Miracle-dz/UniFAR-FTUs huggingface dataset:
A Lowpass Filter Based on Microstrip Splitter-Combiner Section loaded With Multiple CSRR Coupled Units

In this paper, a lowpass filter (LPF) with N-controllable transmission zeros in stopband is proposed. It is consisting of N-stage complementary split ring resonator (CSRR) coupled units and a microstrip splitter-combiner section. The equivalent circuit of the proposed filter and relevant lumped parameters are summarized and applied to predict the resonance frequencies in stopband. The resonance frequencies can be controlled arbitrarily through adjusting the physical parameters of CSRR units. As an example, an LPF with four CSRR coupled units is designed, simulated, experimentally fabricated and measured. The stopband rejection level is suppressed to be better than 17.7 dB within the passband. The measured results compare well with the EM simulated results, which validates the configuration and corresponding equivalent circuit of the proposed class of filter.
Quick Flash Flood Detection Based on Sound Energy Spectrum and Squeeze-and-Excitation Enhanced Deep Learning

Due to fast global climate changes, flash floods are showing increasing impact all over the world, it has become one of the main natural disasters that lead to casualty and economical losses. Early flash flood warning requires intensive water and rain monitoring stations, which is currently not available in most rural and mountainous areas around the world. Therefore, in this paper, we propose a real-time flash flood detection method based on Squeeze-and-Excitation Module enhanced deep learning and sound energy spectrum. Our proposal could effectively detects whether there is a significant increase in the short-time energy mean value of the sound. The collected audio is converted into the form of energy spectrum by operations such as short-time Fourier transform, and then identified by Squeeze-and-Excitation enhanced deep learning model, a detailed introduction of the framework is provided in this paper. The experimental results demonstrate that the method can provide effective real-time detection of flash flooding.
Mechanical Properties of 3-Hydroxybutyric Acid-Induced Vesicles

The vesicle mechanical behaviors were studied upon its exposure to 3-hydroxybutyric acid using an atomic force microscope (AFM). Dipalmitoylphosphatidylcholine (DPPC) and 3-hydroxybutyric acid were used to manufacture the vesicles at their desired ratio. The deflection of an AFM probe with respect to its displacement was measured after characterizing the vesicle adsorption. The movement was analyzed with the Hertzian model to understand the physical behavior of the vesicles. However, in the deflection just prior to the first penetration, the model was a good fit, and the vesicle mechanical moduli were calculated. The moduli became lower with the higher ratio of 3-hydroxybutyric acid to DPPC, but the moduli were saturated at 0.5 of the ratio. These results appear to be the basis for the function of the metabolism associated with 3-hydroxybutyric acid, i.e., anesthetization and glycemic control, on the physical properties of cell membranes.
A NEW PROOF TO CONSTRUCT MULTIVARIABLE GEOMETRIC MEANS BY SYMMETRIZATION

The original geometric mean of two positive definite operators A and B is given by A#B = A1/2(A−1/2BA−1/2)1/2A1/2. In this article we provide a new proof to construct from the two-variable geometric mean to the multivariable mean via symmetrization introduced by Lawson and Lim [5]. Finally we provide an algorithm to find threevariable geometric mean via symmetrization, which plays an important role to construct higher-order geometric means. AMS Mathematics Subject Classification : 47B65; 47H07.
Using Varied Microphysics to Account for Uncertainty in Warm-Season QPF in a Convection-Allowing Ensemble

AbstractTwo approaches for accounting for errors in quantitative precipitation forecasts (QPFs) due to uncertainty in the microphysics (MP) parameterization in a convection-allowing ensemble are examined. They include mixed MP (MMP) composed mostly of double-moment schemes and perturbing parameters within the Weather Research and Forecasting single-moment 6-class microphysics scheme (WSM6) MP scheme (PPMP). Thirty-five cases of real-time storm-scale ensemble forecasts produced by the Center for Analysis and Prediction of Storms during the NOAA Hazardous Weather Testbed 2011 Spring Experiment were examined.The MMP ensemble had better fractions Brier scores (FBSs) for most lead times and thresholds, but the PPMP ensemble had better relative operating characteristic (ROC) scores for higher precipitation thresholds. The pooled ensemble formed by randomly drawing five members from the MMP and PPMP ensembles was no more skillful than the more accurate of the MMP and PPMP ensembles. Significant positive impact w.
Exploring the Relationship Between Entrepreneurial Mindsets and Business Success: Implications for Entrepreneurship Education

