Miracle-dz/UniFAR-FTUs huggingface dataset:
mCSF-Induced Microglial Activation Prevents Myelin Loss and Promotes Its Repair in a Mouse Model of Multiple Sclerosis

A pathological hallmark of multiple sclerosis (MS) is myelin loss in brain white matter accompanied by compromised remyelination. Demyelinated lesions are deeply associated with oligodendrocyte apoptosis and a robust inflammatory response. Although various studies point towards a noxious role of inflammation in MS, others emphasize a positive role for the innate immune cells in disease progression. A cytokine well-known to stimulate cell survival, proliferation and differentiation of myeloid cells, macrophage colony-stimulating factor (mCSF), was administered to mice during a 5 week-long cuprizone diet. Treated mice exhibited reduced myelin loss during the demyelination phase, together with an increased number of microglia and oligodendrocyte precursor cells in lesion sites. Tamoxifen-induced conditional deletion of the mCSF receptor in microglia from cuprizone-fed mice caused aberrant myelin debris accumulation in the corpus callosum and reduced microglial phagocytic response. mCSF therefore plays a key role in stimulating myelin clearance by the brain innate immune cells, which is a prerequisite for proper remyelination and myelin repair processes.
Influence of cross-linking behavior on structure and breakdown property of nanocomposite dielectrics

Polyethylene has excellent electrical and mechanical properties. The thermostability and environmental stress cracking resistance properties can be improved by cross-linking. It is widely used as insulation material for medium-voltage and high-voltage power cables. However, the cross-linking process of polyethylene will change the microstructure of the polymer, thus affecting the electrical properties of the composite. In this paper, polyethylene/montmorillonite (PE/OMMT) and cross-linked polyethylene/montmorillonite (XLPE/OMMT) nanocomposites were prepared by a melting blending method. Small angle X-ray diffraction (XRD) was carried out to characterize the layer spacing of organic montmorillonite (OMMT), which modified by dimethyl-di (hydrogenated tallow) quaternary amine. Under the synergistic effect of compatibilizer, OMMT formed the intercalated nanocomposites. And the intercalation effect of polymer is the best with 2% OMMT mass fraction. The OMMT achieves the exfoliated dispersion state. However due to the establishment of the three-dimensional network structure during the cross-linking process, the intermolecular structure is strengthened and the interval between MMT layers is closer. The melting and crystallization behavior of nanocomposites were studied by differential scanning calorimetry (DSC). The crystal size of the samples was observed by scanning electron microscopy (SEM). The results indicate that the increase of the melting point Tm of the matrix resin in nanocomposites due to heat resistance of adding organic MMT, while after cross-linking, structure limits the orderly arrangement of crystals, so that the melting point Tm decreases, the crystallization rate slows down and the crystal size decreases. The breakdown strength of nanocomposites was tested. It indicates that the addition of OMMT changes the internal structure of the polymer, the field strength is improved and the data dispersion decreases. However, breakdown strength declines after cross-linking. The results show MMT intercalation efficiency and the interface state are the main factors which influencing the breakdown strength.
High-Frequency Voltage-Injection Methods and Observer Design for Initial Position Detection of Permanent Magnet Synchronous Machines

The information of the initial rotor position is essential for smooth startup and robust control of permanent magnet synchronous machines (PMSMs). RoTating Voltage Injection (RTVI) methods in the stationary reference frame have been commonly adopted to detect the initial rotor position at standstill without any position sensors. However, although the Pulsating sqUare-wave Voltage-Injection (PUVI) method performs better in estimation time and accuracy, it is rarely used because the estimation result may converge to the q-axis. In this paper, this fault convergence is avoided by modifying the initial states of the position observer, and the PUVI method can finally be used for the robust initial rotor position detection. Modified signal processing techniques are proposed for both RTVI and PUVI methods for better implementations in fixed-point processors and easier observer gain designs. Detailed comparisons between these two methods are provided. Furthermore, two position estimation observers, i.e., the proportional–integral observer and the extended state observer are compared, and their parameter tuning methods are studied as well. Both simulation and experimental results are provided for verifications.
Survey of Graph Analysis Applications

Recently, many systems for graph analysis have been developed to address the growing needs of both industry and academia to study complex graphs. Insight into the practical uses of graph analysis will allow future developments of such systems to optimize for real-world usage, instead of targeting single use cases or hypothetical workloads. This insight may be derived from surveys on the applications of graph analysis. However, existing surveys are limited in the variety of application domains, datasets, and/or graph analysis techniques they study. In this work we present and apply a systematic method for identifying practical use cases of graph analysis. We identify commonly used graph features and analysis methods and use our findings to construct a taxonomy of graph analysis applications. We conclude that practical use cases of graph analysis cover a diverse set of graph features and analysis methods. Furthermore, most applications combine multiple features and methods. Our findings motivate further development of graph analysis systems to support a broader set of applications and to facilitate the combination of multiple analysis methods in an (interactive) workflow.
Physical scaling effects of differential crosstalk in via arrays up to frequencies of 100 GHz

