Miracle-dz/UniFAR-FTUs huggingface dataset:
Internet of Radars: Sensing versus Sending with Joint Radar-Communications

The Internet of Things (IoT) is made up of interconnected devices for exchanging information through sensors and actuators. One of the main physical sensors to understand the environment beyond the visible world is a radar. Basically, radars have always been a military tool to investigate the environment. However, with the developing technology, radars have become more compact and affordable to use in a building, in a car, in a drone, or even in a wristwatch. In the near future, radar-equipped IoT platforms will start to appear increasingly. For each IoT platform, dual use of spectrum with dual aperture is required for sensing and communicating when using conventional approaches. Emissions from the radar and communication circuitries are the main causes of the increase in energy consumption for any radar sensing IoT device. Furthermore, an increasing number of radars cause congested spectrum, and RF convergence between radar and communication systems becomes more likely to present itself. In recent years, numerous research works have proposed using the single waveform for perceiving the environment and sending information. They are often called "joint radar-communication' (JRC) systems. As a result of the latest advancements in JRC system designs, radar sensing IoT platforms now can be transformed into an "Internet of Radars" (IoR). This article is an attempt to introduce a prospective research direction in order to develop the architectures necessary to make the IoR concept possible. In this article, we present a short survey of JRC technologies likely to be used on radar-sensing-capable IoT devices. Then possible application areas, challenges to enable JRC, and future research perspectives are proposed.
Data mining based Classification of Players in Game of Cricket

Cricket is an outdoor sport that is extremely popular in Asian countries. Generally, the game is played in three different formats. Each format throws its own set of challenges and teams that are chosen in accordance to the format demands. The outcome of a cricket match is highly unpredictable if the gap between the skill levels of opponent teams is very narrow. It should also be noted that, Cricket is a team game, it is not one player, who determines the course of outcome of the match. Hence selecting the right team for a match by assessing the available player performance and playing conditions has a significant bearing on the outcome of the match. This work is further focused towards developing a robust prediction model that can classify players and accordingly help in predicting the Cricket team especially in the ODI format.
Sensitivity of Greenland ice sheet projections to spatial resolution in higher-order simulations: the Alfred Wegener Institute (AWI) contribution to ISMIP6 Greenland using the Ice-sheet and Sea-level System Model (ISSM)

Abstract. Projections of the contribution of the Greenland ice sheet to future sea-level rise include uncertainties primarily due to the imposed climate forcing and the initial state of the ice sheet model. Several state-of-the-art ice flow models are currently being employed on various grid resolutions to estimate future mass changes in the framework of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). Here we investigate the sensitivity to grid resolution of centennial sea-level contributions from the Greenland ice sheet and study the mechanism at play. We employ the finite-element higher-order Ice-sheet and Sea-level System Model (ISSM) and conduct experiments with four different horizontal resolutions, namely 4, 2, 1 and 0.75 km. We run the simulation based on the ISMIP6 core climate forcing from the MIROC5 global circulation model (GCM) under the high-emission Representative Concentration Pathway (RCP) 8.5 scenario and consider both atmospheric and oceanic forcing in full and separate scenarios. Under the full scenarios, finer simulations unveil up to approximately 5 % more sea-level rise compared to the coarser resolution. The sensitivity depends on the magnitude of outlet glacier retreat, which is implemented as a series of retreat masks following the ISMIP6 protocol. Without imposed retreat under atmosphere-only forcing, the resolution dependency exhibits an opposite behaviour with approximately 5 % more sea-level contribution in the coarser resolution. The sea-level contribution indicates a converging behaviour below a 1 km horizontal resolution. A driving mechanism for differences is the ability to resolve the bedrock topography, which highly controls ice discharge to the ocean. Additionally, thinning and acceleration emerge to propagate further inland in high resolution for many glaciers. A major response mechanism is sliding, with an enhanced feedback on the effective normal pressure at higher resolution leading to a larger increase in sliding speeds under scenarios with outlet glacier retreat.
A Static Feature Selection-based Android Malware Detection Using Machine Learning Techniques

