable Opto-Electro Stimulation Device

Next generation of brain-machine interfaces (BMI) will be able to interface with large-scale neuronal ensembles over large brain areas with a distributed architecture consisting of multiple tiny implants. This paper presents a system-on-a-chip (SoC) prototype towards a mm-sized free-floating wirelessly-powered implantable 16-ch opto-electro stimulation (FF-WIOS2) device. FF-WIOS2 is wirelessly powered and controlled through a 3-coil inductive link at 60 MHz. Forward telemetry link delivers stimulation parameters to the FF-WIOS2 via on-off keying (OOK) to configure stimulation patterns. Back telemetry link reports the FF-WIOS2 rectified voltage in a closed-loop fashion via load-shift-keying (LSK) to stabilize the implant received power. The SoC, fabricated in a 0.35-µm standard CMOS process, employs switched-capacitor-based stimulation (SCS) by charging an off-chip capacitor up to 5 V at 37% charging efficiency to provide large instantaneous current. At the onset of stimulation, the capacitor delivers charge, with peak current values of either 1.7-12 mA to a LED array for optical stimulation or 100-700 μA to a microelectrode array (MEA) for biphasic electrical stimulation. The latter mechanism is also actively charge-balanced to ensure stimulation safety.
A Hybrid Approach for Detecting and Resolving Conflicts in Air Traffic Routes

This paper presents a hybrid model for the detection and resolution of conflicts in air traffic routes involving flight level change actions and adjustment of the longitudinal acceleration of aircraft. The strategy comprises an integrated approach that uses a fuzzy model to quantify the level of longitudinal conflict between two aircraft on the same airway. In addition, optimum flight level change actions between aircraft are calculated through a global and dynamic analysis involving the recognition of clusters of aircraft in conflict and the search for the best scenario by means of a genetic algorithm that minimizes the sum of positive conflicts. The results show that the proposed approach is able to detect and remove longitudinal conflicts in advance, providing a potential tool to support decision-making, improve safety and optimize the use of airspace.
Embedded Partitioning Real-Time Operating System Based on Microkernel

The embedded partitioning operating system is active in security-related fields such as avionics and automotive embedded software. The temporal and spatial isolation of the partition is the guarantee of system security. In addition, as these areas become more demanding for applications, improving the real-time performance of partitioning operating systems has become a trend. To reach this goal, we propose a solution that leverages the microkernel architecture in the embedded partitioning operating system. The microkernel ensures the determinacy of real-time scheduling policies and system calls by simplifying kernel functionality and preserving the most basic resources. Partitions built on top of the microkernel enable low-cost communication, fast context switching and mixed task scheduling. Based on the microkernel, we developed a complete real-time partitioning operating system. The system supports multi-core processors to take full advantage of the high performance of existing embedded processors. On different hardware platforms, we conducted two types of tests about interrupt response time and latency. The results show that our proposed architecture exhibits high real-time performance.
An Energy Aware Fuzzy Trust based Clustering with group key Management in MANET Multicasting

The group key maintenance in MANET is especially risky, because repeated node movement, link breakdown and lower capacity resources. The member movement needs key refreshment to maintain privacy among members. To survive with these characteristics variety of clustering concepts used to subdivide the network. To establish considerably stable and trustable environment fuzzy based trust clustering taken into consideration with Group key management. The nodes with highest trust and energy elected as Cluster Head and it forms cluster in its range. The proposed work analyze secure multicast transmission by implementing Polynomial-based key management in Fuzzy Trust based clustered networks (FTBCA) for secure multicast transmission that protect against both internal and external attackers and measure the performance by injecting attack models.
Semitransparent Sb2S3 thin film solar cells by ultrasonic spray pyrolysis for use in solar windows

