Miracle-dz/UniFAR-FTUs huggingface dataset:
Computable extensions of generalized fractional kinetic equations in astrophysics

Fractional calculus and special functions have contributed a lot to mathematical physics and its various branches. The great use of mathematical physics in distinguished astrophysical problems has attracted astronomers and physicists to pay more attention to available mathematical tools that can be widely used in solving several problems of astrophysics/physics. In view of the great importance and usefulness of kinetic equations in certain astrophysical problems, the authors derive a generalized fractional kinetic equation involving the Lorenzo-Hartley function, a generalized function for fractional calculus. The fractional kinetic equation discussed here can be used to investigate a wide class of known (and possibly also new) fractional kinetic equations, hitherto scattered in the literature. A compact and easily computable solution is established in terms of the Lorenzo-Hartley function. Special cases, involving the generalized Mittag-Leffler function and the R-function, are considered. The obtained results imply the known results more precisely.
Multimodel estimates of the changes in the Baltic Sea ice cover during the present century

We project changes in the annual maximum ice extent and the maximum coastal fast ice thickness in the Baltic Sea during the ongoing century. The influence of future warming on the ice conditions was assessed using the November–March Baltic coastal mean temperature as a predictor for the annual maximum ice extent (MIB), and the local freezing degree-day sum as a predictor for the fast ice thickness. Future winter temperatures were derived by adjusting observational baseline-period temperatures in accordance with temperature projections based on 28 global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5. Under the Representative Concentration Pathway (RCP) 4.5 scenario, the ensemble-mean trend of MIB is −6400 km2/10 yr, and from the 2060s onwards in a typical winter MIB remains below 80×103 km2. If the RCP8.5 scenario is realised, the corresponding estimates are −10 900 km2/10 yr for the trend and 60×103 km2 for a typical MIB. For cold rather than typical winters, the projected rate of decrease in MIB is even faster. During the late century under RCP8.5, in 9 out of 10 yr the ice would only cover 5–20% of the total sea area. The projected trends in the mean annual maximum ice thickness are −7.6 … −3.3 cm/10 yr, depending on location and applied scenario. In the 2040s under both scenarios, and in the 2080s under RCP4.5, the ice thickness may still exceed 60 cm in the northernmost Bay of Bothnia, while elsewhere in the Gulf of Bothnia and in the Gulf of Finland, it will vary between about 10 and 40 cm. In the 2080s under RCP8.5, virtually no ice occurs outside the Bay of Bothnia. For both the ice extent and thickness, the spread among the responses based on the temperature projections of individual GCMs is considerable. Nonetheless, a robust finding is that the Baltic Sea is unlikely to become totally ice-free during this century.
A 24-28GHz Compact High-power Amplifier for 5G Millimeter-Wave Front-end

This paper presents a compact high-power amplifier (HPA) operating in K/Ka band (24-28GHz), using OMMIC 100nm Gallium Nitride on Silicon (GaN-on-Si) process. In 24-28GHz, the designed HP A demonstrated a small-signal gain of over 22dB, a saturated output power of 37-38.7dBm and associated Power Added Efficiency (PAE) of 29-31.8%, showing great potential for 5G millimeter-wave applications (i.e. for band n258). The die area of the HPA MMIC is only 7.5mm2.
The Quality of Life in Surgically Treated Head and Neck Basal Cell Carcinoma Patients: A Comprehensive Review