With an increase in popularity and usage of smartphones, attackers are constantly trying to get sensitive information from smartphones. To protect the information, researchers are constantly working on the effective detection of android malware. Since there has been a large-scale increase in the number of new malware being detected, machine learning based techniques have to turn towards for effective large-scale detection. In this paper, CICInvesAndMal2019 have been taken as dataset and used android permissions and intent as a feature set for malware detection. Principal Component Analysis was used as a feature selection approach The dataset is trained and tested over well-known machine learning models and Random Forest was the best classifier with 96.05% accuracy.
Effect of integrative nursing practices on cognitive recovery among severe traumatic brain injury patients

Background and objective: Cognitive recovery after severe traumatic brain injury (TBI) is the biggest challenge facing the critical care nurses (CCNs). Several studies have been reported that the majority of CCNs are concerned with providing conventional nursing practices to severe TBI patients. These practices are directed to stabilize patients’ status rather than to enhance cognitive recovery after TBI. Application of integrative nursing practices for TBI patients can help in enhancing cognitive recovery. Aim: This study aimed to determine the effect of integrative nursing practices on cognitive recovery among severe traumatic brain injury patients. Methods: A quasi experimental research design was utilized. A convenience sample was conducted on 60 adult patients suffering from severe TBI who admitted to the intensive care units of Alexandria Main University Hospital. Patients were assigned into study group (30 patients) and control group (30 patients). One tool was used for data collection namely “Cognitive Recovery Assessment Tool”. This tool was used to assess recovery of cognitive function domains. It consists of level of consciousness using Full Outline of Un-Responsiveness (FOUR) score, level of cognitive functioning using Rancho Los Amigos (RLA) scale and basic cognitive sensory recovery assessment using Western Neuro Sensory Stimulation Profile (WNSSP) scale. Results: The implementation of integrative nursing practices for the study group was associated with statistically significant positive effects. Patients in the study group showed higher means of consciousness revealed by FOUR score and cognitive function revealed by RLA scale. The basic cognitive sensory recovery revealed by WNSSP scale in the study group was also significantly improved. Conclusions: Implementation of integrative nursing practices has been shown to enhance cognitive recovery among severe TBI patients. Thus, it is recommended for use in a nurse’s daily routine of care for severe TBI patients.
College Students' Autonomous Learning Behavior in Blended Learning: Learning Motivation, Self-Efficacy, and Learning Anxiety

Blended Learning has changed the traditional teaching mode and attracted wide attention to the educational community. In blended learning, students have more autonomy. This paper aims to study the autonomous learning behavior of college students in blended learning. In this study, five hypotheses were answered by using multiple linear regression. Results show that learning motivation and academic self-efficacy can effectively predict college students' autonomous learning behavior. In addition, academic self-efficacy has a positive effect on learning motivation, and learning anxiety is negatively correlated with learning motivation, learning anxiety and self-efficacy indirectly affect autonomous learning behavior through learning motivation. The results of this study provide new ideas and suggestions for the implementation of blended learning.
Enabling Higher Order Lamb Wave Acoustic Devices With Complementarily Oriented Piezoelectric Thin Films

In this work, we present a new paradigm for enabling gigahertz higher-order Lamb wave acoustic devices using complementarily oriented piezoelectric (COP) thin films. Acoustic characteristics are first theoretically explored with COP lithium niobate (LiNbO<sub>3</sub>) thin films, showing their excellent frequency scalability, low loss, and high electromechanical coupling (<inline-formula> <tex-math notation="LaTeX">$k^{2}$ </tex-math></inline-formula>). Acoustic resonators and delay lines are then designed and implemented, targeting efficient excitation of higher-order Lamb waves with record-breaking low loss. The fabricated resonator shows a <inline-formula> <tex-math notation="LaTeX">$2^{\mathbf {nd}}$ </tex-math></inline-formula>-order symmetric (S2) resonance at 3.05 GHz with a high quality factor (<inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>) of 657, and a large <inline-formula> <tex-math notation="LaTeX">$k^{2}$ </tex-math></inline-formula> of 21.5% and a <inline-formula> <tex-math notation="LaTeX">$6^{\mathbf {th}}$ </tex-math></inline-formula>-order symmetric (S6) resonance at 9.05 GHz with a high <inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> of 636 and a <inline-formula> <tex-math notation="LaTeX">$k^{2}$ </tex-math></inline-formula> of 3.71%, both among the highest demonstrated for higher-order Lamb wave devices. The delay lines show an average insertion loss (IL) of 7.5 dB and the lowest reported propagation loss of 0.014 dB/<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> at 4.4 GHz for S2. Notable acoustic passbands up to 15.1 GHz are identified. Upon further optimizations, the proposed COP platform can lead to gigahertz low-loss wideband acoustic components. [2020-0127]
Hybrid motion-based object detection for detecting and tracking of small and fast moving drones

