Miracle-dz/UniFAR-FTUs huggingface dataset:
The intracellular auxin homeostasis regulators PIN5 and PIN8 have a divergent membrane topology in Arabidopsis thaliana root cells

PIN proteins establish the auxin concentration gradient, which coordinates plant growth. PIN1-4 and 7 localized at the plasma membrane (PM) and facilitate polar auxin transport while the endoplasmic reticulum (ER) localized PIN5 and PIN8 maintain the intracellular auxin homeostasis. Although an antagonistic activity of PIN5 and PIN8 proteins in regulating the intracellular auxin homeostasis and other developmental events have been reported, how the two proteins which localize at the same intracellular compartment antagonize each other remains unclear. Combining immunolocalization, pH-dependent fluorescent quenching, and topology prediction programs, we mapped the membrane topology of PIN5 and PIN8 in Arabidopsis thaliana root cells. Our results indicate that, except for the similarities in the orientation of the N-terminus, PIN5 and PIN8 have an opposite orientation of the central hydrophilic loop and the C-terminus, as well as an unequal number of transmembrane domains (TMDs). PIN8 has ten TMDs with groups of five alpha-helices separated by the central hydrophilic loop (HL) residing in the ER lumen, and its N- and C-terminals are positioned in the cytoplasm. However, topology of PIN5 comprises nine TMDs. Its N-terminal end and the central HL face the cytoplasm while its C-terminus resides in the ER lumen. Overall, the divergent membrane topology of PIN5 and PIN8 provides a possible explanation for the mutually opposing activity of these intracellular auxin homeostasis regulators.
Parameter Tuning Method for Multi-agent Simulation using Reinforcement Learning

This study proposes a reinforcement-learning-based method for efficient parameter tuning in multi-agent simulations (MAS). MAS usually has a high computational burden because of the agents; thus, it is important to tune its parameters efficiently. Our proposed method is based on a deep deterministic policy gradient (DDPG) and has three additional components proposed in this study: an action converter, a redundant full neural network actor, and a seed fixer. As an experiment, we employed a parameter-tuning task in an artificial financial market simulation. A Bayesian estimation-based method was employed as a baseline. The results show that our model tends to outperform the baseline in terms of tuning performance and indicate that the three additional components of the proposed method are essential. Moreover, the critic of DDPG effectively functions as a surrogate model, that is, as an approximate function of the simulation, which allows the actor to appropriately tune the parameters.
Predicting preeminent Machine Learning Approach on Stars

Numerous statistical methods, including “machine learning”, “predictive modeling” and “data mining” are included in predictive analysis. One of the most intriguing and fascinating recent developments in artificial intelligence is machine learning. With the rise in technology the numbers of algorithms are also increasing for training models and based on the dataset the algorithms are being selected for training a good model with higher accuracy. In this paper I have used a stars dataset imported from Kaggle for predicting the spectral classes of the stars M and O based on the temperature, and have used regression algorithms for predicting it, since it contains continuous real values and regression algorithms work best for this type of cases for predictions and outputs with higher accuracy. By implementing the algorithms, I found that Random Forest Regressor works best with a higher R2_score.
Implementation of Various Analog Filters in EM Wave Domain

In this paper, the variation of gain against the frequency of high pass filter, band pass filter, band reject filter in electromagnetic radiation domain, and electromagnetic shielding domain is compared. Electromagnetic wave domain on MA TLAB has been created, in which electromagnetic radiation is transmitted in negative y-direction, its electric field component is oriented in the negative z-direction and the magnetic field component is oriented in the negative x-direction. Analog high pass filter, band pass filter, band reject filter characteristics have been implemented in electromagnetic radiation domain. Then the comparison of characteristics of analog high pass filter, band pass filter and band reject filter in electromagnetic domain and electromagnetic shielded domain has been done. And the results acquired after comparison are inspected. After providing a shield to the high pass filter, band pass filter and band reject filter circuit, the original characteristics of the filter have been recovered.
Worst Case Uncertainty Construction via Multifrequency Gain Maximization With Application to Flutter Control

