Miracle-dz/UniFAR-FTUs huggingface dataset:
A new 2×4 array design of dual-band millimeter-wave antenna for 5G applications

A new 2×4 array for dual-band milllimeter wave (mm-wave) antenna operating at 28 GHz and 38 GHz has been designed and evaluated in this paper. The proposed antenna array consists of 8 elements with 8 ports in 2×4 square configuration. Dual-band characteristic was produced using slotted patch method. At these frequencies, we also compared the antenna gain between waveguide and SMA port feed techniques. It shows that the gain of antenna array with SMA port reaches 15.8 dBi at 28 GHz and 13.9 dBi at 38 GHz, respectively. There was a slight decrease of antenna gain with SMA port compared to that of the waveguide feed. All the 8 antenna-elements shows a very consistent return-loss (S11) characteristics, in that they have almost identical bandwidth to cover 28 GHz and 38 GHz. Also, each element has a very good isolation between each other, i.e the protection between their feeding point is more than 28.692 dB at 28 GHz and 38.779 dB for 38 GHz, which can meet the inter-element protection requirements.
The role of magnetic resonance imaging and endoscopic retrograde cholangiography in the evaluation of disease activity and severity in primary sclerosing cholangitis

Endoscopic retrograde cholangiography (ERCP) has been considered the gold standard for the diagnosis and follow‐up of primary sclerosing cholangitis, but it has been replaced by less invasive magnetic resonance imaging and cholangiopancreatography (MRI‐MRCP). However, the role of these two techniques in the evaluation of disease activity and severity needs to be elucidated.
The effectiveness of lotus stamen tea on lowering blood lipid level in hyperlipidemic subjects

The purpose of this study is to evaluate the efficacy and safety of oral administration of the lotus stamen tea on the treatment of hyperlipidemia. 4 weeks, randomized, controlled interventional study was performed in 30 participants with hyperlipidemia by divided into 2 groups, oral lotus stamen tea group and control group. This study decided to give an intervention for 4 weeks and followed up the subject at 2nd and 4th week. But this paper showed the results from preliminary study, lotus stamen tea group, 2 weeks of intervention and followed up at 2nd week of the study. After 2 weeks of intervention, lotus stamen tea could decrease blood total cholesterol level and LDL-cholesterol level. Blood HDL-cholesterol level and triglyceride level were not changed, There was no adverse effect and no abnormal kidney and liver function of this intervention, blood kidney function level and blood liver enzymes level were not changed. This study showed the new evidence of lotus stamen might be used as alternative treatment or supplement for dyslipidemia.
SEDC-Based Hardware-Level Fault Tolerance and Fault Secure Checker Design for Big Data and Cloud Computing

Fault tolerance is of great importance for big data systems. Although several software-based application-level techniques exist for fault security in big data systems, there is a potential research space at the hardware level. Big data needs to be processed inexpensively and efficiently, for which traditional hardware architectures are, although adequate, not optimum for this purpose. In this paper, we propose a hardware-level fault tolerance scheme for big data and cloud computing that can be used with the existing software-level fault tolerance for improving the overall performance of the systems. The proposed scheme uses the concurrent error detection (CED) method to detect hardware-level faults, with the help of Scalable Error Detecting Codes (SEDC) and its checker. SEDC is an all unidirectional error detection (AUED) technique capable of detecting multiple unidirectional errors. The SEDC scheme exploits data segmentation and parallel encoding features for assigning code words. Consequently, the SEDC scheme can be scaled to any binary data length “n” with constant latency and less complexity, compared to other AUED schemes, hence making it a perfect candidate for use in big data processing hardware. We also present a novel area, delay, and power efficient, scalable fault secure checker design based on SEDC. In order to show the effectiveness of our scheme, we (1) compared the cost of hardware-based fault tolerance with an existing software-based fault tolerance technique used in HDFS and (2) compared the performance of the proposed checker in terms of area, speed, and power dissipation with the famous Berger code and m-out-of-2m code checkers. The experimental results show that (1) the proposed SEDC-based hardware-level fault tolerance scheme significantly reduces the average cost associated with software-based fault tolerance in a big data application, and (2) the proposed fault secure checker outperforms the state-of-the-art checkers in terms of area, delay, and power dissipation.
Immuno Nanosensor for the Ultrasensitive Naked Eye Detection of Tuberculosis