Data rates on copper-based links are now increasing beyond 50 Gbps which requires frequency-domain analyses up to at least 100 GHz. This work investigates for the first time the frequency behavior of differential crosstalk inside a via array for frequencies up to 100 GHz. It is shown that the crosstalk does not increase indefinitely with frequency. We evaluate if efficient modeling tools like the physics-based via modeling can be used for crosstalk assessments up to 100 GHz and compare the results with full-wave solutions. A reduced model with a single cavity is sufficient to predict the overall frequency dependence of the crosstalk inside the array. The effect of scaling down the geometry of the array is investigated. The via pitch is identified as the parameter with the greatest impact. For a frequency of 50 GHz a reduction of the via pitch from 80 mil to 40 mil could reduce the crosstalk by about 30 dB.
Approximate computing in the nanoscale era

The reduced benefits offered by technology scaling in the nanoscale era call for innovative design approaches, to process bigger and bigger amount of data with always higher performance and lower power consumption. In this respect, Approximate Computing constitutes one of the most promising trend, where efficiency is increased by breaking the dogma of error-free computations, enlarging the design space with the addition of application-specific quality metrics. Approximate Computing paradigm can be applied at different layers, spanning from software to systems and circuits. In this paper we focus on approximate arithmetic circuits for computer vision and machine learning. These kinds of applications have an excellent resiliency to computation errors. Moreover, their arithmetic-intensive processing makes the increase of efficiency of arithmetic circuits a keypoint. In this kind of context Approximate Computing can make the difference, improving, at the same time, performance and power consumption with tolerable quality degradation.
New record of the fish leech Piscicola pojmanskae (Annelida: Hirudinida: Piscicolidae) - DNA barcoding and phylogeny

The aim of this study was to confirm the taxonomic status of Piscicola pojmanskae Bielecki, 1994 found on Salmonidae fish. The fish leech was identified based on a diligent morphological analysis as well as COI gene sequence (DNA barcoding). The phylogenetic relationship with other piscicolid leeches was analyzed as well. Piscicola pojmanskae was found on various fins of both graylings and the resident form of trouts. The prevalence of infection was 1.63%. In this paper, probable causes of the lack of relation between the number of leeches on the fins and the fish body length as well as the host-searching strategy used by P. pojmanskae are discussed.
Multi-MHz IPT Systems for Variable Coupling

In typical multi-MHz inductive power transfer (IPT) systems, a change in coupling or load resistance can significantly deteriorate the end-to-end efficiency due to a deviation from the optimal load of the IPT link and suboptimal operation of the resonant inverter due to the loss of soft switching condition. This paper proposes solutions for an IPT system to operate efficiently when large changes in coupling take place. To achieve high power efficiency independent of coupling, we utilize inherent regulation properties of resonant converters to avoid losing soft switching for any coupling value, and present the optimal load to the IPT link at the maximum energy throughput coupling. A probability-based model is introduced to assess and optimize the IPT system by analyzing coupling as a distribution in time, which depends on the dynamic behavior of the wireless charging system. The proposed circuits are a Class D rectifier with a resistance compression network in the receiving end and a load-independent Class EF inverter in the transmitting end. Experiments were performed at 6.78 and 13.56 MHz verifying high efficiency for dynamic coupling and variable load resistance. End-to-end efficiencies of up to 88% are achieved at a coil separation larger than one coil radius for a system capable of supplying 150 W to the load, and the energy efficiency was measured at 80% when performing a uniformly distributed linear misalignment of 0–12.5 cm, corresponding to a receiver moving at a constant velocity over a transmitter without power throughput control.
Constant Modulus MIMO Radar Waveform Design With Minimum Peak Sidelobe Transmit Beampattern

This paper addresses the problem of minimum peak sidelobe transmit beampattern design for colocated multiple-input multiple-output radar systems. Two new methods are proposed to achieve it via designing constant modulus (CM) waveforms directly: One is to maximize the ratio of the minimum mainlobe level to the peak sidelobe level (PSL) without specifying pattern masks, and another is to minimize PSL under the mainlobe ripple and unspecified waveform modulus constraints. The resultant optimization problems are difficult to solve due to the coupled numerator and denominator of the quadratic fractional programming problem formulation in the former and double-sided quadratic constraints and unknown waveform modulus in the latter. For the former, we decouple the numerator and denominator by equivalent transformation and introduction of boundary-type auxiliary variables in order that feasible methods are derived to tackle them independently and efficiently. For the latter, we simplify the coupled double-sided quadratic constraints on the same waveform vector into those on different single auxiliary variables to tackle the corresponding nonconvex optimization problem. Numerical examples show that the proposed algorithms can attain sufficient low peak sidelobe beampattern levels under the CM constraints.
Virtualization in multicore real-time embedded systems for improvement of interrupt latency

