Miracle-dz/UniFAR-FTUs huggingface dataset:
Knockout of the KH-Type Splicing Regulatory Protein Drives Glomerulonephritis in MRL-Faslpr Mice

KH-type splicing regulatory protein (KSRP) is an RNA-binding protein that promotes mRNA decay and thereby negatively regulates cytokine expression at the post-transcriptional level. Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by dysregulated cytokine expression causing multiple organ manifestations; MRL-Faslpr mice are an established mouse model to study lupus disease pathogenesis. To investigate the impact of KSRP on lupus disease progression, we generated KSRP-deficient MRL-Faslpr mice (MRL-Faslpr/KSRP−/− mice). In line with the predicted role of KSRP as a negative regulator of cytokine expression, lupus nephritis was augmented in MRL-Faslpr/KSRP−/− mice. Increased infiltration of immune cells, especially of IFN-γ producing T cells and macrophages, driven by enhanced expression of T cell-attracting chemokines and adhesion molecules, seems to be responsible for worsened kidney morphology. Reduced expression of the anti-inflammatory interleukin-1 receptor antagonist may be another reason for severe inflammation. The increase of FoxP3+ T cells detected in the kidney seems unable to dampen the massive kidney inflammation. Interestingly, lymphadenopathy was reduced in MRL-Faslpr/KSRP−/− mice. Altogether, KSRP appears to have a complex role in immune regulation; however, it is clearly able to ameliorate lupus nephritis.
A self adaptive method for solving a class of bilevel variational inequalities with split variational inequality and composed fixed point problem constraints in Hilbert spaces

In this work, we propose a new inertial method for solving strongly monotone variational inequality problems over the solution set of a split variational inequality and composed fixed point problem in real Hilbert spaces. Our method uses stepsizes that are generated at each iteration by some simple computations, which allows it to be easily implemented without the prior knowledge of the operator norm as well as the Lipschitz constant of the operator. In addition, we prove that the proposed method converges strongly to a minimum-norm solution of the problem without using the conventional two cases approach. Furthermore, we present some numerical experiments to show the efficiency and applicability of our method in comparison with other methods in the literature. The results obtained in this paper extend, generalize and improve results in this direction.
Nuclear Receptors in Myocardial and Cerebral Ischemia—Mechanisms of Action and Therapeutic Strategies

Nearly 18 million people died from cardiovascular diseases in 2019, of these 85% were due to heart attack and stroke. The available therapies although efficacious, have narrow therapeutic window and long list of contraindications. Therefore, there is still an urgent need to find novel molecular targets that could protect the brain and heart against ischemia without evoking major side effects. Nuclear receptors are one of the promising targets for anti-ischemic drugs. Modulation of estrogen receptors (ERs) and peroxisome proliferator-activated receptors (PPARs) by their ligands is known to exert neuro-, and cardioprotective effects through anti-apoptotic, anti-inflammatory or anti-oxidant action. Recently, it has been shown that the expression of aryl hydrocarbon receptor (AhR) is strongly increased after brain or heart ischemia and evokes an activation of apoptosis or inflammation in injury site. We hypothesize that activation of ERs and PPARs and inhibition of AhR signaling pathways could be a promising strategy to protect the heart and the brain against ischemia. In this Review, we will discuss currently available knowledge on the mechanisms of action of ERs, PPARs and AhR in experimental models of stroke and myocardial infarction and future perspectives to use them as novel targets in cardiovascular diseases.
Cognición imitativa para un robot mediante una comunidad de replicadores neuro-meméticos

Como herramienta de inteligencia artificial, la computacion memetica emplea modelos de ciertos elementos cerebrales, llamados neuro-memes, hipoteticamente implicados en la simbolizacion, diseminacion y evolucion de las caracteristicas culturales en las sociedades humanas. Con la finalidad de simular el gran potencial evolutivo de los neuro-memes, recientemente se presento el Perceptron auto-supervisado (SSP) como replicador neuro-memetico artificial, cuya capacidad de aprendizaje imitativo fue verificada al controlar un robot muy sencillo. Con respecto a dicha capacidad se observo una deficiencia aprehensiva cuando el imitador solamente observa la conducta libremente evidenciada por el instructor. Al atender dicha deficiencia se encontro la incapacidad de imitar una conducta con ciertas caracteristicas. Considerando que el SSP es un modelo orientado al desarrollo de sistemas colectivos, en este articulo se presenta un sistema multi-agente compuesto por varios SSP, con el cual se solucionaron dichas dificultades encontradas en un SSP individual.
Direct, fast, and accurate measurement of V/sub T/ and K of an MOS transistor using a V/sub T/-sift circuit

