Miracle-dz/UniFAR-FTUs huggingface dataset:
COVID-19 diagnosis with hyperparameter optimization using mixture density network(MDN) and EMADE

COVID-19 diagnosis has become a crucial task in today's world due to the rapid spread of the infectious Corona Virus disease caused by the SARS-CoV-2 virus. Analysis of COVID using CT scan images is shown to give better results but it requires expert radiologists and it consumes time. Hence there is a need for a diagnosis system to classify whether it's COVID positive or not for quick and early diagnosis. Deep Learning models are effective in handling classification problems but some models might lead to vanishing gradient problem. A Mixture Density Network (i.e.) Bidirectional Long Short-Term Memory((Bi-LSTM) with Mixture Network is used as the classifier to handle the vanishing gradient problem and to classify based on the probability distribution. Parameter tuning plays a major role in improving the overall efficiency of the classifier. An Enhanced Memetic Adaptive Differential Evolution (EMADE) algorithm is proposed for tuning the parameters of the classifier. Enhanced MADE is a memetic algorithm with proposed Elite chaotic local search (ECLS) which helps in addressing the issue of getting stuck at a local optimal solution and premature convergence. The use of Elitism in the chaotic local search directs the algorithm toward the optimal solution and increases the exploitation ability. Due to high false negatives in RT - PCR, CT scan images have been taken as the input. The dataset is labeled and it consists of 1252 CT scans that are positive for COVID-19, and 1230 CT scans that are negative for COVID-19. The dataset collected from patients in Sao Paulo, Brazil that is available on Kaggle is used [21]. A sample of the dataset is taken for experimentation and an accuracy of 75.83% is achieved. The precision is 80.32% indicating that there are fewer False positive than the existing methods.
The Implementation of the SLAM Method in ROS System and Underwater Robot

Autonomous localization and map construction of underwater robots in unknown environments is a very important research area. Visual SLAM technology is based on visual processing algorithms and can accomplish this task at a low cost. This paper focuses on a set of underwater robot visual SLAM experimental process. Based on ROS system, Mono visual SLAM experiments are performed on UWSim simulation environment and real robot respectively by using mature ORB-SLAM2 algorithm. The experimental results show that this method can accurately build the sparse point cloud map of the environment under the condition of sufficient environmental feature points.
An Artificial Potential Field Based Cooperative UAV Conflict Detection and Resolution under Uncertain Communication Environment

Conflict Detection and Resolution (CD&R) technology is essential for safety operation of Unmanned Aerial Vehicle (UAV). The Artificial Potential Field (APF) method, which is widely used in robot path planning domain, have advantages of low computational cost and fast calculation ability. However basic APF method may lead the UAV to the “repulsive dilemma”. Considering each UAV as their obstacles, we use APF method for UAV's collision avoidance and provide a priority allocation rules and exempt mechanism based on geometry for high-efficiency cooperative conflict resolution, especially in uncertain communication circumstance. In order to validate the effectiveness of the proposed method, we set three cases of experiment and introduce the “clone airspace” inspired by the concept of cell in chemistry sphere for improving the simulation performance. Using the proposed CD&R method, the result shows a decrease of more than 46% of possible Near Mid-Air Collision (NMAC) with high safety and efficiency.
All-optical switch based on beam cross-cleaning effect in graded-index multimode fiber

We introduce the concept of beam all-optical spatial beam switching in graded-index multimode fibers. This consists of seeding a bell-shaped spatial profile to a laser beam at the output of the fiber by exploiting the nonlinear coupling between the modes of the two input beams. Remarkably, we demonstrate that even a weak-control signal allows for improving the spatial profile of a highly multimode intense signal. The device proposed herein will be easily integrated in state-of-the-art optical networks, and will find application in the fields of space-division-multiplexed telecommunication and of multimode fiber lasers.
A Machine Learning Approach for Predicting Patient Mortality A Machine Learning Approach for Predicting Patient Mortality with Heart Rate Variability Statistics with Heart Rate Variability Statistics

