Miracle-dz/UniFAR-FTUs huggingface dataset:
Millennials’ Intention in Stock Investment: Extended Theory of Planned Behavior

The main objective of this research was to empirically examine the interests of millennial investors in investing in stocks using the theory of planned behavior approach consisting of Attitude toward Behavior, Subjective Norms, and Perceived Behavior Control as predictors of Intention, and Actual Behavior as a consequence of Intention. In addition, this research added risk tolerance variable as a development. This research is based on the low investment interest of the Indonesian people when compared to the total population of Indonesia. Respondents in this study are investors who are in accordance with predetermined criteria, who have already invested in stock and are aged between 20-35 years in Kebumen Regency. Data collection in this study was carried out by distributing questionnaires to the respondents. The hypothesis in this research was tested using Structural Equation Modeling (SEM) through WarpPLS software version 6.0. The results of hypothesis testing in this research empirically prove that Attitude toward Behavior, Subjective Norms, and Perceived Behavior Control are predictors of Intention. In addition, this research also proves that Intention has a positive effect on millennial investors' actual behavior in investing in stocks
The Use of Chicken Feather Waste as an Adsorbent for Crude Oil Clean Up from Polluted Water

The present study aims to evaluate the use of chicken feather waste (CFW) as an absorbent for the removal of crude oil from crude oil polluted water (CPW) in comparison with commercial activated carbon (CAC) ) in Nigeria. Oil pollution, can be as a result of natural disaster like earthquake, volcanic eruption, hurricane etc., or as a result of man’s interference for example terrorism, oil bunkering, tanker and oil rig accidents. CAC have been use as adsorbent for crude oil removal from the water environment but very expensive, hence the need to develop cheaper and environment friendly adsorbents from some agricultural waste which could constitute nuisance in the environment. The pulverized chicken feathers were characterized using Rutherford Backscattering Spectrometer (RBS) and Scanning Electron Microscope (SEM) for elemental composition and the determination of surface morphology, respectively. The agricultural wastes used for this study was chicken feathers. The CFW was sourced from a local market at Ile-Ife, Osun State Nigeria, while commercial activated carbon was purchased from Uche-El Water Limited Company. The pulverized CFW was characterized using Scanning Electron Microscopy (SEM) and Original Research Article Okoya et al.; JAERI, 21(3): 43-53, 2020; Article no.JAERI. 55160 44 Particle-induced X-ray Emission (PIXE). Elemental composition of the CFW showed the presence of Na, Mg, Al, P, K, Ca, Ti, Cr, Mn, Fe, Cu, Zn, Sr, Zr, Cd, Sn, Pb and Si within the range 12.8 22566.3 ppm with agglomeration of particle. The results of the scanning electron microscope clearly showed the surface texture and morphological characteristics of CFW. The efficiencies of adsorption increased with increasing initial concentration for the two adsorbents except initial concentration of 20/30 which decreased in the case of CAC. The adsorption efficiencies for all the initial concentrations for the adsorbents is significantly different (F=16.114; P=0.000) at confidence interval of 0.05. CFW showed greater adsorption efficiency of 99.95%, followed by CAC which showed an adsorption potential of 95.08% (P=0.577 > C.I=0.05). The adsorption efficiencies obtained for the chicken feather compare very well with the activated carbon and even better as the dosages of the chicken feather increased. The result of the study shows that chicken feathers is an efficient sorbent for the mopping of crude oil spill in water.
Stability and Dynamic Performance Improvement of Speed Adaptive Full-Order Observer for Sensorless Induction Motor Ultralow Speed Operation

Although the stability of a speed adaptive full-order observer (AFO) has been studied for a sensorless induction motor (IM) ultralow speed operation, few researchers concern its dynamic performance simultaneously. To address this problem, this article proposed a novel feedback gain selection principle of an AFO considering both stability and dynamic performance. Compared with the conventional stability-based feedback gain selection, the proposed method applied the zero-point locus diagram and Bode diagram to further limit the range of stabilized feedback gain, leading to improved dynamic performance. Moreover, the robustness of the AFO is guaranteed with the proposed feedback gain under IM parameter mismatch. The validity of the proposed method is confirmed by comparative experiments.
Some recent aspects of the use of high-pressure for protein investigations in solution