Based on a V/sub T/-sift circuit, a new characterization technique is presented with which the value of both K, the transconductance constant, and V/sub T/, the device threshold voltage, of an MOS transistor can be measured directly, obtained from the drain current of the device to be tested and the voltage difference between the output and input nodes of the V/sub T/-sift circuit, respectively. The proposed method has been verified experimentally and compared advantageously with the commonly used linear regression technique in transistor characterization and wafer manufacturing. An additional application field of the V/sub T/-sift circuit is temperature compensation of analog circuits. >
Tropism and tectonics - fundamental principles of space formation

Abstract The objective of this study is to contribute to the understanding of what characterizes substantive theory in landscape architecture. The discipline is considered to be evolving toward a unique mindset, significant to the sustainable development of human settlements. The aim of this study is to highlight two fundamental, and essentially different, principles of space formation: tropism and tectonics. A philosophical approach is used to discuss different ways of thinking, and approaching, landscape change. The point of departure is to distinguish between the use of terms related to dynamic progression and those related to static conditions. Tropism describes a dynamic principle of the growth of living organisms, while tectonics describes the static principle of erecting a framework, one for a building or a bridge. Tropism is vital to the management of living landscapes and their design through maintenance. The conclusion is that both tropism and tectonics require attention in order to further develop the theoretical framework.
Dynamic Behavioral Data Collection Using an Instrumented Vehicle

A significant problem that has become increasingly apparent in the development of models of driver behavior over the last few years is the absence of reliable data with which simulated processes, such as car following, may be compared. Obtaining such data, and the associated increase in model validity that this would allow, is clearly becoming of greater importance since a reliable baseline is required against which improvements in traffic flow and safety produced by many advanced transport telematics systems can be judged. One source of such data is an instrumented vehicle; a vehicle equipped with relative distance- and speed-measuring sensors that may be deployed in the traffic stream to collect data that are realistic, accurate, and dynamic. The opportunities for data collection afforded by instrumented vehicles are examined, in particular, the construction and testing of a new facility fitted with an optical speedometer, a radar rangefinder (capable of measuring the distance to, and relative speed of, the next vehicle in the traffic stream), and forward- and rear-looking video camera. Examples are given of the use of the vehicle in several current research projects, the operational strategies for which will be presented and discussed along with output. These include experiments on close-following, lane-changing, and the perception of relative speed. In conclusion, future areas of research and development are examined.
MRI CNS Atrophy Pattern and the Etiologies of Progressive Ataxias

MRI shows the three archetypal patterns of CNS volume loss underlying progressive ataxias in vivo, namely spinal atrophy (SA), cortical cerebellar atrophy (CCA) and olivopontocerebellar atrophy (OPCA). The MRI-based CNS atrophy pattern was reviewed in 128 progressive ataxias. A CNS atrophy pattern was identified in 91 conditions: SA in Friedreich’s ataxia, CCA in 5 acquired and 72 (24 dominant, 47 recessive,1 X-linked) inherited ataxias, OPCA in Multi-System Atrophy and 12 (9 dominant, 2 recessive,1 X-linked) inherited ataxias. The MRI-based CNS atrophy pattern may be useful for genetic assessment, identification of shared cellular targets, repurposing therapies or the enlargement of drug indications in progressive ataxias.
Measurement and analysis of temporal fading due to moving vegetation

In order to study the wind speed dependency of radiowave propagation in vegetation environments, measurements have been performed on various types of deciduous trees at 0.9 GHz (co-polarised) and 1.8 GHz (co- and cross-polarised). Strong wind speed dependency of the RF signal was found as wind speed increased from low to medium speed. However the signal behaviour did not vary significantly from medium to high wind speeds. At 0.9 GHz, the fade statistics were not greatly dependent on wind speed. The crosspolarised configuration of the receiver was less affected by vegetation during low wind speed than the co-polarised configuration. Finally, it was concluded that RF propagation transmission through vegetation is strongly dependent on wind speed characteristics, frequency and to an extent on polarisation.
Effect of the Small Punch Test sample geometry on the Liquid Metal Embrittlement of Cu-30 wt% Zn by the eGaIn

Liquid metal embrittlement (LME) is the embrittlement or the modification of the fracture behaviour of a metal or alloy when it undergoes plastic deformation while in contact with a liquid metal or liquid alloy. LME occurrence depends strongly on the properties of the metals involved and on the conditions of the mechanical stresses applied to the solid. The Small Punch Test (SPT) on flat specimens is very sensitive to identify the conditions of LME occurrence. Moreover, there are alternative SPT notched specimen geometries that have the potential to screen solid/liquid couples for sensibility to LME in different conditions. To study the apparition of the LME on an alpha brass with 30 wt% Zn in contact with the eGaIn (Ga-In eutectic), SPT at room temperature were carried out at different displacement rates and using three specimen types: the standard flat geometry and two notched geometries. While the flat specimens did not present LME, the presence of a notch and a high strain rate induced LME on the other specimen geometries. For these last specimens, the eGaIn modifies the SPT load-displacement curves at the crack propagation stage and changes the fracture to a partially ductile fracture followed by a brittle fracture.
A Review on Abstractive Text Summarization Using Deep Learning