Simple Summary Basal cell carcinoma is the most common skin cancer with increasing incidences every year. The face is considered to be the most affected body part and surgery the most often applied treatment method. Although this tumor rarely metastasizes and is generally considered to cause low morbidity, the established oncologic diagnosis and the existing impairment in facial area as well as the surgical treatment, which may leave postoperative scars and facial disfigurement of varied extent, affect the patient’s quality of life. The aim of this article is to review and summarize current literature on the impact of craniofacial basal cell carcinoma surgical treatment on patients’ quality of life and to compare it before and after the surgery. After conducting a comprehensive review, we conclude that there is a lack of studies assessing the impact of surgical treatment on quality of life exclusively in patients with head and neck basal cell carcinoma. Abstract In this review, we examine current literature analyzing the impact of surgical treatment on the QoL in patients with head and neck BCC. A comprehensive literature review was performed using the main databases. As many as six out of 322 articles were selected for the final analysis. The selected articles were published in the period between 2004 and 2021, most published within the last two years. All analyzed studies were prospective. Five out of six studies evaluated NMSC consisting of both BCC and SCC, and only one study selectively evaluated the impact of surgical treatment on QoL in patients with craniofacial BCC. Authors of the selected studies reported that QoL improves following the surgery; however, the effect on QoL varies. Patients’ age, gender, marital status, education level, and employment status had a stronger correlation with QoL postoperatively, especially during the late follow-up period. Younger patients were more bothered by appearance-related issues. One study concluded that elderly patients did not experience a statistically significant improvement in QoL. This literature review demonstrated that there is no clear consensus on the use of a single disease-specific QoL measurement tool. Furthermore, there is a lack of studies assessing the impact of surgical treatment on QoL exclusively in patients with head and neck BCC and studies analyzing the multivariate correlation between QoL and tumor type, size, anatomic site, and treatment outcomes.
Thwarting Alzheimer’s Disease through Healthy Lifestyle Habits: Hope for the Future

Alzheimer’s disease (AD) is a neurodegenerative disorder that slowly disintegrates memory and thinking skills. Age is known to be the major risk factor in AD, but there are several nonmodifiable and modifiable causes. The nonmodifiable risk factors such as family history, high cholesterol, head injuries, gender, pollution, and genetic aberrations are reported to expediate disease progression. The modifiable risk factors of AD that may help prevent or delay the onset of AD in liable people, which this review focuses on, includes lifestyle, diet, substance use, lack of physical and mental activity, social life, sleep, among other causes. We also discuss how mitigating underlying conditions such as hearing loss and cardiovascular complications could be beneficial in preventing cognitive decline. As the current medications can only treat the manifestations of AD and not the underlying process, healthy lifestyle choices associated with modifiable factors is the best alternative strategy to combat the disease.
Short-Term Head-Out Whole-Body Cold-Water Immersion Facilitates Positive Affect and Increases Interaction between Large-Scale Brain Networks

Simple Summary An increasing number of people are turning to cold showers or outdoor swimming to keep fit and for health benefits. After cold-water immersion, the swimmers reported elevated positive emotions and a decreased negative emotional state. The present study aimed to examine how mood changes after cold-water immersion are associated with changes in brain connectivity. Thirty-three healthy adults naïve to cold-water swimming (age range 20–45, 16 females) undertook a 20 °C 5 min whole-body bath. We measured brain connectivity and self-reported emotional state before and after cold-water immersion. Our findings showed that participants felt more active, alert, attentive, proud, and inspired and less distressed and nervous after having a cold-water bath. The changes in positive emotions were associated with the coupling between brain areas involved in attention control, emotion, and self-regulation. A reduction in negative emotions did not show strong associations with changes in brain connectivity. The results indicate that short-term whole-body cold-water immersion may have integrative effects on brain functioning, contributing to the reported improvement in mood. Abstract An emerging body of evidence indicates that short-term immersion in cold water facilitates positive affect and reduces negative affect. However, the neural mechanisms underlying these effects remain largely unknown. For the first time, we employed functional magnetic resonance imaging (fMRI) to identify topological clusters of networks coupled with behavioural changes in positive and negative affect after a 5 min cold-water immersion. Perceived changes in positive affect were associated with feeling more active, alert, attentive, proud, and inspired, whilst changes in negative affect reflected reductions in distress and nervousness. The increase in positive affect was supported by a unique component of interacting networks, including the medial prefrontal node of the default mode network, a posterior parietal node of the frontoparietal network, and anterior cingulate and rostral prefrontal parts of the salience network and visual lateral network. This component emerged as a result of a focal effect confined to few connections. Changes in negative affect were associated with a distributed component of interacting networks at a reduced threshold. Affective changes after cold-water immersion occurred independently, supporting the bivalence model of affective processing. Interactions between large-scale networks linked to positive affect indicated the integrative effects of cold-water immersion on brain functioning.
Design of MIMO Radar Using Cascaded Millimeter-Wave Sensors

