Miracle-dz/UniFAR-FTUs huggingface dataset:
Constructing a Multilevel Modeling to High-Resolution CT (HRCT) Lung in Patients with COVID-19 Infection

: The coronavirus disease, also called COVID-19 is caused by the SARS-CoV-2 virus. Most the people contaminated with the virus will experience mild to moderate symptoms of respiratory diseases. The aim of this paper is constructing a model by multilevel modeling for these patients who sufferers by coronaviruses, we got seven hospitals which totals (636) patients in private and public that 27% from Erbil, 26% from Sulaimani, 23% from Duhok and 24% from Halabja from the period (September 1th, 2019 to February 1th, 2022). In these modelling of multilevel restricted maximum likelihood estimation (RMLE) and full maximum likelihood (FML) acclimate estimate the parameters of multilevel models (fixed and random). The application was on the HRCT lungs of patients, seven hospitals were selected randomly among the county in Kurdistan region of Iraq. The result shows that all three variables are significant at the hospital level, but in the two final models add level-2 predictor (Doctor Experience) that interaction with level-1 predictor (smoker), which is far from significant. However, there is a significant relationship between being a diabetic and having a CT scan, but the relationship between smoking and having a CT scan is not significant.
Preparation and properties of HfB2-HfC and HfB2-HfC-MoB composites by reactive spark plasma sintering

ABSTRACT Ultra-high-temperature ceramics are required for many aerospace applications. In this work, HfB2-30 vol.% HfC and HfB2-26 vol.% HfC-43 vol.% MoB high-density composites were prepared by one-step in-situ reactive spark plasma sintering (R-SPS) using Hf, B4C and Mo powders as starting materials. The influences of sintering temperature on the densification mechanism, microstructural evolution, mechanical properties and oxidation resistance of the composites were thoroughly investigated. The results demonstrate that the raw materials undergo a complete chemical reaction to form new binary HfB2-HfC and ternary HfB2-HfC-MoB composite structures at a temperature of 1300°C. The HfB2-HfC and HfB2-HfC-MoB composites prepared at the optimal conditions (pressure = 50 MPa, temperature = 1800°C, holding time = 5 min) had highre densities of 97% and 98%, respectively. The Vickers hardness, Young’s modulus and fracture toughness of the HfB2-HfC composite were 18.3 GPa, 525 GPa and 6.34 MPa·m1/2, respectively. However, after molybdenum was added, the Vickers hardness of the ternary HfB2-HfC-MoB composite increased to 19.4 GPa but its fracture toughness decreased slightly to 6.1 MPa·m1/2. Compared with the binary composite, the ternary composite exhibited a low and thermally stable oxidation rate up to a temperature of 1400°C, and the test was conducted in air atmosphere.
Suggestible Consequences of Militarizing Self-Determination Movements in Nigeria: A Case Study of Yoruba Separatist Movement

Nigeria, as one of the ethnically heterogeneous African states, has been historically confronted with ethnic conflicts and movements for self-determination, which are often followed by the state’s deployment of military armed forces to suppress them. This article uses a deductive thematic analysis of qualitative data obtained from a created Google form, a free online survey link with self-constructed questions to find out the prospect of the Nigerian government deploying military armed forces to suppress the ongoing Yoruba separatist movements as well as suggestible consequences of such militarization. The result unveils a higher prospect of the government militarizing the movement with the outbreak of mass violence as a suggestible outcome. With the theoretical review of the Remedial Theory of self-determination and the exploration of cases of self-determination in post-colonial African states, the article concludes that the possible eruption of mass violence leading to human rights violations and international interventions might result in the dissolution of Nigeria.
Dirac Equation for Posch-Teller Potential in Radial Section Symmetry Spin Case using Asymptotic Iteration Method

This study aims to determine the value of the energy spectrum and wave function for the Posch-Teller potential in the case of radial spin symmetry. The solution to the Dirac equation using the asymptotic iteration method is done by reducing the second-order differential equation to a hypergeometric type differential equation by means of variable substitution to obtain a relativistic energy equation. The relativistic energy of the system is calculated using matlab software. This study is limited to the case of spin symmetry in the radial section.
Reinforcement Learning-Based Routing Protocols in Vehicular and Flying Ad Hoc Networks – A Literature Survey

Vehicular and flying ad hoc networks (VANETs and FANETs) are becoming increasingly important with the development of smart cities and intelligent transportation systems (ITSs). The high mobility of nodes in these networks leads to frequent link breaks, which complicates the discovery of optimal route from source to destination and degrades network performance. One way to overcome this problem is to use machine learning (ML) in the routing process, and the most promising among different ML types is reinforcement learning (RL). Although there are several surveys on RL-based routing protocols for VANETs and FANETs, an important issue of integrating RL with well-established modern technologies, such as software-defined networking (SDN) or blockchain, has not been adequately addressed, especially when used in complex ITSs. In this paper, we focus on performing a comprehensive categorisation of RL-based routing protocols for both network types, having in mind their simultaneous use and the inclusion with other technologies. A detailed comparative analysis of protocols is carried out based on different factors that influence the reward function in RL and the consequences they have on network performance. Also, the key advantages and limitations of RL-based routing are discussed in detail.
A search for primeval galaxies at z=1.9