Abstract Proteins play a key role in the metabolism of living organisms as, for example, catalysts (enzymes), carriers or receptors of various molecules. These marginally stable biopolymers of amino acids can be perturbed in their activity by pressure, temperature and other environmental variables as organic solvents. Changing environmental conditions can induce metabolism dysfunctions. On isolated systems, i.e. purified proteins, high pressure and other perturbing variables can be used as tools for investigation of protein structure/activity relationships and enzyme mechanisms. The elementary basic physical mechanisms of the action of high pressure upon proteins are stated in the first part of this review. This is followed by a section devoted to technical aspects, including methods for generation of high pressure, and some recent developments, namely stopped-flow spectrometry and electrophoresis under high pressure. Then, the use of pressure as a tool for investigation of enzyme mechanisms and for study.
Cell-based bioassay for compounds with prooxidant activity

There is substantial evidence from epidemiological studies that the etiology of many ‘modern’ diseases is linked in part to environmental pollution. A number of observations suggest that an imbalance in cellular oxidants and antioxidants is a critical underlying factor. Many environmental pollutants, without being redoxactive and capable of causing oxidation in vitro, are able to shift the oxidant/antioxidant balance of the cells, thus triggering pathological responses. It is difficult to assess the biological impact of mixtures of environmental pollutants because of their complexity. We propose the parallel use of normal (parental) and genetically engineered superoxide dismutase (SOD)-deficient E. coli strains, as a tool for the detection of prooxidant-acting environmental pollutants. Doubling time, viability, mutation rate, and induction of antioxidant regulons are used as parameters to assess the pollutants’ toxicity and prooxidant action. SOD-deficient E. coli is highly sensitive to agents causing oxidative stress directly or indirectly. This sensitivity can be measured and is highly reproducible. Using E. coli is advantageous because the organism is well studied, can be stored at low temperatures for a very long time, and can be grown under standard, well-defined conditions. The parallel use of SOD-deficient mutants and SOD-proficient parents permits discrimination between compounds that exert general toxicity and compounds that act as prooxidants in vivo. The bioassay was used for fast screening of potentially hazardous chemicals with pro-oxidative action.
Fates of weed seeds in soil: a seeded core method of study.

1. A method is described for the study of the fates of unprotected seeds in soil. Its key features include: (i) selection of seeds on the basis of anticipated high viability; (ii) placement of unprotected seeds in known positions in the soil; (iii) extraction of soil cores containing the seeds several times each year; (iv) elutriation of these cores and recovery of the seeds; (v) germination and viability testing of the recovered seeds. 2. Initial results for an experiment conducted with seeds of four weed species in an agricultural field in the midwestern USA are used to demonstrate the soundness of the method. 3. The strengths, weaknesses and assumptions of the method are discussed.
Fruit Stalk Extract from Chili Peppers (Capsicum annum L.) as a Natural Antioxidant to Inhibit Oxidation in Crude Palm Oil

