Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of a Simple in-House Test to Presumptively Differentiate Mycobacterium tuberculosis Complex from Nontuberculous Mycobacteria by Detection of p-Nitrobenzoic Acid Metabolites

The timely differentiation of Mycobacterium tuberculosis complex (MTC) and non-tubercular mycobacterium (NTM) species is urgently needed in patient care since the routine laboratory method is time consuming and cumbersome. An easy and cheap method which can successfully distinguish MTC from NTM was established and evaluated. 38 mycobacterial type and reference strains and 65 clinical isolates representing 10 species of mycobacterium were included in this study. Metabolites of p-nitrobenzoic acid (PNB) reduction were identified using liquid chromatography and tandem mass spectrometry (LC/MS/MS). A spectrophotometric method was developed to detect these metabolites, which was evaluated on a number of MTC and NTM species. All of the tested NTM species and strains reduced PNB to p-aminobenzoic acid (PABA), while none of the MTC strains showed a similar activity. Spectrophotometric detection of PABA had 100% sensitivity and specificity for MTC and NTM differentiation among the type strains and the clinical isolates tested. PABA was identified as one of the metabolites of PNB reduction. All the tested NTM species metabolized PNB to PABA whereas the MTC members lacked this activity. A simple, specific and cost-effective method based on PABA production was established in order to discriminate MTC from NTM from cultured organisms.
Empowering Girls and Women through Hookworm Prevention

Human hookworm infection is one of the most ubiquitous illnesses in people who live in extreme poverty. The Global Burden of Disease (GBD) study estimates that in the year 2016, approximately 450 million people lived with hookworms in their small intestines. Hookworms feed on human blood and cause long-term intestinal blood loss, leading to iron de ﬁ ciency. Forindividualswithlowironstores,blood-feeding hookworms can cause suf ﬁ cient iron and blood loss, leading to anemia. A systematic analysis for the GBD study found that a high percentage of anemia disease burden in Oceania and Africa could be attributed to hookworm infection. because of their low iron reserves as a result of men-struation, iron
The Potential Role of PTPN-22 C1858T Gene Polymorphism in the Pathogenesis of Type 1 Diabetes in Saudi Population

ABSTRACT Background: Recent investigations have reported an association between protein tyrosine phosphatase non-receptor type-22 (PTPN-22) gene polymorphism and susceptibility to the development of type 1 diabetes (T1D) in some populations and not in others. In this study, we aimed to investigate the association of PTPN-22 C1858T polymorphism with T1D in Saudi children. Methods: A cohort of 372 type 1 diabetic children and 372 diabetes-free subjects was enrolled in the current investigation. The PTPN-22 C1858T polymorphism was identified using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Results: Our data showed that the frequency of CT and TT genotypes of PTPN-22 C1858T was higher in T1D children (17.7% and 4.3%, respectively) compared to healthy controls (4.8% and 1.6%, respectively), and both genotypes were statistically associated with T1D patients (OR = 4.4, 95% CI: 2.55–7.58, p < 0.001; and OR = 3.2, 95% CI: 1.23–8.28, p = 0.017, respectively). Moreover, the 1858T allele was significantly associated with T1D patients compared to the C allele (OR = 3.2, 95% CI: 1.59–6.88, p < 0.001). In addition, the T allele was significantly associated with elevated levels of HbA1c, anti-GAD, and anti-insulin antibodies (p < 0.001) and a lower concentration of C-peptide (p < 0.001) in T1D children. Conclusion: The data presented here suggests that the T allele of PTPN-22 C1858T polymorphism might be a risk factor for T1D development in Saudi children.
Time-Based PWM Controller for Fully Integrated High Speed Switching DC-DC Converters — An Alternative to Conventional Analog and Digital Controllers

