Miracle-dz/UniFAR-FTUs huggingface dataset:
Commercial drugs containing flavonoids are active in mice with malaria and in vitro against chloroquine-resistant Plasmodium falciparum

BACKGROUND The main strategy to control human malaria still relies on specific drug treatment, limited now by Plasmodium falciparum-resistant parasites, including that against artemisinin derivatives. Despite the large number of active compounds described in the literature, few of them reached full development against human malaria. Drug repositioning is a fast and less expensive strategy for antimalarial drug discovery, because these compounds are already approved for human use. OBJECTIVES To identify new antimalarial drugs from compounds commercially available and used for other indications. METHODS Accuvit®, Ginkgo® and Soyfit®, rich in flavonoids, and also the standard flavonoids, hesperidin, quercetin, and genistein were tested against blood cultures of chloroquine-resistant P. falciparum, as well as chloroquine, a reference antimalarial. Inhibition of parasite growth was measured in immunoenzymatic assay with monoclonal anti-P. falciparum antibodies, specific to the histidine-rich protein II. Tests in mice with P. berghei malaria were based on percent of parasitaemia reduction. These compounds were also evaluated for in vitro cytotoxicity. FINDINGS The inhibition of parasite growth in vitro showed that Accuvit® was the most active drug (IC50 5 ± 3.9 μg/mL). Soyfit® was partially active (IC50 13.6 ± 7.7 μg/mL), and Ginkgo® (IC50 38.4 ± 14 μg/mL) was inactive. All such compounds were active in vivo at a dose of 50 mg/kg body weight. Accuvit® and quercetin induced the highest reduction of P. berghei parasitaemia (63% and 53%, respectively) on day 5 after parasite inoculation. As expected, the compounds tested were not toxic. MAIN CONCLUSIONS The antimalarial activity of Accuvit® was not related to flavonoids only, and it possibly results from synergisms with other compounds present in this drug product, such as multivitamins. Multivitamins in Accuvit® may explain its effect against the malaria parasites. This work demonstrated for the first time the activity of these drugs, which are already marketed.
Characterization of dielectric properties and conductivity in encapsulation materials with high insulating filler contents

The properties of different molding-compound materials with high filler contents have been investigated in order to assess their electrical properties. The experimental part of the present work has been focused on dielectric spectroscopy and steady-state conduction measurements. The results have been used to investigate the electrical properties of the materials at different frequencies, temperatures and electric fields. Differences in the relaxation kinetics with increasing filler content have been found, which can be ascribed to the larger interface regions between the filler particles. In addition, the extracted conductivities show a hopping transport and different activation energies on the temperature range from 20 °C to 190 °C.
High-Resolution Radar Imaging with Unknown Noise

This paper addresses the problem of high-resolution radar imaging in complex environments with unknown noise in a Bayesian framework. In the new statistical model, the noise obeys Gaussian mixture distribution, and the weights are governed by the sparsity-promoting Gamma-Gaussian hierarchical prior. Then, the weights are estimated via the maximum a posterior-expectation maximization (MAP-EM) technique. Experiments have shown that the proposed method provides an effective way of high-resolution radar imaging in complex environments such as barrage jamming.
Draft Genome Sequence of Bifidobacterium bifidum Strain ICIS-310, Isolated from the Feces of a Healthy 5-Year-Old Child from Orenburg, Russia

This report describes the draft genome sequence of Bifidobacterium bifidum strain ICIS-310, isolated from the feces of a healthy 5-year-old child from Orenburg, Russia. The size of the genome was 2,219,632 bp (62.4% G+C content). ABSTRACT This report describes the draft genome sequence of Bifidobacterium bifidum strain ICIS-310, isolated from the feces of a healthy 5-year-old child from Orenburg, Russia. The size of the genome was 2,219,632 bp (62.4% G+C content). Annotation revealed 1,886 coding sequences, including 1,718 proteins, 6 rRNA genes, and 52 tRNA genes.
Near-Complete Genome Sequence of Ralstonia solanacearum T523, a Phylotype I Tomato Phytopathogen Isolated from the Philippines