The prediction of patient mortality in the healthcare system provides a metric by which hospitals can better manage patient care and assess the needs of each individual patient. As such, the development of better predictive methods is vital for improving patient outcomes and overall quality of care. Heart rate variability (HRV) is a measure of the heart’s complex beating patterns, giving medical professionals additional insight into patient health. Previous research has demonstrated the potential use of heart rate variability as a metric for patient mortality prediction for various conditions, however more work is necessary to validate HRV as a metric for a broader and more diverse set of patients. This study uses data from 2664 patients within the MIMIC-III clinical database matched with patient electrocardiogram (ECG) data to link HRV data with later patient mortality, examining the efficacy of HRV as a biomarker for predicting patient mortality and investigating possible avenues for future integration of HRV into patient mortality predictive algorithms.
The Importance of Learner-Learner and Learner-Instructor Interaction among EFL Learners in Payame Noor University: A Constructivist Approach 1

The main purpose of this study was to analyze learner-learner interaction, and learner-instructor interaction among the EFL Learners in Payame Noor University based on the constructivist paradigm. About 100 EFL learners were selected randomly. They were junior students getting a BA in TEFL. They were 90 females and the average age was 28. The materials used in the study were formal and informal interviews, an open ended questionnaire, and a validated Likert questionnaire designed after a pilot study by the researcher. The data were analyzed using the SPSS and the emergent themes were discussed. The results showed little interaction among the learners. The reasons and the pedagogical implications of the study are also given.
Biagioniite, Tl 2 SbS 2 , from the Hemlo gold deposit, Marathon, Ontario, Canada: occurrence and crystal structure

Biagioniite, ideally Tl 2 SbS 2 , is a new mineral from the Hemlo gold deposit, Marathon, Ontario, Canada. It occurs as very rare anhedral crystals up to 65 μ m across associated with aurostibite, stibarsen and native gold in a calcite matrix. Biagioniite is opaque with a metallic lustre and shows a black streak. In reflected light biagioniite is moderately bireflectant and not pleochroic. Under crossed polars it is weakly anisotropic with blueish to light-blue rotation tints. Internal reflections are absent. Reflectance percentages for the four standard wavelengths ( R min and R max ) are 35.9 and 37.5 (471.1 nm); 34.7 and 36.2 (548.3 nm); 33.8 and 35.3 (586.6 nm); and 31.5 and 33.7 (652.3 nm), respectively. A mean of four electron microprobe analyses gave: Tl 65.12(31), Ag 3.52(9), Sb 20.22(12), S 10.80(8), total 99.66 wt. %, corresponding, on the basis of a total of 5 atoms, to (Tl 1.87 Ag 0.19 ) Σ 2.06 Sb 0.97 S 1.97 . Biagioniite is monoclinic, space group Pc , with a = 11.0895(9), b = 14.3124(11), c = 7.9352(6) Å, β = 96.230(8)°, V = 1252.02(17) Å 3 and Z = 8. The four strongest powder-diffraction lines [ d in Å ( I/I 0 ) ( hkl )] are: 3.56 (100) (310); 3.37 (75) ( (cid:1) 231); 3.79 (60) (012); 3.03 (60) (032). In the crystal structure [ R 1 = 0.024 for 2655 reflections with I > 2 σ ( I )], thallium adopts various coordinations extending from quasi-linear to quasi-tetrahedral. Antimony forms Sb – Sb pairs, which lead to the formula [Tl +1 ] 4 [Sb 2 ] 4+ [S 2 – ] 4 . Biagioniite is isostructural with dervillite, Ag 2 AsS 2 . The new mineral has been approved by the International Mineralogical Association Commission on New Minerals, Nomenclature and Classification (IMA2019 – 120) and named for Cristian Biagioni, Associate Professor of Mineralogy at the Department of Earth Sciences of the University of Pisa, Italy.
Thickness of frozen rocks and the cryolithosphere on Mars