Fruit stalk of chili pepper (Capsicum annum L.) so far is still an untapped waste. The content of active compounds in fruit and fruit stalk of chili pepper (C. annum L.) is known to have good antioxidant activity. The purpose of this study was to evaluate the extract of fruit stalk of chili pepper in inhibiting the oxidation of crude palm oil (CPO). In this study, the extraction of fruit stalk of chili pepper (C. annum L.) was carried out with n-hexane (from now on referred to as CHE) solvent and with ethanol solvent (from now on referred to as CEE). CHE and CEE were analyzed for total phenolic and flavonoid analyzes. Next, an evaluation of antioxidant activity was carried out using the DPPH method. The effectiveness test of adding the two extracts to the quality of CPO was carried out for ten days using a Completely Randomized Design (CRD) analysis. The parameters observed were peroxide numbers, free fatty acids, and iodine numbers. Data were analyzed by ANOVA and followed by a Least Significance Different (LSD) test. The results show that the total phenolic value is 0.257 mg QE/g dry weight in CEE and 0.003 mg QE/g dry weight in CHE. Total flavonoid values are 0.155 mg QE/g dry weight in CEE and 0.003 mg QE/g in CHE. IC50 values for DPPH test extract are 223.72 μg/mL in CEE and 953.77 μg/mL in CHE. The test results of the effectiveness of the two extracts against CPO show thin CEE, and CHE significantly (P <0.05) influences to CPO free fatty acids, peroxide number, and iodine number. Both extracts can protect CPO from oxidation. CEE is more effective in maintaining CPO quality for ten days with free fatty acid values (2.1%), peroxide value values 0.48 meq/kg, and iodine number 54.8. Furthermore, this result meets the CPO quality standard, according to SNI-01-2901-2006.
Regulatory change in cell division activity and genetic mapping of a tomato (Solanum lycopersicum L.) elongated-fruit mutant

Tomato elongated-fruit mutants have proven useful for elucidation and mapping of genes that regulate fruit elongation. We previously identified a novel tomato mutant, Solanum lycopersicum elongated fruit1 ( Slelf1 ), which exhibits an elongated fruit shape caused by increased cell layers in the ovary proximal region, and located the causal genes on the long arm of chromosome 8. In this study, we isolated and characterized two independent tomato mutants, Solanum lycopersicum elongated fruit2 and 3 ( Slelf2 and Slelf3 ). Histological analysis revealed that the Slelf2 mutant ovary displayed an overall elongated shape, whereas the developing ovary of the Slelf3 mutant was primarily expanded in the proximal region. We developed an intra-specific F 2 population by crossing Slelf3 with Ailsa Craig, a related cultivar. Mapping of this population confirmed that the candidate gene of the Slelf3 mutation was positioned on the short arm of chromosome 7, in a region of approximately 0.4 Mb. These results indicate that the causal gene is a novel locus differing from previous genes known to affect fruit shape elongation in tomatoes. In addition, analysis of transcript levels of genes related to cell division and expansion in the Slelf3 mutant suggested that the mutated gene most likely regulates cell division activity, predominantly in the proximal region.
Gesture recognition algorithm based on multi-scale feature fusion in RGB-D images

With the rapid development of sensor technology and artificial intelligence, the video gesture recognition technology under the background of big data makes human–computer interaction more natural and flexible, bringing the richer interactive experience to teaching, on-board control, electronic games etc. To perform robust recognition under the conditions of illumination change, background clutter, rapid movement, and partial occlusion, an algorithm based on multi-level feature fusion of two-stream convolutional neural network is proposed, which includes three main steps. Firstly, the Kinect sensor obtains red–green–blue-depth (RGB-D) images to establish a gesture database. At the same time, data enhancement is performed on the training set and test set. Then, a model of multi-level feature fusion of a two-stream convolutional neural network is established and trained. Experiments show that the proposed network model can robustly track and recognise gestures under complex backgrounds (such as similar complexion, illumination changes, and occlusion), and compared with the single-channel model, the average detection accuracy is improved by 1.08%, and mean average precision is improved by 3.56%.
Colloidal quantum dots decorated micro-ring resonators for efficient integrated waveguides excitation

Abstract Micro-ring resonators made of titanium dioxide were decorated with local light sources comprising CdSe/CdS colloidal quantum dot aggregates. The active micro-resonators are operated to achieve efficient evanescent excitation of nearby co-planar integrated waveguides. Coupled-mode analysis and numerical simulations are used to capture the dynamic of the optical interaction between locally activated resonators and integrated waveguides. In this context, we exemplify the key role of resonator intrinsic loss. Next, we show that locally activated or bus-waveguide excited resonators are in optimum waveguide interaction for the same so-called critical coupling condition, although the physical origin of this property is different for each configuration. More importantly, we found that a locally activated resonator is a fabrication imperfection tolerant configuration for the coupling light of local sources into waveguides. This remarkable property originates from the opposite change of the power cycling into the resonator and the waveguide coupling efficiency as a function of the resonator-waveguide separation gap. By operating an 8-μm-radius ring resonator with loaded quality factors around Q = 2100, we experimentally demonstrate a 5.5-dB enhancement of the power coupled into the output waveguide compared to a direct local source waveguide excitation.
Multiaperture Antenna Architecture Design for Azimuth Uniform Sampling in High-Resolution Wide-Swath SAR

