Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian Error-in-Variables Models for the Identification of Distribution Grids

The increasing integration of renewable energy requires a good model of the existing power distribution infrastructure, represented by its admittance matrix. However, a reliable estimate may either be missing or quickly become obsolete, as distribution grids are continuously modified. In this work, we propose a method for estimating the admittance matrix from voltage and current measurements. By focusing on $\mu $ PMU measurements and partially observed networks, we show that voltage collinearity and noisy samples of all electric variables are the main challenges for accurate identification. Moreover, the accuracy of maximum likelihood estimation is often insufficient in real-world scenarios. To overcome this problem, we develop a flexible Bayesian framework that allows one to exploit different forms of prior knowledge about individual line parameters, as well as network-wide characteristics such as the sparsity of the interconnections. Most importantly, we show how to use maximum likelihood estimates for tuning relevant hyperparameters, hence making the identification procedure self-contained. We also discuss numerical aspects of the maximum a posteriori estimate computation. Realistic simulations conducted on benchmark electrical systems demonstrate that, compared to other algorithms, our method can achieve significantly greater accuracy than previously developed methods.
Precipitation measurements using VHF wind profiler radars: Measuring rainfall and vertical air velocities using only observations with a VHF radar

In addition to a proper radar calibration, quantitative estimation of precipitation from radars also requires the extraction of the precipitation signal out of the Doppler spectra. It also requires the proper conversion of this precipitation signal into reflectivity factor. This study shows how the measurement of rainfall and vertical air velocities can be performed using only observations from a radar operating at the VHF band (i.e., meter wavelengths). We verify the assumption that the dielectric factor ∣K∣2 = 0.93 is valid for rain observations in the VHF band. We then derive, analytically and numerically, a more general version of the radar equation valid for vertically pointing radars with targets within a few kilometers range but still within the antenna far‐field region. Following this, we describe a new algorithm for extraction of rain signal out of VHF Doppler spectra. To validate our methods, we made colocated measurements of VHF Doppler spectra aloft and raindrop sizes at the ground. The analytical version of our radar equation compares well with similar equations available in current literature, and this validates the particular case of our numerically derived radar equation. We combine our numerical version of the radar equation and our algorithm for extracting precipitation signal. This combination allows us to obtain reflectivity factors (from rain signals) and vertical velocities (from air signals), these being simultaneous observations within the same sampling volume. From the data set collected, we found good agreement (linear correlation coefficient around 0.8) between the rain signals derived from VHF observations aloft and from drop sizes at ground level. Hence we are able to measure rainfall amounts and vertical air velocities in a simpler and more efficient way, using only observations from a VHF wind profiler. This represents a promising step toward the analysis of precipitation from large sets of radar data.
Conformal Parallel Plate Waveguide Polarizer Integrated in a Geodesic Lens Antenna

Here, we propose a low-profile polarizing technique integrated in a parallel plate waveguide (PPW) configuration, compatible with fully metallic geodesic lens antennas. The geodesic shape of the antenna is chosen to resemble the operation of a Luneburg lens. The lens is fed with 11 waveguide ports with 10° separation producing 11 switchable beams in an angular range of <inline-formula> <tex-math notation="LaTeX">$\pm \mathrm{50}^{\circ }$ </tex-math></inline-formula>. Two metallic polarizing screens are loaded into the aperture of the antenna to rotate the electric field from a vertical linear polarization, which is the polarization of the transverse electromagnetic (TEM) mode supported in the lens, to a <inline-formula> <tex-math notation="LaTeX">$+ \mathrm{45}^{\circ }$ </tex-math></inline-formula> linear polarization. Since the polarizing unit cells are integrated into the aperture of the antenna, the final design is compact. In addition, the size of the polarizing unit cells is about <inline-formula> <tex-math notation="LaTeX">$0.55\lambda $ </tex-math></inline-formula> at the central frequency of operation making the antenna suitable to produce an array formed of stacked lenses. A prototype of the antenna in the <inline-formula> <tex-math notation="LaTeX">$\text{K}_{\text {a}}$ </tex-math></inline-formula>-band was manufactured and tested, verifying the performance obtained in simulations.
A deep X‐ray observation of the supernova remnant G304.6+0.1 (Kes 17) using Suzaku

