Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Analog Predistorter for Satellite Communication in Ku-Band

The distortions associated with the power amplifier (PA) is a common phenomenon at high input power levels in communication systems. There are predistortion techniques to overcome it, but as the frequency of operation increases, it becomes difficult for conventional predistortion techniques to achieve efficient linearization. This letter proposes an analog predistorter (APD) that works efficiently with the high PAs in the Ku-band. The experimental results show that the PA with the proposed APD achieves an improvement in the carrier-to-third-order-intermodulation ratio (C/I3) of 15.12 dB over PA at 15.5 GHz for a two-tone signal with a tone spacing of 20 MHz. The PA with APD achieves the C/I3 of 30 dBc and above, making it suitable for satellite communication with a small footprint. The technique can be extended to other frequency ranges depending on the applications.
Bioelectrical Impedance Spectroscopy for Monitoring Mammalian Cells and Tissues under Different Frequency Domains: A Review

Bioelectrical impedance analysis and bioelectrical impedance spectroscopy (BIA/BIS) of tissues reveal important information on molecular composition and physical structure that is useful in diagnostics and prognostics. The heterogeneity in structural elements of cells, tissues, organs, and the whole human body, the variability in molecular composition arising from the dynamics of biochemical reactions, and the contributions of inherently electroresponsive components, such as ions, proteins, and polarized membranes, have rendered bioimpedance challenging to interpret but also a powerful evaluation and monitoring technique in biomedicine. BIA/BIS has thus become the basis for a wide range of diagnostic and monitoring systems such as plethysmography and tomography. The use of BIA/BIS arises from (i) being a noninvasive and safe measurement modality, (ii) its ease of miniaturization, and (iii) multiple technological formats for its biomedical implementation. Considering the dependency of the absolute and relative values of impedance on frequency, and the uniqueness of the origins of the α-, β-, δ-, and γ-dispersions, this targeted review discusses biological events and underlying principles that are employed to analyze the impedance data based on the frequency range. The emergence of BIA/BIS in wearable devices and its relevance to the Internet of Medical Things (IoMT) are introduced and discussed.
Measurement theory of a density profile of small colloids around a large colloid: Conversion of force between two-large spheres into pressure on the surface element

We suggest a transform theory for calculating a density distribution of small colloids around a large colloid from a force curve between the two-large colloids. The main idea (calculation process) is that the force curve between the two-large colloids is converted into the pressure on the surface element of the large colloid. This conversion is different from the celebrated Derjaguin approximation. A numerical matrix calculation is performed in the conversion to calculate it more precisely. Subsequently, the pressure on the surface element is transformed into the density distribution of the small colloids around the large colloid by using a transform theory for surface force apparatus proposed by Amano. In this letter, the process of the transformation is explained and a prototype result of the transformation is shown.
Influence of the Physical Inclusion of ZrO2/TiO2 Nanoparticles on Physical, Mechanical, and Morphological Characteristics of PMMA-Based Interim Restorative Material

Polymethyl methacrylate (PMMA) is often used in restorative dentistry for its easy fabrication, aesthetics, and low cost for interim restorations. However, poor mechanical properties to withstand complex masticatory forces are a concern for clinicians. Therefore, this study aimed to modify a commercially available PMMA-based temporary restorative material by adding TiO2 and ZrO2 nanoparticles in different percentages as fillers and to investigate its physio-mechanical properties. Different percentages (0, 0.5, 1.5, and 3.0 wt%) of TiO2 and ZrO2 nanoparticles were mixed with the pristine PMMA resin (powder to liquid ratio: 1 : 1) and homogenized using high-speed mixer. The composites obtained were analyzed for their flexural strength (F.S.), elastic modulus (E.M.), Vickers hardness (H.V.), surface roughness Ra, morphology and water contact angle (WCA). The mean average was determined with standard deviation (SD) to analyze the results, and a basic comparison test was conducted. The results inferred that adding a small amount (0.5 wt%) of TiO2 and ZrO2 nanoparticles (NPs) could significantly enhance the physio-mechanical and morphological characteristics of PMMA interim restorations. EM and surface hardness increased with increasing filler content, with 3.0 wt. % ZrO2 exhibiting the highest EM (3851.28 MPa), followed by 3.0 wt. % TiO2 (3632.34 MPa). The WCA was significantly reduced from 91.32 ± 4.21° (control) to 66.30 ± 4.23° for 3.0 wt. % ZrO2 and 69.88 ± 3.55° for 3.0 wt. % TiO2. Therefore, TiO2 and ZrO2 NPs could potentially be used as fillers to improve the performance of PMMA and similar interim restorations.
Walk-in NPC Behavior Based on RVO Using Waypoints