Conceptions of thickness of frost rock and cryolithosphere of Mars were considered by R.Kuzmin (Kuzmin 1983), M. Krass and V.Merzlikin (Krass & Merzlikin 1990), S.M. Clifford and T.J.Parker (Clifford & Parker 2001). Mostly the evaluations of martian cryolithosphere thickness were carried out on the base of model of stable temperature field. The thickness of frost rock massive Hm was found by the profile of stationary distribution of temperature with the depth for one and two-layer lithological model. We input average annual temperature of surface, temperature of phase change of H20 and temperature of heat transfer and value of heat flux to the lower boarder of permafrost. The difference was in the choosing of parameters: average values of heat conductivity coefficient of upper layers, values of heat flux from inside, average temperature of surface, profile model.
Pointwise estimates for degenerate parabolic equations

In this paper we establish an invariant Harnack type inequality for positive solutions of linear degenerate parabolic equations. Consequently we prove Holder continuity of weak solutions.The cylinders on which this invariant Harnack inequality holds are not anymore the usual parabolic cylinders. On the contrary their shape is different from point to point depending on the degeneracy of the operator
The Hierarchical Logistic Regression Model for Multilevel Analysis

Abstract A hierarchical logistic regression model is proposed for studying data with group structure and a binary response variable. The group structure is defined by the presence of micro observations embedded within contexts (macro observations), and the specification is at both of these levels. At the first (micro) level, the usual logistic regression model is defined for each context. The same regressors are used in each context, but the micro regression coefficients are free to vary over contexts. At the second level, the micro coefficients are treated as functions of macro regressors. An empirical Bayes estimation procedure is proposed for estimating the micro and macro coefficients. Explicit formulas are provided that are computationally feasible for large-scale data analyses; these include an algorithm for finding the maximum likelihood estimates of the covariance components representing within— and between—macro-equation error variability. The methodology is applied to World Fertility Survey data.
Piezoelectric fields of localized states in trapezoidal InGaN quantum wells

The piezoelectric fields of localized states in trapezoidal InGaN quantum wells (QWs) were investigated using electric field dependent electroreflectance (ER) spectroscopy. From the energy shift in ER peak in a bias range from 0 to −24 V, the piezoelectric field of the dominant QWs was estimated to be −1.22 MV/cm. In contrast, the localized states exhibited a piezoelectric field that was about 30%–60% weaker than for the dominant QW states. The reduced piezoelectric field in the localized states can be attributed to the partial release of compressive strain in the local InGaN regions, along with a relative reduction in the effective reverse-bias. The relative decrease in the reverse-bias can be explained by the voltage drop in the localized states that is caused by an increase in the leakage current under a reverse-bias.
Controllability under decentralized information structure

In this paper, the controllability under decentralized information structure is studied for linear continuous-time systems. It is defined as follows. A system is controllable under the decentralized information structure if there exists a decentralized control law which transfers any unknown initial state to the origin in a finite time interval Necessary and sufficient conditions of the controllability under the decentralized information structure are given. It is also shown that the controllability under the decentralized information structure is a necessary condition of the pole-assignability with a local dynamic feedback control law.
Multicolor imaging photometer for the MAGNUM project

We present the optical, mechanical and electronic design of MAGNUM-MIP. The MAGNUM project plans to carry out multi color monitoring observations for hundreds of AGNs over several years under remote and automated operation. MAGNUM- MIP has two channels that offer optical and IR broad-band imaging observations at the same time. The IR channel has a SBRC InSb 256 by 256 array which covers a wavelength range from 1 to 4 microns, and the optical channel uses a 1024 by 1024 SITE CCD which covers 0.35 micron to 1 micron. The two channels use the same optics and a beam splitter. We adopted a reflecting optical system in order to get good imaging quality over the wide wavelength range. Because the monitoring is expected to be carried out remotely for several years with minimum manual support and maintenance, the camera is designed to work with only semi-annual maintenance. It has a mechanical cooler, a low outgas design, and an automated vacuum system.
Estimation of solar radiation using a neural network based on radiative transfer

