Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-Band SIW Cavity-Backed Slot Array Using TM020 and TM120 Modes for 5G Applications

In this communication, dual-band and low-profile circular cavity-backed slot array using TM<sub>020</sub> and TM<sub>120</sub> modes is proposed based on the substrate integrated waveguide for the fifth-generation (5G) applications. Two key issues are solved: multiresonance and proper frequency ratio. For the former one, the proximity-coupled slot is utilized to excite the high-order modes and depress the polarization degenerate modes. For the latter one, the TM<sub>020</sub> and TM<sub>120</sub> modes of the circular cavity are used to cover the 28/38 GHz bands. Finally, a cavity-backed slot array with excellent performance is achieved. The mechanism is discussed in this communication, and for demonstration, the prototype is fabricated and measured. The results show that the operating bands of 26.3–32.3 and 37.4–38.4 GHz are achieved, which cover the 28 and 38 GHz bands, respectively. The realized gains are 13.2 dBi at 28 GHz and 14.6 dBi at 38 GHz. The thickness of the array is <inline-formula> <tex-math notation="LaTeX">$0.12\lambda $ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> is the wavelength at 28 GHz. The proposed array is eligible for the 5G applications in the <italic>Ka</italic>-band.
An opportunistic energy‐efficient dynamic self‐configuration clustering algorithm in WSN‐based IoT networks

The demand for the Internet of Things (IoT) has significantly increased in the current scenario; specific sectors that require IoT include industrial automation, home control, health care applications, military and surveillance applications, habitat monitoring, and nanoscopic sensor applications. The use of optimal wireless sensor networks (WSNs) in transmission techniques has resulted in their involvement. A WSN is made up of thousands of randomly distributed sensor nodes that sense and transmit environmental data such as temperature, pressure, humidity, light, and sound. One of the most important requirements when using these sensor nodes is energy. As a result, it has become a major area of research in recent years; additionally, several design techniques and protocols have been presented in the last decade, particularly for IoT‐based applications. As a result, the systemization of an energy‐optimized WSN in dynamic functional conditions with automatic self‐configuration of sensor nodes is a critical goal. This paper proposed an opportunistic energy‐efficient dynamic self‐configuration routing (OEDSR) algorithm for IoT‐based applications. Initially, the optimal route to the base station (BS) is calculated by using the residual energy and mobility factor of the sensor nodes obtained through a routing tree model based on graph theory. To reduce the number of connections, an optimal path is determined based on dynamic cluster generation through a hierarchical tree architecture. Finally, the network‐related parameters, such as throughput, delay and packet delivery ratio (PDR), are compared with the peer existing routing protocols to depict the efficiency of the OEDSR protocol.
Reconstruction 3D pour la volcanologie : apports d'une méthode multi-vues par photogrammétrie numérique

La reconstruction 3D est un outil primordial en volcanologie : etudes morpho-structurales, deformation du sol, modelisation analogique. Une approche originale de reconstruction 3D specifique aux applications volcanologiques a ete developpee. Basee sur l'utilisation de plusieurs images numeriques acquises autour d'une surface, elle se decompose en deux etapes : (1) un calibrage precis du capteur optique (2) une reconstruction 3D reposant sur la deformation iterative d'un modele 3D initial. La methode a ete developpee et testee en laboratoire sur divers modeles analogiques. Les resultats montrent qu'elle constitue un outil de quantification souple et puissant permettant de detecter des variations fines de la morphologie. Des tests sur site reel ont aussi montre le potentiel important de la methode dans le cadre de la surveillance volcanologique. L'approche, a la frontiere entre Volcanologie et Vision par Ordinateur, offre une alternative aux methodes classiquement utilisees.
Hierarchical Nash equilibrium seeking strategies of quadratic time‐varying games with Euler–Lagrange players

This article investigates the distributed Nash equilibrium seeking problem of quadratic time‐varying games with Euler–Lagrange (EL) players, where external disturbances and parametric uncertainties are involved. A gradient‐based hierarchical algorithm consisting of a game layer and a control layer is proposed. Specifically, in the game layer, EL players communicate with neighbors through a graph to reach the consensus on potential aggregate values, which will be employed to calculate the gradient of each player's objective function, and then, a gradient‐based sliding mode controller is developed to track time‐varying gradient in the control layer. Thus, the convergence results are hierarchically obtained through the Lyapunov stability method. In addition, the hierarchical control strategy is extended to address the constrained problems through the utilization of a smooth penalty function. By appropriately choosing control parameters, the Nash equilibrium seeking errors can be arbitrarily small. The relation between the optimal solutions of the original problem and the dual one is further discussed. Finally, the proposed methods are numerically verified.
Applications and Field Testing of a Flash LIDAR System for Future Planetary Missions