Results are reported from a search for primeval galaxies at redshifts lower than 2. An area of 0.1 deg sq has been searched for emission-line objects at 3500 A; none has been found down to a 2sigma surface-brightness threshold of 5.4 x 10 to the -17th erg/sq cm sec sq arcsec, corresponding to a surface brightness of about 27.6 mag sq/arsec (for a pure emission-line source). For objects with structure similar to that of the z = 18 emission-line galaxy 3C 326.1, the limiting flux is somewhat brighter. From this limit, constraints have been placed on the formation of galaxies at redshifts 1.8 or greater. 32 refs.
Formulation and release kinetics of ibuprofen–bentonite tablets

Abstract Bentonite-based tablets offer multiple advantages over other types of formulated tablets, including being biocompatible and cost-effective, and they can be used to develop gel-like matrices that have potential for use in sustained-release formulations. Developing a high-load sustained-release formulation has been reported to be challenging; therefore, the aim of this study was to develop systematically bentonite-based sustained-release tablets for a high-load active agent (ibuprofen) and investigate their release kinetics. Ibuprofen-loaded tablets (800 mg) were prepared using wet and dry granulation followed by enteric coating of the tablets. Fourier-transform infrared spectroscopy, differential scanning calorimetry and X-ray powder diffraction were used to evaluate the compatibility of ibuprofen with bentonite. The results show that these tablets comply with compendial requirements. In addition, the release profile of the formulations reveals that the drug follows a non-Fickian release model. The present formulation demonstrates a new use of bentonite as a safe and cost-effective excipient with adequate binding and compaction for preparing sustained-release tablets.
The high-luminosity BL Lacertae object PKS 0823 - 22

Simultaneous IR, optical, and UV observations of the BL Lac object PKS 0823 - 22 are presented. The identification of the observed absorption doublet at 5341 and 5355 A with Mg II 2796 and 2803 A gives an absorption redshift z(abs) = 0.910. At this redshift, the object is one of the most luminous of its class with M(V) less than about -29.4. The spectral flux distribution of the source and the properties of intervening absorbing matter are discussed. Analogies with other sources suggest that the object may be gravitationally lensed. 29 refs.
The synthesis of biologically active 1-sulfonyl-1, 2, 3-triazoles from sulfonyl azides and alkynes: a focus review

In this review, we spotlight the methods for the direct synthesis of synthetically and biologically important 1-sulfonyl-1, 2, 3-triazoles via [3+2] cycloaddition between easily available terminal alkynes and sulfonyl azides. The review is divided into two major sections. The first section focuses exclusively on the synthesis of 1-(N-sulfonyl)-4-substituted 1,2,3-triazoles, while the second section will discuss preparation of 1-(N-sulfonyl)-5-substituted 1,2,3-triazole derivatives. GRAPHICAL ABSTRACT
How Do Sky Conditions Affect the Relationships Between Ground‐Based Solar‐Induced Chlorophyll Fluorescence and Gross Primary Productivity Across Different Plant Types?

Solar‐induced chlorophyll fluorescence (SIF) has been used as a proxy for gross primary productivity (GPP) estimations. However, knowledge on how links between SIF and GPP across different plant types vary in response to sky conditions remain unclear. Here, we investigated the effects of sky conditions on the GPP‐SIF relationship based on continuous measurements of SIF and flux across four different plant types. Our analysis shows that the GPP‐SIF links are affected by sky conditions and these linking patterns respond differently across plant types. We propose that the inconsistent responses of SIF and GPP to sky conditions are primarily driven by variations in light use efficiency (LUE = GPP/absorbed photosynthetic active radiation (APAR)). Furthermore, we explore a quantitative variation in LUE and SIFyield (SIF/APAR) separately via a decoupling of clearness index (CI) and photosynthetic active radiation under different sky conditions. LUE is more sensitive to sky conditions for the C3 plants (Forest, Wheat and Rice) than the C4 plant (Maize), and SIFyield shows more sensitivity to sky conditions for the forest than croplands. Due to the tight link between CI and other environmental factors, the incorporation of CI into the SIF‐based GPP model improves GPP estimates for all C3 plants at both instantaneous and daily scales. Our study implies that a consideration of sky conditions into the SIF‐based GPP model can significantly advance the GPP modeling under all sky conditions.
Regularity properties of Hausdorff dimension in infinite conformal iterated function systems

