Miracle-dz/UniFAR-FTUs huggingface dataset:
Support Vector Machine-Based Aqueduct Safety Assessment

According to water power, structure and foundation conditions of aqueduct, it has established aqueduct safety assessment indicator system and standards. Based on statistical learning theory, support vector machine shifts the learning problems into a convex quadratic programming problem with structural risk minimization criterion, which could get the global optimal solution, and be applicable to solving the small sample, nonlinearity classification and regression problems. In order to evaluate the safety condition of aqueduct, it has established the aqueduct safety assessment model which is based on support vector machine. It has divided safety standards into normal, basically normal, abnormal and dangerous. According to the aqueduct safety assessment standards and respective evaluation level, the sample set is generated randomly, which is used to build a pair of classifier with many support vectors. The results show that the method is feasible, and it has a good application prospect in irrigation district canal building safety assessment.
A Generalisable Component-Level ESD Failure Characterisation for TLP Measurements

Designing an electronic system to be robust against electrostatic discharges remains challenging. Components have to be characterised with respect to system-relevant soft-failures in addition to the commonly investigated hard-failures. A method to provide this information is proposed in this paper. The method is based on transmission line pulsing measurements with freely definable failure detection and processing routines, and is able to simultaneously check several failure criteria. This allows to adapt the measurements depending on the requirements of a random component and its surrounding system.
Spark Parameter Monitoring Feedback System for Preparation of Nanosilver Colloid in EDM

This study developed a system monitoring the electric discharge machine's (EDM) discharge energy and success rate to replace conventional oscilloscope observation. By using logic circuit, the signals are transmitted to the PC monitoring platform in order to display the discharge success times, discharge success rate, and electrode's consumption energy. The advantage of the proposed system is the capability to observe real-time discharges and record the experimental conditions, as well as optimize the discharge parameter settings. The experimental results suggest that, in the preparation of nanosilver colloid, the cost-performance of Ton–Toff at 10–100 µs is the optimal setting. The monitoring system also can take advantage of the discharge success rate to control the energy consumption of the electrode to obtain the standardization of products. The results suggest that, while discharge success rate, electrode's weight loss and wavelength of the absorption peak are considerably accurate, but concentration accuracy is relatively poor. The discharge success rate monitoring system is an innovative method that can help to realize electric discharge processing, optimize product quality, and it may be a powerful processing tool in the future.
Accelerating 3D scene analysis for autonomous driving on embedded AI computing platforms

The design of 3D object detection schemes that use point clouds as input in automotive applications has gained a lot of interest recently. Those schemes capitalize on Deep Neural Networks (DNNs) that have demonstrated impressive results in analyzing complex scenes. The proposed schemes are generally designed to improve the achieved performance, leading however to high performing approaches with high computational complexity. To mitigate this high complexity and to facilitate their deployment on edge devices, model compression and acceleration techniques can be utilized. In this paper, we propose compressed versions of two well-known 3D object detectors, namely, PointPillars and PV-RCNN, utilizing dictionary learning-based weight-sharing techniques. It is demonstrated that significant acceleration gains can be achieved with acceptable average precision loss when evaluated on the KITTI 3D object detection benchmark. These findings constitute a concrete step towards the deployment of high-performance networks in edge devices of limited resources, such as NVIDIA’s Jetson TX2.
A Tentative Study of the Presentation of Culture in Present College English Textbooks

Cultivating students’ intercultural communication competence( ICC) is the focus of college English teaching. As the textbook is seen as the major vehicle to transmit culture, importance has been attached to the presentation of culture in textbooks, which looms large in students’ ICC. Based on two surveys , the author finds that positive aspects of foreign culture and native culture are presented in textbooks, however, foreign culture is so much in proportion to native culture that ultimately results in students’ failure in ICC. Teachers shoul balance two cultures in teaching, and launch a dialogue between them on the basis of the choice , intergration and balanced utilization of the two cultures. With the two-culture-dialogue, students can promote their ICC effectively.
Dual-Pump Hydraulic Hybrid Excavator with Combined Common Pressure Rail and Valve-Controlled System

To solve the low efficiency problem of hydraulic excavator, one type of Dual-Pump hydraulic architecture with combined Common Pressure Rail (CPR) and traditional valve controlled system is presented. Firstly, we analyze the energy consumption of excavator during one cycle to know the energy distribution among each actuator. Then, the Dual-Pump system is explained to design an easy to modify, cost efficient hydraulic hybrid excavator. Moreover, we focus on the boom system and construct the model. Finally, a simulation is created and the results illustrate that the proposed system can satisfy the design requirement.
Application of Breather Solutions for the Investigation of Wave/Structure Interaction in High Steep Waves

