Miracle-dz/UniFAR-FTUs huggingface dataset:
Convective diffusive mixing in concentration polarization: from Taylor dispersion to surface convection

Abstract We analyse the steady-state convection–diffusion mixing of a solute by a creeping circulatory flow in a long sealed rectangular two-dimensional channel with impermeable sidewalls and fixed different solute concentrations at the two opposite edges. Solution circulation is due to a constant velocity slip along the sidewalls and a back flow along the channel axis. This simple model distils the essence of circulation in concentration polarization of an electrolyte solution under a DC electric current in a micro-channel sealed by an ion-selective element (a nano-channel or a cation exchange membrane). It is observed that in the slow circulation regime (small $Pe$ numbers) the solute flux through the channel is governed by the Taylor–Aris dispersion mechanism, i.e. the flux is driven by the cross-sectional average axial concentration gradient, whereas upon increase in $Pe$ this mechanism fails. The general question addressed is where the system goes after the breakdown of the Taylor–Aris dispersion regime. In order to find out the answer, the following specific questions have to be addressed. (1) How does the Taylor–Aris dispersion mechanism break down upon increase in $Pe$ ? (2) Why does it break down? (3) What is the role of the channel aspect ratio in this breakdown? The answers to these questions are obtained through analysing a hierarchy of suitable auxiliary model problems, including the unidirectional zero discharge channel flow and the circulatory analogue of plane-parallel Couette flow, for which most of the analysis is done. They may be summarized as follows. Upon increase in circulation velocity, the Taylor–Aris dispersion mechanism fails due to the formation of lateral non-uniformities of longitudinal solute concentration gradient driving the dispersion flux. These non-uniformities accumulate in protrusion-like disturbances of the solute concentration (wall fingers) emerging near the channel sidewall at the flow exit from the edge. Wall fingers propagate along the sidewalls with increase in $Pe$ and eventually reach the opposite channel edges, transforming into narrow surface convection layers. These layers, together with the edge diffusion layers, form a closed mass transport pattern carrying most of the mass flux through the channel with the bulk largely excluded from the transport. The formation of this pattern finalizes the transition from Taylor–Aris dispersion to the surface convection regime. For large circulation velocities, concentration distribution in the surface convection layers attains an oscillatory spiral structure reminiscent of thermal waves in heat conduction.
Evaluation of tomato ( Solanum lycopersicum L.) hybrids for growth and yield attributes under coastal conditions of Andhra Pradesh

An investigation was undertaken with fifty mustard genotypes to study the correlation and path coefficient analysis of twelve yield contributing characters. Correlation analysis revealed that seed yield per plant is positively and significantly correlated with harvest index followed by number of secondary branches per plant and number of siliquae per plant at genotypic level. Path coefficient analysis revealed that days to maturity, number of secondary branches per plant, number of siliquae per plant, siliqua length, 1000 seed weight, harvest index and oil content had direct positive effect on seed yield per plant. Whereas, days to 50% flowering, plant height, number of primary branches per plant and number of seed per siliqua had direct negative effects on seed yield per plant both at genotypic and phenotypic levels. Based on the results it has been concluded that harvest index, number of secondary branches per plant and number of siliquae per plant exerted high correlation and direct influence on seed yield per plant. These traits may be considered for selection and to improve the yield of mustard genotypes.
Implementing Blended Learning Approach for Enhancement of Scientific Attitude of Undergraduate Students

COVID-19 has changed the teaching-learning scenario all around the globe as educational institutions are functioning in a hybrid mode. Blended Learning or Hybrid Learning approach has been a great boon during the pandemic. The blended learning approach mixes online teaching with traditional offline teaching methods to get the best of both approaches. Scientific attitude is a requirement of today's multicultural society for a peaceful and meaningful living. The present research determines the scientific attitude of undergraduate students in blended learning situations. A module of one week duration for the course 'Assessment of Learning' was prepared and implemented for the students of Integrated BA-B.Ed. programme using the Blended Learning approach. The findings indicate a significant enhancement in the scientific attitude of undergraduate students after implementing the blended learning approach. The present research recommends the blended learning approach in the classroom to maximize learning outcomes. The results also provide an idea to implement flexible teaching methods to cater to the diverse learning needs of learners.
Convective methods of pumping and drag reduction