A hybrid detecting and tracking system that is made especially for small and fast moving drones in which the other existing techniques cannot detect is presented. This new automatic system integrates geometry estimation, 2D object detection, 3D localization, trajectory estimation and tracking for dynamic scene interpretation. This caters to moving cameras, e.g. those mounted on a separate flying platform. The technique is built on the unified two-step real-time algorithm for detection and tracking of moving objects (DATMO) in dynamic outdoor environments. The first step is built on the motion-based detection approach for early detection of an object when the targeted object is still far away and appears very small in the scene. The second step is based on the appearance-based detection approach for continual detection, further identification and verification of the object. The camera's own position is estimated by 3D triangulation of the static landscape in the scene, doubled up as ground truth. This includes both the pan-tilt-zoom motion and the camera's vibration compensation. Therefore, the drone can be tracked, even when the camera is in motion and/or under jittery condition. As a result, the position of the tracked drone in the global inertial coordinate is further improved. Subsequently, the drone motion is tracked using the Extended Kalman Filter scheme. Initial results show that this hybrid system is able to detect a small drone from a distance away in less than a few frames after such a drone appears in the scene. The drone is always tracked as long as it is in the camera's field of view. As this technique is vision-based, this drone detection and tracking system can expand to detect multiple drones.
Design and Fabrication of a Band-Pass Filter With EBG Single-Ridge Waveguide Using Additive Manufacturing Techniques

A novel band-pass filter topology in waveguide technology is presented in this work. The proposed filter design is based on a periodic structure that uses modified sections of a single-ridge waveguide (SRW) as the unit cell to produce the desired frequency response. Two-step height profiles are included in the central part of the SRW, which provide useful parameters to yield a simple design method to achieve the required filtering characteristics. The suggested topology and design process are used to achieve band-pass filter responses with different fractional bandwidth and rejection characteristics. A 54% fractional bandwidth band-pass filter centered at 5.4 GHz is implemented using low cost 3-D additive manufacturing techniques, which allow fast prototyping and the fabrication of complex geometries. Experimental measurements are in agreement with the expected simulated response of the designed band-pass filter.
Diversity of early life-history traits in freshwater eels and the evolution of their oceanic migrations

Early life-history traits of all 19 anguillid eel species and subspecies were examined to help understand the evolution- ary processes of their oceanic migrations in comparison with their migration distances and the geography of their species ranges. Tropical species were found to have fewer myomeres, greater body depths, higher growth rates, shorter larval durations, and smaller maximum larval sizes than temperate species. The relationships among larval characteristics such as growth rate, age at metamorphosis, and maximum larval size differed among tropical and temperate species and corresponded with the maximum latitudes of their species ranges. Temperate eel leptocephali with slow growth and large maximum size with slender bodies appear to be specialized for long migrations and dispersal over a wide range of distances to higher latitudes, while having flexible sizes of metamorphosis and recruitment. Tropical species with faster growth metamorphose earlier at a relatively fixed size, which would facilitate larval retention near their species ranges at low latitudes. Changes in the early life-history traits of tropical eels appear to have occurred during the evolution of longer migrations as they entered temperate regions.
A Risk-based Path Planning Strategy to Compute Optimum Risk Path for Unmanned Aircraft Systems over Populated Areas