This paper deals with families of conformal iterated function systems (CIFS). The space of all CIFS, with common seed space X and alphabet I, is successively endowed with the topology of pointwise convergence and a new, weaker topology called $\lambda$-topology. It is proved that the pressure and the Hausdorff dimension of the limit set are continuous with respect to the topology of pointwise convergence when I is finite, and are lower semi-continuous, though generally not continuous, when I is infinite. It is then shown that these two functions are, in any case, continuous in the $\lambda$-topology. The concepts of analytic, regularly analytic and plane-analytic families of CIFS are also introduced. It is established that if a family of CIFS is regularly analytic, then the Hausdorff dimension function is real-analytic; if a family is plane-analytic, then the Hausdorff dimension function is continuous and subharmonic, though not necessarily real-analytic. These results are then applied to finite parabolic CIFS. Counter-examples highlighting breakdowns of real-analyticity in the Hausdorff dimension among analytic, but not regularly analytic, families are further provided. Such families often exhibit a phenomenon known as phase transition. Sufficient conditions preventing the occurrence of such transitions are supplemented.
Distribution of Electrolytes with Excluded Volume around a Charged DNA Molecule

In this paper we evaluate the distribution of ions around a charged cylinder, in thermal equilibrium, taking into account the main effects of the excluded volume of the counterions. The cylinder is a model of a DNA molecule. There are major corrections to the standard Gouy-Chapman theory when the electrostatic energy due to the charge of the cylinder is large as compared to the thermal energy. The concentration shows a distinct saturation effect over a finite region, which may be interpreted as the Stern layer of immobilized ions. The known saturation of the electrostatic potential at the surface of the cylinder is removed.
Navigation of Robotic-Arms using Policy Gradient Reinforcement Learning

: In this paper, the Deep Deterministic Policy Gradient (DDPG) reinforcement-learning algorithm is employed to enable a double-jointed robot arm to reach continuously changing target locations. The experimentation of the algorithm is carried out by training an agent to control the movement of this double-jointed robot arm. The architectures of the actor and critic networks are meticulously designed and the DDPG hyperparameters are carefully tuned. An enhanced version of the DDPG is also presented to handle multiple robot arms simultaneously. The trained agents are successfully tested in the Unity Machine Learning Agents environment for controlling both a single robot arm as well as multiple simultaneous robot arms. The testing shows the robust performance of the DDPG algorithm for empowering robot arm maneuvering in complex environments.
Analysis and modeling of resistive switching statistics

The resistive random access memory (RRAM), based on the reversible switching between different resistance states, is a promising candidate for next-generation nonvolatile memories. One of the most important challenges to foster the practical application of RRAM is the control of the statistical variation of switching parameters to gain low variability and high reliability. In this work, starting from the well-known percolation model of dielectric breakdown (BD), we establish a framework of analysis and modeling of the resistive switching statistics in RRAM devices, which are based on the formation and disconnection of a conducting filament (CF). One key aspect of our proposal is the relation between the CF resistance and the switching statistics. Hence, establishing the correlation between SET and RESET switching variables and the initial resistance of the device in the OFF and ON states, respectively, is a fundamental issue. Our modeling approach to the switching statistics is fully analytical and contai.
Automated classification of odontocetes in open ocean environments using a novel multiclass suport vector machine

Mid‐frequency active sonar has recently been implicated in several marine mammal stranding events in various geographic locations. This has caused increased interest in monitoring and mitigating the effects of anthropogenic noise on marine mammals. Some species can be more susceptible sonar than others. For example, beaked whales (particularly Mesoplodon densirostris) have been the predominant species involved in most of the strandings. Key to effective monitoring and mitigation is the ability to automatically detect and identify the animals present, especially the species of high interest like beaked whales. This paper presents a novel class‐specific support vector machine (CS‐SVM) methodology for automated, species‐level classification of small odontocetes. A CS‐SVM has been developed and trained to identify click vocalization from several species of odontocetes including Mesoplodon densirostris. The algorithm processes time series data in a fully automated fashion first detecting and then classifying c.
A Convergence of ODE Method in Constrained Optimization

Abstract This paper proposes a convergence theory of the ordinary differential equations (ODE) method for finding the local optima of general constrained optimization. We prove that solutions starting from the neighbourhood of a critical point of the differential equations in this paper about part variables always converge to the feasible point of the problem. We also study the initial relationship between neural computation in optimization (NCO) and ODE methods. Some detailed connections of the two methods in solving the linear and quadratic programming on R n + are shown in this paper.
C-Supplemented subgroups of finite groups

A subgroup H of a group G is said to be c-supplemented inG if there exists a subgroup K of G such thatHK=G and H \cap K is contained in Core_G (H). We follow Hall's ideas to characterize the structure of the finite groups in which every subgroup is c-supplemented. Properties of c-supplemented subgroups are also applied to determine the structure of some finite groups.
Understanding partnerships in teacher and student feedback literacy: Shared responsibility