In the present study, a beneficial approach for the ultrasensitive and affordable naked eye detection and diagnosis of tuberculosis (TB) by utilizing plasmonic enzyme-linked immunosorbent assay (ELISA) via antibody-antigen interaction was studied. Here, the biocatalytic cycle of the intracellular enzymes links to the formation and successive growth of the gold nanoparticles (GNPs) for ultrasensitive detection. The formation of different colored solutions by the plasmonic nanoparticles in the presence of enzyme labels links directly to the existence or non-existence of the TB analytes in the sample solutions. For disease detection, the adapted protocol is based mainly on the conventional ELISA procedure that involves catalase-labeled antibodies, i.e., the enzymes consume hydrogen peroxide and further produce GNPs with the addition of gold (III) chloride. The amount of hydrogen peroxide remaining in the solution determines whether the GNPs solution is to be formed in the color blue or the color red, as it serves as a confirmation for the naked eye detection of TB analytes. However, the conventional ELISA method only shows tonal colors that need a high concentration of analyte to achieve high confidence levels for naked eye detection. Also, in this research, we proposed the incorporation of protein biomarker, Mycobacterium tuberculosis ESAT-6-like protein esxB (CFP-10), as a means of TB detection using plasmonic ELISA. With the use of this technique, the CFP-10 detection limit can be lowered to 0.01 µg/mL by the naked eye. Further, our developed technique was successfully tested and confirmed with sputum samples from patients diagnosed with positive TB, thereby providing enough evidence for the utilization of our technique in the early diagnosis of TB disease.
Ernährungsmodifikation: eine Therapiemöglichkeit der arteriellen Hypertonie

Abstract Modifying nutrition is one of the most important therapeutic principles in arterial hypertension, WHO says in its update recommendations. In the order of importance these modifications are: weight reduction, sodium chloride (common salt) reduction, normalisation of alcohol consumption and possibly additively active measures such as potassium supplementation, employing n-3 fatty acids and a vegetarian dietary regime. These items will often reduce blood pressure sufficiently well to normalise a mild blood pressure increase. The efficacy of the necessary drug treat-ment is definitely enhanced by an accompanying modification of dietary habits. No side effects may be expected from such non-drug measures.
A survey on spectrum sensing algorithms for cognitive radio networks

Cognitive radio (CR) has emerged as one of the most promising candidate solutions to answer the spectrum scarcity problem. Spectrum sensing is an essential task in improving spectrum utilization efficiency. This paper constitutes a brief survey of CR sensing algorithms along with the corresponding CR system characteristics as well as the techniques that enhance sensing parameters. Special attention is paid to the use of sub-Nyquist techniques, including compressive sensing (CS). Conclusions and future challenges in spectrum sensing in CR are further provided.
Application of machine learning methods in maritime safety information classification

In order to ensure the safety of maritime navigation, International Maritime Organization (IMO) developed the Global Maritime Distress and Safety System (GMDSS), which includes an important Maritime Safety Information (MSI) Broadcasting System that can broadcast navigational warnings and other crucial information. However, in most sea areas, the broadcast messages are still not pre-classified. Seafarers need to identify the theme of those received messages artificially, with low efficiency and accuracy. To solve this problem, several machine-learning based solutions are presented, implemented, and compared. Thousands of Navigational Telex (NAVTEX) messages, from 2011 to 2017, are used in the training and evaluation progress. The classifiers are compared in terms of accuracy, efficiency, precision and recall rate, and F-Measure respectively; and one of them is chosen as the optimal classifier. The chosen classifier performs well on solving the NAVTEX classification problem, and may further be used in other similar problems.
Identification of cardioprotective drugs by medium-scale in vivo pharmacological screening on a Drosophila cardiac model of Friedreich's ataxia

