Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-based vs. Data-driven Approaches for Predicting Rain-induced Attenuation in Commercial Microwave Links: A Comparative Empirical Study

Real-time analysis and forecasting of rain-induced attenuation patterns in terrestrial microwave links has gained increasing attention in the field of communication and meteorology, enabling preparation for upcoming events. This paper presents an empirical study of model-based and data-driven techniques applied to multi-step predictions of rain attenuation in terrestrial microwave links. Data-driven approaches have been adopted in many research fields, including time series forecasting, which allows the modeling of complex data patterns without assuming a particular model representation. However, the superiority of such algorithms over traditional time series model-based methods has yet to be resolved for short-term rain attenuation predictions. We provide a comprehensive evaluation through empirical analysis using real-world measurements by comparing the performances of six main state-of-the-art algorithms involving two dimensions: the available training dataset and forecast horizon. The empirical results demonstrate the superiority of data-driven algorithms over model-based methods with an increasing gap as the forecast horizon grows, reaching over 20% gain in the RMSE. Nevertheless, adopting data-driven algorithms in rainfall prediction requires a sufficient amount of available data and typically requires a significant number of observed rainfall hours, highlighting the challenge when the dataset is limited or unavailable.
Evaluation of Flathead Grey Mullets (Mugil cephalus) Immunization and Long-Term Protection against Vibrio harveyi Infection Using Three Different Vaccine Preparations

In recent years, flathead grey mullets (Mugil cephalus) cultured in Eilat (Israel) have been highly affected by Vibrio harveyi, showing neurological signs such as uncoordinated circular swimming followed by high mortality rates. Despite the advances in and different approaches to control vibriosis associated with Vibrio harveyi, including commercial vaccines, most of them have not succeeded in long-term protection. In this study, we evaluated the effectiveness, long-term protection, and antibody production of three vaccine preparations: heat-killed bacteria (HKB), membrane proteins denaturation (BME PROT), and internal proteins (INT PROT) developed specifically against Vibrio harveyi for grey mullets. Our results show that fish immunized with heat-killed bacteria emulsified with adjuvant presented the most effective and long-lasting protection against the bacterium, and a cross-protection against other bacteria from the harveyi clade. The effectiveness of each immunization treatment correlated with the levels of specific antibody production against Vibrio harveyi in the serum of the immunized fish.
A comparative study on electrospun fibers of cyanobiphenyl liquid crystal homologues

Abstract Cyanobiphenyl homologues are important liquid crystals to use in some applications since they exhibit intrinsic properties in a certain temperature interval including room temperature. Recently, generating composites with polymers and liquid crystals by electrospinning has drawn great interest. Here, cyanobiphenyl homologues of chain carbon numbers 5–8 and polyacrylonitrile were spun using single-needle electrospinning for the first time. Morphological, optical, aligning, and thermal properties of spun fibers investigated. The thinnest and thickest fibers were obtained in fibers involving cyanobiphenyl of chain carbon number 5 and 6, respectively considering the scanning electron microscopy images. Also, it was proved that all the cyanobiphenyl members were self-aligned throughout the fibers as a core using polarized optical microscopy. The existence of the cyanobiphenyl homologues in the structure of the fibers was presented by infrared spectroscopy results. In addition, the mass variation depending on temperature and calorimetric measurements were studied. Phase transition temperatures of the bulk cyanobiphenyls and the fibers were compared. The results showed that cyanobiphenyl homologues of chain carbon numbers 5–8 and polyacrylonitrile were able to be spun successfully and the fibers had the potential to be used in applications because the physical properties of the fibers were attractive.
Cross-Domain Diffusion Based Speech Enhancement for Very Noisy Speech

Deep learning based speech enhancement has achieved remarkable success, but challenges remain in low signal-to-noise ratio (SNR) nonstationary noise scenarios. In this study, we propose to incorporate diffusion-based learning into an enhancement model and improve robustness in extremely noisy conditions. Specifically, a frequency-domain diffusion-based generative module is employed, and it accepts the enhanced signal obtained from a time-domain supervised enhancement module as an auxiliary input to learn to recover clean speech spectrograms. Experimental results on the TIMIT dataset demonstrate the advantage of this approach and show better enhancement performance over other strong baselines in both -5 and -10 dB SNR noisy conditions.
On sound generated aerodynamically I. General theory