In the analysis of uncertain systems, we often search for a worst case perturbation that drives the $H_\infty $ gain of the system to the maximum over the set of allowable uncertainties. Employing the classical technique, an uncertainty sample is obtained, which, indeed, maximizes the gain but only at the single frequency where that maximum occurs. In contrast, this article considers a method to calculate a worst case perturbation that maximizes the gain of a system with mixed uncertainty at multiple frequencies simultaneously. This approach involves a nonlinear optimization that selects the worst case value of the uncertain parameters and the application of the boundary Nevanlinna–Pick interpolation to calculate the dynamic uncertainty sample. Such a perturbation can be used to augment Monte Carlo simulations of uncertain systems, especially if the system has multiple resonance frequencies. The worst case analysis of a flutter control system designed for a small flexible aircraft is provided to demonstrate the applicability of the proposed method.
Comparing Different Pedestrian Representations for Testing Automated Driving Functions in Mixed Reality Environments

Validation of safety-critical driver assistance systems is usually performed on test tracks in scenario-based test procedures like the Euro NCAP safety assessment program. With higher automation, the test effort increases exponentially due to the system complexity, which requires new and more efficient test methods that also consider the complexity of every-day road traffic situations. So far, mixed reality environments have been proposed to provide an efficient way of virtual testing and also allow for more realistic interactions between vulnerable road users and automated vehicles. In this work, we investigate the use of different pedestrian representations with varying levels of fidelity (articulated pedestrian target, animated pedestrian, full-body motion capture) regarding their impact on the performance of an exemplary AEB driving function. The results show that the detection of the underlying algorithm and the function's response differ only slightly for the three pedestrian representations. We conclude that all the proposed methods of representing human movement are applicable for testing automated driving functions in mixed reality and can be deployed, depending on the specific test scenario and available resources.
Power Distribution in Clustered NOMA

Non-Orthogonal Multiple Access (NOMA) technology is developed for effective usage of spectrum in next generation wireless network. This paper focuses on power allocation with user clustering in a NOMA system to improve network sum data rate. The enhancement of user data rate is achieved by grouping users by K-means algorithm based on channel quality indicator and signal to noise ratio. The membership function of each cluster is defined for Inter cluster power scheduling. Weight factor of each user within a cluster determines intra cluster power allocation. The channel state information of the user in the busy hour is measured using Shadow Lab App developed by Chandhar Research Lab of India. Simulation results show that the proposed scheme outperforms clustered NOMA. The sum data rate is increased with the increase of clusters for poor channel condition in the proposed two stage power distribution scheme.
A Note on the Artinian Cofinite Modules

In this paper we shall prove the following result, which is a generalization of the Melkersson's main result proved in [16]. Let (R, 𝔪) be a Noetherian local ring such that is integral over R. Let I be a proper ideal of R and A be an Artinian R-module. Then A is I-cofinite if and only if Rad(I + Ann R (A)) = 𝔪. Also, we present an example to show that this result does not hold for an arbitrary local Noetherian ring in general. As an application of this result we prove the following generalization of the Lichtenbaum-Hartshorne Vanishing Theorem (see [5, Theorem 8.2.1]). Let (R, 𝔪) be a Noetherian local ring such that is integral over R. Let I an ideal of R and M be a nonzero finitely generated R-module of dimension n. Then the following conditions are equivalent: (i) . (ii) There exists a prime ideal 𝔭 in AsshR(M) such that Rad(𝔭 +I) = 𝔪.
Natural Self-Excitation of the Induction Generator

This paper presents a methodology for the analysis of the natural self-excitation process under no load of the Induction Generator (IG). A spatial vector mathematical model of the Self-Excited Induction Generator (SEIG) is used as a starting point and the effect of the magnetic non-linearity on the magnetization inductance is considered, then the natural self-excitation region is determined and the self-excitation process of the Induction Generator is simulated. The methodology is applied using a three-phase induction motor with squirrel cage rotor of 3 HP, 230 V, 60 Hz, 4 poles, star connection and efficiency class IE1. Finally, simulations of the transient in the first instants are presented to verify the conditions that must be fulfilled to trigger the natural self-excitation process of the induction generator.
Perceived Trust and Enjoyment: Predicting Behavioural Intention to use Mobile Payment Systems