This paper presents a MIMO radar system cascading four commercially available millimeter-wave sensors. The sensor is able to work in the frequency range between 77 and 81 GHz and based on frequency modulated continuous wave radar principle (FMCW). This radar system shares a common Local Oscillator (LO) signal and timing synchronization signal across all the transmitters and receivers. This radar system has 12 transmit (TX) antennas and 16 receive (RX) antennas, which are arranged in two dimensions forming a 6 by 32 virtual array. The 2-dimensional physical antenna configuration provides the radar system with azimuth and elevation estimation capability, and can be used to high-resolution imaging and non-contact monitoring of vital signs. A FPGA SoC is used for radar waveform parameters configuration, echo signal acquisition, pre-processing and data transmission. Data and status are exported to host PC through ethernet. This radar system is evaluated by detecting static and moving object in time division multiplexing MIMO mode.
A Synthetic Design Approach of Wideband Bandpass Power Divider

Prototypes of three categories filtering bandpass power dividers are presented in this letter. Their common points are M-sections cascaded transformer structure and $M+1$ sections shorted stubs. To realize different performance, three specific structures are adopted in these categories' prototypes of power divider. Specifically, three different performances of proposed three prototypes are perfect isolation in the passband, smaller circuit size and out-of-band rejection, respectively. Three proposed prototypes are analysis by even- and odd-mode method, and the binding relationship in mathematics are deduced. Finally, three experimental circuits of corresponding prototypes are fabricated, and high consistency exist in the measured results and simulated results.
A High-Gain and Broadband Optically- Transparent Liquid Antenna With Plate Dielectric Lens

In this paper, a high-gain wideband optically-transparent liquid antenna loaded with plate dielectric lens is proposed. The gain of the antenna is improved by loading plate dielectric lens above the pure water patch antenna. The patch and the ground are realized by wrapping pure water in transparent plexiglass, and the dielectric lens is composed of transparent ionic liquids and plexiglass. Therefore, the whole antenna is almost transparent except the metal feed structure. The antenna can achieve 39 % impedance bandwidth for | S11| < − 10 dB in the range of 12 – 18 GHz, and the radiation efficiency is almost 60 %. Due to the loading of plate dielectric lens, the gain of the antenna can be increased to 13.2 dBi. The designed liquid antenna has the advantages of wideband, high gain, high radiation efficiency, optical transparency and low cost.
Transport and magnetic properties of a ferromagnetic metal: Eu1-xRxTiO3

We report the transport and magnetic properties of a series of ferromagnetic metallic compounds, ${\mathrm{Eu}}_{1\ensuremath{-}x}{R}_{x}{\mathrm{TiO}}_{3},$ where the maximum ${T}_{C}$ is 8 K at $x=0.1. $ Magnetic interaction between Eu $4f$ spins mediated by itinerant Ti $3d$ electrons is essential for the ferromagnetism of this compound, and a clear correlation between transport properties and magnetism exists in this series. Possible roles of the electron-correlation effect in Ti $3d$ electrons are also discussed.
The Ripple-Spreading Algorithm for the $k$-Color Shortest Path Problem

The $k$-color shortest path problem ($k$-CSPP) aims to find the shortest path that traverses at most $k$ colors on edge-colored graphs, which plays a pivotal role in the field of network reliability. This paper proposes a nature-inspired ripple-spreading algorithm (RSA) to solve such problems. The RSA is devised by mimicking ripple propagation patterns on the perturbed water surface. Based on the properties of the k-CSPP, several strategies are proposed to stop exploring non-optimal or infeasible subpaths at an early stage without losing optimality. In addition, the RSA can solve the $k$-CSPP with multiple destination nodes within a single run with minor modifications to the termination judgment of the algorithm. An illustrative example of how the RSA solves the $k$-CSPP is presented, using ripple spreading and triggering phenomena to make its processes more comprehensible. Moreover, extensive experiments against existing algorithms exhibit the outstanding efficiency and robustness of the RSA, especially on large-scale networks. The experimental data imply that the RSA speeds up the problem-solving efficiency at least ten times. The RSA can be expected to make a difference in the real-world problems modeled as the $k$-CSPP.
Low-frequency radio emission in the massive galaxy cluster MACS J0717.5+3745