This paper investigates the possibilities of using virtualization in multicore real-time embedded systems based on combination of general-purpose and real-time operating systems running on separate processor cores. The research is focused on ARM processor architecture due to its widespread usage in numerous application domains. The paper describes the concepts and practical considerations of using virtualization to achieve better interrupt latency both in Linux, as a typical representative of commonly used general-purpose operating system in applications requiring real-time response, and real-time operating system running on separate cores. In the proposed approach we demonstrate how to use virtualization mechanism to decouple cores responsible for real-time and non real-time tasks in a multiprocessor system with real-time requirements. Xen Hypervisor is used as a virtual machine monitor with default credit and new experimental null scheduler. The aim of research was to study the system response time characteristics and to assess practical usability of such approach in applications with hard real-time requirements.
Model-free resource management of cloud-based applications using reinforcement learning

The digital system of the future will face the growing challenge of controlling the system behavior in complex dynamically evolving environments. In this paper, we examine the applicability of a new management paradigm based on Reinforcement Learning approach, where no preliminary specification of the system model is required. In contrast, the learning agent identifies the most adequate control policies in live interaction with a partially observed system and provides it with autonomous management capabilities. We present the results of experimentation with Cloud- based applications and discuss the technical challenges that need to be addressed in this field.
Foodie Moodie: A crowdsourcing platform for interrelating food with mood

The present paper provides researchers with data to enhance understanding the interrelation between food and mood in their search for a relevant scientific evidence. Foodie Moodie is a serious mobile game that gathers data from players reflecting the types of food they eat when they have a certain mood. Moreover, the game provides guidelines for future and interested players offering them food lists commensurate with certain moods. This project was introduced not only to bridge the gap in data count but also help players to keep track of what they eat and understand how it affects their brain, consequently affecting their mood.
Hybrid posicast controller for a DC-DC buck converter

A new Posicast compensated hybrid controller for the DC-DC Buck converter is investigated. Posicast is a feedforward compensator, which eliminates the overshoot in the step response of a lightly damped system. However, the traditional method is sensitive to variations in natural frequency. The new method described here reduces this undesirable sensitivity by using Posicast within the feedback loop. Design of the Posicast function is independent of computational delay. The new controller results in a lower noise in the control signal, when compared to a conventional PID controller.
A high-efficiency radio frequency rectifier-booster regulator for ambient WLAN energy harvesting applications

In this paper, a novel high-efficiency rectifier-booster regulator operating in radio frequency (RF) is firstly proposed. Then an entire WLAN energy harvesting system is demonstrated. A flower-shaped broadband dual-polarized cross dipole rectenna with matching network is employed to harvest electromagnetic energy from a WiFi router. A novel rectifier-booster regulator (RBR) is proposed to rectify the AC energy to DC and boost the high output voltage. It evolves from a Grein-acher rectifier and two Dickson charge pump to form a full wave rectifier. The measurement results show that the RBR can achieve up to ×3.4 voltage boosting with 85% voltage conversion efficiency (VCE) and provide over 1 V output voltage within a distance of 50 cm between a power amplifier (PA) with 20 dBm transmitting power and the rectenna. Maximum energy of 245 μW is harvested by the entire system. The good performance shows its wide practicality for Internet-of-Thing (IoT) applications.
Data-Driven Scratch Generation for Rigid-Body Models

The procedural scratch generation process for rigid-body models automates the process of locating and painting scratches on a texture map. A script computes points where a scratch is most likely to occur at each frame of an animation sequence based on whether the distance between two objects lies within a threshold. These points are then used to create a map of the scratch pattern to guide the blending of scratches onto the image. The tool may be useful to expedite the animated film production pipeline as well as predict areas of wear on machines before they are manufactured.
Evolution of Excitation–Inhibition Ratio in Cortical Cultures Exposed to Hypoxia