A theory is initiated, based on the equations of motion of a gas, for the purpose of estimating the sound radiated from a fluid flow, with rigid boundaries, which as a result of instability contains regular fluctuations or turbulence. The sound field is that which would be produced by a static distribution of acoustic quadrupoles whose instantaneous strength per unit volume is ρvivj + pij - a20ρδij, where ρ is the density, vi the velocity vector, pij the compressive stress tensor, and a0 the velocity of sound outside the flow. This quadrupole strength density may be approximated in many cases as ρ0vivj. The radiation field is deduced by means of retarded potential solutions. In it, the intensity depends crucially on the frequency as well as on the strength of the quadrupoles, and as a result increases in proportion to a high power, near the eighth, of a typical velocity U in the flow. Physically, the mechanism of conversion of energy from kinetic to acoustic is based on fluctuations in the flow of momentum across fixed surfaces, and it is explained in § 2 how this accounts both for the relative inefficiency of the process and for the increase of efficiency with U. It is shown in § 7 how the efficiency is also increased, particularly for the sound emitted forwards, in the case of fluctuations convected at a not negligible Mach number.
Co-Design for Mimo Radar and Mimo Communication Aided by Reconfigurable Intelligent Surface

This paper focuses on the problem of reconfigurable intelligent surface (RIS) aided co-design for multiple-input-multiple-output (MIMO) radar and MIMO communication systems with shared spectrum resources. The purpose is to maximize the radar output signal-to-interference-plus-noise-ratio (SINR) while ensuring the communication functionalities, where there is no line-of-sight (NLOS) propagation between the radar and the target. To achieve the goal, we develop a cyclic framework based on semi-definite programming (SDP), semi-definite relaxation (SDR), and alternating direction method of multiplier (ADMM) to jointly optimize the radar transmit waveforms, the receive filters, the communication codebook, and the RIS coefficients. Numerical experiments are conducted to evaluate the effectiveness of the proposed algorithm.
Potential of Kappaphycus alvarezii (seaweed) extract as biostimulant on the growth of mangrove propagules (Rhizophora mangle L.) through foliar application

This study investigated the potential of seaweed extract of Kappaphycus alvarezii as biostimulant in 3% concentration on the relative growth rate, net assimilation rate, and root to shoot ratio of mangrove propagules of Rhizophora mangle L. through different day-intervals of foliar application under field experiment. There were two factors included: factor A-types of treatment (A1-water, A2-seaweed extract, A3-commercial biostimulant); and, factor B-different day-interval of application (B1-4 days, B2-8 days, B3-12 days). It was revealed that 3% concentration of seaweed extract of K. Alvarezii had no significant effect on the rate growth rate, net assimilation rate, and root to shoot ratio of mangrove propagules of R. Mangle L. Moreover, seaweed extract of K. Alvarezii as biostimulant in 3% concentration had no significant difference to the commercial foliar biostimulant and to the different day-intervals of application. This study recommends to explore higher concentration of seaweed extract from K. Alvarezii on propagules of R. Mangle L. and other mangrove species in a greenhouse setting.
Bayesian model calibration and damage detection for a digital twin of a bridge demonstrator

Using digital twins for decision making is a very promising concept which combines simulation models with corresponding experimental sensor data in order to support maintenance decisions or to investigate the reliability. The quality of the prognosis strongly depends on both the data quality and the quality of the digital twin. The latter comprises both the modeling assumptions as well as the correct parameters of these models. This article discusses the challenges when applying this concept to real measurement data for a demonstrator bridge in the lab, including the data management, the iterative development of the simulation model as well as the identification/updating procedure using Bayesian inference with a potentially large number of parameters. The investigated scenarios include both the iterative identification of the structural model parameters as well as scenarios related to a damage identification. In addition, the article aims at providing all models and data in a reproducible way such that other researcher can use this setup to validate their methodologies.
Toward Extra Large-Scale MIMO: New Channel Properties and Low-Cost Designs

Extra large-scale multiple-input–multiple-output (MIMO) has been recognized as one of the potential development directions of massive MIMO. By employing even more antennas than massive MIMO in the fifth-generation era, extra large-scale MIMO can further exploit the spatial domain resources and enable ultra-high data rates, low latency communications as well as emerging applications, such as sensing and localization, in sixth-generation mobile communication systems. However, with the increase of the size of the antenna array, and the decrease of the distance between a user and the array, new channel properties, that did not manifest in conventional massive MIMO, start to kick in. Most importantly, existing research strategies pertaining to massive MIMO cannot be directly applied or simply extended to fit the extra large-scale MIMO case. Moreover, increasing the number of antennas will inevitably boost the total cost, which refers to not only the high hardware cost, but also the burden of vast processing and computations as well as the substantial training overhead. In this article, we make a survey on the state-of-the-art on the new channel properties of and low-cost designs for extra large-scale MIMO systems. Particularly, we pursue a mathematical analysis to explain why the new features appear and illustrate how they affect the system model. Furthermore, we summarize and compare the low-cost designs from various perspectives and give our suggestions from a practical deployment point of view.
Fast 3D Human Pose Estimation Using RF Signals