During the design process of floating structures, different specifications have to be aligned such as the range of application, the warranty of economical efficiency as well as the reliability and are an inevitable integral part of the evaluation process during the design stage. The validation of the performance by means of model tests in terms of sea state behavior and the associated local and global structural loads are an important milestone within this process. Therefore it is necessary to determine an adequate test procedure which covers all essential areas of interest. Thereby one field of interest are limiting criteria of the design such as maximum local and global loads as well as maximum accelerations due to the impact of extraordinarily high waves, at which the floating structure has to survive. Different alternatives are available to conduct model tests in high, steep waves — transient wave packages, regular waves, irregular waves with random phases or more sophisticated deterministic tailored irregular wave sequences such as reproductions from numerical simulations and real-world measurements.This paper introduces a new approach for the systematic investigation of wave/structure interaction in high, steep waves. Exact solutions of the nonlinear Schrodinger equation — the so called breather solutions — are implemented for the generation of extraordinarily high waves. Three types of breather solutions are investigated in the seakeeping basin and to cover the full range of interest, each solution has been used to generate freak waves at certain frequencies.To evaluate the applicability of breather solutions for model tests two types of ships — a LNG Carrier and a Chemical Tanker — are investigated in the seakeeping basin. The ships are segmented and connected with strain gauges to detect the vertical wave bending moment. Furthermore, green water probes are installed on deck to evaluate the local impact on the bow of the freak waves. The obtained results are compared to investigations in regular waves with certain frequency and steepness as well as in real-world freak wave reproductions.Copyright © 2012 by ASME
An asymmetric memory cell using a C-TFT for single-bit-line SRAM's

This paper proposes a compact single-bit line SRAM memory cell, which we call an asymmetric memory cell (AMC), using a complementary thin-film transistor (C-TFT). A C-TFT is composed of a top-gate n-channel TFT and a bottom-gate p-channel TFT. The proposed cell size can be reduced to 88% as compared with the conventional one using 0.4-/spl mu/m design rules. Stable read and write operations under low-voltage can be realized by using a C-TFT.
Microwave exposure and safety associated with personal wireless telecommunication base stations

There are considerable public concerns regarding the biological effects and safety of microwave exposure from wireless base stations. There have been repeated calls for measures and tools that would reduce the exposure to microwave radiation from cellular mobile telephone operations. The radiated power from a base station antenna can vary from less than 1 to as high as 500 W per channel (or transmitter), depending on the location and type of the antenna used for a cellular communication system. The level of public exposure to microwave energy from any base station varies depending on antenna type, location, and distance from the base station. The microwave exposure a person receives from a base station thus depends on both the distances from the antenna, and the angle below the direction of the main beam.
Comparative analysis of model-free and model-based HVAC control for residential demand response

In this paper, we present a comparative analysis of model-free reinforcement learning (RL) and model predictive control (MPC) approaches for intelligent control of heating, ventilation, and air-conditioning (HVAC). Deep-Q-network (DQN) is used as a candidate for model-free RL algorithm. The two control strategies were developed for residential demand-response (DR) HVAC system. We considered MPC as our golden standard to compare DQN's performance. The question we tried to answer through this work was, What % of MPC's performance can be achieved by model-free RL approach for intelligent HVAC control? Based on our test result, RL achieved an average of ≈ 62% daily cost saving of MPC. Considering the pure optimization and model-based nature of MPC methods, the RL showed very promising performance. We believe that the interpretations derived from this comparative analysis provide useful insights to choose from various DR approaches and further enhance the performance of the RL-based methods for building energy managements.
Understanding and Synergy: A Single Concept at Different Levels of Analysis?

Biological systems differ from the inanimate world in their behaviors ranging from simple movements to coordinated purposeful actions by large groups of muscles, to perception of the world based on signals of different modalities, to cognitive acts, and to the role of self-imposed constraints such as laws of ethics. Respectively, depending on the behavior of interest, studies of biological objects based on laws of nature (physics) have to deal with different salient sets of variables and parameters. Understanding is a high-level concept, and its analysis has been linked to other high-level concepts such as “mental model” and “meaning”. Attempts to analyze understanding based on laws of nature are an example of the top-down approach. Studies of the neural control of movements represent an opposite, bottom-up approach, which starts at the interface with classical physics of the inanimate world and operates with traditional concepts such as forces, coordinates, etc. There are common features shared by the two approaches. In particular, both assume organizations of large groups of elements into task-specific groups, which can be described with only a handful of salient variables. Both assume optimality criteria that allow the emergence of families of solutions to typical tasks. Both assume predictive processes reflected in anticipatory adjustments to actions (motor and non-motor). Both recognize the importance of generating dynamically stable solutions. The recent progress in studies of the neural control of movements has led to a theory of hierarchical control with spatial referent coordinates for the effectors. This theory, in combination with the uncontrolled manifold hypothesis, allows quantifying the stability of actions with respect to salient variables. This approach has been used in the analysis of motor learning, changes in movements with typical and atypical development and with aging, and impaired actions by patients with various neurological disorders. It has been developed to address issues of kinesthetic perception. There seems to be hope that the two counter-directional approaches will meet and result in a single theoretical scheme encompassing biological phenomena from figuring out the best next move in a chess position to activating motor units appropriate for implementing that move on the chessboard.
Simultaneous channel and OSNR monitoring using a polarization-selective modulator and an LED