Ralstonia solanacearum strain T523 is the major phytopathogen causing tomato bacterial wilt in the Philippines. Here, we report the complete chromosome and draft megaplasmid genomes with predicted gene inventories supporting rhizosphere processes, extensive plant virulence effectors, and the production of bioactive signaling metabolites, such as ralstonin, micacocidin, and homoserine lactone. ABSTRACT Ralstonia solanacearum strain T523 is the major phytopathogen causing tomato bacterial wilt in the Philippines. Here, we report the complete chromosome and draft megaplasmid genomes with predicted gene inventories supporting rhizosphere processes, extensive plant virulence effectors, and the production of bioactive signaling metabolites, such as ralstonin, micacocidin, and homoserine lactone.
A Note on the Behavior of Majority Voting in Multi-Class Domains with Biased Annotators

Majority voting is a popular and robust strategy to aggregate different opinions in learning from crowds, where each worker labels examples according to their own criteria. Although it has been extensively studied in the binary case, its behavior with multiple classes is not completely clear, specifically when annotations are biased. This paper attempts to fill that gap. The behavior of the majority voting strategy is studied in-depth in multi-class domains, emphasizing the effect of annotation bias. By means of a complete experimental setting, we show the limitations of the standard majority voting strategy. The use of three simple techniques that infer global information from the annotations and annotators allows us to put the performance of the majority voting strategy in context.
Enabling Fixtureless Assemblies in Human-Robot Collaborative Workcells by Reducing Uncertainty in the Part Pose Estimate

This paper presents an automated part localization technique for performing fixtureless assembly operations in a human-robot collaborative workcell. The main focus of this paper is to localize the part in the least possible time and ensure the part is not damaged during the contact-based probing phase due to the uncertainty in the preliminary pose estimation. Given the preliminary estimate of the part pose in the workcell, we automatically generate contact patches on the part for probing. We then estimate the probing time by considering the different subset of patches and select the subset with the least estimated probing time. The robot motions for part probing consider the potential error in the initial estimate to keep the part safe during the contact-based localization procedure. The probed positions of the contact patches are used to reduce the uncertainty in the part pose. We have characterized the performance of the developed method using both simulation and experimental studies. 1.1. DISCLAIMER: Certain commercial equipment instruments, or materials are identified in this paper to foster understanding. Such identification does not imply recommendation or endorsement by National Institute of Standards and Technology. It does not imply that the materials or equipment identified are necessarily the best available for the purpose.
Thermal Analysis of a Low Speed Permanent Magnet Synchronous Generator for Wind Turbine Applications

When it comes to designing a new electrical machine the thermal analysis should be as important as electromagnetic analysis. The strong connection between the electromagnetic and thermal designs cannot be neglected, as the losses are directly dependent on the temperature and the temperature in the machine is determined by the level of the losses. This paper presents the numerical Finite Element Method simulations and experimental tests results of the thermal behavior of a low speed external rotor permanent magnet synchronous generator used for wind applications.
Thermal Pattern Contrast Diagnostic of Microcracks With Induction Thermography for Aircraft Braking Components

Reciprocating impact load leads to plastic deformation on the surface of the kinematic chains in an aircraft brake system. As a result, this causes fatigue and various complex natural damages. Due to the complex surface conditions and the coexistence damages, it is extremely difficult to diagnose microcracks by using conventional thermography inspection methods. In this paper, the thermal pattern contrast method is proposed for weak thermal signal detection using eddy current pulsed thermography. In this process, the extraction and subsequent separation differentiate a maximum of the thermal spatial-transient pattern between defect and nondefect areas. Specifically, a successive optical flow is established to conduct a projection of the thermal diffusion. This directly gains the benefits of capturing the thermal propagation characteristics. It enables us to build the motion context connected between the local and the global thermal spatial pattern. Principal component analysis is constructed to further mine the spatial-transient patterns to enhance the detectability and sensitivity in microcrack detection. Finally, experimental studies have been conducted on an artificial crack in a steel sample and on natural fatigue cracks in aircraft brake components in order to validate the proposed method.
A Dual-Band Frequency Selective Surface with Wide Bandwidths