Existing deep learning-based wireless sensing models usually require intensive computation. In this paper, we introduce a lightweight RF-based 3D human pose estimation model, i.e., Fast RFPose, to enable real-time human pose estimation. Specifically, Fast RFPose first estimates the human locations in the RF heatmap and crops the human location regions, then estimates the fine-grained human poses based on the cropped small RF heatmaps. In the experiments, we build a radio system and a multi-view camera system to acquire the RF signals and the ground-truth human poses, and compare Fast RFPose with state-of-the-art methods. Experimental results demonstrate that Fast RFPose outperforms the alternative methods. Besides, we further deploy the trained Fast RFPose model on a laptop with a CPU and Fast RFPose can achieve 66 FPS processing speed, which means it can meet the real-time running requirements in mobile devices.
The Derivation of Joint Distribution and Correlation between Relatives by the Use of Stochastic Matrices

The absolute frequencies of the various genotypic parent-offspring and sib-pair combinations with respect to one pair of genes, autosomal or sex-linked, are well known to geneticists, for they are of practical value in certain types of studies in human heredity. These frequencies are, however, obtained by a rather long process, even for the simple case of full sibs. The procedure of obtaining the frequencies of unclenephew or first cousinl combinations is entirely too tedious evenly with the help of matrix notations (Hogben, 1933). The purpose of the present communication is three-fold. The first is to give a simple procedure of finding the frequencies of the various genotype combinations of near relatives by using matrices of conditional probabilities. The second purpose is to express such matrices of conditional probabilities of relatives in the form of a linear function of some basic matrices. The third is to deduce the correlations between relatives from such linear functions of the basic matrices. The meaning of these statements will be made clear in later sections. For many years there existed two apparently very different methods of obtaining the genotypic correlations between relatives. One is a straightforward but long procedure by which the frequencies of the various combinations of the stated relatives in the general population are first found and then the correlation is calculated from such a "correlation table". On the other hand, they may be obtained by the method of path coefficients, developed by Wright (1921 and later). The latter method gives the required correlation coefficient almost instantly once the relationship is specified, but does not give us any information about the frequencies of the various combinations of the relatives in the population. Moreover, one has to be familiar with the mathematical theorems concerning the path coefficients before he can use them to derive the required correlations. The method of stochastic process and its final reduction to some basic matrices, as described in the following pages, will give us both the frequencies of relative-pairs and their correlation in a very simple manner. It is hoped that the present method will bridge the gap between the two existing procedures.
Algebraic Model Applied to Vibrations in the Electronic Ground State of NO2

An algebraic model of boson realization and a corresponding q-deformed model are used to study tile vibrations in the electronic ground state of NO2. The two models are applied to fit the 142 vibrational band origins below 9000 cm-1 with the standard deviations 3.29 cm-1 and 3.12 cm-1, respectively.
Uncovering the Complexities of Coping: A Qualitative Study on the Challenges Faced by Special Education Teachers in the Sandwich Generation

This article explored the challenges encountered by Special Education (SPED) teachers who belong to the "sandwich generation," a group of middle-aged adults responsible for caring for their elderly parents and children while maintaining professional obligations. The study employed the Interpretative Phenomenological Analysis (IPA) research method to gather and analyze participant data. The study results reveal that SPED teachers experience physical and mental demands, excessive responsibilities, and obstacles that hinder their self-fulfillment, leading to harsh and challenging circumstances. Nevertheless, these individuals demonstrate spiritual and social resilience through adaptive coping mechanisms, including effective time management, prioritizing quality time with loved ones, and engaging in religious practices. This research provides valuable insights into the unique challenges that SPED teachers in the sandwich generation encounter and suggest strategies for supporting them in their personal and professional lives. These findings are significant for policymakers, educators, and practitioners in special education, as they shed light on the need for targeted support systems that address the complex demands of this population.
Predictive value of Heart Rate Variability measurements and the Brief Resilience Scale for workability and vitality