Behavior is one of the major points for Artificial Intelligence (AI). One of the most common researches regarding AI behavior is the behavior in the navigation system, in order to generate navigation for AI to make it more natural. In some simulations, the pedestrian’s behavior in navigation is not natural, predictable, and causes other unexpected events such as deadlock, and so on. This study employs the navigation system with Waypoints Navigation to determine paths or branches to take, also to restrict and to liberate AI in walking along the path, and the obstacle avoidance system from Reciprocal Velocity Obstacle (RVO) to assist in avoiding obstacles or other agents. Experiment results show that agents have various and unpredicted results in their behavior where first, the adjustment of parameters enables the number of the pedestrians randomly entering the branch path. Second, the possibility of the deadlock occurs can be reduced by 50 % or more, depends on the numbers of agents and value used in the parameters. Third, a balance between the number of pedestrians walking and standing still or idling can be achieved.
Design, Modeling, and Analysis of a 3-D Spiral Inductor With Magnetic Thin-Films for PwrSoC/PwrSiP DC-DC Converters

A solution architecture for monolithic system-on-chip (SoC) power conversion is in high demand to enable modern electronics with a reduced footprint and increased functionality. A promising solution is to reduce the microinductor size by using novel magnetically-enhanced 3-D design topologies. This work presents the design, modeling, and analysis of a 3-D spiral inductor with magnetic thin-films for power supply applications in the frequency range of 3–30 MHz. A closed-form analytical expression is derived for the inductance, including both the air- and magnetic-core contributions. To validate the air-core inductance model, we implement a 3-D spiral inductor on PCB. The theoretical calculation of air-core inductance is in good agreement with experimental data. To validate the inductance model of the magnetic-core, a 3-D spiral inductor is modeled with Ansys Maxwell electromagnetic field simulation software. A winding AC resistance model is additionally presented. We perform a design space exploration (DSE) to investigate the significance of the 3-D spiral inductor structure. Two important performance parameters are discussed: dc quality factor <inline-formula> <tex-math notation="LaTeX">$(Q_{dc})$ </tex-math></inline-formula> and ac quality factor <inline-formula> <tex-math notation="LaTeX">$(Q_{ac})$ </tex-math></inline-formula>. Also, a 3-D spiral inductor structure with magnetic thin-films is characterized in Ansys Maxwell to estimate its potential, and a novel fabrication method is proposed to implement this inductor. The measured relative permeability (<inline-formula> <tex-math notation="LaTeX">$\mu _{r}$ </tex-math></inline-formula>) and the magnetic loss tangent (<inline-formula> <tex-math notation="LaTeX">$tan~\delta $ </tex-math></inline-formula>) of Co-Zr-Ta-B magnetic thin-films, developed in-house, are used to simulate the proposed structure. The promising results of the DSE can be easily extended to improve the performance of other 3-D inductor topologies, such as the solenoid and the toroid. The numerical simulations reveal that the 3-D spiral inductor with magnetic thin-films has the potential to demonstrate a figure-of-merit (FOM) that is significantly higher than traditional inductors.
First absolute wind measurements in Saturn's stratosphere from ALMA observations

Context. Past observations of Saturn with ground-based and space telescopes have enabled the monitoring of tropospheric wind speeds using cloud-tracking techniques. The most remarkable feature is a broad and fast prograde jet at the equator that reaches speeds of ∼ 400ms − 1 . Saturn’s stratospheric dynamics are less well-known. At low latitudes, they are characterized by the thermal signature of an equatorial oscillation; the observed thermal structure implies that there is a strong oscillating
Study on Relay Networks based on Lagrangian Points for Optical-based Mars-to-Earth Communications

Future colonies on Mars will require any kind of support from Earth. This will results in a huge amount of data to be transferred through the long-haul connection established between the two planets. A radio-frequency (RF) direct link is not apparently sufficient to guarantee the required capacity. Free space optics (FSO) can be chosen to outperform RF in terms of bandwidth availability, narrow beam divergence, reduced power consumption and lower mass and size of the implemented transceivers. In this paper, an optical multi-relay network for Mars-to-Earth connection has been proposed and tested by taking advantage of the Lagrangian points. Spacecrafts, parked in such Space equilibrium points, work as decode-and-forward (DF) relay nodes forwarding data to the next relay found in the position assuring the lowest path distance, and, therefore the highest capacity. Simulation results confirms the viability of the proposed solution, assuring quasi-error-free connections at an average data rate of more than 20 Mb/s, clearly outperforming state-of-the-art solutions based on direct optical transmission.
Classification for diabetic retinopathy by using staged convolutional neural network