Introduction: Ball Aerospace and Technologies Corp has developed and field tested a versatile Flash LIDAR instrument which can provide real-time (30 Hz) imaging for a wide variety of planetary science and exploration mission applications. The instrument has an overall Technology Readiness Level of 5 (prototype validation in a relevant environment), built with subassemblies which have even greater maturity, including flight heritage. Ball is currently developing flash LIDAR for a 2010 flight (discussed below). This paper highlights key features of the flash LIDAR instrument, discusses direct applications of the system for planetary science investigations, and describes instrument maturity, including ongoing efforts and results from recent field testing. Flash LIDAR Features: Flash LIDAR systems are analogous to a camera with a flashbulb (flood illumination), but with the flash being provided by laser illumination and the use of a detector with a clock to determine the time it takes for the flash to depart, reflect off of the target, and return. By measuring the time of flight of the reflected laser pulse, the sensor can determine a range measurement along with intensity for each pixel in the image. This information set over the range of all detector pixels is referred to as a 3D LIDAR image or point cloud.
THE EFFECT OF DROPOUT PREVENTION PROGRAM OF 9th GRADE RETENTIONS STUDENTS ON DROPOUT RISK, SELF-EFFICACY BELIEF AND LEARNING MOTIVATION STRATEGIES

High school dropout is a common problem in many countries and governments are trying to solve this problem for years. School counsellors can play an important role in dropout prevention by implementing school-based interventions. The aim of this study is to examine the effect of the Social-Cognitive Learning theory-based dropout prevention program which is applied to 9th grade retention students of the Anatolian and vocational high school students who were at risk for dropout. The dropout prevention program was aimed at reducing dropout risk, enhancing self-efficacy belief, and learning motivation strategies of students. The program was implemented in 11 sessions for the experimental students. For the data analysis, ‘ANOVA’ for the repeated measures and ‘Bonferroni test were used to evaluate the effect of the program on students. The result of the study showed that the dropout prevention program is effective in reducing participants’ dropout risk, enhancing learning motivation strategies, and moderating self-efficacy beliefs. In conclusion, it can be said that Social-Cognitive Learning theory-based psychoeducation program is effective to reduce the dropout risk at high schools. Article visualizations:
Assessing the Influence of the COVID-19 Pandemic on the Purchasing Intention of Vitamins in Kuwait using the Theory of Planned Behavior

Using the Theory of Planned Behavior model developed by Ajzen in 1985, the authors assessed the influence of attitude (ATT) toward vitamins, health awareness (HA), perceived behavioral control (PBC), subjective norms (SN), and knowledge of COVID-19 (KN) on the purchasing intention (PI) of vitamins in Kuwait during the COVID-19 pandemic. A total of 587 adults living in Kuwait completed the online survey, which was available in both Arabic and English. The measured variables included health awareness, attitude, knowledge about COVID-19, purchasing intention, perceived behavioral control, and subjective norms. The findings indicate that HA has a significant impact on ATT. Furthermore, the results revealed that HA significantly influences ATT, ATT has a significant influence on PI, KN has a significant influence on ATT, KN has a significant influence on PI, PBC positively influences PI, SN has a significant influence over PI, and SN positively influences PI.
White matter microstructure alterations in idiopathic restless legs syndrome: a study combining crossing fiber-based and tensor-based approaches

Introduction Restless legs syndrome (RLS) is a common sensorimotor disorder characterized by an irrepressible urge to move the legs and frequently accompanied by unpleasant sensations in the legs. The pathophysiological mechanisms underlying RLS remain unclear, and RLS is hypothesized to be associated with alterations in white matter tracts. Methods Diffusion MRI is a unique noninvasive method widely used to study white matter tracts in the human brain. Thus, diffusion-weighted images were acquired from 18 idiopathic RLS patients and 31 age- and sex-matched healthy controls (HCs). Whole brain tract-based spatial statistics (TBSS) and atlas-based analyzes combining crossing fiber-based metrics and tensor-based metrics were performed to investigate the white matter patterns in individuals with RLS. Results TBSS analysis revealed significantly higher fractional anisotropy (FA) and partial volume fraction of primary (F1) fiber populations in multiple tracts associated with the sensorimotor network in patients with RLS than in HCs. In the atlas based analysis, the bilateral anterior thalamus radiation, bilateral corticospinal tract, bilateral inferior fronto-occipital fasciculus, left hippocampal cingulum, left inferior longitudinal fasciculus, and left uncinate fasciculus showed significantl increased F1, but only the left hippocampal cingulum showed significantly higher FA. Discussion The results demonstrated that F1 identified extensive alterations in white matter tracts compared with FA and confirmed the hypothesis that crossing fiber-based metrics are more sensitive than tensor-based metrics in detecting white matter abnormalities in RLS. The present findings provide evidence that the increased F1 metric observed in sensorimotor tracts may be a critical neural substrate of RLS, enhancing our understanding of the underlying pathological changes.
Understanding and addressing smartphone addiction: A multidisciplinary perspective