[1] This study developed an algorithm for estimating solar radiation from space using a neural network (NN) with an improved learning algorithm to approximate radiative transfer code. The NN solver for the solar radiation budget is based on radiative transfer calculations. All data sets for testing and training the NN were generated from radiative transfer code. Thus the NN traces the radiative transfer calculation that is approximated by a learning algorithm. To demonstrate the effectiveness of the NN approach for high-speed estimation and multiparameter problems, the NN was applied to data from a geostationary satellite and a Sun-synchronous subrecurrent orbit satellite. The developed algorithm was applied to data from the Multi-functional Transport Satellite-1 Replacement (MTSAT-1R) geostationary satellite, and estimations were validated against in situ observations for March 2006 at four SKYNET sites. Byproducts of the algorithm include UVA, UVB, and photosynthetically active radiation (PAR) fluxes as well as direct and diffuse components. The NN approach enables semi-real-time analysis of these products by high-speed calculation. In addition, the NN allows for consideration of detailed particle optical parameters in the solar radiation budget without the need for a massive database. The method was also applied to observations from the Advanced Earth Observing Satellite-II/Global Imager (ADEOS-II/GLI) for May 2003. The results showed trends in the direct and diffuse components of downward solar radiation over the North Pacific Ocean. This report outlines the construction of the NN for radiation budget estimation and demonstrates the effectiveness of the NN approach.
Profiling Laser-Induced Temperature Fields for Superconducting Materials Using Mathematical Experimentation

The equations of energy balance and heat conductivity are queried by introducing known parameters using virtual mathematical experimentation. Distribution of temperature by layers in depth for samples of superconducting material is obtained under different conditions. The structural defect at different state-liquid and solid was analyzed. The theoretical model generated was validated by experimental data. The temperature distribution under the irradiating laser intensity (0.45 W) shows an effective decay rate probability density function that is peculiar to the concept of photoluminescence.
Visualization of EGFR and Grb2 interaction using bimolecular fluorescence complementation

The dimerization of epidermal growth factor receptor (EGFR) and its endocytic transport are important in regulating signal transduction. In the present study, we applied the strategy of Bimolecular Fluorescence Complementation (BiFC), EGFR homodimer and hetrodimer of EGFR and its partner Grb2 in cells were visualized. This strategy takes advantage of the ability of two nonfluorescent fragments of Venus fluorescent protein to form a fluorescent signal when fused to the amino termini of EGFR and Grb2. Since EGFR is a large protein contains more than 1800 amido acids, proper fold of the fusion protein is essential for the BiFC assay of EGFR and its partners. Our results indicate that BiFC is a suitable application for research of EGFR interaction with other proteins.
Encapsulation of organic light-emitting diode using thermal chemical-vapour-deposition polymer film

The encapsulation effect of thermal chemical-vapour-deposition polymer films (TCVDPF) has been studied for organic light-emitting diodes (OLED). We used poly-p-xylylene (PPX) and/or poly-2-chloro-p-xylylene (PCPX) films as TCVDPF. For the encapsulation, TCVDPF was deposited on the OLED during a dry process at room temperature. The lifetime of an encapsulated OLED with 0.6 µm thick TCVDPF was about four times longer than that of a non-encapsulated OLED in air. The lifetime of the OLED increased with increasing thickness of the TCVDPF. We conclude that the effect of TCVDPF encapsulation on the long-term stability of the OLED is due to the prevention of oxygen and moisture in air and several other factors.
The L 1 Method for Robust Nonparametric Regression

Abstract Consider the problem of estimating the regression function underlying a set of data that is contaminated by a heavy-tailed error distribution. The two standard approaches to such a problem are each flawed. Robust parametric least squares is appropriate only if there is good reason to believe that the underlying function has some particular form, whereas most nonparametric regression methods are asymptotically equivalent to kernel regression methods, which are not resistant against outliers. Existing algorithms for robustifying nonparametric regression procedures use either nonlinear optimization of an influence function or iterative solution of local polynomial fitting using reweighted least squares. Neither of these two approaches combines computational ease with asymptotic theoretical results. Furthermore, application of the robust procedure has been limited almost exclusively to the case of a single explanatory variable with the response variable. In this article a new hybrid method is propose.
Nonlinear absorption in InN under resonant- and non-resonant excitation