The task of creating a summary from a somewhat longer text is known as text summarization. This summary is comprised of a few sentences and would still express the main idea of the text. It has applications in sentiment analysis, document summarization, search engine queries, and business analysis etc. Over time, a lot of research has happened on the topic of abstract text summarization, especially with the emergence of deep learning. Many new Recurrent Neural Network and Convolutional Neural Network models have been proposed by the researchers. The performance of the models based on the Recurrent Neural Network and Convolutional Neural Network has been satisfactory. Models based on the pre-trained Transformer have recently demonstrated state-of-the-art performance in the field of Natural Language Processing in recent research. The amount of work done in the field is quite extensive and challenging to be brought together, this review attempts to do the same.
The Fault Recognition of Motor Based on the Fusion of Neural Network and D-S Evidence Theory

In order to reflect the motor from various aspects and realize the motor system state failure mode automatic identification and accurate diagnosis, neural network combined with the D-S evidence theory to form the motor fault diagnosis system. In data fusion level, fault characteristic is classified; and then the fault feature is extracted by the BP neural network and the local fault of the motor is diagnosed, as a result, the independent evidence is obtained; at last the D-S evidence theory fusion algorithm is used on the evidence to achieve the fault of the motor accurate diagnosis.Broken test proved that the diagnosis system improves the motor of the fault diagnosis of accuracy, and can meet the needs of real-time diagnosis. The diagnostic test proved that the diagnosis system improves the accuracy of motor fault diagnosis, and can satisfy the diagnosis in real-time.
3-D Coordinate Determination from 2-D Automotive Sketches: Part II

In this part, the perspective projection has been obtained if one more planar point is given according to the four planar points discussed in Part I. The precision of this reversing transformation has been investigated. The way to obtain four or five points from automotive sketches has been introduced. It has been implemented into a 23D system, and the results are satisfied.
Measuring dynamic strain of structures using a gold-deposited extrinsic Fabry–Perot interferometer

In this paper, we present a new type of extrinsic Fabry–Perot interferometer (EFPI) for measurement of dynamic strain. Gold was deposited on the second reflecting surface of the optical fibre in this sensor to increase its reflectivity. Thus, we have termed it a gold-deposited extrinsic Fabry–Perot interferometer (G-EFPI). If a gap between two reflecting surfaces increases, the loss of intensity of the light that passes through the gap increases, causing a subsequent decrease in the output intensity of the sensor. Conversely, if the gap decreases, the amount of loss decreases and the output intensity increases. Therefore, it is possible to determine the variation of the gap size by observing the output intensity of the sensor. Finally, the dynamic strain of a composite specimen was measured successfully using the G-EFPI.
Human Sleep Posture Recognition Based on Millimeter-Wave Radar

In this paper, we propose a robust human sleep posture recognition method via multidimensional feature representation and learning based on millimeter-wave (mmw) radar. Firstly, through time-frequency processing of the radar echo signal reflected by the human body, the range spectrum, Doppler spectrum, range-Doppler spectrum, azimuth angle spectrum and elevation angle spectrum of the estimated target are obtained. By setting a fixed frame window length and splicing the above feature spectrums, 5 single-channel 2D radar features are obtained, and combining them in parallel can get a variety of different multi-channel 2D radar feature representations. Finally, a lightweight multi-channel convolutional neural network (CNN) with Inception-Residual module (IRM) is designed to learn and classify multidimensional features. Extensive experiments were carried out using the developed mmw radar system, and a large amount of data was obtained to train and test the classifier. The results show that the proposed sleep posture recognition method can effectively distinguish different sleep postures and achieve better robust performance and generalization compared to other methods.
Vibration and Noise Analysis for a Motor of Pure Electric Vehicle

To control the pure electric vehicle motors vibration and noise, the dynamic characteristics of the motor are analyzed. Dynamic characteristic include the natural frequency and response characteristics of different parts of the motors structural member. This paper uses three-dimensional software Pro/E modeling of the motor: By making appropriate assumptions and equivalent treatment of the motors stator, rotor core and coil winding, establish the finite element simulation model of the various components . Using the finite element analysis software Workbench analyzes the windings and motor model modal analysis, to get natural frequency of each mode. To make a modal analysis test, we can use hammering method done on the motor. By using real-time signal analyzer AWA6291 make spectral analysis of the motor online, comprehensive comparative analysis of the results and used to guide motor design.
Reliability Analysis Based on Fault Tree of Failure of Boiler Drum