The integration of photovoltaic (PV) solar energy in zero-energy buildings requires durable and efficient solar windows composed of lightweight and semitransparent thin film solar cells. Inorganic materials with a high optical absorption coefficient, such as Sb2S3 (>105 cm−1 at 450 nm), offer semitransparency, appreciable efficiency, and long-term durability at low cost. Oxide-free throughout the Sb2S3 layer thickness, as confirmed by combined studies of energy dispersive X-ray spectroscopy and synchrotron soft X-ray emission spectroscopy, semitransparent Sb2S3 thin films can be rapidly grown in air by the area-scalable ultrasonic spray pyrolysis method. Integrated into a ITO/TiO2/Sb2S3/P3HT/Au solar cell, a power conversion efficiency (PCE) of 5.5% at air mass 1.5 global (AM1.5G) is achieved, which is a record among spray-deposited Sb2S3 solar cells. An average visible transparency (AVT) of 26% of the back-contact-less ITO/TiO2/Sb2S3 solar cell stack in the wavelength range of 380–740 nm is attained by tuning the Sb2S3 absorber thickness to 100 nm. In scale-up from mm2 to cm2 areas, the Sb2S3 hybrid solar cells show a decrease in efficiency of only 3.2% for an 88 mm2 Sb2S3 solar cell, which retains 70% relative efficiency after one year of non-encapsulated storage. A cell with a PCE of 3.9% at 1 sun shows a PCE of 7.4% at 0.1 sun, attesting to the applicability of these solar cells for light harvesting under cloud cover.
Design and Comparison of Two Hybrid Less-Rare-Earth Permanent Magnet Machines with Different Rotor Topologies

Nowadays, the hybrid less-rare-earth permanent magnet (HLPM) machines featuring low-priced and good performances have potential application prospect in electric vehicles (EVs). In this paper, two HLPM machines with different rotor topologies are proposed for analysis and comparison. The main differences between two HLPM machines are the arrangement of permanent magnet and the design of flux barrier. Via the finite element analysis (FEA), the electromagnetic performances and mechanical performances of these two HLPM machines, such as air-gap flux density, back-EMF, torque characteristic are analyzed in detail. The results will reveal the influences of different rotor topologies on the electromagnetic performances and mechanical performances for HLPM machines.
Multi-Criteria Review-Based Recommender System–The State of the Art

In recent times, the recommender systems (RSs) have considerable importance in academia, commercial activities, and industry. They are widely used in various domains such as shopping (Amazon), music (Pandora), movies (Netflix), travel (TripAdvisor), restaurant (Yelp), people (Facebook), and articles (TED). Most of the RSs approaches rely on a single-criterion rating (overall rating) as a primary source for the recommendation process. However, the overall rating is not enough to gain high accuracy of recommendations because the overall rating cannot express fine-grained analysis behind the user’s behavior. To solve this problem, multi-criteria recommender systems (MCRSs) have been developed to improve the accuracy of the RS performance. Additionally, a new source of information represented by the user-generated reviews is incorporated in the recommendation process because of the rich and numerous information included (i.e. review elements) related to the whole item or to a certain feature of the item or the user’s preferences. The valuable review elements are extracted using either text mining or sentiment analysis. MCRSs benefit from the review elements of the user-generated reviews in building their criteria forming multi-criteria review based recommender systems. The review elements improve the accuracy of the RS performance and mitigate most of the RS’s problems such as the cold start and sparsity. In this review, we focused on the multi-criteria review-based recommender system and explained the user reviews elements in detail and how these can be integrated into the RSs to help develop their criteria to enhance the RSs performance. Finally, based on the survey, we presented four future trends based on this type of RSs to support researchers who wish to pursue studies in this area.
Modeling Human Pilot Behavior for Aircraft With a Smart Inceptor

This article presents a model of the human pilot for an aircraft with a smart inceptor, as a means to mitigate human–vehicle system loss–of–control. A key feature of the pilot model is the capability to reflect the interaction between the human–vehicle interface and the human pilot. The proposed human pilot model is primarily composed of a perception module, adaptation module, and execution module. The visual and tactile cues perceived from the human–vehicle interface including a smart inceptor are utilized to model the perception module. The adaptation module, including the central nervous system, is introduced to describe the adaptive behavior of the human pilot. In addition, the execution module contains the neuromuscular system of the human pilot so that the dynamics of the neuromuscular system and the smart inceptor are considered. The human pilot model is assessed by the time domain and wavelet–based analysis in comparison with the experiments of pilot–in–the–loop flight simulation. The simulation results indicate that the tracking results of the time histories given by this model are in good agreement with the behavioral characteristics of a test pilot. The potential applications of the human pilot model include the design of the smart inceptor and evaluation of aircraft loss–of–control events.
TraV: An Interactive Exploration System for Massive Trajectory Data