ABSTRACT Friedreich's ataxia (FA) is caused by reduced levels of frataxin, a highly conserved mitochondrial protein. There is currently no effective treatment for this disease, which is characterized by progressive neurodegeneration and cardiomyopathy, the latter being the most common cause of death in patients. We previously developed a Drosophila melanogaster cardiac model of FA, in which the fly frataxin is inactivated specifically in the heart, leading to heart dilatation and impaired systolic function. Methylene Blue (MB) was highly efficient to prevent these cardiac dysfunctions. Here, we used this model to screen in vivo the Prestwick Chemical Library, comprising 1280 compounds. Eleven drugs significantly reduced the cardiac dilatation, some of which may possibly lead to therapeutic applications in the future. The one with the strongest protective effects was paclitaxel, a microtubule-stabilizing drug. In parallel, we characterized the histological defects induced by frataxin deficiency in cardiomyocytes and observed strong sarcomere alterations with loss of striation of actin fibers, along with full disruption of the microtubule network. Paclitaxel and MB both improved these structural defects. Therefore, we propose that frataxin inactivation induces cardiac dysfunction through impaired sarcomere assembly or renewal due to microtubule destabilization, without excluding additional mechanisms. This study is the first drug screening of this extent performed in vivo on a Drosophila model of cardiac disease. Thus, it also brings the proof of concept that cardiac functional imaging in adult Drosophila flies is usable for medium-scale in vivo pharmacological screening, with potent identification of cardioprotective drugs in various contexts of cardiac diseases. Editor's choice: The first medium-scale pharmacological in vivo screen on a Drosophila cardiac model identified 11 compounds with protective effects on Friedreich's ataxia cardiomyopathy.
Investigation of the Accuracy of 18 Marketed Blood Glucose Monitors

OBJECTIVE Cleared blood glucose monitors (BGMs) for personal use may not always deliver levels of accuracy currently specified by international and U.S. regulatory bodies. This study’s objective was to assess the accuracy of 18 such systems cleared by the U.S. Food and Drug Administration representing approximately 90% of commercially available systems used from 2013 to 2015. RESEARCH DESIGN AND METHODS A total of 1,035 subjects were recruited to have a capillary blood glucose (BG) level measured on six different systems and a reference capillary sample prepared for plasma testing at a reference laboratory. Products were obtained from consumer outlets and tested in three triple-blinded studies. Each of the three participating clinical sites tested a different set of six systems for each of the three studies in a round-robin. In each study, on average, a BGM was tested on 115 subjects. A compliant BG result was defined as within 15% of a reference plasma value (for BG ≥100 mg/dL [5.55 mmol/L]) or within 15 mg/dL (0.83 mmol/L) (for BG <100 mg/dL [5.55 mmol/L]). The proportion of compliant readings in each study was compared against a predetermined accuracy standard similar to, but more lenient than, current regulatory standards. Other metrics of accuracy included the overall compliance proportion; the proportion of extreme outlier readings differing from the reference value by >20%; modified Bland-Altman analysis including average bias, coefficient of variation, and 95% limits of agreement; and proportion of readings with no clinical risk as determined by the Surveillance Error Grid. RESULTS The different accuracy metrics produced almost identical BGM rankings. Six of the 18 systems met the predetermined accuracy standard in all three studies, 5 systems met it in two studies, and 3 met it in one study. Four BGMs did not meet the accuracy standard in any of the three studies. CONCLUSIONS Cleared BGMs do not always meet the level of analytical accuracy currently required for regulatory clearance. This information could assist patients, professionals, and payers in choosing products and regulators in evaluating postclearance performance.
Parallel aggregated MAB framework for source selection in multi-antenna RF harvesting circuit