This study examines the behavioral intention to use mobile payment services based on the technology acceptance model (TAM). The data was collected from users who had experience using FastPay and ZainCash Applications, the valid questionnaire was 209. The smart-PLS analyzed the proposed model, and the measurement and structural analysis were run to ensure reliability, validity, and to examine the proposed hypotheses. The results indicated that the perceived ease of use, perceived usefulness, perceived trust, and perceived enjoyment have a positive and significant impact on behavioral intention to use mobile payment. This study can assist the providers of mobile payment services in making decisions on how to grow their user base, as well as provide a clear image to the m-payment providers about the factors that users pay more attention such as trust and usefulness.
Blockchain technology adoption in SMEs: the extended model of UTAUT

The purpose of this study is to measure the behavioral intention to adopt blockchain technology (BT) among SME managers based on the theory of "Unified theory of acceptance and use of technology" (UTAUT). The study was conducted among SME managers in Iraq who adopted blockchain technology. The study deployed the quantitative method and the purposive sample technique was used. The data collected by questionnaires and the valid questionnaires was 192 analyzed by Smart-PLS after ensuring the validity and reliability of the proposed model.The results indicated that performance expectancy, facilitating conditions, technology readiness, and blockchain transparency positively and significantly impact SME managers' intention to adopt blockchain technology. On the other hand, social influence has an insignificant impact on BI’s decision to adopt the blockchain among SME managers.
The Effect of Acoustic Features on Chinese EFL Learners’ Perception of English Accentual Prominence

A group of Chinese EFL learners participated in a perception experiment to identify English narrow focus words located in sentence-initial, -medial and -final positions. The results showed that learners had relatively high recognition accuracy for sentence-initial focus but performed significantly worse on sentence-final focus. Acoustic analysis revealed that, although native English speaker modulated a series of acoustic features significantly to realize accentual prominence for the focused words, only pitch range, peak F0, duration and intensity were used by Chinese EFL learners in the perception task, while F0 movement was largely ignored by them. These results indicated a strong native language influence for the Chinese EFL learners, that they transferred the Chinese focus realization habit in their English focus perception.
Isotopic CO Images near the Young Triple Star GSS 30

We present synthesized images of gas and dust associated with the nearby, low-mass core GSS 30, in the J = 1-0 line of 12C18O and 13C16O, and in 2.7 mm continuum emission. We detected a flattened core roughly orthogonal to the major axis of the bipolar infrared reflection nebula. The core has a mass of about 0.5 M☉ and size of 30'' × 20''. The molecular gas in the core forms a 2400 AU shell expanding at a speed of 0.7 km s-1. This region seems to represent a dense core disrupted by an episode of star formation in the recent past. The 2.7 mm continuum emission is detected toward the youngest component, IRS 3 (LFAM 1), of the three embedded sources. The continuum source remains unresolved at 8. ″9 × 4. ″6 resolution. The deconvolved size of 5'' sets an upper limit of 800 AU on the size of circumstellar material. Molecular gas emission does not peak at any of the known infrared sources. This suggests that the dust and gas may not evolve simultaneously in the star-forming cores.
Active Linear Regression for ℓp Norms and Beyond