The proliferation of modern GPS-enabled devices like smartphones have led to significant research interest in large-scale trajectory exploration, which aims to identify all nearby trajectories of a given input trajectory. Trajectory exploration is useful in many scenarios, for example, in identifying incorrect road network information or in assisting users when traveling in unfamiliar geographical regions as it can reveal the popularity of certain routes/trajectories. In this study, we develop an interactive trajectory exploration system, named TraV. TraV allows users to easily plot and explore trajectories using an interactive Graphical User Interface (GUI) containing a map of the geographical region. TraV applies the Hidden Markov Model to calibrate the user input trajectory and then makes use of the massively parallel execution capabilities of modern hardware to quickly identify nearby trajectories to the input provided by the user. In order to ensure a seamless user experience, TraV adopts a progressive execution model that contrasts to the conventional query-before-process model. Demonstration participants will gain experience with TraV and its ability to calibrate user input and analyze billions of trajectories obtained from Grab drivers in Singapore.
Applying Convolutional Neural Network for Malware Detection

Failure to detect malware at its very inception leaves room for it to post significant threat and cost to cyber security for not only individuals, organizations but also the society and nation. However, the rapid growth in volume and diversity of malware renders conventional detection techniques that utilize feature extraction and comparison insufficient, making it very difficult for well-trained network administrators to identify malware, not to mention regular users of internet. Challenges in malware detection is exacerbated since complexity in the type and structure also increase dramatically in these years to include source code, binary file, shell script, Perl script, instructions, settings and others. Such increased complexity offers a premium on misjudgment.In order to increase malware detection efficiency and accuracy under large volume and multiple types of malware, this research adopts Convolutional Neural Networks (CNN) , one of the most successful deep learning techniques. The experiment shows an accuracy rate of over 90% in identifying malicious and benign codes. The experiment also presents that CNN is effective with detecting source code and binary code, it can further identify malware that is embedded into benign code, leaving malware no place to hide.This research proposes a feasible solution for network administrators to efficiently identify malware at the very inception in the severe network environment nowadays, so that information technology personnel can take protective actions in a timely manner and make preparations for potential follow-up cyber-attacks.
Direct Optical-Flow-Aware Computational Framework for 3D Reconstruction

In this paper, a direct computational method is presented which combines optical flow and structure from motion (SfM) by putting the SfM problem in the framework of optical flow estimation. In other word, the optical flow is reparametrized in term of the camera’s motion and scene’s depth, resulting in a similar variation optimization as in optical flow estimation. Meanwhile, three techniques are proposed to improve the accuracy and robustness of the direct approach, including the fast guided interpolation (FGI), the left-right consistency constraint and the soft segment constraint. Experimental results on the Middlebury dataset and KITTI2012 dataset show that the proposed approach can achieve highly-accurate 3D reconstruction with the dense and smooth surface which results in a state-of-the-art performance in optical flow.
Electromagnetic shielding design for magnetic coupler of N-type dynamic electric vehicle wireless power transfer systems

In order to reduce the electromagnetic radiation of the dynamic wireless power transfer (DWPT) system, this paper proposed an electromagnetic shielding scheme combining active and passive shielding for the N-type magnetic coupling mechanism coupler. Based on the finite element analysis (FEA) software, the magnetic field distribution of the magnetic coupler without and with different shielding structures are analyzed. The passive shielding scheme is rationally configured and optimized, and the electromagnetic radiation above the vehicle is effectively shielded. For the side area of the vehicle which is difficult to shield by passive shielding, an active shielding scheme with a separate coil is further designed. A experiment platform for electric vehicles with with frequency of 20 kHz and output power of 20 kW was built. The two methods of passive shielding and active shielding were experimentally verified. The results show that the magnetic field in the upper and side area of the vehicle meets ICNIRP standard after the proposed method is applied, which proves the feasibility of the passive and active shielding schemes proposed in this paper.
Effect of static longitudinal end effect on performance of arc linear induction motor

The arc linear induction motor (ALIM) has a static longitudinal end effect unique to the linear motor due to the truncated stator core, which has a negative impact on the performance of the motor. In this paper, based on the three-phase inductance imbalance phenomenon of the stator winding, the effect of static longitudinal end effect on air gap magnetic field, electromagnetic torque and no-load speed is deeply analyzed according to the electromagnetic field theory and the finite element calculation when the pole number is three poles and six poles, respectively. The experimental results are in agreement with the simulation results.
Towards Image Processing Based on System of Difference Equations