In this paper, we present the analysis of a deep (99.6 ks) observation of G304.6+0.1 with the X-ray Imaging Spectrometer on board the Suzaku satellite. The X-ray spectral data are well fitted with a plasma model consisting of a thermal component, in collisional ionization equilibrium, and a non-thermal component. The thermal emission is well fitted with the vmekal model with an electron temperature of kTe∼ 0.75 keV, a high absorbing column density of NH∼ 3.9 × 1022 cm−2 and near/lower solar abundances, which indicate that the X-ray emitting plasma of G304.6+0.1 is dominated by a swept-up ambient medium. The non-thermal component is well fitted with a power-law model with a photon index of Γ∼ 1.4. We have found a relatively high electron density ne∼ 2.3f−1/2 cm−3, an age t∼ 1.4 × 104f1/2 yr and an X-ray emitting mass Mx∼ 380f1/2 M⊙ at an adopted distance of d= 10 kpc. Using the morphological and spectral X-ray data, we confirm that the remnant is a new member of the mixed-morphology supernova remnants.
A hybrid deep learning based assist system for detection and classification of breast cancer from mammogram images

The most common cancer disease among all women is breast cancer. This type of disease is caused due to genetic mutation of ageing and lack of awareness. The tumour that occurred may be a benign type which is a non-dangerous and malignant type that is dangerous. The Mammography technique utilizes the early detection of breast cancer. A Novel Deep Learning technique that combines the deep convolutional neural networks and the random forest classifier is proposed to detect and categorize Breast cancer. The feature extraction is carried over by the AlexNet model of the Deep Convolutional Neural Network and the classifier precision is increased by Random Forest Classifier. The images are collected from the various Mammogram images of predefined datasets. The performance results confirm that the projected scheme has enhanced performance compared with the state-of-art schemes.
Enhanced thermoelectric figure of merit in vertical graphene junctions

In this work, we investigate thermoelectric properties of junctions consisting of two partially overlapped graphene sheets coupled to each other in the cross-plane direction. It is shown that because of the weak van-der Waals interactions between graphene layers, the phonon conductance in these junctions is strongly reduced, compared to that of single graphene layer structures, while their electrical performance is weakly affected. By exploiting this effect, we demonstrate that the thermoelectric figure of merit, ZT, can reach values higher than 1 at room temperature in junctions made of gapped graphene materials, for instance, graphene nanoribbons and graphene nanomeshes. The dependence of thermoelectric properties on the junction length is also discussed. This theoretical study hence suggests an efficient way to enhance thermoelectric efficiency of graphene devices.
Spin Relaxation Dynamics in Highly Uniform InAs Quantum Dots

We have investigated carrier spin dynamics in highly uniform self‐assembled InAs quantum dots. The highly uniform quantum dots allowed us to observe the spin dynamics in the ground state and that in the first excited state separately, without the disturbance of inhomogeneous broadening. The spin relaxation times in the ground state and the first excited state were measured to be 1.0 ns and 0.6 ns, respectively. Our measurements reveal the absence of the carrier density dependence of the spin relaxation time. The measured spin relaxation time decreases rapidly from 1.1 ns at 10 K to 200 ps at 130 K. This large change in the spin relaxation time is well explained in terms of the mechanism of acoustic phonon emission.
NXPH4 Used as a New Prognostic and Immunotherapeutic Marker for Muscle-Invasive Bladder Cancer