To investigate the nonthermal emission mechanism and their interaction during cluster mergers, we analyze multiple low-frequency radio data for the X-ray luminous massive galaxy cluster MACS J0717.5 + 3745, located at z = 0.5548. Large-scale structure-formation models in the Universe suggest that galaxy clusters grow via constant accretion of gas and the merger of galaxy groups and smaller clusters. Low-frequency radio observations trace these mergers in the form of relics and halos. The dual frequency observations were performed on MACS J0717.5 + 3745 to investigate the spectral index pattern of the nonthermal emission and its interaction within the intracluster medium (ICM), during merger process. Methods: Continuum observations were carried out using GMRT at 0.235 and 0.61 GHz on MACS J0717.5 + 3745 and archival data from the VLA (0.074 and 1.42 GHz) and WSRT (0.325 GHz) was used to complement the results. Furthermore, to explore the thermal and nonthermal interactions within the ICM and the morphological distribution, Chandra X-ray and HST data were used. Results: A highly complex nonthermal radio emission distribution is seen in the cluster at very low frequencies, with a global spectral index α0.2350.61˜-1.17±0.37. We have detected a giant radio halo within the cluster system with a linear size of 1.58 Mpc and a "Chair-shaped" filament structure between the merging subclusters of linear size 853 kpc at 0.235 GHz. This is the most powerful halo ever observed with P1.4 = 9.88 × 1025 WHz-1 and an equipartition magnetic field estimate of ~6.49 μG. The bright filament structure is well located in the central merging region of subclusters with enhanced temperature, as shown by Chandra and HST data analysis, further indicating the formation of this structure due to shock waves encountered within the ICM during the merger events.
A Cost-Effective Over-the-Air Test Verification Method for 5G Active Antennas

The integrated design of antenna and power amplifier brings great challenges to RF testing, where the traditional conduction test method is no longer applicable, so the over the air (OTA) test method is highly needed. With the 5G mobile communications expanding its spectrum to the millimeter-wave band, OTA test requires larger test sites, more complex test links, and more expensive test instruments, which leads to higher economic and time costs. To this end, this paper proposes an OTA test verification model to verify the active integrated antenna performance in an efficient and economical way. The test method has been experimentally verified in the Sub-6GHz band and can be applied to the millimeter-wave band.
Finite-Time Adaptive Tracking Control for Uncertain Nonlinear Systems with Time-Varying State Constraints

The objective of this paper is uncertain nonlinear systems with external disturbances and finite-time tracking control is studied for it when the states subject to the time-varying constraints. Firstly, the state constraints including the factor of time can be avoided by virtue of the approach named a barrier Lyapunov function(BLF). The parameter separation technique and the adaptive method are taken into account together to settle the parametric uncertainties. Based on the combination with the method of backstepping, an adaptive design process is constructed. In the sequel, the boundedness of signals appearing in the closed-loop systems are ensured in the stability analysis. At the same time, the finite-time tracking control is achieved based on the methods mentioned above. Finally, an example is provided to illustrate that the methods mentioned above are effective.
Machine Learning-Based Uplink Scheduling Approaches for Mixed Traffic in Cellular Systems