Drum is the core pressure equipment of Natural Circulation Boiler. The harsh working conditions lead drum to be prone to failure in power station boiler system. This article presents a systematic analysis of factors which may cause the failure of the drum and builds the fault tree with the drum failure as the top event. Through calculating each order of minimum cut sets and importance degree of each basic event probability to determine the major influent factors for the failure of drum, this article puts forward the corresponding solutions and brings reference value to safe operation and maintenance of boiler drum.
Evaluation of the Huawei UDS cloud storage system for CERN specific data

Cloud storage is an emerging architecture aiming to provide increased scalability and access performance, compared to more traditional solutions. CERN is evaluating this promise using Huawei UDS and OpenStack SWIFT storage deployments, focusing on the needs of high-energy physics. Both deployed setups implement S3, one of the protocols that are emerging as a standard in the cloud storage market. A set of client machines is used to generate I/O load patterns to evaluate the storage system performance. The presented read and write test results indicate scalability both in metadata and data perspectives. Futher the Huawei UDS cloud storage is shown to be able to recover from a major failure of losing 16 disks. Both cloud storages are finally demonstrated to function as back-end storage systems to a filesystem, which is used to deliver high energy physics software.
Molecular Network and Crosstalk Effects for Network Reliability

We propose the use of molecular networks for drug delivery and diagnosis applications. Three modules of molecular networks such as bus, star,and ring networks are designed and manipulated based on a micro and nanoring resonator system. The transportation of the trapping molecule by light in the networks is described, the theoretical background is reviewed. However, the problems of large microscopic volumes and networks may be caused problems, in which the searching for new guide pipe and medium for instance, nanotube and specific medium and crosstalk effects will be the issue of investigations. Moreover, the qualities of network reliability are measurement in the form of signal transmission, i.e. signal to noise ratio (SNR) and crosstalk effects are discussed in details.
Kramers–Kronig Relation for Attenuated Total Reflection from a Metal–Dielectric Interface Where Surface Plasmon Polaritons Are Excited

The applicability of the Kramers–Kronig relation for attenuated total reflection (ATR) from a metal–dielectric interface that can excite surface plasmon polaritons (SPP) is theoretically investigated. The plasmon-induced attenuation of reflected light can be taken as the resonant absorption of light through a virtual absorptive medium. The optical phase shift of light reflected from the SPP-generating interface is calculated using the KK relation, for which the spectral dependence of ATR is used at around the plasmonic resonance. The KK relation-calculated phase shift shows good agreement with that directly obtained from the reflection coefficient, calculated by a field transfer matrix formula at around the resonance. This indicates that physical causality also produces the spectral dependence of the phase of the leakage field radiated by surface plasmons that would interfere with the reflected part of light incident to the interface. This is analogous with optical dispersion in an absorptive medium where the phase of the secondary field induced by a medium polarization, which interferes with a polarization-stimulating incident field, has a spectral dependence that stems from physical causality.
Influence of High Temperature Processing on the Substructure of Laser Shock Processed Titanium Alloy

The paper aims to study the influence of high temperature processing on the substructure of laser shock processed titanium alloy. The titanium alloy specimens were first treated by laser shock processing (LSP), then treated at 700°C for three hours and air cooled to the room temperature to investigate the influence of the high temperature processing. To evaluate such influence, the hardness and substructure on the surface were investigated by micro hardness tester and transmission electron microscope (TEM), respectively. Results show that after three times LSP, the hardness of TC11 alloy was improved by 30.9%. The cause of such an improvement in hardness is that the crystal grains in the surface layer under the shock wave stress were strongly deformed, causing a dynamic recrystallization. The substructure is mainly twin crystals, highly tangled and dense dislocations. After high temperature processing in vacuum, the average hardness is decreased by 12% compared to that of the specimens after LSP. And the substructures are mainly small dislocation, nanocrystalline.
A 45 ps time digitizer with a two-phase clock and dual-edge two-stage interpolation in a field programmable gate array device

We present a time digitizer having 45 ps resolution, integrated in a field programmable gate array (FPGA) device. The time interval measurement is based on the two-stage interpolation method. A dual-edge two-phase interpolator is driven by the on-chip synthesized 250 MHz clock with precise phase adjustment. An improved dual-edge double synchronizer was developed to control the main counter. The nonlinearity of the digitizer's transfer characteristic is identified and utilized by the dedicated hardware code processor for the on-the-fly correction of the output data. Application of presented ideas has resulted in the measurement uncertainty of the digitizer below 70 ps RMS over the time interval ranging from 0 to 1 s. The use of the two-stage interpolation and a fast FIFO memory has allowed us to obtain the maximum measurement rate of five million measurements per second.