Background One of the most common malignant tumors of the urinary system is muscle-invasive bladder cancer (MIBC). With the increased use of immunotherapy, its importance in the field of cancer is becoming abundantly evident. This study classifies MIBC according to GSVA score from the perspective of the GSEA immune gene set. Methods This study integrated the sequencing and clinical data of MIBC patients in TCGA and GEO databases, then scored the data using the GSVA algorithm, the CNMF algorithm was implemented to divide the subtypes of GEO and TCGA datasets, respectively, and finally screened and determined the key pathways in combination with clinical data. Simultaneously, LASSO Cox regression model was constructed based on key pathway genes to assess the model's predictive ability (ROC) and describe the immune landscape differences between high- and low-risk groups; key genes were further analyzed and verified in patient tissues. Results 404 TCGA and 297 GEO datasets were divided into C1-3 groups (TCGA-C1:120/C2:152/C3:132; GEO- C1:112/C2:101/C3:84), of which TCGA-C2 (n = 152) subtype and GEO-C1 (n = 112) subtype had the worst prognosis. LASSO Cox regression model with ROC (train set = 0.718, test set = 0.667) could be constructed. When combined with the Cancer Immunome Atlas database, it was found that patients with high-risk scores were more sensitive to PD-1 inhibitor and PD-1 inhibitor combined with CTLA-4. NXPH4, as a key gene, plays a role in MIBC with tissue validation results show that nxph4 is highly expressed in tumor. Conclusion The immune gene score of MIBC data in TCGA and GEO databases was successfully evaluated using GSVA in this research. The lasso Cox expression model was successfully constructed by screening immune genes, the high-risk group had a worse prognosis and higher sensitivity to immunotherapy, PD-1 inhibitors or PD-1 combined with CTLA-4 inhibitors can be preferentially used in high-risk patients who are sensitive to immunotherapy, and NXPH4 may be a molecular target to adjust the effect of immunotherapy.
Linear convergence of first order methods under weak nondegeneracy assumptions for convex programming

The standard assumption for proving linear convergence of first order methods for smooth convex optimization is the strong convexity of the objective function, an assumption which does not hold for many practical applications. In this paper, we derive linear convergence rates of several first order methods for solving smooth non-strongly convex constrained optimization problems, i.e. involving an objective function with a Lipschitz continuous gradient that satisfies some relaxed strong convexity condition. In particular, in the case of smooth constrained convex optimization, we provide several relaxations of the strong convexity conditions and prove that they are sufficient for getting linear convergence for several first order methods such as projected gradient, fast gradient and feasible descent methods. We also provide examples of functional classes that satisfy our proposed relaxations of strong convexity conditions. Finally, we show that the proposed relaxed strong convexity conditions cover important applications ranging from solving linear systems, Linear Programming, and dual formulations of linearly constrained convex problems.
RAPID INFRARED VARIABILITY OF THREE RADIO-LOUD NARROW-LINE SEYFERT 1 GALAXIES: A VIEW FROM THE WIDE-FIELD INFRARED SURVEY EXPLORER

Using newly released data from the Wide-field Infrared Survey Explorer, we report the discovery of rapid infrared variability in three radio-loud narrow-line Seyfert 1 galaxies (NLS1s) selected from the 23 sources in the sample of Yuan et al. J0849+5108 and J0948+0022 clearly show intraday variability, while J1505+0326 has a longer measurable timescale within 180 days. Their variability amplitudes, corrected for measurement errors, are ∼0.1–0.2 mag. The detection of intraday variability restricts the size of the infrared-emitting region to ∼10−3 pc, significantly smaller than the scale of the torus but consistent with the base of a jet. The three variable sources are exceptionally radio-loud, have the highest radio brightness temperature among the whole sample, and all show detected γ-ray emission in Fermi/LAT observations. Their spectral energy distributions resemble those of low-energy-peaked blazars, with a synchrotron peak around infrared wavelengths. This result strongly confirms the view that at least some radio-loud NLS1s are blazars with a relativistic jet close to our line of sight. The beamed synchrotron emission from the jet contributes significantly to and probably dominates the spectra in the infrared and even optical bands.
Cosmology with equivalence principle breaking in the dark sector