Diabetic retinopathy (DR) is the leading cause of permanent blindness in the working-age population, which is one of the common complications of diabetes. DR grading is crucial in determining the relevant treatment to reduce vision loss. Automatic grading approaches of DR are very significant for helping ophthalmologists design adequate treatment to patients. However, DR grading is challenging due to the facts of intra-class variations and inter-class similarities. The key point of solving DR grading is to find abundant discriminative lesions corresponding to subtle visual differences, such as microaneurysms, soft exudates and hemorrhages. To solve the problem, we proposed a two-stage classification process to firstly classify the presence or absence of DR based on the characteristics of fundus images of DR patients. Then for fundus images with DR, we proposed a novel lesion attention module to perceive and capture lesion features for fine-grained classification. Comprehensive experiments are conducted on DDR dataset to evaluate the effectiveness of the proposed DR grading method. Our method achieves the state-of-the-art results on DDR dataset.
Non-Keplerian Dynamics

Exoplanets are often found with short periods or high eccentricities, and multiple-planet systems are often in resonance. They require dynamical theories that describe more extreme motions than those of the relatively placid planetary orbits of the Solar System. We describe the most important dynamical processes in fully-formed planetary systems and how they are modeled. Such methods have been applied to detect the evolution of exoplanet orbits in action and to infer dramatic histories from the dynamical properties of planetary systems.
Solving multistage decision problems with non-separable performance indices via successive approximation

The authors present a successive approximation algorithm for solving a class of deterministic multistage decision problems with general performance indices, which cover both separable and non separable objective functions. Convergence of the algorithm is proved under certain conditions. The constraint qualification for the problems considered is also discussed. Since only a trajectory is needed to be stored in each iteration, the method can be used to solve some high-dimensional dynamic programming problems. The algorithm implementation and numerical results are presented, and future research is discussed. <<ETX>>
Transcriptomes of Wet Skin Biopsies Predict Outcomes after Ionizing Radiation Exposure with Potential Dosimetric Applications in a Mouse Model

Countermeasures for radiation diagnosis, prognosis, and treatment are trailing behind the proliferation of nuclear energy and weaponry. Radiation injury mechanisms at the systems biology level are not fully understood. Here, mice skin biopsies at h2, d4, d7, d21, and d28 after exposure to 1, 3, 6, or 20 Gy whole-body ionizing radiation were evaluated for the potential application of transcriptional alterations in radiation diagnosis and prognosis. Exposure to 20 Gy was lethal by d7, while mice who received 1, 3, or 6 Gy survived the 28-day time course. A Sammon plot separated samples based on survival and time points (TPs) within lethal (20 Gy) and sublethal doses. The differences in the numbers, regulation mode, and fold change of significantly differentially transcribed genes (SDTGs, p < 0.05 and FC > 2) were identified between lethal and sublethal doses, and down and upregulation dominated transcriptomes during the first post-exposure week, respectively. The numbers of SDTGs and the percentages of upregulated ones revealed stationary downregulation post-lethal dose in contrast to responses to sublethal doses which were dynamic and largely upregulated. Longitudinal up/downregulated SDTGs ratios suggested delayed and extended responses with increasing IR doses in the sublethal range and lethal-like responses in late TPs. This was supported by the distributions of common and unique genes across TPs within each dose. Several genes with potential dosimetric marker applications were identified. Immune, fibrosis, detoxification, hematological, neurological, gastric, cell survival, migration, and proliferation radiation response pathways were identified, with the majority predicted to be activated after sublethal and inactivated after lethal exposures, particularly during the first post-exposure week.
Gender, Achievement, and Language Learning Strategies of Tertiary Students

The paper aimed to determine the predominant strategies in language learning of tertiary students. It also examined the relationships between the students’ gender and their language learning strategies, the students’ achievement and the language learning strategies used according to their gender, and students’ achievement according to their gender. The researchers adopted a questionnaire which was floated to 300 first year students to gather data. The findings showed that students who were bisexuals often used metacognitive and cognitive strategies in learning English. Lesbians, on the other hand, frequently used social and compensation strategies to learn English while gays commonly employed social and meta-cognitive strategies. Male students regularly used social and memory strategies while female students often employed social and meta-cognitive strategies. It also appeared that there was significant relationship between language learning strategies used and students’ gender when it came to gay respondents only. Moreover, the study showed that language learning strategies used by the students did not influence their achievement in English. Lastly, findings revealed that the result of the mean grades of the students in their academic achievement was different from each gender. Therefore, students’ achievement in English varies according to gender.
Internet of Things and Shop-Floor Digital Twin: an Aerospace case study