A compact module including a polarization-selective electrooptic modulator and a light-emitting diode (LED) sensor is utilized for optical signal-to-noise-ratio (OSNR) monitoring and channel recognition. The modulator acts as a polarizer and provides signal dithering to improve the detection sensitivity, while the LED is used as a channel sensor. The channel sensor can monitor a wide wavelength range that is rapidly adjustable and can have much relaxed tolerance on temperature control. The combination of a polarization controller/rotator and the polarized modulator can accurately measure the OSNR between 5 and 35 dB with an error less than 0.5 dB.
Rural Variable Speed Limit System for Southeast Wyoming

Variable speed limit (VSL) is a type of intelligent transportation system that has shown promise for improving safety on roadways that are subject to adverse weather conditions. A new rural VSL system was installed by the Wyoming Department of Transportation along I-80 in the southeastern part of the state. Statistics on the use of the system during its initial months of implementation are presented along with analyses of the impact on observed speeds of measured weather variables and speed limits on the VSL system. Preliminary results indicate that drivers reduce their speeds by 0.47 to 0.75 mph for every mile per hour in posted speed reduction. The research lays the foundation for a decision support system that will be used in future operations of the VSL system.
EFFECTS OF INSTRUMENT ASSISTED SOFT TISSUE MOBILIZATION TECHNIQUES ON POST-OPERATIVE KNEE PAIN AND STIFFNESS: A CASE REPORT

34-year-old male visited to MGM Physiotherapy Rehabilitation and Fitness Centre, Aurangabad. He presented with the complaint of pain and difficulty in bending left knee. In this study, The Nord Blade 2.0 was used to perform instrument assisted soft tissue mobilisation technique (IASTM) on the quadriceps, hamstring, and calf muscles. This technique was given 3 times in a week for 1 week of protocol. As a result, study concludes that application of IASTM was more beneficial and effective in pain reduction and increasing knee range of motion.
Neuropeptide Y Variation Is Associated With Altered Static and Dynamic Functional Connectivity of the Salience Network

Neuropeptide Y (NPY) is a neurotransmitter that has been implicated in the development of anxiety and mood disorders. Low levels of NPY have been associated with risk for these disorders, and high levels with resilience. Anxiety and depression are associated with altered intrinsic functional connectivity of brain networks, but the effect of NPY on functional connectivity is not known. Here, we test the hypothesis that individual differences in NPY expression affect resting functional connectivity of the default mode and salience networks. We evaluated static connectivity using graph theoretical techniques and dynamic connectivity with Leading Eigenvector Dynamics Analysis (LEiDA). To increase our power of detecting NPY effects, we genotyped 221 individuals and identified 29 healthy subjects at the extremes of genetically predicted NPY expression (12 high, 17 low). Static connectivity analysis revealed that lower levels of NPY were associated with shorter path lengths, higher global efficiency, higher clustering, higher small-worldness, and average higher node strength within the salience network, whereas subjects with high NPY expression displayed higher modularity and node eccentricity within the salience network. Dynamic connectivity analysis showed that the salience network of low-NPY subjects spent more time in a highly coordinated state relative to high-NPY subjects, and the salience network of high-NPY subjects switched between states more frequently. No group differences were found for static or dynamic connectivity of the default mode network. These findings suggest that genetically driven individual differences in NPY expression influence risk of mood and anxiety disorders by altering the intrinsic functional connectivity of the salience network.
Whole-Genome Selective Scans Detect Genes Associated With Important Phenotypic Traits in Sheep (Ovis aries)