This tutorial discusses design of a highly integrated, low quiescent current continuous time PWM controller using time-based signal processing. By virtue of the continuous-time digital nature of the time-based PWM controller, it is capable of achieving very high resolution and speed without using any error amplifier and large compensation capacitor or any high resolution A/D converter and digital PWM while preserving all the benefits of both analog and digital PWM controllers. Using time as the processing variable, the controller operates with CMOS-level digital-like signals but without adding any quantization error. A voltage/current controlled ring oscillator is used as an integrator in place of conventional opamp-RC or Gm-C integrator while a voltage/current controlled delay line is used to perform voltage-to-time conversion. Starting with trade-offs with high speed design of conventional analog and digital PWM controllers, the concept of time based proportional-integral-derivative (PID) controller with complete architecture of a time-based buck converter is presented. The technique was successfully demonstrated on silicon with implementation of 10-25MHz single phase and 30-70MHz 4-phase buck converters on 180nm and 65nm CMOS processes, respectively.
Large-Scale Indexing, Discovery, and Ranking for the Internet of Things (IoT)

Network-enabled sensing and actuation devices are key enablers to connect real-world objects to the cyber world. The Internet of Things (IoT) consists of the network-enabled devices and communication technologies that allow connectivity and integration of physical objects (Things) into the digital world (Internet). Enormous amounts of dynamic IoT data are collected from Internet-connected devices. IoT data are usually multi-variant streams that are heterogeneous, sporadic, multi-modal, and spatio-temporal. IoT data can be disseminated with different granularities and have diverse structures, types, and qualities. Dealing with the data deluge from heterogeneous IoT resources and services imposes new challenges on indexing, discovery, and ranking mechanisms that will allow building applications that require on-line access and retrieval of ad-hoc IoT data. However, the existing IoT data indexing and discovery approaches are complex or centralised, which hinders their scalability. The primary objective of this article is to provide a holistic overview of the state-of-the-art on indexing, discovery, and ranking of IoT data. The article aims to pave the way for researchers to design, develop, implement, and evaluate techniques and approaches for on-line large-scale distributed IoT applications and services.
Nicotinic acid impairs assembly of leading edge in glioma cells

Malignant glioma is a clinically formidable disease. It commonly leads to death within 5 years after diagnosis. Physicians are often baffled since the inevitable diffuse invasion deteriorates clinical outcomes rapidly. Therefore, cancerous infiltration presents a foremost challenge to all therapeutic strategies on glioblastoma multiforme (GBM). Previously, we demonstrated that nicotinic acid (NA) possesses a brand new function by targeting F-actin stress fibers. By treating HEK293 or NIH3T3 cells with a certain concentration of NA, the F-actin stress fiber was significantly disassembled. This notable finding inspired us to explore NA further in cancer cell lines, such as GBM cells, since F-actin stress fibers are the critical foundation of cell migration, proliferation and numerous essential signaling pathways. Expectedly, we observed that optimized concentrations of NA, 3.5 mM and 7.0 mM, detached U251 from culturing petri dishes. Moreover, 7.0 mM of NA was capable of disrupting the leading-edge assembly. Additionally, we collected paraffin specimens from 85 GBM patients and evaluated the expression pattern of paxillin. Notably, we found that discernable paxillin signals were detected in 67 out of 85 samples. Given that leading edge is critical for cancer cell migration, we propose that NA treatment may be developed into a potential therapy for malignant glioma.
Superconductivity above the lowest Earth temperature in pressurized sulfur hydride

A recent experiment has shown a macroscopic quantum coherent condensate at 203 K, about 19 degrees above the coldest temperature recorded on the Earth surface, 184 K in pressurized sulfur hydride. This discovery is relevant not only in material science and condensed matter but also in other fields ranging from quantum computing to quantum physics of living matter. It has given the start to a gold rush looking for other macroscopic quantum coherent condensates in hydrides at the temperature range of living matter . We present here a review of the experimental results and the theoretical works and we discuss the Fermiology of focusing on Lifshitz transitions as a function of pressure. We discuss the possible role of the shape resonance near a neck disrupting Lifshitz transition, in the Bianconi-Perali-Valletta (BPV) theory, for rising the critical temperature in a multigap superconductor, as the Feshbach resonance rises the critical temperature in Fermionic ultracold gases.
Gesture Recognition Using Dynamic Time Warping and Kinect: A Practical Approach