In this paper, a X/Ka dual-band frequency selective surface works with high incident angle and dual polarization is proposed. In conventional FSS design, mutual coupling effect between each resonator mostly leads to the optimization stage's being inadequate or time consuming. Therefore, a new design technique is presented to be able to optimize the upper resonance frequency without affecting the lower resonance frequency. Besides, as an important feature, the frequency spacing between the two resonance frequencies is as large as 30GHz. The upper operating band keeps wide although under large incident angle up to 60 degree.
An UWB location algorithm for indoor NLOS environment

In the UWB indoor wireless positioning system, to solve the problem of the NLOS error caused by the complex indoor environment and the changeable obstacles makes the positioning precision reduced. This paper uses ranging residuals to identify NLOS error, Kalman Filter is performed on the range of the LOS environment, Bias Kalman Filter based on ranging residuals compensation is performed in NLOS environment, if the ranging residuals compensation caused by some NLOS error mutations failed to reach the threshold value, according to the redundant range value after compensation, which adjusts the gain of Bias Kalman Filter automatically to reconstruct the range of LOS environment further. Least Square algorithm and Sliding Window Filter are used to calculate coordinate and smooth trajectory, experimental results show that the algorithm can effectively reduce the effect of NLOS error on location. The error of static positioning of 95% probability is not less than 0. 075m, the maximum positioning error is no more than 0. 082m, and the accuracy of dynamic positioning can be stabilized within 0. 26m, which satisfies the needs of most indoor locations.
Circularly Polarized Planar Slot Array Antenna at Ku Band

This paper introduces the design of a circularly polarized planar slot array antenna at Ku band, and the simulated results are proposed. $2\times 2$ cavity slot sub-array is adopted as the basic unit, where the circular polarization is achieved by the loading open-ended waveguide with two trimmed diagonal corners. Furthermore, full corporate waveguide feed network is constituted for the operation in the required band. For the $8\times 8$ array demonstrator, the VSWR in the band is less than 1.7, with the axial ratio within 2.2 dB. The realized gain of the proposed array is higher than 27 dB, suitable for high gain application.
A Study on High Resolution Batch-Mode Micro-Utralsonic-Machining with Constant Feed Force of Sapphire for MEMS Application

Sapphire has widely used for application to MEMS due to its excellent optical property, mechanical property, chemical stability, high melting point and electrical insulation property, such as X-ray resonator cavities, optical wall shear stress sensor for high temperature applications, lateral overtone bulk acoustic resonator with high f-Q and increasing the output power of LED. This paper presented a high resolution batch-mode micro-utralsonic-machining $(\mu\mathbf{USM})$ with constant feed force of sapphire for MEMS application, and it has advantages of high machining efficiency, resolution and surface quality compared to other machining method. High aspect ratio $(> \mathbf{4})$ structure with the feature resolution below 1μm of sapphire has been machined by batch-mode $\mu\mathbf{USM}$. A machining depth of $\mathbf{40}\mu\mathbf{m}$ has been achieved at a removal rate up-to $\mathbf{4}\mu\mathbf{m}/\mathbf{min}$, and its bottom surface roughness is below Ra 80nm.
Postfault Strategy for Dual Three-Phase Machines With Minimum Loss in the Full Torque Operation Range Under Two Open Phases