A long-range force acting only between nonbaryonic particles would be associated with a large violation of the weak equivalence principle. We explore cosmological consequences of this idea, which we label ReBEL (daRk Breaking Equivalence principLe). A high resolution hydrodynamical simulation of the distributions of baryons and dark matter confirms our previous findings that a ReBEL force of comparable strength to gravity on comoving scales of about 1 h{sup -1} Mpc causes voids between the concentrations of large galaxies to be more nearly empty, suppresses accretion of intergalactic matter onto galaxies at low redshift, and produces an early generation of dense dark-matter halos. A preliminary analysis indicates the ReBEL scenario is consistent with the one-dimensional power spectrum of the Lyman-Alpha forest and the three-dimensional galaxy autocorrelation function. Segregation of baryons and DM in galaxies and systems of galaxies is a strong prediction of ReBEL. ReBEL naturally correlates the baryon mass fraction in groups and clusters of galaxies with the system mass, in agreement with recent measurements.
Automatic Contact-Less Monitoring of Breathing Rate and Heart Rate Utilizing the Fusion of mmWave Radar and Camera Steering System

The demand for noncontact breathing and heart rate measurement is increasing. In addition, because of the high demand for medical services and the scarcity of on-site personnel, the measurement process must be automated in unsupervised conditions with high reliability and accuracy. In this article, we propose a novel automated process for measuring breathing rate and heart rate with mmWave radar and classifying these two vital signs with machine learning. A frequency-modulated continuous-wave (FMCW) mmWave radar is integrated with a pan, tilt, and zoom (PTZ) camera to automate camera steering and direct the radar toward the person facing the camera. The obtained signals are then fed into a deep convolutional neural network to classify them into breathing and heart signals that are individually low, normal, and high in combination, yielding six classes. This classification can be used in medical diagnostics by medical personnel. The average classification accuracy obtained is 87% with precision, recall, and an F1 score of 0.93.
The Abuse of Power in the Alleged Covid-19 Polymerase Chain Reaction Test Business: Criminal Aspects

The abuse of power during the Covid-19 pandemic was felt to be very massive by the governmentbecause the health sector received far more attention than others. The Covid-19 test was made mandatory to travel in spite of it being very expensive for the community, and various news spread in the community made suspicion of abuse of power. By using qualitative methods and Nvivo 12 Plus to map the data, this research was conducted to determine whether the abuse of power actually occurred. The results of the study show that the cases that occur are too subjective to be considered an abuse of power, in this case, the government and corporations are also working according to the needs of the community to overcome the Covid-19 pandemic. However, to see the disadvantages of this, the author feels that further research is still needed regarding the urgency of the Covid-19 test while traveling and its impact on state budget losses. Keywords: abuse of power, pandemic, Covid-19 test, corporations
The Compactification of QCD4 to QCD2 in a Flux Tube

We show from action integral that under the assumption of longitudinal dominance and transverse confinement, QCD4 in (3+1) dimensional space-time can be approximately compactified into QCD2 in (1+1) dimensional space-time. In such a process, we find the relation between the coupling constant g(2D) in QCD2 and the coupling constant g(4D) in QCD4. We show how the quark and the gluon in QCD2 acquire masses arising their being confined within the tube, and how all these quantities depend on the excitation of the partons in the transverse degree of freedom. The variation of the gluon fields leads to an additional mass that depends on the coupling constant g(2D). The compactification facilitates the investigation of some problems in QCD4 in the simpler dynamics of QCD2.
The Puzzling Spectrum of HD 94509