It is the convection of the velocity field by itself that renders many fluid mechanics problems mathematically challenging, and produces complicated, and often non-intuitive flow phenomena. Pumping and drag reduction are effectively related concepts, in that they both involve increasing the volume flux of the fluid. In this work, we consider three different methods of pumping and drag reduction, all of which result, partially or entirely, from the effect of convection. The first of these methods is the drag reduction obtained by the addition of elastic polymers to a turbulently flowing liquid. This effect is not well understood, and a complete physical explanation of the phenomenon remains to be made. However, it is clear that the polymer has the capacity to transport energy and momentum within the fluid, and energy may also dissipate within the polymer itself. In this work, it is proved that the addition of elastic polymers to a turbulent flow cannot reduce the drag to a level below that of the equivalent laminar flow. This proof can also be applied to similar methods of drag reduction, such as the presence of surfactant micelles within a turbulently flowing liquid and the presence of sand particles within high winds and water droplets within cyclones. The second method is known as "transpiration", and consists of a dynamic regime of blowing and suction at the wall of the pipe or channel which imparts no net volume flux upon the flow. Using a perturbation analysis, the pumping effect of transpiration has been quantified in this work. It is shown that this pumping results from convection, and relies on the presence of large velocity gradients within the flow. The third method consists of oscillating waves in the wall of the pipe or channel. This has particular relevance to the valveless impedance pump, which consists of a thin tube, one section of which is elastic and is subjected to rhythmic pinching at some point offset from its centre. This pinching induces oscillating waves within the wall of the tube, which in turn induce a flow. The flow induced by small-amplitude oscillations, in the wall, has been derived through a perturbation analysis. In this way, we are able to separate the effect of convection from the more readily intuitive dragging effect that the wave has upon the fluid, and thereby quantify the importance of convection in such systems. It is found that even within small tubes, the effect of convection remains generally of the same order of magnitude as the dragging effect, and that no effective model of the valveless impedance pump could safely neglect the effect of convection.
Traditional uses, phytochemistry and pharmacology of Commelina diffusa Burm: An updated systematic review

The goal of this research is to compile information on Commelina diffusa 's traditional applications, phytochemistry, and pharmacological activity. Scientific databases such as PubMed, Google, Google Scholar, and Research gate were searched using certain keywords. It's been used for centuries to treat urinary tract infections, swellings, inflammation, diarrhoea, hemorrhoids, conjunctivitis, and ophthalmia. Alkaloids, flavonoids, saponins, tannins, cardiac glycosides, terpenoids, and steroids were discovered by phytochemical analysis. The existence of 21 phytochemical components was confirmed by GC-MS spectrum profiles, the majority of which were sterols, terpenoids, and alkanes. Commelina diffusa contains anti-inflammatory, antioxidant, antibacterial, and antifungal, nephro-protective, hepatoprotective, diuretic and CNS depressant properties, according to scientific evidence. Toxicologically, there was no evidence of toxicity. More research is needed to determine the processes that mediate the plant's bioactivities in connection to therapeutic purposes, as well as to look into any potential toxicity in preparation for future clinical trials.
Transcranial random noise stimulation of the primary visual cortex but not retina modulates visual contrast sensitivity

Transcranial random noise stimulation (tRNS) has been shown to significantly improve visual perception. Previous studies demonstrated that tRNS delivered over cortical areas acutely enhances visual contrast detection of stimuli when tRNS intensity is optimized for the individual. However, it is currently unknown whether tRNS-induced signal enhancement could be achieved within different neural substrates along the retino-cortical pathway and whether the beneficial effect of optimal tRNS intensities can be reproduced across sessions. In 3 experimental sessions, we tested whether tRNS applied to the primary visual cortex (V1) and/or to the retina improves visual contrast detection. We first measured visual contrast detection threshold (VCT; N=24, 16 females) during tRNS delivery separately over V1 (no tRNS, 0.75, 1, 1.5mA) and over the retina (no tRNS, 0.1, 0.2, 0.3mA), determined the optimal tRNS intensities for each individual (ind-tRNS), and retested the effects of ind-tRNS within the sessions. We further investigated whether we could reproduce the ind-tRNS-induced modulation on a different session (N=19, 14 females). Finally, we tested whether the simultaneous application of ind-tRNS to the retina and V1 causes additive effects. We found that at the group level tRNS of 0.75mA decreases VCT compared to baseline when delivered to the V1. Beneficial effects of ind-tRNS could be replicated when retested within the same experimental session but not when retested in a separate session. Applying tRNS to the retina did not cause a systematic reduction of VCT, irrespective of whether the individually optimized intensity was considered or not. We also did not observe consistent additive effects of V1 and retina stimulation. Our findings demonstrate that V1 seems to be more sensitive than the retina to tRNS-induced modulation of visual contrast processing. Significance statement Our findings confirm previous evidence showing acute online benefits of tRNS of V1 on visual contrast detection in accordance with the stochastic resonance phenomenon. We further extend it, demonstrating that the optimal tRNS intensity varies among participants, but when individually tailored it can improve visual processing when re-tested within the experimental session. The tRNS-induced enhancement in visual sensitivity seems to be specific for cortical contrast processing as stimulation of the retina did not lead to systematic effects.
RELATIONSHIP OF T704C AGT GENE POLYMORPHISM WITH RESISTANT ARTERIAL HYPERTENSION IN UZBEK POPULATION