Dual three-phase machines (D3PMs) are particularly attractive due to their fault-tolerance capability. In general, under open-phase (OP) faults, the current references are adapted following a minimum-loss strategy (MLS) or a maximum-torque strategy (MTS). The MLS offers lower copper loss than the MTS for any given torque, but a smaller torque operation range (TOR). The full-range MLS (FRMLS) has recently been proposed, providing minimum copper loss, for each torque value, in the whole TOR (the MTS TOR); however, only one OP was considered. Furthermore, neither the TOR of the MLS nor the copper loss of the MLS or MTS have been assessed with two OPs. Consequently, it is difficult to infer a priori the relevance that the FRLMS may have for two OPs. This paper evaluates the extension of the FRMLS to D3PMs with two OPs. First, the procedure to carry out this extension is described. Then, the convenience of the FRMLS for two OPs is studied for different situations. It is concluded that for two OPs in most cases the FRMLS is substantially better than the MTS and MLS in terms of copper loss and TOR. Experimental results verify the theory.
Design of Seabed Beacon Positioning Hardware Platform Based on Single Hydrophone

Underwater acoustic beacon is an important auxiliary tool for marine engineering. It undertakes many important tasks such as underwater positioning, marine environment observation and navigation of underwater vehicles. With the increase of marine activities and the expansion of work scope, beacons face more threats and are more easily lost. In this paper, a new method for searching lost beacons is present. The search method in this paper is based on the hyperboloid positioning principle. A surface vessel equipped with global positioning system maneuvers on the surface of the water and continuously receives underwater acoustic signals. When the signal detection result meets the preset detection condition, the position and time of the ship at this moment are recorded. When the number of recorded receiving points is enough, more than 5 sets of receiving points and time differences are selected to form a non-linear system of equations. In this case, the hybrid estimation algorithm can be used to obtain the estimated target position.
Segmentation of Underwater Object in Videos

Video segmentation is a necessary step for object tracking. Existing methods that are used to extract object from the background based on an intensive sequence of searching all across the frames, thus this process performs lots of searching works result with low efficiency, whereas other methods obtain segmentation by clustering pixels which resulting in over-segmentation. Inspired by breakthroughs in semantic segmentation, in this paper, we propose to combine appearance and dynamic cues, which is a common conception and plays a key role in successfully segmenting objects in videos. To implement this idea, we combine Deep Convolutional Neural Network (DCNN) and optical flow information of two continuous frames. To overcome the difficulty of segmentation of underwater object in videos induced by the presence of different types of suspension particle from like the water droplets and dust particles to the poor lighting and over lighting conditions, In this work, Contrast-Limited Adaptive Histogram Equalization (CLAHE) and a simple color resign method are used to enhance details and reduce greenish and bluish effects. Some DCNN variants are applied to semantic segmentation and achieve great efficiency. Specifically, because DCNN can obtain different spatial scale information, as a DCNN variant, DeepLab gets a good performance in semantic segmentation. By using atrous convolution, DeepLab network's filters can observe greater receptive field without reducing the feature map dimension, therefore this structure keeps global and position information. Consequently, we compromises above mentioned methods, The optical flow estimation is carried out on the image processed by the CLAHE method, and the accurate segmentation results are obtained by using the DeepLab network. Experiments show good performance of our method.
POMon: From Simple Keyword Matching to Stream-Based Live Probabilistic Topic Matching

Public opinion monitoring is defined as story detection and matching with particular Internet news event. Traditional method used topic discovery and text matching techiques to get results. However, it has some limitations: hidden topic discovery and incorrect match ranking on big data. In this demonstration, we present the architecture evolution of public sentiment monitoring system (POMon) and ranking method of live probabilistic topic matching. Meanwhile, we discuss the evolution from simple keyword matching to stream-based live probabilistic topic matching.
Doppler Aided Synthetic Long Baseline Navigation for a Fast-Moving Underwater Vehicles

Underwater navigation that relies solely on dead reckoning suffers from unbounded position error growth. In traditional positioning method, the cost and trouble of deploying, recovering, and assembly have become insuperable obstacle. Based on combination SLBL with an AUV, a new positioning method of autonomous navigation is proposed in the paper. And based on pattern time delay shift coding pulse, Doppler Aided Synthetic LBL method could be described with Doppler effects from AUV moving. Under the underwater multipath and a fast moving AUV, the reasons to bring out positioning error would be given and some advices of the path planning of AUV would be suggested also. At last, the positioning solution of AUV in the relative field trial could be finished and verified.
A Reconfigurable Water Dense Dielectric Patch Antenna with Cross-Shape Feeding Structure