Recently, the circuits capable of RF energy harvesting (RFEH) simultaneously from multiple dedicated RF sources have been developed. To enable RFEH from any ambient and unknown RF sources (operating in distinct frequency bands), such circuits need the capability to characterize RF sources. In this paper, a new characterization and selection policy (CSP) using parallel and aggregated multi-armed bandit (PA-MAB) framework has been proposed to aid optimum RF source selection in multi-antenna RFEH circuits. The novel contributions of this paper are, 1) Parallel framework which allows simultaneous selection of multiple optimal arms (i.e. RF sources), 2) Bayesian approach based Thompson Sampling algorithm to accomplish the characterization and selection tasks, 3) Bayesian inference to estimate the RF potential of individual band from the aggregated energy harvested from multiple chosen bands, and 4) Tunable RFEH duration to minimize the number of frequency band switching and increase RFEH duration. Derived theoretical performance bounds, as well as simulation results, validate the superiority of the proposed CSP over existing CSPs in stationary as well as quasi-stationary spectrum environments.
Signal Parameter Estimation for Passive Bistatic Radar With Waveform Correlation Exploitation

This paper addresses the problem of target delay and Doppler frequency estimation for passive bistatic radar employing noncooperative illuminators of opportunity (IOs), where the receivers are contaminated by nonnegligible noise, clutter, and direct-path interference. A parametric approach is proposed by modeling the unknown signal transmitted from the IO as an autoregressive process whose temporal correlation is jointly estimated and exploited for passive estimation. An iterative estimator based on the expectation-maximization (EM) principle is utilized to solve this highly nonlinear problem. We also discuss the initialization of the EM-based estimator and a fast implementation based on the fast Fourier transform and interpolation techniques. In addition, we derive the Cramér–Rao lower bound for the estimation problem to benchmark the performance of the proposed estimator. Simulation results show that the proposed estimator behaves similarly to a clairvoyant EM estimator, which assumes knowledge of the IO waveform covariance matrix, and significantly outperforms other methods that ignore the waveform correlation.
Development of a half bridge circuit for decoupling second harmonic power in single phase system

This paper presents a suitable switching scheme in order to decouple second harmonic power in single phase systems. Single phase ac/dc or dc/ac systems are subjected to harmonic disturbance caused by ripple power with double line frequency. This issue can be eliminated by installing bulky electrolytic capacitors in dc link. But this could result in lower power density and reduction of lifespan. A symmetrical half bridge circuit that utilizes the dc link capacitors for absorbing ripple power is proposed in this paper. Two switches and a small filtering inductor are the additional elements in the circuit. By this method the capacitance can be reduced to one tenth. Simulation of the circuit in MATLAB is presented.
Kinematic Evidence for an Embedded Protoplanet in a Circumstellar Disk

Disks of gas and dust surrounding young stars are the birthplace of planets. However, the direct detection of protoplanets forming within disks has proved elusive to date. We present the detection of a large, localized deviation from Keplerian velocity in the protoplanetary disk surrounding the young star HD 163296. The observed velocity pattern is consistent with the dynamical effect of a two-Jupiter-mass planet orbiting at a radius ≈260 au from the star.
A real value negative selection algorithm based on antibody evolution for anomaly detection

Traditional negative selection algorithm generates immune detectors randomly, when the antigens distribute complicatedly and unevenly, the detectors are difficult to generate in the gap which between self samples and nonself samples. On the contrary, the detectors are redundant in the regions where antigens distribute sparsely. To deal with this limitation, this paper proposes a real value negative selection algorithm based on antibody evolution (AERNSA). AERNSA contains two kinds of antibody evolution: evolution based on “distribution of antigens” and evolution based on “antibody competition”. The two kinds of evolution can guarantee the detectors to be effectively generated in the region where antigens distribute densely and to reduce the redundant detectors in the area where antigens distribute sparsely. The experimental results show that, on the artificial dataset Rectangle (2D) and the UCI standard datasets, compared with the classical RNSA and V-detector algorithm, AERNSA can significantly improves the detection rate with fewer detectors and shorter training times.
Macrophage MicroRNAs as Therapeutic Targets for Atherosclerosis, Metabolic Syndrome, and Cancer