Objective: to study the association of T704C polymorphism of AGT gene with resistant arterial hypertension (AH) in Uzbek population. Design and method: Study included 178 patients with AH I–III degree of both sexes. The mean age of patients was 57.15 ± 11.01 years, duration of AH was 9.55 ± 5.75 years. Genotyping of the T704C polymorphism of the AGT gene was performed using real-time PCR using gene-specific primers of allele-specific probes. Relative risk (RR) was calculated using genetic models. Calculations were performed using the online program “Calculator for calculating statistics in case-control studies”. The results of all studies were considered statistically significant at p<0.05. Results: Patients were divided into two groups: 1 - patients with resistant AH (cases, n = 61) and 2 - patients with controlled hypertension (controls, n = 117). TT genotype - determined in 16.4%, TC genotype - in 32.8%, CC genotype - 50.8%, 2 = 16.279, p = 0.000. The allelic distribution showed the predominance of C allele: C allele - 67.2%, T allele - 32.8%, ⇙2 = 27.557, p = 0.000. In group 2, C allele in 52.6%, T allele in 47.4%, respectively, ⇙2 = 1.034, p = 0.309. The ratio of TT:TC:CC- genotypes was as follows: 20.5%: 53.8%: 25.6%, ⇙2 = 33.923, p = 0.000. An analysis revealed an association of the C allele T704C of the AGT gene polymorphism with resistant AH. 61 patients with resistant AH of group 1, the C allele was more common than in patients with of group 2 (67.2%; ⇙2 = 7.05; P = 0.008; OR = 1.85, 95% CI 1.17-2.92) and 32.8% had T allele. Accumulation of CC genotype among patients of group 1 (50.8%; ⇙2 = 11.59; P = 0.003; OR = 3.00, 95% CI 1.56-5.75), while TC genotype was found in 32, 8% of cases and TT genotype in 16.4% of cases. Whereas in the 2nd group, the CC genotype was less common - in 25.6% of cases than the TCgenotype (53.8%) cases. Conclusions: The results obtained indicate a significantly greater accumulation of the C-allele of T704C polymorphism of the AGT gene among patients with resistant hypertension. The C allele and CC genotype T704C of AGT gene polymorphism are associated with resistant hypertension in the Uzbek population.
Signalling over a Gaussian channel with feedback and autoregressive noise

We study in detail the case of first-order regression, but our results can be extended to the general regression in a straightforward manner. An average energy constraint ((1.2) below) is imposed on each signal. In Section 2 we give an optimal linear signalling scheme (definition and proof in Section 4) for this channel. We conjecture that this scheme is optimal among all signalling schemes. Then the capacity C of the channel is (see Section 5) – log b, where b is the unique positive root (in x) of the equation x 2 = (1 + g 2(1 + |α|x)2)–1. Here a is the regression coefficient, and g 2 is the ratio of the average energy per signal to the variance of the noise. An equivalent expression is C = ½log(1 + g2(1 + |α| b)2).
CNN-LSTM Based Stress Recognition Using Wearables

Mental health diseases such as depression, anxiety, and heart-related disorders are a big concern in today’s life. As a result, it is now crucial to monitor stress levels. Here, we propose and suggest a deep learning hybrid approach convolution neural network-long short-term memory (CNN-LSTM) model that can recognize stress. Electrocardiogram (ECG), electromyography (EMG), body temperature, electrodermal activity (EDA), and respiration biomedical signals vary, when a human being is exposed to stress. Physiological signals can be measured using wearable devices, which can help measure stress. Therefore, it is possible to recognize stress using wearables-based physiological signals. For stress detection, the deep learning approach CNN-LSTM was implemented for feature learning and three-class stress classification (baseline, stress, amusement). To evaluate the model performance on stress detection, confusion matrix, and accuracy were used. The accuracy obtained by the proposed model was 90.20 % for stress classification, which is higher as compared to other previous studies. Consequently, the proposed model can help people in stress management in office working environments, in driving conditions, or everyday life. Furthermore, integrating the proposed model with other mechanisms such as attention and explainability may become more accurate and capable of stress detection and healthcare systems development.
The effect of bacteria inoculation on the lignocellulose degradation and the microbial properties during cow dung composting

Liuyan Zhou Xinjiang Academy of Agricultural Sciences Xinping Yang Xinjiang Academy of Agricultural Sciences Yuqing Xie Xinjiang Academy of Agricultural Sciences Xiaowu Wang Xinjiang Academy of Agricultural Sciences Jinping Dai Xinjiang Academy of Agricultural Sciences Zhifang Wang Xinjiang Academy of Agricultural Sciences Huitao Zhang Xinjiang Academy of Agricultural Sciences Lei Feng (  zly_20181201@163.com ) Xinjiang Academy of Agricultural Sciences
The CHAIN WRITING METHOD IN LEARNING WRITING FOR INFORMATION TECHNOLOGY FACULTY STUDENTS: The Effectiveness