The adoption of the Internet of Things (IoT) technology in the Industry 4.0 framework is increasingly on the rise. Industrial organizations, including those operating in the aerospace sector, are interested in exploiting sensed data in a virtual environment. The Digital Twin (DT) emerges as the virtual counterpart of a real-world system for analysing, monitoring and simulating its behaviour and supporting decisions process. While the concepts of both IoT and DT are widely discussed by the academia, empirical demonstrations on their synergic integration seem to lack in the literature. Considering the HexaSFDT framework, this paper aims to narrow this gap and to discuss a practical case study of an aerospace company. Moreover, it focuses on contextualizing the framework in a process-oriented DT. Following a collaborative approach, several interviews have been conducted with both operational and strategic profiles of the aerospace company. Data flows sensed from the industrial scenario have been analysed to monitor the behaviour of the critical materials management process. Accordingly, the HexaSFDT framework has been customized for fitting the process of the case study. The paper provides a double implication. It discusses the adoption of IoT and DT technologies by presenting an empirical research. Also, through an industrial case study, it supports practitioners, and in particular aerospace companies, in understanding how these technologies can be leveraged to assist people in decision-making.
A Study of Mongolian Emotion Classification Incorporating Emojis

A Mongolian emotion classification algorithm incorporating emojis is proposed to address the problems of small Mongolian emotion classification corpus, poor classification results, and underutilization of emoji emotion features. Firstly, we extract Mongolian text data from the corpus, vectorize it using FastText algorithm and further learn the Mongolian text features. Secondly, emojis data are extracted from the corpus, vectorized and trained in GRU network to fully learn the emotion features of emoji. Then the attention mechanism is used to adjust the attention dynamics of text and emoji features in the model. Finally, the sentiment features of text and emoji are classified with softmax layer for sentiment classification. The experimental results show that the Mongolian sentiment classification algorithm with fused emojis outperforms FastText, Word2vec_BiLSTM and Glove _ BiLSTM sentiment classification algorithms in terms of precision, recall, F1 value and accuracy. The results show the effectiveness of the proposed method and provide a reference for Mongolian sentiment analysis and opinion prediction.
Real-Time Detection of Premature Ventricular Contraction Using Discrete Wavelet Transform

Heart rhythm disorder is a heart disease that requires immediate treatment. One of the most common heart rhythm disorders is Premature Ventricular Contraction (PVC). PVC is an abnormal extra pulse. This beat is called premature because it occurs prematurely from the ventricles of the heart. PVCs often cause no symptoms, but palpitations or a missing heartbeat are the most common. The ancillary test used to diagnose PVC is electrocardiogram. Patients suffering from PVC are usually late for ECG monitoring at the hospital, so a portable system with embedded algorithms is needed for cardiac diagnosis. This paper proposes an approach to detect the risk of early sudden cardiac death in patients with PVCs. This study took the signal data with ECG Click module in real-time, then processed using Discrete Wavelet Transform (DWT) to obtain the PVC morphology. The data was sent via USB UART click and displayed on the TFT LCD screen of the microcontroller. The results of this study, a system can detect PVC signals automatically. This study also conducted testing using Physionet data. The PVC signal in the AHADB 0201 database was detected in sequence of 791, while in the AHADB 0201 database was detected in sequence of 6725. This result can help clinicians detect early symptoms of sudden cardiac death at the clinical level.
Algorithm Of Radar Pattern Clustering In Passive Radar Systems

This article discusses the application of signal pattern clustering algorithms to increase the efficiency of passive radar complexes at the stage of detection of marks from targets. The solution of such a problem will allow in the future to select more effective algorithms for secondary (trajectory) processing of targets. Implementation of effective clustering of marks will allow in the future to adequately form the trajectories of target groups, which will lead to energy gain and reduce the number of false runs by an order of magnitude. To solve the problem of radar pattern clustering, we developed the cDBSCAN clustering algorithm, a density-based spatial clustering algorithm with the presence of noise, using a cascade of heuristic rules. The results on the resulting simulation model showed that the algorithm correctly detects patterns in the sample with high accuracy, more than 98%. At the same time, the value of false detection of patterns is about 2%.
Review on Health Management System for Lithium-Ion Batteries of Electric Vehicles

The battery is the most ideal power source of the twenty-first century, and has a bright future in many applications, such as portable consumer electronics, electric vehicles (EVs), military and aerospace systems, and power storage for renewable energy sources, because of its many advantages that make it the most promising technology. EVs are viewed as one of the novel solutions to land transport systems, as they reduce overdependence on fossil energy. With the current growth of EVs, it calls for innovative ways of supplementing EVs power, as overdependence on electric power may add to expensive loads on the power grid. However lithium-ion batteries (LIBs) for EVs have high capacity, and large serial/parallel numbers, when coupled with problems like safety, durability, uniformity, and cost imposes limitations on the wide application of lithium-ion batteries in EVs. These LIBs face a major challenge of battery life, which research has shown can be extended by cell balancing. The common areas under which these batteries operate with safety and reliability require the effective control and management of battery health systems. A great deal of research is being carried out to see that this technology does not lead to failure in the applications, as its failure may lead to catastrophes or lessen performance. This paper, through an analytical review of the literature, gives a brief introduction to battery management system (BMS), opportunities, and challenges, and provides a future research agenda on battery health management. With issues raised in this review paper, further exploration is essential.