The large diffusion of Unmanned Aircraft Systems (UAS) requires a suitable strategy to design safe flight missions. In this paper, we propose a novel path planning strategy to compute optimum risk path for UAS over populated areas.The proposed strategy is based on a variant of the RRT* (Rapidly-exploring Random Tree "Star") algorithm, performing a risk assessment during the path planning phase. Like other RRT-based algorithms, the proposed path planning explores the state space by constructing a graph. Each time a new node is added to the graph, the algorithm estimates the risk level involved by the new node, evaluating the flight direction and velocity of the UAS placed in the analyzed node.The risk level quantifies the risk of flying over a specific location and it is defined using a probabilistic risk assessment approach taking into account the drone parameters and environmental characteristics.Then, the proposed algorithm computes an asymptotically optimal path by minimizing the overall risk and flight time.Simulation results in realistic environments corroborate the proposed approach proving how the proposed risk-based path planning is able to compute an effective and safe path in urban areas.
DEPICTING THE ROLE OF ORGANIC AMENDMENTS FOR BIO AVAILABLE PHOSPHORUS RELEASE FROM DIFFERENT SOURCES OF ROCK PHOSPHATE AND UPTAKE BY MAIZE CROP

A pot study was conducted in the laboratory to evaluate the effect of organic amendments on phosphorus release from imported and indigenous sources of rock phosphate and its impact on growth of maize. Seeds were sown in sand and soil (pHs pre study = 8.15, pHs post study = 8.02, ECe = 1.28 dSm, SAR = 4.77 (mmol L), saturation percentage = 29%, Available P = 7.1 mg kg, sandy clay loam texture) culture of 1:1 ratio. In this controlled conditions laboratory experiment, two sources of RP; A;. Alwaha rock phosphate (RPB-rock phosphate brown) and BHazara rock phosphate (RPB-rock phosphate brown) with 9 different combinations of organic amendments in a ratio of 1:2 were tested. The experiment comprised of 19 treatment replicated thrice using CRD design: T1: control(check P), T2:RPB, T3: RPB+CM, T4: RPB+FCP, T5: RPB+ WS, T6: RPB+FYM, T7: RPB+PM, T8: RPB+PSM, T9: RPB+CP+PGPR, T10: RPB+ 1⁄2 PM+ 1⁄2 FCP, T11: RPR, T12: RPR+CM, T13: RPR+FCP, T14: RPR+WS, T15: RPR+FYM, T16: RPR+ PM, T17: RPR+PSM, T18: RPR+CP+PGPR, and T19: RPB+ 1⁄2 PM+ 1⁄2 FCP. The collected data was subjected to statistical analysis using R-software for windows and least significant difference among the treatments means. Results suggested that use of filter cake press mud (FCP) proved superior in terms of enhancing P release from RP and subsequent uptake by maize crop.
New Optimal $Z$-Complementary Code Sets Based on Generalized Paraunitary Matrices

The concept of paraunitary (PU) matrices arose in the early 1990 s in the study of multi-rate filter banks. These matrices have found wide applications in cryptography, digital signal processing, and wireless communications. Existing PU matrices are subject to certain constraints on their existence and hence their availability is not guaranteed in practice. Motivated by this, for the first time, we introduce a novel concept, called <inline-formula><tex-math notation="LaTeX">$Z$</tex-math></inline-formula>-paraunitary (ZPU) matrix, whose orthogonality is defined over a matrix of polynomials with identical degree not necessarily taking the maximum value. We show that there exists an equivalence between a ZPU matrix and a <inline-formula><tex-math notation="LaTeX">$Z$</tex-math></inline-formula>-complementary code set when the latter is expressed as a matrix with polynomial entries. Furthermore, we investigate some important properties of ZPU matrices, which are useful for the extension of matrix sizes and sequence lengths. We propose a new construction framework for optimal ZPU matrices which includes existing PU matrices as special cases. Finally, we give the enumeration formula for the constructed <inline-formula><tex-math notation="LaTeX">$Z$</tex-math></inline-formula>-complementary sequences from the optimal ZPU matrices.
Maintenance Scheduling in Power Electronic Converters Considering Wear-out Failures