We study active sampling algorithms for linear regression, which aim to query only a small number of entries of a target vector and output a near minimizer to the objective function. For $\ell_{p}$ norm regression for any $ 0\lt p \lt \infty$, we give an algorithm based on Lewis weight sampling which outputs $\mathrm{a}(1+\epsilon)$-approximate solution using just $\tilde{O}(d/\epsilon^{2})$ queries to b for $p\in(0,1)$, $\tilde{O}$ $(d/\epsilon)$ queries for $p\in(1,2)$, and $\tilde{O}$ $(d^{p/2}/\epsilon^{p})$ queries for $p\in(2,\ \infty)$. For $p\in(0,2)$, our bounds are optimal up to logarithmic factors, thus settling the query complexity for this range of p. For $p\in(2,\ \infty)$, our dependence on d is optimal, while our dependence on $\epsilon$ is off by at most a single $\epsilon$ factor, up to logarithmic factors. Our result resolves an open question of Chen and Dereziński, who gave near optimal bounds for the $\ell_{1}$ norm, but required at least $d^{2}/\epsilon^{2}$ samples for $\ell_{p}$ regression with $p\in(1,2)$, and gave no bounds for $p\in(2,\ \infty)$ or $p\in(0,1)$. We also provide the first total sensitivity upper bound for loss functions with at most degree p polynomial growth. This improves a recent result of Tukan, Maalouf, and Feldman. By combining this with our techniques for $\ell_{p}$ regression, we obtain the first active regression algorithms for such loss functions, including the important cases of the Tukey and Huber losses. This answers another question of Chen and Dereziński. Our sensitivity bounds also give improvements to a variety of previous results using sensitivity sampling, including Orlicz norm subspace embeddings, robust subspace approximation, and dimension reduction for smoothed p-norms. Finally, our active sampling results give the first sublinear time algorithms for Kronecker product regression under every $\ell_{p}$ norm. Previous results required reading the entire b vector in the kernel feature space.1 1Extended abstract; full version available at https://arxiv.org/abs/2111.04888.
State-space algorithm for the computation of superoptimal matrix interpolating functions

A state-space algorithm is studied which generates the (unique) superoptimal Nehari extension of a general rational matrix $. The procedure is to use a set of all-pass transformations to sequentially minimize each frequency-dependent singular value (of the interpolating function) in a dimension peeling algorithm. These all-pass transformations are determined by the maximal Schmidt pairs of a sequence of Hankel operators. The process terminates when the original problem is reduced to one of rank one; at this stage all the available degrees of freedom have been exhausted. The work is an extension of that by Young (1986) and gives a ‘concrete’ state-space implementation of his operator-theoretic arguments. In addition, bounds are given on the minimum achievable values for s1 ∞ (E) = supωeRSi (E(jω)), i = 1, 2,. , rank (G0), and also the McMillan degree of the final superoptimal extension. Here Si. (.) denotes the ith singular value of a (frequency-dependent) matrix, and the numbering is taken to be in decrea.
Nonisolated Dual-Output Single-Phase Boost Inverter With Reduced Active and Passive Components

This article proposes a nonisolated dual- output single-phase boost inverter with reduced active and passive components. The suggested inverter can serve two single-phase ac loads independently like two full-bridge inverters, but owing to the use of a pair of three-switch legs in the inverter bridge, it has a 25% reduction in active switches. The proposed inverter is capable of obtaining a boost output voltage while employing fewer passive components compared to the traditional impedance source inverter. And the high-frequency current commutation problem of diodes in the traditional split-source inverter is solved by replacing the diodes with two complimentary switches. A hybrid sinusoidal and constant pulsewidth modulation control strategy is elaborated, which enables the proposed inverter to operate in equal frequency mode and different frequency mode. Comprehensive working principles, modulation strategy, steady-state analysis, and parameter design guideline are introduced, both simulation and experimental results are presented to confirm the characteristics of the proposed topology.
Properly learning monotone functions via local correction