Entrepreneurship is becoming an increasingly popular topic these days. Many people are interested in becoming an entrepreneur and developing their own business. However, not everyone has the ability to become a successful entrepreneur. There are several factors that can influence business success, one of which is having an entrepreneurial mindset. The purpose of this paper is to explore the relationship between entrepreneurial mindset and business success and to discuss the implications for entrepreneurship education. This research is qualitative in nature. Data collection techniques include listening and recording important information to conduct data analysis through data reduction, data display, and conclusion drawing. This study shows that there is a positive relationship between entrepreneurial mindset and business success. Entrepreneurial mindset consists of five main dimensions namely opportunity orientation, innovativeness, proactiveness, self-confidence and risk tolerance. Entrepreneurs who have a strong entrepreneurial mindset are more likely to achieve success in their business. The study also suggests that teaching entrepreneurship should focus on developing entrepreneurial mindset to prepare students to become successful entrepreneurs in the future.
A novel carrier tracking method for frequency-hopping system

The frequency-hopping (FH) method is widely applied in broadband satellite communication systems because of its low interception rate and good anti-jamming performance. In order to design an FH system, the core issue to be considered is synchronization. For a frequency-hopping time-division multiple access (FH-TDMA) system set in satellite optical communication or satellite wireless communication with large orbital angular momentum (OAM), imperceptible changes in carrier frequencies due to the network properties of large bandwidth, low signal-to-noise ratio (SNR), and high-frequency will cause large equivalent doppler frequency shift of the baseband signal, manifesting ‘linear inconsistence’ in the FH pattern of the network. Furthermore, the receiver of such a system needs to be robust to adapt to complex and harsh environments of noise interference for the purpose of fast synchronization and tracking progress. This paper proposes an open-loop carrier synchronization and tracking method based on dichotomous iterations by establishing a maximum likelihood (ML) doppler frequency shift estimation model. This method realizes the multidimensional search for frequencies and phases at low SNR. Compared with traditional open-loop carrier synchronization methods, this method can be functional based on mere complex multiplications and additions and can realize high accuracy frequency offset estimation of data at normalized frequency offset within 4.8e-4.
Response of turbulent boundary layers to multiple strain rates

Many practical applications, such as in blade cascades and turbomachinery, involve inhomogeneous turbulent shear flows subjected simultaneously to multiple strains. In principle, the applied strain can be combined to yield an effective strain. However, no simple stress–strain relation is capable of establishing turbulent stress or energy balance in the mean or on an instantaneous basis. In the current investigation, a turbulent boundary layer is examined in the presence of convex curvatures of different strengths combined with streamwise (favourable and adverse) pressure gradients, with various values of pressure gradient ratio, (∂P/∂s)/(∂P/∂n). Measurements of the mean and turbulent parameters and flux Richardson number show appreciable changes, mainly in the outer portion of the boundary layer (y+ > 100). The turbulent burst frequency, particularly at the location of application of the additional strain rate, also changes relative to its value with wall curvature alone. Three primary observations from these experiments are as follows: (i) in all cases, the mean velocity profile and all of the measured Reynolds stresses collapse in the near-wall region using standard inner scaling; (ii) the applied strains combine nonlinearly, with one of the strains dominating the local flow during its development; (iii) the ratio of the radial to axial pressure gradient magnitude influences both classical turbulence correlations and mean flow, as well as the physical production cycle of turbulence; and (iv) application rate of newly introduced strain rates is at least as important as their magnitudes.
Dispersion of Carbon Nanotubes Improved by Ball Milling to Prepare Functional Epoxy Nanocomposites