Power electronic converters are one of failure sources in energy systems, and hence drivers of downtime costs in power systems. Different approaches can be employed for converter reliability enhancement including design/control for reliability methods, condition monitoring and fault diagnosis, and maintenance strategies. This paper proposes optimal preventive maintenance strategies based on wear-out failure model of converter components. The proposed approaches employ two different performance measures at converter-level and system-level. The converter-level measures take into account planned and unplanned maintenance times or costs in a single unit or small-scale system. Moreover, the system-level measure considers not only maintenance times, but also energy losses and additional maintenance costs induced by aging of the converter components. The outcome is optimal replacement time of converter and its components, which depends on the employed performance measure. Optimal replacement scheduling is of importance for risk management and decision-making during planning of modern power electronic based power systems. The applicability of the proposed approaches is illustrated by numerical analysis in a photovoltaic system.
Glycine in Broiler Nutrition

ABSTRACT SINCE the discovery of vitamin B12, it has been possible to formulate poultry feeds using vegetable products as the sole source of protein. One of the most widely used of these products is soybean oil meal. It has been shown by analysis to be deficient in methionine for the chick (Almquist, 1957). Therefore, when soybean oil meal constitutes the principle source of protein in a broiler feed, methionine becomes the first limiting amino acid. Early work using methionine supplementation of broiler feeds gave somewhat inconclusive results which have been partially explained by later work. Baldini and Rosenberg (1955) observed a relationship between the methionine requirement of the chick and the productive energy content of the diet. They concluded that the methionine requirement of the chick, expressed in percent of diet, increased as the productive energy level of diet increased. Further work by Rosenberg and Baldini (1957), indicated a relationship between .
Quantifying the correlation between mobile continents

13 Continents influence the mantle’s convective wavelength and the heat flow escaping from 14 the planet’s surface. Over the last few decades, many numerical and analytical studies 15 have contributed to the debate about whether the continents can warm up the subcon16 tinental mantle or not and if they do, then to what extent? However, a consensus regard17 ing the exact nature and magnitude of this correlation between continents and elevated 18 temperatures in the subcontinental mantle remains to be achieved. By conducting a sys19 tematic parameter study using 2D global mantle convection simulations with mobile con20 tinents, we provide qualitative and quantitative observations on the nature of this cor21 relation. In our incompressible and compressible convection models, we observe the gen22 eral processes of downwellings bringing cold material into the mantle along continental 23 margins and a subsequent buildup of warm thermal anomalies underneath the continents. 24 We compute the amplitude and degree of this correlation using spectral decomposition 25 of the temperature and composition fields. The dominant degree of correlation evolves 26 with time and changes with continental configuration. Using simple empirical fits, we 27 observe that this correlation decreases with increasing core temperature, number of con28 tinents, internal heating, or decreasing reference viscosity. We also report simple regres29 sions of the time-dependence of this correlation. Additionally, we show that decompres30 sion melting as a result of a mantle upwelling or small-scale sublithospheric convection 31 leads to voluminous volcanism. The emplacement of this dense basalt-eclogite material 32 breaks the continents apart and destroys the correlation. 33
Development of genomic resources for four potential environmental bioindicator species: Isoperla grammatica, Amphinemura sulcicollis, Oniscus asellus and Baetis rhodani

A low-coverage genome was generated for each of four environmental key-species of macroinvertebrate taxa for the primary purpose of microsatellite marker development. De novo assemblies and microsatellite markers were designed for the freshwater species Isoperla grammatica, Amphinemura sulcicollis, and Baetis rhodani but have not been completed for the common shiny woodlice Oniscus asellus. Here, the data is made available, and the methods and pipeline are described which led to the creation of this resource. As widespread and functionally important organisms, which are often neglected in favour of studies on vertebrates, this data will be a useful resource for further research.