We give a $2^{\tilde{O}(\sqrt{n}/\varepsilon)}$-time algorithm for properly learning monotone Boolean functions under the uniform distribution over $\{0,1\}^{n}$. Our algorithm is robust to adversarial label noise and has a running time nearly matching that of the state-of-the-art improper learning algorithm of Bshouty and Tamon (JACM 96) and an information-theoretic lower bound of Blais et al (RANDOM ’15). Prior to this work, no proper learning algorithm with running time smaller than $2^{\Omega(n)}$ was known to exist. The core of our proper learner is a local computation algorithm for sorting binary labels on a poset. Our algorithm is built on a body of work on distributed greedy graph algorithms; specifically we rely on a recent work of Ghaffari (FOCS’22), which gives an efficient algorithm for computing maximal matchings in a graph in the LCA model of Rubinfeld et al and Alon et al (ICS’II, SODA’12). The applications of our local sorting algorithm extend beyond learning on the Boolean cube: we also give a tolerant tester for Boolean functions over general posets that distinguishes functions that are $\varepsilon$/3-close to monotone from those that are $\varepsilon-$far. Previous tolerant testers for the Boolean cube only distinguished between $\varepsilon/\Omega(\sqrt{n}$)-close and $\varepsilon-$far.
Natural Language Processing Approach for Learning Process Analysis in a Bioinformatics Course

Natural Language Processing (NLP) has been employed in different applications. Learning processes in education are difficult to establish. However, the employment of these new approaches from the Artificial Intelligence (AI) can contribute to support the learning measuring. Identify the knowledge acquired during a course is important to determine the achievement of the objectives and to develop strategies to improve the course. In this paper is presented the employment of NLP tools for determining differences in conceptualization between beginning and ending of processes for a bioinformatics course inside of a biomedical engineering program. Results established that there are differences in the conceptualization of the students in a first sight of the bioinformatics course and the end of academic period.
Comparing the Fidelity of Contemporary Pointing with Controller Interactions on Performance of Personal Space Target Selection

The goal of this research is to provide much needed empirical data on how the fidelity of popular hand gesture tracked based pointing metaphors versus commodity controller based input affects the efficiency and speed-accuracy tradeoff in users’ spatial selection in personal space interactions in VR. We conduct two experiments in which participants select spherical targets arranged in a circle in personal space, or near-field within their maximum arms reach distance, in VR. Both experiments required participants to select the targets with either a VR controller or with their dominant hand’s index finger, which was tracked with one of two popular contemporary tracking methods. In the first experiment, the targets are arranged in a flat circle in accordance with the ISO 9241-9 Fitts’ law standard, and the simulation selected random combinations of 3 target amplitudes and 3 target widths. Targets were placed centered around the users’ eye level, and the arrangement was placed at either 60%, 75%, or 90% depth plane of the users’ maximum arm’s reach. In experiment 2, the targets varied in depth randomly from one depth plane to another within the same configuration of 13 targets within a trial set, which resembled button selection task in hierarchical menus in differing depth planes in the near-field. The study was conducted using the HTC Vive head-mounted display, and used either a VR controller (HTC Vive), low-fidelity virtual pointing (Leap Motion), or a high-fidelity virtual pointing (tracked VR glove) conditions. Our results revealed that low-fidelity pointing performed worse than both high-fidelity pointing and the VR controller. Overall, target selection performance was found to be worse in depth planes closer to the maximum arms reach, as compared to middle and nearer distances.
Spanish Stops And Their Allophones Produced By Proficient Mandarin Learners Of Spanish

This study examined the pronunciation of Spanish stops by Mandarin learners of Spanish, with the focus on the realization of voiced stops, voiceless stops, and allophonic spirants of voiced stops in isolated words and in running speech. We recruited 10 Mandarin-speaking learners with high-proficiency Spanish skills and 6 native Peninsular Spanish speakers. They read words containing the target sounds and a short paragraph. Voice onset time was measured for the stops and the manner of articulation was coded for the allophones of voiced stops. The results showed that Mandarin learners of Spanish could distinguish the two types of stops. However, their production of voiceless stops in isolated words and the voiced stops in the paragraph were significantly different from native speakers. Moreover, most Mandarin speakers could not produce spirantized allophone of voiced stops as much as native speakers did in both reading tasks. These results indicate that the pronunciation of phonemes in a second language and the acquisition of nonnative allophonic phonemes are still challenging even for high-proficiency learners.