ABSTRACT Feedback literacy has been phenomenally studied across research and practices in the past decade. However, the partnership in teacher and student feedback literacy (TFL and SFL) has been scarcely studied. As a response, this study explored the statistical relationship between TFL and SFL and the perceptions of feedback-literate students and teachers, using two parallel questionnaires’ data from 200 students and 20 teachers at a southwestern Chinese university. Analyses revealed mismatched understandings of the TFL and SFL (at micro and macro level) and a medium positive correlation between TFL and SFL (at meso and macro level). Such empirical evidence validates that student–teacher partnerships should be well foregrounded to improve their feedback literacy. Meanwhile, new empirical insights – ‘awareness of the student–teacher partnership’ and ‘perception of the relationship between feedback and learning effects’ – should be added to existing SFL frameworks.
Analysis of orbital perturbations acting on objects in orbits near geosynchronous earth orbit

Orbital evolution has been numerically simulated for objects started in geosynchronous Earth orbit (GEO) or in orbits near GEO, during a project to study potential orbital debris problems in this region. Perturbations simulated include nonspherical terms in the Earth's geopotential field, lunar and solar gravity, and solar radiation pressure. Objects simulated include large satellites, for which solar radiation pressure is insignificant, and small particles (a few microns in diameter), for which solar radiation pressure is an important force. Results for large satellites are largely in agreement with previous GEO studies that used classical perturbation techniques; orbital evolution studies were extended to possible storage orbits slightly above or below GEO. One notes that while the orbit planes of GEO satellites initially placed in equatorial orbits precess, so that those orbits reach inclinations of 14° to 15° to the equator, a “stable plane” exists inclined approximately 7.3° to the equator. The orbit planes of GEO satellites placed in such a stable plane orbit experience very little precession, remaining always within 1.2° of their initial orientation. Solar radiation pressure generates two major effects on small particles. One is an orbital eccentricity oscillation anticipated from previous research. The other is an oscillation in orbital inclination. This orbital inclination pattern is due to a precession of the small particle's orbital angular momentum vector about an axis offset from the Earth's polar axis. The magnitude of the precession axis offset angle depends on the particle's cross-sectional area to mass ratio. The rate for this precession differs greatly from the precession rate predicted in a previous study using perturbation techniques. This difference points up the inadequacy of those perturbation techniques for orbits with large eccentricities. For one sequence of runs with small particles, Poynting-Robertson drag was added to the simulation in order to slowly reduce the orbital semimajor axis and probe for possible orbital period resonances near the GEO distance. A significant resonance was found at the geosynchronous distance, where small grains are trapped into a 1:1 resonance with the Earth's daily rotation.
Quantitative detection of multi-frequency disturbance signal by ϕ-OTDR system

Recently, the combination of pattern recognition technology and distributed fiber sensing systems has become increasingly common, so whether the disturbance signal can be well recovered has become increasingly important. To verify the recovery and linear response of a distributed fiber optic sensing system to multi-frequency disturbance signals, a heterodyne coherent detection system for phase-sensitive optical time-domain reflectometry is developed. The output beat signal is extracted using the digital in-phase/quadrature demodulation algorithm. The signal can be precisely located on a 7 km length range, and the disturbance signal can be restored well through the phase information. Not only the superposition signal composed of the same signal but also that composed of different kinds of signals can be successfully restored. A fast Fourier transform algorithm is used to obtain the frequency information of the superimposed signal. Combined with the use of a finite impulse response filter, the superposed signal is decomposed according to its frequency components, which perfectly restores the two signals before they are superimposed. In addition, their amplitude is highly linear with the driving voltage of the piezoelectric transducer. The system can fully retain the details of each frequency component in the recovery of multi-frequency disturbance signals. More importantly, in field experiments, the disturbance behavior is well recovered, which has broad prospects in the application of perimeter security.
DPpackage: Bayesian Semi- and Nonparametric Modeling in R

Data analysis sometimes requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against mis-specification of the probability model. In the Bayesian context, this is accomplished by placing a prior distribution on a function space, such as the space of all probability distributions or the space of all regression functions. Unfortunately, posterior distributions ranging over function spaces are highly complex and hence sampling methods play a key role. This paper provides an introduction to a simple, yet comprehensive, set of programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently, DPpackage includes models for marginal and conditional density estimation, receiver operating characteristic curve analysis, interval-censored data, binary regression data, item response data, longitudinal and clustered data using generalized linear mixed models, and regression data using generalized additive models. The package also contains functions to compute pseudo-Bayes factors for model comparison and for eliciting the precision parameter of the Dirichlet process prior, and a general purpose Metropolis sampling algorithm. To maximize computational efficiency, the actual sampling for each model is carried out using compiled C, C++ or Fortran code.