This paper presents a reconfigurable water dense dielectric patch antenna (DDPA) with cross-shape feeding structure. The distilled water patch acts as an electric wall. The height of distilled water in the polyvinyl chloride (PVC) plastic box can be adjusted for frequency reconfiguration. The cross-shape feeding structure and the cylindrical copper is used for improving the impedance matching. Moreover, an air gap is inserted between the water patch and the substrate to improve radiation efficiency. Impedance bandwidth of the antenna achieves 20% and radiation efficiency is 50%-75%.
A Distributed Algorithm for Sensor Fault Detection

In intelligent buildings, faults occurring to sensors are common due to external interference or the limited service life of sensors. In this paper, we propose a distributed fault detection algorithm based on energy balance. With the increase of building scale, the algorithm has higher efficiency and better adaptability than the commonly used centralized fault detection methods. The algorithm is suitable for failures of disconnected sensors or devices, and makes judgements on whether the devices and sensors are faulty by the energy balance relations of adjacent nodes. Theoretical analysis and simulation show that this algorithm has lower time complexity than centralized algorithm which is also based on energy balance.
A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system

Industrial Control Systems are part of our daily life in industries such as transportation, water, gas, oil, smart cities, and telecommunications. Technological development over time have improved their components including operating system platforms, hardware capabilities, and connectivity with networks inside and outside the organization. Consequently, the Industrial Control Systems components are exposed to sophisticated threats with weak security mechanism in place. This paper proposes a supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system. A testbed of such a system is implemented using the Festo MPA Control Process Rig. The machine-learning algorithms, which include SVN, KNN, and Random Forest, perform classification tasks process in three different datasets obtained from the testbed. The algorithms are compared in terms of accuracy and F-measure. The results show that Random Forest achieves 5% better performance over KNN and SVM with small datasets and 4% regarding large datasets. For the time taken to build the model, KNN presents the best performance. However, its difference with Random Forest is smaller than with SVM.
A wideband 6-bit Digital Attenuator with high accuracy in 65nm CMOS

A wideband 6-bit digital attenuator with high accuracy in 65nm CMOS is proposed. To achieve a high accuracy attenuator, a phase compensation network is used to reduce the phase error without increasing insertion loss, and a new amplitude compensation network is present to reduce the amplitude error. The post simulation results show that over the entire band of 8-18GHz, RMS amplitude error is <0.1dB, which is much less than other literatures, and the RMS phase error is less than 5.5°. The insertion loss is 6.14-8.59dB and the input 1-dB compression point is 11.941dBm at 13GHz. The core chip size is 0.91×0.30 mm2.
Extreme Pathway Analysis of Mycobacterium Tuberculosis

Tuberculosis is a multisystem disorder characterized by the formation of swelling that is filled with blood which is caused from breakage in the wall of a blood vessel. This breakage can occur in different organs of the body and is caused by a bacterium known as Mycobacterium Tuberculosis (mtb) which can be represented as a metabolic network with genes, proteins and enzymes that are interconnected. This interconnection defines the uniqueness of any bacteria. The analysis of a metabolic network system is achievable through different computational techniques depending on what information is available. The flux balance analysis is mostly used for analyzing this type of network because of the little amount of information required. The application of flux balance analysis to mtb involves the conversion of the metabolic network into a stoichiometric matrix where the rows represents the metabolites and the columns represent the reactions. In this study, the stoichiometric matrix is an 828 by 1027 matrix. The analysis generated a linear problem having more unknowns than the number of equations. This type of problem is normally solved using an extreme pathways algorithm to extract independent paths and simplex method for optimization of biomass. Here, the extreme pathways analysis was used in the categorization of the metabolite of mtb while biomass was employed as the objective function using default constraints. The output represents three categories of metabolite: 31 metabolites that form part of the biomass component that are inactive, 14 metabolites that remain active and 32 metabolites that are activated after the optimization process.