Azimuth multichannel synthetic aperture radar (SAR) is an essential remote sensing device to obtain images with high resolution and wide swath (HRWS). However, using a conventional multichannel phased array antenna, azimuth uniform sampling cannot be ensured, if the operated pulse repetition frequency of the system deviates from the optimum value. A novel multichannel antenna architecture design approach in HRWS SAR is proposed for uniform sampling. Phase center positions of both transmitting aperture and receiving subapertures can be adjusted flexibly by invalidating the elements of the antenna. First, a limited number of elements of receiving subapertures can be closed to adjust receive phase center spacing. The transmit phase center could be further adjusted, if the azimuth nonuniform sampling still cannot be fully compensated for. With this multiaperture antenna architecture, azimuth uniform sampling could be ensured and system performances are obviously improved. Advantages of the proposed azimuth multiaperture antenna architecture adjust method are verified by a simulation experiment.
Image Classification with Convolutional Neural Networks Using Gulf of Maine Humpback Whale Catalog

While whale cataloging provides the opportunity to demonstrate the potential of bio preservation as sustainable development, it is essential to have automatic identification models. This paper presents a study and implementation of a convolutional neural network to identify and recognize humpback whale specimens by processing their tails patterns. This work collects datasets of composed images of whale tails, then trains a neural network by analyzing and pre-processing images with TensorFlow and Keras frameworks. This paper focuses on an identification problem, that is, since it is an identification challenge, each whale is a separate class and whales were photographed multiple times and one attempts to identify a whale class in the testing set. Other possible alternatives with lower cost are also introduced and are the subject of discussion in this paper. This paper reports about a network that is not necessarily the best one in terms of accuracy, but this work tries to minimize resources using an image downsampling and a small architecture, interesting for embedded system.
Salt-tolerant and plant growth-promoting bacteria isolated from Zn/Cd contaminated soil: identification and effect on rice under saline conditions

The bacteria of PDMCd0501, PDMCd2007, and PDMZnCd2003 were isolated from a Zn/Cd contaminated soil. They were classified as salt-tolerant bacteria in this experiment. The bacteria had indole-3-acetic acids (IAA) production, nitrogen fixation, and phosphate solubilization, under 8% (w/v) NaCl condition. Biochemical test (API 20E) and 16S rDNA sequencing identified PDMCd2007 and PDMCd0501 as Serratia sp. and PDMZnCd2003 was Pseudomonas sp. The effect of Pseudomonas sp. PDMZnCd2003 on the germination and seedlings of Oryza sativa L.cv. RD6 was determined under a salinity of 0–16 dS/m. The salinity levels of 4–16 dS/m affected to decrease germination and seedlings of rice. Comparison between uninoculated and inoculated system, however, Pseudomonas sp. PDMZnCd2003 had a negative impact on the rice growth. This unexpected effect was a case that should be concerned and studied further before application as a plant growth-promoting bacteria (PGPB).
Fold-over Regions in Nonlinear First Order PDEs

Milton F. Maritz (mfmaritz@sun.ac.za, MR ID 119990, ORCID 0000-0003-2766-8206) completed a Ph.D. in Applied Mathematics at the University of the Free State, and taught there for some years, before moving to the Department of Physics at the same university, where he taught physics for five years. In 2001, he joined the Department of Applied Mathematics at Stellenbosch University. His interests are too varied to mention here, but it suffices to say that he loves both physics and mathematics, and finds it difficult to choose.
The N and C termini of the coat proteins of potyviruses are surface-located and the N terminus contains the major virus-specific epitopes.