There has been an increase in interest in developing functional polymer composites based on green chemistry principles. The purpose of this study was to investigate the preparation of functional epoxy/carbon nanotube nanocomposites using ball milling methods. In contrast to mechanical mixing, ball milling promoted good dispersion of CNTs within the epoxy matrix, thereby improving their mechanical properties and electrical conductivity. In epoxy nanocomposites with ball milling, Young’s modulus and tensile strength were increased by 653% and 150%, respectively, when CNT loading was 1.0 vol%. Additionally, the ball milling of CNTs improves their dispersion, resulting in a low percolation threshold at 0.67 vol%. The epoxy/CNT film sensor that was produced using the ball milling approach not only exhibited high reliability and sensitivity to mechanical strains and impact loads, but also possessed the ability to self-detect damage, such as cracks, and accurately locate them. This study marks a notable milestone in the advancement of functional epoxy/CNT composites through the ball milling approach.
SCL14 Inhibits the Functions of the NAC043–MYB61 Signaling Cascade to Reduce the Lignin Content in Autotetraploid Populus hopeiensis

Whole-genome duplication often results in a reduction in the lignin content in autopolyploid plants compared with their diploid counterparts. However, the regulatory mechanism underlying variation in the lignin content in autopolyploid plants remains unclear. Here, we characterize the molecular regulatory mechanism underlying variation in the lignin content after the doubling of homologous chromosomes in Populus hopeiensis. The results showed that the lignin content of autotetraploid stems was significantly lower than that of its isogenic diploid progenitor throughout development. Thirty-six differentially expressed genes involved in lignin biosynthesis were identified and characterized by RNA sequencing analysis. The expression of lignin monomer synthase genes, such as PAL, COMT, HCT, and POD, was significantly down-regulated in tetraploids compared with diploids. Moreover, 32 transcription factors, including MYB61, NAC043, and SCL14, were found to be involved in the regulatory network of lignin biosynthesis through weighted gene co-expression network analysis. We inferred that SCL14, a key repressor encoding the DELLA protein GAI in the gibberellin (GA) signaling pathway, might inhibit the NAC043–MYB61 signaling functions cascade in lignin biosynthesis, which results in a reduction in the lignin content. Our findings reveal a conserved mechanism in which GA regulates lignin synthesis after whole-genome duplication; these results have implications for manipulating lignin production.
"Comments Matter and The More The Better!": Improving Rumor Detection with User Comments

While many online platforms bring great benefits to their users by allowing user-generated content, they have also facilitated generation and spreading of harmful content such as rumors. Researcher have proposed different rumor detection methods based on features extracted from the original post and/or associated comments, but how comments affect the performance of such methods remains largely less understood. In this paper, we first propose a new BERT-based rumor detection method that can outperform other state-of-the-art methods, and then used it to study the role of comments in rumor detection. Our proposed method concatenates the original post and associated comments to form a single long text, which is then segmented into shorter chunks more suitable for BERT-based vectorization. Features extracted from all trunks are fed into a classifier based on an LSTM network or a transformer layer for the classification task. The experimental results on the PHEME and Ma-Weibo datasets proved the superior performance of our method. We conducted additional experiments on different settings of our proposed method to study different aspects of the role comments play in the rumor detection task. These additional experiments led to some very interesting findings, including the surprising result that fixed-length segmentation is better than natural segmentation, and the observation that including more comments can help improve the rumor detector’s performance. Some of these findings have profound operational implications for online platforms, e.g., commentators can contribute to rumor detection positively so online platforms can leverage the crowd intelligence to detect online rumors more effectively without applying overstrict content consensus policies.
Plasma Checkerboard Electromagnetic Surfaces for Wideband Radar Cross Section Reduction

