Phenological,Nutritional and Molecular Diversity Assessment among 35 Introduced Lentil (Lens culinaris Medik.) Genotypes Grown in Saudi Arabia

Morphological, nutritional and molecular analyses were carried out to assess genetic diversity among 35 introduced lentil genotypes (Lens culinaris Medik.). The genotypes exhibited significant differences for their field parameters and some of them showed noticeable superiority. The nutritional and proximate analysis showed that some genotypes were excellent sources of proteins, essential amino acids, minerals, anti-oxidants, total phenolic contents (TPC) and total flavonoid contents (TFC) and hence, highlights lentil nutritional and medicinal potential. Sequence-related amplified polymorphism (SRAP) and amplified fragments length polymorphism (AFLP) markers were used to estimate the genetic variability at the molecular level. The existence of a considerable amount of genetic diversity among the tested lentil genotypes was also proven at the molecular level. A total of 2894 polymorphic SRAP and 1625 AFLP loci were successfully amplified using six SRAP and four AFLP primer pair combinations. Polymorphism information content (PIC) values for SRAP and AFLP markers were higher than 0.8, indicating the power and higher resolution of those marker systems in detecting molecular diversity. UPGMA (unweighted pair group method with arithmetic average) cluster analysis based on molecular data revealed large number of sub clusters among genotypes, indicating high diversity levels. The data presented here showed that FLIP2009-64L and FLIP2009-69L could be used as a significant source of yield, total protein, essential amino acids, and antioxidant properties. The results suggest potential lentil cultivation in the central region of Saudi Arabia for its nutritional and medicinal properties, as well as sustainable soil fertility crop.     

Variable reference alignment: an improved peak alignment protocol for NMR spectral data with large intersample variation

In an effort to address the variable correspondence problem across large sample cohorts common in metabolomic/metabonomic studies, we have developed a prealignment protocol that aims to generate spectral segments sharing a common target spectrum. Under the assumption that a single reference spectrum will not correctly represent all spectra of a data set, the goal of this approach is to perform local alignment corrections on spectral regions which share a common "most similar" spectrum. A natural beneficial outcome of this procedure is the automatic definition of spectral segments, a feature that is not common to all alignment methods. This protocol is shown to specifically improve the quality of alignment in (1)H NMR data sets exhibiting large intersample compositional variation (e.g., pH, ionic strength). As a proof-of-principle demonstration, we have utilized two recently developed alignment algorithms specific to NMR data, recursive segment-wise peak alignment and interval correlated shifting, and applied them to two data sets composed of 15 aqueous cell line extract and 20 human urine (1)H NMR profiles. Application of this protocol represents a fundamental shift from current alignment methodologies that seek to correct misalignments utilizing a single representative spectrum, with the added benefit that it can be appended to any alignment algorithm.     

特高压平行双回线路高阻短路下距离保护算法(英文)

特高压平行双回线路距离保护在单相接地故障时受到两回线路互感和故障电阻的不利影响。针对此问题,提出一种新的平行双回线路距离保护算法。算法的核心思想是利用故障点故障电压和故障点电流同相位的特点,并对故障相的电压、电流以及相邻一回线路的零序电流进行傅里叶变换,通过列方程,求解故障距离。还讨论了新算法在平行双回线路的一回检修或者两回线路分裂运行下的效果。理论分析和PSCAD/EMTDC仿真实验证明,该算法耐过渡电阻能力高,不受两回线路互感和负荷的影响,不会引起平行双回线路距离保护一段误动或拒动。该算法有望构成新型的特高压平行双回线路距离保护。     

High-performance flexible supercapacitors based on C/Na<Subscript>2</Subscript>Ti<Subscript>5</Subscript>O<Subscript>11</Subscript> nanocomposite electrode materials

A new solution method to synthesize Na₂Ti₅O₁₁ with titanium powder is presented, and the C/Na₂Ti₅O₁₁ nanocomposite with high specific surface area and tunnel structure as the electrode material has excellent electrochemical performance. The single electrode composed of the C/Na₂Ti₅O₁₁ nanocomposite based on carbon fiber fabric (CFF) has the highest area capacitance of 1066 mF cm^?2 at a current density of 2 mA cm^?2, which is superior to other titanates and Na-ion materials for supercapacitors (SCs). By scan-rate dependence cyclic voltammetry analysis, the capacity value shows both capacitive and faradaic intercalation processes, and the intercalation process contributed 81.7% of the total charge storage at the scan rate of 5 mV s^?1. The flexible symmetric solid-state SCs (C/Na₂Ti₅O₁₁/CFF//C/Na₂Ti₅O₁₁/CFF) based on different C/Na₂Ti₅O₁₁ mass were fabricated, and 7 mg SCs show the best supercapacitive characteristics with an area capacitance of 309 mF cm^?2 and a specific capacitance of 441 F g^?1, it has a maximum energy density of 22 Wh kg^?1 and power density of 1286 W kg^?1. As for practical application, three SCs in series can power 100 green light-emitting diodes (LEDs) to light up for 18 min, which is much longer than our previous work by Wang et al. lighting 100 LEDs for 8 min. Thus, the C/Na₂Ti₅O₁₁ nanocomposite has promising potential application in energy storage devices.     