The spectral features of HD 94509 are highly unusual, adding an extreme to the zoo of Be and shell stars. The shell dominates the spectrum, showing lines typical for spectral types mid-A to early-F, while the presence of a late/mid B-type central star is indicated by photospheric hydrogen line wings and helium lines. Numerous metallic absorption lines have broad wings but taper to narrow cores. They cannot be fit by Voigt profiles. We aim to describe and illustrate unusual spectral features of this star, and make rough calculations to estimate physical conditions and abundances in the shell. Furthermore, the central star is characterized. We assume mean conditions for the shell. An electron density estimate is made from the Inglis-Teller formula. Excitation temperatures and column densities for Fe I and Fe II are derived from curves of growth. The neutral H column density is estimated from high Paschen members. The column densities are compared with calculations made with the photoionization code Cloudy. Atmospheric parameters of the central star are constrained employing non-LTE spectrum synthesis. Overall chemical abundances are close to solar. Column densities of the dominant ions of several elements, as well as excitation temperatures and the mean electron density are well accounted for by a simple model. Several features, including the degree of ionization, are less well described. HD 94509 is a Be star with a stable shell, close to the terminal-age main sequence. The dynamical state of the shell and the unusually shaped, but symmetric line profiles, require a separate study.
Monte Carlo Simulation with Applications to Finance

Review of Probability Probability Space Independence and Conditional Probability Random Variables Random Vectors Conditional Distributions Conditional Expectation Classical Limit Theorems Brownian Motion Brownian Motion Running Maximum of Brownian Motion Derivatives and Black-Scholes Prices Multidimensional Brownian Motions Arbitrage Free Pricing Arbitrage Free Principle Asset Pricing with Binomial Trees The Black-Scholes Model Monte Carlo Simulation Basics of Monte Carlo Simulation Standard Error and Confidence Interval Examples of Monte Carlo Simulation Summary Generating Random Variables Inverse Transform Method Acceptance-Rejection Method Sampling from Multivariate Normal Distributions Variance Reduction Techniques Antithetic Sampling Control Variates Stratified Sampling Importance Sampling Basic Ideas of Importance Sampling The Cross-Entropy Method Applications to Risk Analysis Stochastic Calculus Stochastic Integrals Ito Formula Stochastic Differential Equations Risk-Neutral Pricing Black-Scholes Equation Simulation of Diffusions Euler Scheme Eliminating Discretization Error Refinements of Euler Scheme The Lamperti Transform Numerical Examples Sensitivity Analysis Commonly Used Greeks Monte Carlo Simulation of Greeks Appendix A: Multivariate Normal Distributions Appendix B: American Option Pricing Appendix C: Option Pricing Formulas Bibliography Index Exercises appear at the end of each chapter.
The Principal’s Attitude on Teacher Performance: A Case Study of Senior High School in South Tangerang Area

This article aimed to determine 1) to determine the effect of the principal's attitude on high school teachers’ performance in South Tangerang area, 2) to find out how much influence principal’s attitude has on teachers’ performances in South Tangerang, 3) to determine principal’s attitude that can affect teacher performance. This study employed a quantitative approach with correlational and ex post facto methods. The population was high school teachers in South Tangerang area while the subject of this study was 32 high school teachers in South Tangerang area. The independent variable (X) in this study is the principal’s attitude and the dependent variable (Y) in this study is teacher performance. Data collection techniques using a questionnaire and analysis method using Simple Regression. To test the hypothesis, correlation analysis and simple linear regression analysis were employed. Prior to the analysis test, the prerequisite tests were carried out, namely the normality test and the linearity test. Testing the hypothesis with a significance level of 5%, it was found that the p-value of the correlation between the principal's attitude variable and teacher performance was 0.079. The significance value of p > 0.05 (0.079 > 0.05). Because the value of F count is smaller than F table, it can be concluded that there is a significant influence between the variables of the principal's attitude on teacher performance.
Quantum imaging gets super smart

Quantum ghost imaging is an alternative imaging technique which utilises pairs of entangled photons to reconstruct an image. Due to the scanning nature of spatially resolving detectors and the inherent low light levels of quantum experiments, imaging speeds are inefficient and scale quadratically with the required resolution. We leveraged artificial intelligence capabilities to achieve early object recognition and to super-resolve the reconstructed image. We achieved a 5x reduction in image acquisition times and super-resolved the images to a resolution 4x greater than the measured resolution. Leading to efficient image acquisition times without losing fine details of the image.