A novel plasma checkerboard electromagnetic surface is proposed for wideband radar cross section (RCS) reduction. The different units of the plasma checkerboard produce a proper reflection phase gradient and can reduce the backscattered wave. We designed a plasma checkerboard that can reduce RCS by more than 80%, from 5.4GHz to 12.6GHz.
Proteome and Ubiquitylome Analyses of Maize Endoplasmic Reticulum under Heat Stress

High temperatures severely affect plant growth and pose a threat to global crop production. Heat causes the accumulation of misfolded proteins in the endoplasmic reticulum(ER), as well as triggering the heat-shock response (HSR) in the cytosol and the unfolded protein response (UPR) in the ER. Excessive misfolded proteins undergo further degradation through ER-associated degradation (ERAD). Although much research on the plant heat stress response has been conducted, the regulation of ER-localized proteins has not been well-studied thus far. We isolated the microsome fraction from heat-treated and untreated maize seedlings and performed proteome and ubiquitylome analyses. Of the 8306 total proteins detected in the proteomics analysis, 1675 proteins were significantly up-regulated and 708 proteins were significantly down-regulated. Global ubiquitination analysis revealed 1780 proteins with at least one ubiquitination site. Motif analysis revealed that alanine and glycine are the preferred amino acids upstream and downstream of ubiquitinated lysine sites. ERAD components were found to be hyper-ubiquitinated after heat treatment, implying the feedback regulation of ERAD activity through protein degradation.
The α Cephei instability strip

We carried out a series of linear stability analyses of the radial and low-degree non-radial p modes for stellar models with initial masses of . The stellar models were computed by using convective overshoot distance , 0.25 and 0.40 HP. Our numerical results show that the β Cephei instability strip forms a horn-shaped region pointing upwards near the main sequence on the Hertzsprung–Russell diagram (HRD). The lower part of the instability strip for the radial modes join the zero-age main-sequence (ZAMS) at , while the top of the instability strip extends up to . The instability strip for the non-radial modes is even wider. The overall instability strip is dominated by the radial and non-radial fundamental modes. The first overtone (the radial-order index is also pulsationally unstable. We have shown that the β Cephei stability is almost independent of the overshoot parameter dover used for the stellar models, while it depends critically on the metal abundance. With decreasing metal abundance, the instability region shrinks and eventually disappears for .
On the MX/G/∞ queue by heterogeneous customers in a batch

We consider the Mx/G/∞ queue in which customers in a batch belong to k different types, and a customer of type i requires a non-negative service time with general distribution function Bi (s) (1 ≦ i ≦ k). The number of customers in a batch is stochastic. The joint probability generating function of the number of customers of type i being served at a fixed time t > 0 is derived by the method of collective marks.
Estimates for the arctangent function related to Shafer's inequality

The aim of this article is to give new refinements and sharpenings of Shafer’s inequality involving the arctangent function. These are obtained by means of a suitable change of variables which makes the computations much easier than the classical approach used by some of the earlier authors on this subject. 2010 Mathematics Subject Classification. Primary 26A09; 33B10; Secondary 26D99.
Benchmarks for the benchmark approach to valuing long-term insurance liabilities: comment on Fergusson & Platen (2023)

Abstract This article comments on the paper “Less-expensive long-term annuities linked to mortality, cash and equity” by Kevin Fergusson and Eckard Platen, appearing in this issue of the Annals of Actuarial Science. It adds two perspectives to their thought-provoking contribution. The first is a similarity to some recent work in quantitative finance on “deep hedging” that leverages machine learning models to find the cheapest replication strategy for a derivative payoff in a largely model-free setting. The second perspective engages with some of the interesting implications of their approach and draws parallels to literature in asset pricing and macro-finance. These perspectives point to the potential need for more fundamental shifts than the authors of the paper are advertising.
Analysis and comparison of the scalar diffraction theory and coupled-wave theory about grating

The scalar diffraction theory to calculate the diffraction efficiency of grating is an approximate method;the coupled-wave theory is an accurate method.The two methods in solving the diffraction efficiency of grating are different.In this paper,these differences are presented in detail.Some useful conclusions are drawn:grating period and groove are two important approximate conditions.
Safety SysML: An Executable Safety-Critical Avionics Requirement Modeling Language