Correlation,Kalman filter and adaptive fast mean shift based heuristic approach for robust visual tracking

Correlation tracker is computation intensive (if the search space or the template is large), has template drift problem, and may fail in case of fast maneuvering target, rapid changes in its appearance, occlusion suffered by it and clutter in the scene. Kalman filter can predict the target coordinates in the next frame, if the measurement vector is supplied to it by a correlation tracker. Thus, a relatively small search space can be determined where the probability of finding the target in the next frame is high. This way, the tracker can become fast and reject the clutter, which is outside the search space in the scene. However, if the tracker provides wrong measurement vector due to the clutter or the occlusion inside the search region, the efficacy of the filter is significantly deteriorated. Mean-shift tracker is fast and has shown good tracking results in the literature, but it may fail when the histograms of the target and the candidate region in the scene are similar (even when their appearance is different). In order to make the overall visual tracking framework robust to the mentioned problems, we propose to combine the three approaches heuristically, so that they may support each other for better tracking results. Furthermore, we present novel method for (1) appearance model updating which adapts the template according to rate of appearance change of target, (2) adaptive threshold for similarity measure which uses the variable threshold for each forthcoming image frame based on current frame peak similarity value, and (3) adaptive kernel size for fast mean-shift algorithm based on varying size of the target. Comparison with nine state-of-the-art tracking algorithms on eleven publically available standard dataset shows that the proposed algorithm outperforms the other algorithms in most of the cases.     

Electrical properties of MgAl2-2xZrxMxO4 (M = Co, Ni and x = 0.00-0.20) synthesized by coprecipitation technique using urea

This paper presents the results of a study concerning the structural and electrical properties of MgAl_2-2xZr_xM_xO₄ (x = 0.00-0.20 and M = Co²⁺ and Ni²⁺) prepared by a coprecipitation technique using urea as a precipitating agent. The X-ray diffraction data for the pure and its doped samples are consistent with the single-phase spinel and their crystallite sizes are in the range 7-20 ± 4 nm. The DC resistivity increases from 3.09 × 10⁹ Ω cm to 6.73 × 10⁹ and 8.06 × 10⁹ Ω cm whereas dielectric constant decreases from 5.80 to 5.11 and 4.95 on doping with Zr-Co and Zr-Ni, respectively. The electrical resistivity variations with increase in the dopant contents indicate two types of conduction mechanisms in operation. Several parameters such as, hopping energy (W), metal-semiconductor transition temperature (T_MS) and Debye temperature (θ_D) have also been determined. The increase in DC resistivity and decrease in dielectric constant suggest that the synthesized materials can be considered for application as an insulating and structural material in fusion reactors.     

A Miniaturized Frequency Reconfigurable Patch Antenna for IoT Applications

Wireless Personal Communications - This work presents a novel frequency reconfigurable patch antenna design for Internet of Things (IoT) applications. The proposed antenna structure has hexagonal...     

Hemodynamic Response Detection Using Integrated EEG-fNIRS-VPA for BCI

For BCI systems, it is important to have an accurate and less complex architecture to control a device with enhanced accuracy. In this paper, a novel methodology for more accurate detection of the hemodynamic response has been developed using a multimodal brain-computer interface (BCI). An integrated classifier has been developed for achieving better classification accuracy using two modalities. An integrated EEG-fNIRS-based vector-phase analysis (VPA) has been conducted. An open-source dataset collected at the Technische Universität Berlin, including simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) signals of 26 healthy participants during n-back tests, has been used for this research. Instrumental and physiological noise removal has been done using preprocessing techniques followed by individually detecting activity in both modalities. With resting state threshold circle, VPA has been used to detect a hemodynamic response in fNIRS signals, whereas phase plots for EEG signals have been constructed using Hilbert Transform to detect the activity in each trial. Multiple threshold circles are drawn in the vector plane, where each circle is drawn after task completion in each trial of EEG signal. Finally, both processes are integrated into one vector-phase plot to get combined detection of hemodynamic response for activity. Results of this study illustrate that the combined EEG-fNIRS VPA yields considerably higher average classification accuracy, that is 91.35%, as compared to other classifiers such as support vector machine (SVM), convolutional neural networks (CNN), deep neural networks (DNN) and VPA (with dual-threshold circles) with classification accuracies 82%, 89%, 87% and 86% respectively. Outcomes of this research demonstrate that improved classification performance can be feasibly achieved using multimodal VPA for EEG-fNIRS hybrid data.     

A cross layer error control scheme for efficient WLAN multimedia streaming

Multimedia Tools and Applications - Efficient streaming of bandwidth intensive and delay sensitive multimedia contents over error prone wireless links has proven to be one of the most challenging...     

Initial Plasma Formation in the GLAST-II Spherical Tokamak

This paper reports the initial plasma formation in glass spherical tokamak (GLAST-II) with electron cyclotron resonance pre-ionization assisted startup. Initially, a plasma current of 3 kA has been produced for duration of about 0.5 ms after establishing optimum conditions for microwave absorption at 2.45 GHz. Plasma current is then enhanced up to 5 kA by applying a small vertical magnetic field that provides additional plasma heating and shaping. Applied vertical field is optimized experimentally and optimal value is found to be 40 Gauss for this experiment. Plasma current and loop voltage are monitored by using Rogowski coil and toroidal loop of wire. A fast framing camera (5000 fps) is used for temporal investigation of plasma during the discharge scenario. A fast photodiode (BPX-65) and USB4000 spectrometer are used to record the signature of plasma current and the impurity content (O₂, H etc.). Cross-sectional average electron temperature is also estimated from plasma resistivity and found to be 6.1 eV for maximum plasma current of 5 kA.