In the core of a brain infarct, neuronal death occurs within minutes after loss of perfusion. In the penumbra, a surrounding area with some residual perfusion, neurons initially remain structurally intact, but hypoxia-induced synaptic failure impedes neuronal activity. Penumbral activity may recover or further deteriorate, reflecting cell death. Mechanisms leading to either outcome remain ill-understood, but may involve changes in the excitation to inhibition (E/I) ratio. The E/I ratio is determined by structural (relative densities of excitatory and inhibitory synapses) and functional factors (synaptic strengths). Clinical studies demonstrated excitability alterations in regions surrounding the infarct core. These may be related to structural E/I changes, but the effects of hypoxia /ischemia on structural connectivity have not yet been investigated, and the role of structural connectivity changes in excitability alterations remains unclear. We investigated the evolution of the structural E/I ratio and associated network excitability in cortical cultures exposed to severe hypoxia of varying duration. 6–12 h of hypoxia reduced the total synaptic density. In particular, the inhibitory synaptic density dropped significantly, resulting in an elevated E/I ratio. Initially, this does not lead to increased excitability due to hypoxia-induced synaptic failure. Increased excitability becomes apparent upon reoxygenation after 6 or 12 h, but not after 24 h. After 24 h of hypoxia, structural patterns of vesicular glutamate stainings change. This possibly reflects disassembly of excitatory synapses, and may account for the irreversible reduction of activity and stimulus responses seen after 24 h.
Determination of Friendship Intensity between Online Social Network Users Based on Their Interaction

Online social networks (OSN) are one of the most popular forms of modern communication and among the best known is Facebook. Information about the connection between users on the OSN is often very scarce. It's only known if users are connected, while the intensity of the connection is unknown. The aim of the research described was to determine and quantify friendship intensity between OSN users based on analysis of their interaction. We built a mathematical model, which uses: supervised machine learning algorithm Random Forest, experimentally determined importance of communication parameters and coefficients for every interaction parameter based on answers of research conducted through a survey. Taking user opinion into consideration while designing a model for calculation of friendship intensity is a novel approach in opposition to previous researches from literature. Accuracy of the proposed model was verified on the example of determining a better friend in the offered pair.
Boosting Ride Sharing With Alternative Destinations

People living in highly populated cities increasingly experience decreased quality of life due to pollution and traffic congestion. With the objective of reducing the number of circulating vehicles, we investigate a novel approach to boost ride-sharing opportunities based on the knowledge of the human activities behind individual mobility demands. We observe that in many cases the activity motivating the use of a private car (e.g., going to a shopping mall) can be performed in many different places. Therefore, when there is the possibility of sharing a ride, people having a pro-environment behavior or interested in saving money can accept to fulfill their needs at an alternative destination. We thus propose activity-based ride matching (ABRM), an algorithm aimed at matching ride requests with ride offers, possibly reaching alternative destinations where the intended activity can be performed. By analyzing two large mobility datasets extracted from a popular social network, we show that our approach could largely impact urban mobility by resulting in an increase up to 54.69% of ride-sharing opportunities with respect to a traditional destination-oriented approach. Due to the high number of ride possibilities found by ABRM, we introduce and assess a subsequent ranking step to provide the user with the top-k most relevant rides only. We discuss how ABRM parameters affect the fraction of car rides that can be saved and how the ranking function can be tuned to enforce pro-environment behaviors.
S-EMG Signal Compression in One-Dimensional and Two-Dimensional Approaches

This paper presents algorithms designed for one-dimensional (1-D) and 2-D surface electromyographic (S-EMG) signal compression. The 1-D approach is a wavelet transform based encoder applied to isometric and dynamic S-EMG signals. An adaptive estimation of the spectral shape is used to carry out dynamic bit allocation for vector quantization of transformed coefficients. Thus, an entropy coding is applied to minimize redundancy in quantized coefficient vector and to pack the data. In the 2-D approach algorithm, the isometric or dynamic S-EMG signal is properly segmented and arranged to build a 2-D representation. The high efficient video codec is used to encode the signal, using 16-bit-depth precision, all possible coding/prediction unit sizes, and all intra-coding modes. The encoders are evaluated with objective metrics, and a real signal data bank is used. Furthermore, performance comparisons are also shown in this paper, where the proposed methods have outperformed other efficient encoders reported in the literature.
An all-digital physical and MAC layer architectures for a reconfigurable Bluetooth transmitter

Bluetooth (BT) is a standard that is massively used worldwide and continuously evolving. In addition, the upcoming increasing of internet of things considered BT as one of the main protocols that will support inter-devices connectivity. Hence, it is necessary to perform research on reconfigurable architectures that allow the rapid changes between new versions of this standard. In this paper, it is presented an architecture composed of a reconfigurable transmitter and a multi-version MAC layer of the BT standard. Using the reconfigurable CPM transmitter, the proposed architecture is compliant with nonlinear modulations of the physical layer of BT (up to V.5.0). In addition, the proposed MAC layer supports 1.2 and low energy versions of BT. Synthesis results on FPGA shows that this architecture uses 3% of a Cyclone IV, and implementation results in Synopsys CMOS SAED32nm process use an area of 94,874 um2 and power consumption of 2.48 mW.