We report the wavelength-dependent nonlinear absorption (NLA) of InN film grown on anr-plane sapphire by molecular beam epitaxy technique. In order to understand the nonlinear optical properties of InN, the Z-scan measurement was performed at two different wavelengths, the photon energies of which are near (resonant excitation) and much higher (non-resonant excitation) than the bandgap of InN, respectively. Under non-resonant excitation, band-filling effect leads the dominant saturable absorption, while under resonant excitation, reverse saturable absorption dominates the nonlinear absorption. From the open-aperture Z-scan measurement under resonant excitation, we found that InN exhibits more than one nonlinear absorption process simultaneously. Particularly, under relatively weak resonant excitation, the transformation from saturable absorption to 2PA through the intermediate excitation state absorption was observed as the sample approaches the beam focus. The close-aperture Z-scan signals of InN show valley-peak response, implying that the nonlinear refraction in InN is caused by the self-focusing of the Gaussian laser beam. Using the Z-scan theory, the corresponding nonlinear parameters, such as saturation intensity, 2PA coefficient, and nonlinear refractive index, of InN were estimated.
LPV Modelling and Control of Burgers’ Equation

Abstract Linear parameter-varying (LPV) modelling and control of a nonlinear PDE is presented in this paper. The one-dimensional viscous Burgers’ equation is discretized using a finite difference scheme and the boundary conditions are taken as control inputs. A nonlinear high-order state space model is generated and proper orthogonal decomposition is used for model order reduction and the accuracy of the reduced model is verified. A discrete-time quasi-LPV model that is affine in scheduling parameters is derived based on the reduced model and a polytopic LPV controller is synthesized. A low-order functional observer is designed to estimate the scheduling parameters required for LPV controller. Simulation results demonstrate the high tracking performance and disturbance and measurement noise rejection capabilities of the designed LPV controller comparing with an LQG controller based on a linearized model.
Sample depolarization effects from thin films of ZnS on GaAs as measured by spectroscopic ellipsometry

Thin films of ZnS grown on GaAs by laser ablation are examined using spectroscopic two‐channel polarization modulation ellipsometry (2‐C PME). It is found that variations in the film thickness over the illumination spot result in the quasidepolarization of the incident light, which can be measured directly using 2‐C PME. Quantitative fits of the ellipsometry data using a distribution‐of‐thicknesses model agree with independent reflectivity measurements of the thickness gradient, and allow for the accurate determination of the optical functions of the ZnS film.
Strategic games on a hierarchical network model

Among complex network models, the hierarchical network model is the one most close to such real networks as world trade web, metabolic network, WWW, actor network, and so on. It has not only the property of power-law degree distribution, but also the scaling clustering coefficient property which Barabási-Albert (BA) model does not have. BA model is a model of network growth based on growth and preferential attachment, showing the scale-free degree distribution property. In this paper, we study the evolution of cooperation on a hierarchical network model, adopting the prisoner’s dilemma (PD) game and snowdrift game (SG) as metaphors of the interplay between connected nodes. BA model provides a unifying framework for the emergence of cooperation. But interestingly, we found that on hierarchical model, there is no sign of cooperation for PD game, while the frequency of cooperation decreases as the common benefit decreases for SG. By comparing the scaling clustering coefficient properties of the hierarchical network model with that of BA model, we found that the former amplifies the effect of hubs. Considering different performances of PD game and SG on complex network, we also found that common benefit leads to cooperation in the evolution. Thus our study may shed light on the emergence of cooperation in both natural and social environments.
Far-infrared (λ≃87 μm) bound-to-continuum quantum-cascade lasers operating up to 90 K

We report terahertz frequency (3.5 THz, λ≃87 μm) emission from quantum-cascade lasers employing a bound-to-continuum transition in the active region. The maximum operating temperature is in excess of 90 K. Peak powers of 20 mW at 20 K and 10 mW at 77 K are achieved. The same devices show continuous-wave operation up to 55 K with measured optical powers of 15 mW at 10 K.