The problem of the uplink resource allocation of mixed-traffic types in cellular networks is a challenging problem that has not been addressed sufficiently in the literature. In this paper, we consider the 5G uplink scheduling for Ultra-Reliable and Low Latency Communications and enhanced Mobile Broad-Band (eMBB) traffic types. There are three main scheduling techniques to be considered, namely, the grant-based (GB), the semi-persistent, and the grant-free (GF) techniques. Furthermore, there are three different schemes used in GF scheduling, namely, the reactive, the k-repetitions, and the proactive schemes. We devise a mathematical model for the GF services using the k-repetitions scheme as the first model to define such traffic in a single cell. In addition, the GB scheduling model for eMBB traffic is adapted to fit our problem. We formulate the scheduling problem as a mixed-integer non-linear programming optimization problem. We introduce a complete system model that includes GF and GB subsystems. We introduce a novel mixed scheduler that combines the advantages of two well-known schedulers in the literature. We introduce novel machine-learning-based scheduling algorithms and evaluate them in comparison to well-known algorithms in the literature in addition to the optimal bound that we also derive. The results show that the proposed algorithms produce near-optimal results in real time.
Advanced Energy Management Strategy of Photovoltaic/PEMFC/Lithium-Ion Batteries/Supercapacitors Hybrid Renewable Power System Using White Shark Optimizer

The slow dynamic response of a proton exchange membrane fuel cell (PEMFC) to high load change during deficit periods must be considered. Therefore, integrating the hybrid system with energy storage devices like battery storage and/or a supercapacitor is necessary. To reduce the consumed hydrogen, an energy management strategy (EMS) based on the white shark optimizer (WSO) for photovoltaic/PEMFC/lithium-ion batteries/supercapacitors microgrid has been developed. The EMSs distribute the load demand among the photovoltaic, PEMFC, lithium-ion batteries, and supercapacitors. The design of EMSs must be such that it minimizes the use of hydrogen while simultaneously ensuring that each energy source performs inside its own parameters. The recommended EMS-based-WSO was evaluated in regard to other EMSs regarding hydrogen fuel consumption and effectiveness. The considered EMSs are state machine control strategy (SMCS), classical external energy maximization strategy (EEMS), and optimized EEMS-based particle swarm optimization (PSO). Thanks to the proposed EEMS-based WSO, hydrogen utilization has been reduced by 34.17%, 29.47%, and 2.1%, respectively, compared with SMCS, EEMS, and PSO. In addition, the efficiency increased by 6.05%, 9.5%, and 0.33%, respectively, compared with SMCS, EEMS, and PSO.
MSFusion: Multilayer Sensor Fusion-Based Robust Motion Estimation

Vision-based measurement has become a research hotspot for autonomous vehicles, but most works ignored the information from other perspectives, and its robustness and accuracy still need to be improved. In this letter, we proposed a novel multilayer fusion framework to achieve front-rear camera arrangement-based multisensor fusion localization using a nonlinear optimization method. In this work, we have designed a factor to evaluate the effect of optical flow tracking, realized the complementarity of front and rear visual-inertial odometry, and proposed a bidirectional loopback strategy, thereby improving the robustness and flexibility of the system. The performance of our method has been evaluated on open source dataset and in the real world, and it is demonstrated that our method outperforms other state-of-the-art algorithms.
A high-performance linear magnetic gear

Currently, the demand for high force density linear actuators is being met almost exclusively by employing a leadscrew and nut to transform rotary to linear motion. The paper describes an alternative technology, viz., a linear magnetic gear, which employs rare-earth magnets, and which simulation studies have shown to have a highly competitive force density.
Securing IoT devices using Ensemble Machine Learning in Smart Home Management System

In this modern era, we are habituated to small smart home appliances that are typically known as the Internet of Things (IoT) devices. While these devices make our daily life easier with the help of internet connectivity, they are becoming an easy target for attackers to penetrate various cyber-attacks. Distributed Denial of Service (DDoS) is one of the pernicious attacks that can be attempted easily on IoT devices. To make our home smart, these devices play a vital role and as a security expert, it is our responsibility to ensure the security of these IoT devices. In this paper, we propose a security scheme to ensure the IoT devices' security. With the capability of the ensemble machine learning technique, we designed and implemented an intrusion detection system in securing IoT devices. To utilize the full capability of our security solution, we verified it with various well-known and benchmark datasets including the IoT dataset. The results show the efficiency of our security solution by producing better F-1 score and lower false alarms compared to any existing approaches.