Sheep (Ovis aries) is one of the important livestock with diverse phenotypic traits. However, little is known about the molecular mechanism of diverse phenotypic traits in domestic sheep. Using the genome-wide high-density SNP data (600K) in 253 samples from 13 populations, we conducted the tests of selective sweeps (i.e., pairwise F ST and XP-CLR) associated with several important phenotypic traits (e.g., tail types, horn morphology, prolificacy, coat pigmentation, ear size, milk production, meat production, body size and wool fineness). We identified strong selective signatures in previously reported (e.g., T, RXFP2, BMPR1B, TYRP1, MSRB3, TF, CEBPA, GPR21 and HOXC8) and novel genes associated with the traits, such as CERS6, BTG1, RYR3, SLC6A4, NNAT and OGT for fat deposition in the tails, FOXO4 for fertility, PTCH1 and EMX2 for ear size, and RMI1 and SCD5 for body size. Further gene annotation analysis showed that these genes were identified to be the most probable genes accounting for the diverse phenotypic traits. Our results provide novel insights into the genetic mechanisms underlying the traits and also new genetic markers for genetic improvement in sheep and other livestock.
Association of GAK rs1564282 With Susceptibility to Parkinson’s Disease in Chinese Populations

The susceptibility of the GAK rs1564282 variant in Parkinson’s disease (PD) in Europeans was identified using a series of published genome-wide association studies. Recently, some studies focused on the association between rs1564282 and PD risk in Chinese populations but with inconsistent results. Thus, we conducted an updated meta-analysis with a total of 7,881 samples (4,055 PD cases and 3,826 controls) from eligible studies. After excluding significant heterogeneity, we showed that the rs1564282 variant was significantly associated with PD in Chinese populations (p = 1.00E-04, odds ratio = 1.28 and 95% confidence interval = 1.16–1.42). The sensitivity analysis showed that the association between rs1564282 and PD was not greatly influenced, and there was no significant publication bias among the included studies. Consequently, this meta-analysis indicates that the GAK rs1564282 variant is significantly associated with susceptibility to PD in Chinese populations.
Chromosome-Scale Reference Genome of Amphicarpaea edgeworthii: A New Resource for Amphicarpic Plants Research and Complex Flowering Pattern

Amphicarpaea edgeworthii, an annual twining herb, is a widely distributed species and an attractive model for studying complex flowering types and evolutionary mechanisms of species. Herein, we have generated a high-quality assembly of A. edgeworthii by using a combination of PacBio, 10× Genomics libraries, and Hi-C mapping technologies. The final 11 chromosome-level scaffolds covered 90.61% of the estimated genome (343.78Mb), which is a chromosome-scale assembled genome of an amphicarpic plant. Subsequently, we characterized the genetic diversity and population structure of A. edgeworthii species by resequencing individuals collected from their natural area of distribution. Using transcriptome profiling, we observed that specific phenotypes are regulated by a complex network of light, hormones, and MADS-box gene families. These data are beneficial for the discovery of genes that control major agronomic traits and spur genetic improvement of and functional genetic studies in legumes, as well as supply comparative genetic resources for other amphicarpic plants.
Operational Detection of Sun Glints in DSCOVR EPIC Images

Satellite images often feature sun glints caused by the specular reflection of sunlight from water surfaces or from horizontally oriented ice crystals occurring in clouds. Such glints can prevent accurate retrievals of atmospheric and surface properties using existing algorithms, but the glints can also be used to infer more about the glint-causing objects—for example about the microphysical properties and radiative effects of ice clouds. This paper introduces the recently released operational glint product of the Earth Polychromatic Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) spacecraft. Most importantly, the paper describes the algorithm used for generating the key component of the new product: a glint mask indicating the presence of sun glint caused by the specular reflection of sunlight from ice clouds and smooth water surfaces. After describing the glint detection algorithm and glint product, the paper shows some examples of the detected glints and discusses some basic statistics of the glint population in a yearlong dataset of EPIC images. These statistics provide insights into the performance of glint detection and point toward possibilities for using the glint product to gain scientific insights about ice clouds and water surfaces.
Association of Glycosylated Hemoglobin A1c Level With Sudden Sensorineural Hearing Loss: A Prospective Study

Glycosylated hemoglobin A1c (HbA1c) level has strong relevance to microvascular disorders, which are also thought to be the current main aspect of sudden sensorineural hearing loss (SSNHL), so we aim to elucidate the association of the HbA1c level with the severity, types, and prognosis of SSNHL. In this study, comparative analyses based on propensity score matching of the severity, types, and prognosis of SSNHL with the HbA1c level in 116 patients diagnosed as SSNHL were conducted, where they were divided into diabetes mellitus (DM) group and non-DM group. We finally found that, among patients with SSNHL, diabetic patients had a higher HbA1c level, more severe hearing loss, and poorer prognosis than non-diabetic patients. The HbA1c level was found to be significantly correlated with the severity and types of SSNHL, while no strong relevance was found between the higher HbA1c level and the poorer prognosis of SSNHL.