The present study investigates the escalating dependency on smartphones, with tendencies toward severe addiction, thereby causing detrimental effects on both psychological and physiological well-being. The group addicted to mobile phones exhibits behavioral and neurophysiological differences compared to the non-addicted group. Non-invasive neural modulation techniques such as transcranial direct current stimulation and aerobic exercises such as HPCOSMOS exergaming (Treadmill-based, combining action control and motion perception in a Switch game) may represent cost-effective, adaptable, and promising therapeutic approaches. That will contribute to establishing a theoretical foundation for the rehabilitation and treatment of individuals afflicted with smartphone addiction.
Convective Heat Transfer between Liquid Argon Flows and Heated Carbon
 Nanotube Arrays using Molecular Dynamics

This paper presents the molecular dynamics simulations of unconfined forced convective flow through the nanostructures at steady state condition. A better understanding of forced convective flow through the nanostructures is important because of its wide range of applications in nano-scale devices. Present work focuses on the heat transfer process of argon flow over a carbon nanotube and carbon nanotube arrays with constant surface temperature using molecular dynamics simulations. We consider two elementary configurations for the case of carbon nanotube arrays based on the unit cell structure. The simulation domain consists of fixed carbon nanotubes surrounded with the flowing argon atoms. An extensive study of momentum and thermal transport between carbon nanotube and surrounded argon atoms are analyzed from its microscopic state. The heat transfer coefficient is found in the order of 10 W/mK. The method proposed in this paper can be an elementary step for the geometry calculation of nano-structured heat sink in the high heat flux electronic chips.
Comparison of Braitenberg Vehicles with Bio-Inspired Algorithms for Odor Tracking in Laminar Flow

Odor gas tracking is a capability exhibited by animals but sorely needed by humans for applications in areas such as security, search and rescue and industrial monitoring; amongst others. The research documented in this document proposes a new algorithm based on Braitenberg vehicle that mimics the strategy of animals and insects for odor tracking. Simulation results show that the proposed algorithm was able to independently track an odor plume to its source, comparable to other prominent algorithms. Deployment of a multirobot system using the same algorithm shows an improvement in the completion of the plume tracking task in terms of completion time. Furthermore, comparisons with other algorithm have shown that the proposed algorithm performs better than the typical single and multi-robot strategies.
A Hybrid Optimization Algorithm combining Genetic Algorithm with Neural Network for Web Service Selection

Web service composition provides a key technology to build loosely coupled, integrated and service oriented applications. The task of service selection that satisfies the user functional requirements is complicated. Due to the availability of the different services with same functionalities around the web, a structure must be designed that facilitates the consumer to select the required services with non-functionality characteristics such as Quality of Services (QoS). This paper shows the advantages of using the neural networks with evolutionary techniques to address the web service selection problem. The structure of the hidden layers in neural network is not modified since the system concerns only with calculation of weights. The genetic algorithm works on the weights of neural network and makes exchange between them using crossover and mutation operators to get advanced a network which produces user satisified services as output. Experimental results prove that the proposed algorithm outperforms the results obtained by genetic algorithm and neural networks individually.
QoS Based Ranking Methodology for Semantic Search System

The huge amount of data is making search more and more difficult with traditional search methods as they return vast data for a given query which is containing of related or unrelated data. So, users are not satisfied with searching the information by current search engine. Subsequently the problem of re-ranking searches or results has become one of the main problems in web search. Currently searching methods are mainly based on traditional technique but this technique has some problem. The first problem is that web users cannot express their search intention accurately or properly using several
Identifying Variation in the Newborn Life Support Procedure: An Automated Method

This research is conducted for developing an automated method to recognize variations in the Newborn Life Support (NLS) procedure. Compliance with the NLS standard guideline is essential to prevent any adverse consequences for the newborn. Video recordings of resuscitation are frequently used in research to identify types of variations and understand how to minimize unwanted ones. Despite their benefits, it takes a significant amount of time and human resources to manually evaluate the procedure from videos. Therefore
Some Upper Visean columnate tetracorals from the Holy Cross Mountains (Poland)