This paper describes a detailed methodology that allows gesture recognition performed with the upper limbs of the human body, based on Dynamic Time Warping (DTW) technique using a Kinect in order to control a slide-show. Several involved parameters on the DTW algorithm will be analyzed allowing an accurate recognition, considering variations on the gesture velocity and even if subject's physical shape differ. A software was developed in Microsoft Visual C# to show and test how different parameters affects the performance of the algorithm. Finally an accuracy of 84.07% was obtained in this approach.
Kinematic Analysis and Trajectory Planning for Serial Robot in Hazardous Biochemical Treatment

Aiming at the application of serial robot in the treatment of hazardous biochemical products, the kinematic analysis and trajectory planning are carried out in our study. Serial robot is used to replace humans to handle the hazardous biochemical products, making operations to be more accurate and efficient. The robot’s kinematics modeling has been built through Denavit-Hartenberg (D-H) method. Forward and inverse kinematic equations have been deduced and validated. Then, the Jacobian matrix of the robot is obtained by the differential transform method. Finally, the trajectory planning is accomplished in Cartesian and joint spaces.
Bézier Curves Based Novel Calibration Technique of Beamformers in IEEE 802.11 WLAN Networks

IEEE 802.11 WLAN networks face challenges for end- to-end service performance concerning new mobility applications: real-time interactive communications, analytics and business intelligence. In dense indoor deployments, co-channel interference is a major issue. One of Radio Resource Management (RRM) techniques that is used to tackle this issue and maximize transmit opportunity is beamforming. From a signal processing perspective, the related-work concentrates on array elements' signal weighting and phase shifting to achieve the desired angle of radiation, direction of arrival and gain. This work presents a novel beamformer's calibration technique that enhances related-work results in the context of indoor WLAN network with a considerably lessened processing time and an augmented transmission quality. Our solution model approach is based on concepts from Computed Aided Graphical Design (CAGD) especially Bézier curves, and takes advantage of now-a-day WLAN networks design and deployment characteristics.
An Efficient Network Motif Discovery Approach for Co-Regulatory Networks

Co-regulatory networks, which consist of transcription factors (TFs), micro ribose nucleic acids (miRNAs), and target genes, have provided new insight into biological processes, revealing complicated and comprehensive regulatory relationships between biomolecules. To uncover the key co-regulatory mechanisms between these biomolecules, the identification of co-regulatory motifs has become beneficial. However, due to high-computational complexity, it is a hard task to identify co-regulatory network motifs with more than four interacting nodes in large-scale co-regulatory networks. To overcome this limitation, we propose an efficient algorithm, named large co-regulatory network motif (LCNM), to detect large co-regulatory network motifs. This algorithm is able to store a set of co-regulatory network motifs within a $G$ -tries structure. Moreover, we propose two ways to generate candidate motifs. For three- or four-interacting-node motifs, LCNM is able to generate all different types of motif through an enumeration method. For larger network motifs, we adopt a sampling method to generate candidate co-regulatory motifs. The experimental results demonstrate that LCNM cannot only improve the computational performance in exhaustive identification of all of the three- or four-node motifs but can also identify co-regulatory network motifs with a maximum of eight nodes. In addition, we implement a parallel version of our LCNM algorithm to further accelerate the motif detection process.
The pulmonary artery catheter: is it still alive?