In the last few years image processing and analysis, particularly, video and image compression became very important due to immense development of new multi-media products, surveillance systems, automotive industry, etc, and the shortage of bandwidth and storage space of the memory. In the paper we consider a mathematical model as an approach to image processing, compression and restoration. We use edge detection algorithm to construct infinite system of difference equations, which is encoded by means of given family of functions, i.e. low degree polynomials, piece-wise linear functions or Heaviside step functions. Corresponding encoding and decoding algorithm is proposed, along with comprehensive theoretical background. The existence and uniqueness of decoded image is considered. This paper presents some preliminary study of the advantages and drawbacks of the approach and indicates areas of possible further research.
Design of Novel Variable Reluctance Resolver with Outer Rotor

The Variable Reluctance (VR) resolver is a kind of robust position sensor. In order to adapt to some special applications, a novel type of VR resolver with the outer rotor is designed in this paper. Firstly, the operation principles of VR resolver are introduced. Secondly, the advantages and disadvantages of different combinations of poles and slots are analyzed, and the number of poles and slots is determined as 2 and 8, respectively. At last, the output voltage harmonics are analyzed and reduced via optimally designed air gap function to enhance the detection accuracy. Different design scenarios are compared, and the effectiveness of the proposed design is verified via finite element analysis (FEA).
A Simple Inverter Nonlinearity Compensation Method Using On-Line Voltage Error Observer

Nonlinearity characteristics of the inverter will cause the output voltage and current waveform distortion, directly affecting the torque output stability and speed control performance of the AC motor drive system. For this reason, a new inverter nonlinearity compensation method for permanent magnet synchronous motor (PMSM) is proposed in the paper. A simple voltage error observer based on current deviation of the reference model and the actual system is used in d-q synchronous coordinate system. The method is simple to implement and does not require the precise polarity of current and additional design of testing circuit. The proposed scheme is applied to the discretized Simulink model for PMSM and the simulation results demonstrate the effectiveness of the method.
A Multi-User Beamforming Scheme for Uplink Wireless LAN

Multiple-input multiple-output (MIMO) technology has been used in wireless local area network (WLAN) systems to enhance system throughput. Many medium access control (MAC) protocols have been proposed for uplink. However, most of them do not consider the operations in physical layer and are difficult to implement in real-world. In this paper, we propose a simple uplink scheme to solve the problem. The main idea is to conduct beamforming in access point such that it can receive signals from multiple users, simultaneously and asynchronously. The distinct advantage of our scheme is that its MAC protocol is compliant to the standard distributed coordination function (DCF) of IEEE 802.11. Simulations show that the proposed scheme significantly outperforms the existing WLAN system.
Design of a Low Power Consumption Control System of Permanent Magnet Synchronous Motor for Automated Guided Vehicle

Permanent Magnet Synchronous Motor (PMSM) is widely used in industrial control fields such as numerical control machine tools and transfer robots due to its excellent speed regulation performance. As a typical representative of transfer robots, Automated Guided Vehicle (AGV) has attracted extensive attention and research. PMSM control system for AGV is specified on many aspects, such as small size, high power density and low power consumption. In this paper, the control system of PMSM for AGV is studied, including the design of hardware circuit and software control algorithm. STM32's abundant on-chip resources are fully utilized and Intelligent control strategies such as space vector pulse width modulation and fuzzy PID control are adopted to control the system in real time. By experimental test and results analysis, the control system designed in this paper shows good dynamic performance and low power consumption.
Evaluation of Full-Mesh Networks for Smart Home Applications

Wireless mesh network (WMN) is a promising technology for the next generation of wireless network. Because of its strong points, it is considered to dominate over other wireless networks while human had entered the era of the Internet of Things, WMN is being developed rapidly and inspiring large number of applications. This article intends to study and expand low-cost networking for smart home applications using 6LoWPAN/IPv6 (new and modern technology of WMN), and this development is able to be future platform for advanced smart home systems (using low-profile hardware to popularize this platform). Therefore, it concentrates on contributing to a solution which allows to expand and exploit thoroughly 6LoWPAN technology by combining 6LoWPAN/IPv6 with mesh-wifi. In addition, Batman-adv routing protocol and OpenWRT platform are chosen for mesh-wifi nodes. Particularly, the performance evaluations are investigated in terms of throughput, latency, jitter, and switching time of mesh-wifi nodes and possibility of interconnecting two wireless mesh network technologies to give an objective view for people prior to making a choice for enhancing 6LoWPAN network.