This paper is an elaboration of the representatives of the Upper Visean tetracoral families Amygdalophyllidae Grabau and Rozkowskiidae n. fam. of the Holy Cross Mts. Development trends within the superfamily Aulophyllicae, as well as the microstructure of septa and columellae are presented in the general part, in which the microstructure of columella has been assumed as a basis for erecting families. The systematic part contains descriptions of 16 species (and two subspecies) belonging to four genera and two families. Most taxonomic units have for the first time been erected in the present paper.
Immunoglobulin E (IgE)-Mediated Multiple Myeloma Presenting as Pleural Effusion

Multiple myeloma (MM) is a disease characterized by the abnormal production of plasma cells. These plasma cells have the property to produce immunoglobulins (Ig), on the basis of which MM can be classified. Immunoglobulin G is responsible for most of the cases, while IgE mediates the rarest form of MM. Since the first case was reported in 1967, knowledge regarding IgE-mediated MM is based on individual case reports. Based on the information available, it is thought that IgE-mediated MM presents clinically with the involvement of renal, bone, and hematological symptoms, which are the same as any other myeloma. However, the MM rarely involves the pleura, leading to malignant pleural effusion. We present a case of IgE-mediated MM with a unique feature of pleural effusion. The patient presented with constitutional symptoms of MM, which were followed by lab investigations revealing low hemoglobin, hypercalcemia, and high creatinine levels. An incidental computed tomography angiography (CTA) revealed lytic lesions in the spine. This was followed by skull and chest X-rays as part of the workup to determine the extent of the disease. It revealed further lytic lesions in the skull, humerus, and scapula, along with pleural effusion. This led to the suspicion of MM, which was ultimately confirmed by serum protein electrophoresis and a bone marrow biopsy. The patient was started on a triple regimen of bortezomib, thalidomide, and dexamethasone, which led to substantial improvement in his symptoms.
GBNN algorithm enhanced by movement planner for UV‐C disinfection

In order to maintain adequate levels of cleanliness and sanitation in public facilities, prevent the buildup of viruses and other harmful pathogens, and ensure health and safety, health and labor authorities have repeatedly warned of the need to adhere to proper disinfection protocols in the workplace. This is particularly important in public places where food is handled, where there are more vulnerable people, including hospitals and health care centers, or where there is a large concentration of people. One promising approach is the combination of ultraviolet‐C (UV‐C) light and mobile robots to automate disinfection processes. Being this technology effective for disinfection, an excessive dose of UV can damage the materials, limiting its applicability. Therefore, a major challenge for automatic disinfection is to find a route that covers the entire surface, ensures cleanliness, and provides the correct radiation dose while preventing environmental materials from being damaged. To achieve this, in this paper a novel intelligent control approach is proposed. A bio‐inspired Glasius neural network with a motion planner, an UV estimation module, a speed regulator, and pure pursuit controller are combined into one intelligent system. The motion planner proposes a sequence of movements to go through the space in the most efficient way possible, avoiding obstacles of the environment. The speed controller adjusts the dose of UV‐C radiation and the pure pursuit regulator ensures the following of the path. This approach has been tested in various simulation scenarios of increasing complexity and in four different areas of dosing requirements. In simulation, a 44% reduction of the maximum dose is achieved, 17% less distance travelled by the robot and, what is more important, 229% more locations with the appropriate dose.
Effects of measurement methods and growing conditions on phenotypic expression of photosynthesis in seven diverse rice genotypes

Introduction Light response curves are widely used to quantify phenotypic expression of photosynthesis by measuring a single sample and sequentially altering light intensity within a chamber (sequential method) or by measuring different samples that are each acclimated to a different light level (non-sequential method). Both methods are often conducted in controlled environments to achieve steady-state results, and neither method involves equilibrating the entire plant to the specific light level. Methods Here, we compare sequential and non-sequential methods in controlled (greenhouse), semi-controlled (plant grown in growth chamber and acclimated to field conditions 2-3 days before measurements), and field environments. We selected seven diverse rice genotypes (five genotypes from the USDA rice minicore collection: 310588, 310723, 311644, 311677, 311795; and 2 additional genotypes: Nagina 22 and Zhe 733) to understand (1) the limitations of different methods, and (2) phenotypic plasticity of photosynthesis in rice grown under different environments. Results Our results show that the non-sequential method was time-efficient and captured more variability of field conditions than the sequential method, but the model parameters were generally similar between two methods except the maximum photosynthesis rate (Amax ). Amax was significantly lower across all genotypes under greenhouse conditions compared to the growth chamber and field conditions consistent with prior work, but surprisingly the apparent quantum yield (α) and the mitochondrial respiration (Rd ) were generally not different among growing environments or measurement methods. Discussion Our results suggest that field conditions are best suited to quantify phenotypic differences across different genotypes and nonsequential method was better at capturing the variability in photosynthesis.