This study purposes in determining the effectiveness of students writing ability on descriptive text being taught using the Chain Writing Method for the B class of Informatics Engineering Study Program Balitar Islamic University 2020/2021 academic year. This research is an experimental research, which uses the chain writing method to find out its effectiveness from student learning outcomes. The population of this study were first semester students of Informatics Engineering Study program which consisted of 21 students as a sample. The researchers applied one group pretest posttest. The sampling technique is random sampling. The method used is a quasi-experimental design. The pretest result done by Informatics Engineering students shown the average was 44.19%. The pre-test was conducted by researcher in March 2020. Then it can be concluded that their Writing Descriptive text ability are not good enough. The results of data analysis, known that the chain writing method is more effectively used in learning to write descriptive text for B class of Informatics Engineering students. It has significance difference in mean of determining by précising statistics of dependent T-test. From the calculating result of the t-test found that the t-value obtained was 5,959, while the required critical t-value at p> . 05, the level of significance of the two tailed test is 2.086 (df = 20), p> . 01 the two tailed significant level of test was 2.845 (df = 20). The data results of this research indicates that there is a significance difference in pretest and posttest score result. This proves that the chain writing method is effective method in learning the descriptive texts for the informatics engineering class in the 2020/2021 academic year.
Demystifying Digital Resilience in Online Teaching: using the Technology Acceptance Model to Magnify Human Factors

- The rapid advancement of technology in the learning environment has accelerated the digitalization of education, necessitating academicians’ embrace of digitalization in teaching and learning to meet the demand for educational activities. While it was anticipated that academicians would effectively accept the new changes, the transformation of online teaching practices spawned complexities. This study aims to comprehend the behaviour and attitude of academics toward online teaching based on a quantitative survey of 142 respondents (N = 142). The Technology Acceptance Model (TAM) is tested for gauging people’s acceptance of technology in various settings. The TAM has been expanded in this study to assess the success of actual academics in adopting online teaching practices. The previous literature review identified self-efficacy, digital anxiety, and subjective norms as human factors in online teaching. Following identifying these variables, a conceptual model with emotional aspects was designed as a new contribution to this study. Understanding academics’ digital adoption and highlighting their attitudes and behaviours regarding the acceptance of online teaching are essential goals of this research. This study is expected to provide academics with theoretical support when deciding on human factors to include in the TAM model. This study is novel in its conceptualization of the model that employs emotional aspects as an external construct to forecast academics’ acceptance of online teaching. Results show that human factors play a vital role in academics to form attitudes and behaviour toward online teaching, which may be used as a guide for implementing online teaching.
Searches for Axion-Like Particles with NGC1275: Observation of Spectral Modulations

Axion-like particles (ALPs) can induce localised O(10%) oscillatory modulations in the spectra of photon sources passing through astrophysical magnetic fields. Ultra-deep Chandra observations of the Perseus cluster contain over $5 \times 10^5$ counts from the central NGC1275 AGN and represent a dataset of extraordinary quality for ALP searches. We use these to search for X-ray spectral irregularities from the AGN. The absence of irregularities at the O(30%) level allows us to place leading constraints on the ALP-photon mixing parameter $g_{a\gamma\gamma} \lesssim 1.5 - 5.4 \times 10^{-12} {\rm GeV}^{-1}$ for $m_a \lesssim 10^{-12}$eV, depending on assumptions on the magnetic field realisation along the line of sight. At O(10%) level two modulations are present at high statistical significance, an excess in the 2-2.2 keV region and a deficit at 3.4-3.5 keV. We are unable to account for these through conventional instrumental or astrophysical processes and, interpreted as a signal, they would correspond to an ALP-photon coupling in the range $g_{a \gamma \gamma} \sim 1-5 \times 10^{-12} {\rm GeV}^{-1}$.
Search for dark matter and unparticles produced in association with a Z boson in proton-proton collisions at √s=8 TeV

A search for evidence of particle dark matter (DM) and unparticle production at the LHC has been performed using events containing two charged leptons, consistent with the decay of a Z boson, and large missing transverse momentum. This study is based on data collected with the CMS detector corresponding to an integrated luminosity of 19.7 inverse femtobarns of pp collisions at the LHC at a center-of-mass energy of 8 TeV. No significant excess of events is observed above the number expected from the standard model contributions. The results are interpreted in terms of 90% confidence level limits on the DM-nucleon scattering cross section, as a function of the DM particle mass, for both spin-dependent and spin-independent scenarios. Limits are set on the effective cutoff scale Lambda, and on the annihilation rate for DM particles, assuming that their branching fraction to quarks is 100%. Additionally, the most stringent 95% confidence level limits to date on the unparticle model parameters are obtained.