Purpose of reviewThe present review discusses the current role of the pulmonary artery catheter (PAC) in the hemodynamic monitoring of critically ill patients. Recent findingsThe PAC has an important role in the characterization and management of hemodynamic alterations in critically ill patients. Use of the PAC has decreased in the last 30 years because of recent advances in less invasive hemodynamic monitoring techniques, in particular transpulmonary thermodilution and echocardiography, combined with the publication of the results of several randomized trials that failed to show improvements in outcome with the use of the PAC in various settings. Although it is obvious that the PAC should not be used in most critically ill patients, the PAC is still indicated in some patients with circulatory and/or respiratory failure, especially when associated with pulmonary hypertension or left heart dysfunction. As for any technique, optimal PAC use requires expertise in insertion, acquisition, and interpretation of measurements. The decrease in use of the PAC may unfortunately limit exposure of junior doctors and nurses to this device, so that they become less familiar with using the PAC, making it more complicated and less optimal. SummaryThe PAC still has an important role in the cardiopulmonary monitoring of critically ill patients.
Single-channel speech dereverberation based on block-wise weighted prediction error and nonnegative matrix factorization

This paper proposes a speech dereverberation method based on a block-wise weighted prediction error (BWPE) method and nonnegative matrix factorization (NMF). The proposed BWPE method iteratively estimates late reverberation using maximum likelihood (ML) estimation in a block-wise manner. To ensure consistent de-reverberation performance over time, a forgetting factor is applied on intermediate estimates. Thus, the recent statistics of the signal are emphasized during the block-wise processing. In addition, the NMF-based source separation method is applied to reduce early reverberation that remains in the signal processed by the proposed BWPE method. The performance of the proposed method is compared with that of the conventional weighted prediction error (WPE) method by measuring the Segmental signal-to-noise ratio (SSNR). It is shown from the comparison that the proposed method achieves a higher SSNR than the conventional method. Moreover, the proposed method can be implemented in a real-time audio recording device with an algorithmic delay of 20ms.
Representations of Animal Companions on Student Learning Perception: Static, Animated and Tangible

Educational agents (including animal companions) are a kind of interface agent, which is a significant component in educational systems, and has great impacts on student learning. However, with the development of emerging technologies (e.g., tangible technology), few studies have yet investigated how tangible technology can be used to combine with animal companions to foster student learning and interaction. In addition, different representation styles of animal companions on student learning are also seldom investigated. To address these research questions, this paper develops a My-Dragon system which blends tangible and animal companions for maximizing young student interaction. The system is further evaluated by an empirical study by eighteen pupils compared with a static and an animated version. The results reveal that such a tangible system is of benefit to the student learning perception in terms of attention, emotion, and interaction aspects. Some implications on findings and future system development are also discussed.
Malware classification using deep learning methods

Malware, short for Malicious Software, is growing continuously in numbers and sophistication as our digital world continuous to grow. It is a very serious problem and many efforts are devoted to malware detection in today's cybersecurity world. Many machine learning algorithms are used for the automatic detection of malware in recent years. Most recently, deep learning is being used with better performance. Deep learning models are shown to work much better in the analysis of long sequences of system calls. In this paper a shallow deep learning-based feature extraction method (word2vec) is used for representing any given malware based on its opcodes. Gradient Boosting algorithm is used for the classification task. Then, k-fold cross-validation is used to validate the model performance without sacrificing a validation split. Evaluation results show up to 96% accuracy with limited sample data.
Group velocity of wave propagation in carbon nanotubes

The group velocities of longitudinal and flexural wave propagations in single- and multi-walled carbon nanotubes are studied in the frame of continuum mechanics. The dispersion relations between the group velocity and the wavenumber for flexural and longitudinal waves, described by a beam model and a cylindrical shell model, are established for both single- and multi-walled carbon nanotubes. The effect of microstructures in carbon nanotubes on the wave dispersion is revealed through the non-local elastic models of a beam and a cylindrical shell, including the second-order gradient of strain and a parameter of microstructure. It is shown that the microstructures in the carbon nanotubes play an important role in the dispersion of both longitudinal and flexural waves. In addition, the non-local elastic models predict that the cut-off wavenumber of the dispersion relation between the group velocity and the wavenumber is approximately 2×1010 m−1 for the longitudinal and flexural wave propagations in both single- and multi-walled carbon nanotubes. This may explain why the direct molecular dynamics simulation cannot give a proper dispersion relation between the phase velocity and the wavenumber when the wavenumber approaches approximately 2×1010 m−1, much lower than the cut-off wavenumber for the dispersion relation between the phase velocity and the wavenumber predicted by continuum mechanics.
Design of efficient rectifying circuit for RF energy harvesting applications