Establishing formal modeling and verification methods for requirements has become the key to enhancing avionics software’s safety and development efficiency. As the mainstream modeling language used in Model-Based Software Engineering (MBSE), SysML is often applied to software requirements specifications. However, due to the lack of systematic and rigorous semantic definitions, SysML can cause problems in terms of accuracy and consistency in system development, threatening the correctness of safety-critical avionics software. To address the problem, this paper defines Safety SysML State Machine, an extended SysML state machine for safety control functions. Stepwise, the authors illustrate the formal specification and the refinement rules of the Safety SysML State Machine to construct the avionics integration model. Furthermore, a tool is implemented integrating the modeling and verification of the Safety SysML State Machine. Our contribution has a profound potential to broaden the use of MBSE and its well-known advantages in safety-critical applications. A specific case study on the aircraft roll angle control system demonstrates the effectiveness of our approach and the tool.
A High-Q Planar Multi-Resonator for UWB Chipless RFID Tagging and Sensing Application

This paper involves the design and realization of a new planar microstrip parallel L-shaped multi-resonator (PLMR) for the chipless radio frequency identification (CRFID) that works in ultra-wide band (UWB) frequency region. The proposed PLMR has identifying (IDing) and sensing capabilities to work as a tag-sensor. The PLMR works within 5.36 GHz – 8.63 GHz with a high quality-factor (Q) of 412, a very good spatial density of as low as 3.17 mm2/bit, good spectral density of 4.21 bits/GHz, and a coding capacity of 8 bit with one-bit sensing ability. A coding bit stream of 11111111 also is extracted to show the ability of the proposed design. This will motivate the CRFID designers to design a small and high-capacity tag-sensors for UWB applications.
Collaborative Task Allocation in Mobile Crowd Sensing

Task allocation, i.e., allocating mobile crowd sensing tasks to candidates, attracts more attention in recent years. In the real world, many complicated tasks like troubleshooting, event organization, etc., often require to hire a group of workers with i) group collaboration, i.e., the workers in the group complete the task collaboratively; ii) customized group size, i.e., a certain number of workers according to the task's requirement. However, most of existing task allocation studies neglect the above two aspects. Motivated by this, in this paper we propose a Collaborative Task Allocation (CTA) framework. It includes two stages: firstly, in order to capture collaboration preferences and abilities, it learns the embedding of groups and tasks respectively; secondly, it searches the optimal group for each task that can maximize the overall utility. Extensive experiments are conducted on two real-world datasets. The results show that, compared to the four baselines, the average task execution performance of the proposed method increases up to 155.17%.
A New Efficient Algorithm for Computational Aeroacoustics on Parallel Processors

One of the great challenges in computational physics is the prediction of flow associated noise, where the quantities of interest, namely the sound waves can be at high frequencies and are usually orders of magnitude smaller in magnitude than the mean quantities. In order to numerically resolve such small scales governed by the fluid dynamics equations, high resolution schemes are required. Thus solutions of flow noise problems are computationally intensive. An efficient, hybrid, data parallel computational aeroacoustics algorithm has been developed for the prediction of noise radiation and scattering from three-dimensional geometries. The algorithm solves the Euler/NavierÂ? Stokes equations in the interior and nonreflecting boundary conditions on the outer boundaries. A moving surface Kirchhoff method is coupled to the flow solver for far-field predictions. The algorithm uses standard time and spatial discretization techniques but utilizes several new optimization strategies that are highly suitable for single zone solutions on data parallel processors. One strategy, for example, enables simultaneous residual evaluations of the interior and far-field nonreflecting boundary conditions equations, reducing the computational effort spent on them by approximately 60% CPU time savings. The algorithms for the flow solver and the Kirchhoff method and their coupling are described in this paper, and results for some example radiation and scattering problems are presented.