Summary Mild proteolysis by trypsin of particles of six potyviruses (bean yellow mosaic virus, clover yellow vein virus, Johnson grass mosaic virus, passion-fruit woodiness virus, potato virus Y and watermelon mosaic virus II) revealed that the N- and C-terminal regions of their coat protein are exposed on the particles' surfaces. The enzyme treatment removed the N-terminal region (30 to 67 amino acids long, depending on the virus) and 18 to 20 amino acids from the C terminus of the coat proteins, leaving a fully assembled virus particle composed of coat protein cores consisting of 216 or 218 amino acid residues. These core particles were indistinguishable from untreated native particles in an electron microscope and were still infectious. The core particles lacked the virus-specific surface epitopes that are recognized by the bulk of the polyclonal antibodies raised against the whole virus particles. Epitopes thought to be group-specific were located in the trypsin-resistant core protein region. The implications of these findings are discussed in relation to the similar surface location of the N- and C-terminal regions of the coat protein of other rod-shaped plant viruses and the observed common structural features displayed by isometric plant and animal viruses.
Robustness of Interval Monge Matrices in Fuzzy Algebra

Max–min algebra (called also fuzzy algebra) is an extremal algebra with operations maximum and minimum. In this paper, we study the robustness of Monge matrices with inexact data over max–min algebra. A matrix with inexact data (also called interval matrix) is a set of matrices given by a lower bound matrix and an upper bound matrix. An interval Monge matrix is the set of all Monge matrices from an interval matrix with Monge lower and upper bound matrices. There are two possibilities to define the robustness of an interval matrix. First, the possible robustness, if there is at least one robust matrix. Second, universal robustness, if all matrices are robust in the considered set of matrices. We found necessary and sufficient conditions for universal robustness in cases when the lower bound matrix is trivial. Moreover, we proved necessary conditions for possible robustness and equivalent conditions for universal robustness in cases where the lower bound matrix is non-trivial.
An Overview on Automatic Speaker Verification System Techniques

: Automatic Speaker Verification (ASV) is a widely used voice-based biometric system. Like every other biometric system, ASV is also vulnerable to malicious attacks. Replay attacks in ASV systems are a greater threat compared to other attacks. Many types of research have been conducted to find the countermeasures for the replay attacks. Feature extraction and classification are the two fundamental processes of speaker verification. A wide variety of features and classifiers were implemented in the past studies to check their performances. The feature extraction methods discussed in this paper are Mel-Frequency Cepstral Coefficients (MFCC), Linear Prediction Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC), Discrete Wavelet Transform (DWT) and Perceptual Linear Prediction (PLP). Some of the classifiers that are discussed are Gaussian Mixture Model (GMM), Gaussian Mixture Model-Universal Background Model (GMM-UBM), Hidden Markov Model (HMM), Support Vector Machine (SVM), Dynamic Time Wrapping (DTW) and deep learning networks like Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). This paper intends to focus on the various attacks in the ASV system along with these two fundamentals of the system.
Towards Anti-Interference Human Activity Recognition Based on WiFi Subcarrier Correlation Selection

As an essential technology in the field of the Internet of Things, Human activity recognition (HAR) is a well-researched topic. Recently, some state-of-the-art WiFi-based HAR systems have been presented due to its characteristics of no-invasion, no privacy leakage, and high recognition accuracy rates (RARs). However, the commodity WiFi devices for identification are usually in a complex electromagnetic environment, where the interference caused by WiFi devices from channel overlap is common and severe. Furthermore, our extensive experiments show that the performance of these pioneer WiFi-based HAR systems may degrade significantly in co-channel interference (CCI) scenarios. To solve the above problem, we propose WiAnti, a WiFi-based HAR system that is robust to CCI. Two adaptive subcarrier selection algorithms, WiAnti-Pearson and WiAnti-DTW, are proposed to mitigate the impact of CCI and to improve the recognition performance in CCI scenarios. As demonstrated in the experimental results, WiAnti-Pearson yields a 95% RAR on average, which can improve up to a 14% RAR in the presence of constant CCI. Moreover, WiAnti-DTW achieves an 8% higher RAR in the varying CCI scenario, reaching 94%.