BACKGROUND: Sustainable employability is increasingly important with current socio-economic challenges. Screening for resilience could contribute to early detection of either a risk, or a protector for sustainable employability, the latter being operationalized as workability and vitality. OBJECTIVE: To study the predictive value of Heart Rate Variability (HRV) measurements and the Brief Resilience Scale (BRS) for worker self-reported workability and vitality after 2–4 years. METHODS: Prospective observational cohort study with mean follow-up period of 38 months. 1,624 workers (18–65 years old) in moderate and large companies participated. Resilience was measured by HRV (one-minute paced deep breathing protocol) and the BRS at baseline. Workability Index (WAI), and the Vitality dimension of the Utrecht Work Engagement Scale-9 (UWES-9-vitality) were the outcome measures. Backward stepwise multiple regression analysis (p < 0.05) was performed to evaluate the predictive value of resilience for workability and vitality, adjusted for body mass index, age and gender. RESULTS: N = 428 workers met inclusion criteria after follow-up. The contribution of resilience, measured with the BRS, was modest but statistically significant for the prediction of vitality (R2 = 7.3%) and workability (R2 = 9.2%). HRV did not contribute to prediction of workability or vitality. Age was the only significant covariate in the WAI model. CONCLUSION: Self-reported resilience modestly predicted workability and vitality after 2–4 years. Self-reported resilience may provide early insight into the ability of workers to stay at work, although caution must be applied because explained variance was modest. HRV was not predictive.
Impact of COVID-19 Pandemic on Weight Change Among Adults in the UAE

Background The COVID-19 pandemic which started in November 2019 and since then has led to multiple lockdowns aimed towards controlling the pandemic, these lockdowns contributed to major changes in individuals’ lifestyles including eating patterns and restriction of physical activity due to continues house confinement. Such changes have significantly contributed to weight change, with increasing rates of obesity in the UAE, COVID-19 have posed a major concern to the country’s obesity levels. Aim To measure the prevalence and investigate the views related to weight change among adults in the UAE during the COVID-19 pandemic. Methods A cross-sectional study was conducted through a self-administered online questionnaire distributed using social media platforms between February 15th and March 14th, 2021. The sample size was 439 adults in the UAE (18–59 years), collected by volunteer sampling. Analysis was done using SPSS with a significance of 5.0%. Exclusion criteria included pregnancy and bariatric surgeries history. Results 51.1% of participants gained weight, 36.2% lost weight and 12.7% maintained their weight. Meal consumption frequency and weight gain were correlated. Consuming fast food resulted in 65.7% of participants gaining weight. 66.2% of people who lost weight during the COVID-19 pandemic did exercise. Stress management and sleeping patterns were not contributing factors to the weight change. 64.4% of the participants who were not satisfied with their weight and believed that they need to make changes in their lifestyle received no guidance from professional personnel to reach their desired weight. Conclusion In this study, the majority of participants have witnessed an increase in weight. UAE health authorities must provide guidance and support to the population via structured nutritional programs and lifestyle awareness campaigns.
Machine Learning-Aided Piece-Wise Modeling Technique of Power Amplifier for Digital Predistortion

We propose a new power amplifier (PA) behavioral modeling approach, to characterize and compensate for the signal quality degrading effects induced by a PA with a machine learning (ML) aided piece-wise (PW) modeling approach. Instead of using a single pruned Volterra model, we use multiple small-size pruned Volterra models by classifying the input data into different classes. For that purpose, an ML classifier model is trained by extracting some crucial features from both the input signal statistics and the PA operating point. The simulation results indicate that our approach contributes to an improved performance/complexity trade-off than a single generalized memory polynomial (GMP) model in terms of PA behavior modeling and linearization.
Reflections on Teaching Piano to Young Children Diagnosed with Autism Spectrum Disorders

Abstract It is not possible for professionals, including music teachers, to avoid interacting with and teaching children living with or affected by an autism spectrum disorder, because this condition is prevalent among young learners. Although previous studies have explored the effect of music and music therapy on children with autism, few have studied the practical instruction of teaching a musical instrument to these learners from the perspective of autism and its comorbidities. We used a qualitative research method, namely an action research model that incorporated observations, journal writing, and reflection. Twelve learners with autism spectrum disorder were given piano lessons, and during this process, adaptations of teaching methods and the materials were assessed. To help us achieve our objectives, we used the book My First Piano Adventure for the Young Learner as our guide. Our main findings were that incorporating physical exercises to improve fine and gross motor skills, using visual adaptations in instructions, and being sensitive to co-occurring conditions such as attention deficit disorder, anxiety or hypersensitivity to the environment enhanced the learning experience. This approach should fit in well with the modern paradigm in interventions that entail teaching children on the autism spectrum: teaching skills in a natural environment, integrated across domains, and bearing in mind the need to feel empathy for learners’ unique diversity.