This paper presents a new design of rectifying circuit for RF energy harvesting application over 900 MHz band of frequency. The proposed rectifying circuit employs the Dickson charge pump rectifier with a novel optimized matching unit. This matching unit is comprised of radial stubs, open stubs, and evolves by the usage of interdigital capacitors. The rectifying circuit is simulated using Advance design software (ADS), and provides maximum RF to DC conversion efficiency of 77% at the frequency of 900 MHz. The extracted layout of the circuit is found to be 7 × 5 × 1.6 cm3, which can be considered to be quite compact at the operating frequency.
Positive Selection Driving Cytoplasmic Genome Evolution of the Medicinally Important Ginseng Plant Genus Panax

Panax L. (the ginseng genus) is a shade-demanding group within the family Araliaceae and all of its species are of crucial significance in traditional Chinese medicine. Phylogenetic and biogeographic analyses demonstrated that two rounds of whole genome duplications accompanying with geographic and ecological isolations promoted the diversification of Panax species. However, contributions of the cytoplasmic genomes to the adaptive evolution of Panax species remained largely uninvestigated. In this study, we sequenced the chloroplast and mitochondrial genomes of 11 accessions belonging to seven Panax species. Our results show that heterogeneity in nucleotide substitution rate is abundant in both of the two cytoplasmic genomes, with the mitochondrial genome possessing more variants at the total level but the chloroplast showing higher sequence polymorphisms at the genic regions. Genome-wide scanning of positive selection identified five and 12 genes from the chloroplast and mitochondrial genomes, respectively. Functional analyses further revealed that these selected genes play important roles in plant development, cellular metabolism and adaptation. We therefore conclude that positive selection might be one of the potential evolutionary forces that shaped nucleotide variation pattern of these Panax species. In particular, the mitochondrial genes evolved under stronger selective pressure compared to the chloroplast genes.
Automatization Aspects of Dyslexia Speed Limitations in Word Identification, Sensitivity to Increasing Task Demands, and Orthographic Compensation

A study is presented in which three characteristics of dyslexia were examined: (a) speed limitations in word identification, (b) sensitivity to increasing task demands, and (c) orthographic compensation. Ten students with dyslexia (10 years old) were compared to 10 chronological-age controls and 20 reading-age controls on their performance in reading. Response latencies of the students with dyslexia were slower when familiar words, letter clusters, and nonwords had to be named. A larger word-frequency effect and a larger word-length effect in the these students indicates that they have difficulty with increasing task demands. In addition, a subword-frequency effect was found to be larger in the students with dyslexia. These differences among the three groups of students are interpreted in terms of automatization. Furthermore, it is suggested that students with dyslexia may have a preference for large orthographic units, which is used as a compensatory tool in reading.
Beam Tracking for UAV Mounted SatCom on-the-Move With Massive Antenna Array

Unmanned aerial vehicle (UAV)-satellite communication has drawn dramatic attention for its potential to build the integrated space-air-ground network and the seamless wide-area coverage. A key challenge to UAV-satellite communication is its unstable beam pointing due to the UAV navigation, which is a typical SatCom on-the-move scenario. In this paper, we propose a blind beam tracking approach for Ka-band UAV-satellite communication system, where UAV is equipped with a hybrid large-scale antenna array. The effects of UAV navigation are firstly released through the mechanical adjustment, which could approximately point the beam towards the target satellite through beam stabilization and dynamic isolation. Specially, the attitude information for mechanical adjustment can be realtimely derived from data fusion of low-cost sensors. Then, the precision of beam pointing is blindly refined through electrically adjusting the weight of the massive antennas, where an array structure based simultaneous perturbation algorithm is designed. Simulation results are provided to demonstrate the superiority of the proposed method over the existing ones.