Macrophages play a crucial role in the innate immune system and contribute to a broad spectrum of pathologies in chronic inflammatory diseases. MicroRNAs (miRNAs) have been demonstrated to play important roles in macrophage functions by regulating macrophage polarization, lipid metabolism and so on. Thus, miRNAs represent promising diagnostic and therapeutic targets in immune disorders. In this review, we will summarize the role of miRNAs in atherosclerosis, metabolic syndrome, and cancer by modulating macrophage phenotypes, which has been supported by in vivo evidence.
Advances and challenges in barcoding of microbes, parasites, and their vectors and reservoirs

SUMMARY DNA barcoding is now a common tool in parasitology and epidemiology, which require good methods for identification not only of parasites and pathogens but vectors and reservoirs. This special issue presents some advances and challenges in barcoding of microbes, parasites, and their vectors and reservoirs. DNA barcoding found new applications in disease ecology, conservation parasitology, environmental parasitology and in paleoparasitology. New technologies such as next-generation sequencing and matrix-assisted laser desorption–ionization time-of-flight have made it now possible to investigate large samples of specimens. By allowing the investigation of parasites at the interface between environment, biodiversity, animal and human health, barcoding and biobanking have important policy outcomes as well as ethics and legal implications. The special issue ‘Advances and challenges in the barcoding of parasites, vectors and reservoirs’ illustrates some recent advances and proposes new avenues for research in barcoding in parasitology.
Unified service delivery framework for 5G edge networks

Global mobile traffic pattern is recently experiencing a paradigm shift largely influenced by the exponentially growing social networking services. These services are uniquely characterized by bandwidth-intensive asynchronously accessed multiple-object based popular contents. Traditional mobile networks have not been designed to cater to these new requirements. Consequently, in 5G networks there is a need to bring in novel architectural enhancements directed towards efficient network performance in terms of service delivery. Previous works in literature have proposed edge node caching based approaches. However, the treatment is not pragmatic as it is not linked opportunistically with contents and delivery methods diversity. In this paper, first we present a service-level multi-connectivity approach that leverages the combined potential of multicast and unicast in disseminating contents/sub-contents. Further, we extend the approach to build a unified service delivery framework while incorporating proximal Device-to-Device (D2D) clusters and relay systems. We propose a bandwidth resource effective method of initial spreading of cache-able contents via multicast delivery and provide an algorithm for selecting caching devices directed to maximize the coverage of contents along with optimizing resource cost and latency performance for the network. We show with simulation results the proposed system brings significant performance gains over previous approaches for both synchronous and asynchronous contents.
Modeling small cell lung cancer (SCLC) biology through deterministic and stochastic mathematical models

Mathematical cancer models are immensely powerful tools that are based in part on the fractal nature of biological structures, such as the geometry of the lung. Cancers of the lung provide an opportune model to develop and apply algorithms that capture changes and disease phenotypes. We reviewed mathematical models that have been developed for biological sciences and applied them in the context of small cell lung cancer (SCLC) growth, mutational heterogeneity, and mechanisms of metastasis. The ultimate goal is to develop the stochastic and deterministic nature of this disease, to link this comprehensive set of tools back to its fractalness and to provide a platform for accurate biomarker development. These techniques may be particularly useful in the context of drug development research, such as combination with existing omics approaches. The integration of these tools will be important to further understand the biology of SCLC and ultimately develop novel therapeutics.
Theoretical Design of Plasmonic Refractive Index Sensor Based on the Fixed Band Detection

In this paper, we theoretically and numerically reported a simple plasmonic sensor design for the accurate detection of refractive index (RI). The sensing property was characterized by a derived theoretical model, which demonstrated the accurate sensing by measuring the intensity of a fixed narrow passband. It was found that the coupling phase modulation caused by the analyte was the main mechanism of the plasmonic sensing. The main advantage of this sensor design was that the sensing response band (or resonance wavelength) was fixed and narrow, even when the RI of analyte increases. Thus, an optical detector with certain working wavelength range can be used to detect the wide range of the RI, this was also confirmed by a two times narrower range than the common used approach in detecting the same analyte. The specific sensor design and the results may provide some guidance for the integrated plasmonic sensor design and make the sensor more flexible in the RI detecting.