Miracle-dz/UniFAR-FTUs huggingface dataset:
A list of bright interferometric calibrators measured at the European Southern Observatory Very Large Telescope Interferometer

In a previous publication, we described a program of observations of candidate calibrator stars at the European Southern Observatory Very Large Telescope Interferometer (VLTI), and presented the main results from a statistical point of view. In the present paper, we concentrate on establishing a new homogeneous group of bright interferometric calibrators, based entirely on publicly available K-band VLTI observations carried out with the VINCI instrument up to 2004 July. For this, we have defined a number of selection criteria for the quality and volume of the observations, and we have accordingly selected a list of 17 primary and 47 secondary calibrators. We have developed an approach to a robust global fit for the angular diameters using the whole volume of quality-controlled data, largely independent of a priori assumptions. Our results have been compared with direct measurements, and indirect estimates based on spectrophotometric methods, and general agreement is found within the combined uncertainties. The stars in our list cover the range K = -2.9 to +3.0 mag in brightness, and 1.3-20.5 mas in uniform-disc diameter. The relative accuracy of the angular diameter values is on average 0.4 and 2 per cent for the primary and secondary calibrators, respectively. Our calibrators are well suited for interferometric observations in the near-infrared on baselines between ≈20 and 200 m, and their accuracy is superior, at least for the primary calibrators, to other similar catalogues. Therefore, the present list of calibrators has the potential to lead to significantly improved interferometric scientific results.
Loss Functions in Financial Sector: An Overview

The loss function or cost function is a principal component of all optimizing problems such as statistical theory, decision theory, policy making, estimation process, forecasting, learning, classification and financial investment. In this study various types of loss functions and their uses were studied. In this study linex loss function, the analyst’s loss function, the optimal prediction under asymmetric loss, loss functions for forecasting financial returns, loss function and forecast biasedness, loss functions for estimation and evaluation, loss functions for probability forecasts and volatility forecasts have been studied. Further loss function for testing Granger-causality and loss function for uncertainty and policy aggressiveness have been also studied. This study suggested that among asymmetric loss functions linex loss function is more useful and to be applied in many financial situations.
Cycle Aging Effect on the Open Circuit Voltage of Lithium-Ion Battery

Nowadays, the issues concerning green mobility and energy production are leading researchers to study novel energy storage systems. Among them, lithiumion batteries are currently one of the most popular technologies under study. Battery modeling and parameter estimation are important challenges to build reliable battery management systems able to allow the battery to work in proper conditions. State of charge (SOC) estimation is one of the most important for predicting the current battery available energy. Many methods to estimate the SOC need knowledge of the open circuit voltage (OCV) curve. In the literature, it is possible to find a lot of OCV models as a function of SOC. Another important aspect is how these curves change as a function of battery degradation. Some studies deal with the correction of the OCV-SOC curve considering the aging, but the dependency of the OCV curve as a function of the exchanged absolute charge on aging seems to be lacking. In the present work, a simple model of the OCV-charge curve that considers the cycle aging is proposed and analyzed. An experimental campaign was carried out to validate the proposed model.
Power Minimization Strategy Based Subcarrier Allocation and Power Assignment for Integrated Sensing and Communication

Integrated sensing and communication (ISAC) has received increasing attention as a potential technology to alleviate spectrum shortage. This paper studies the power-saving problem based on power assignment and subcarrier allocation in ISAC. Specifically, we propose a joint design method to jointly optimize the subcarrier and transmit power allocated to sensing services and communication services respectively. To ensure the quality of sensing service (SS) and communication service (CS), the minimum total power required by the system is obtained by optimizing the allocation of subcarriers and transmission power. Since the formulated problem is nonconvex, which is generally difficult to solve effectively. Inspired by the classical subcarrier allocation algorithm based on channel gain information, we decompose the formulated problem into two convex optimization subproblems that are easy to solve. Numerical simulation results show that the proposed algorithm can effectively improve the power-saving performance of the system compared with the existing algorithms.
Sparse Superimposed Pilot Based Channel Estimation in OTFS Systems

Traditional orthogonal time frequency space (OTFS) channel estimation schemes dedicate an entire frame or a part of the frame for accommodating pilot and guard symbols to avoid pilot-data interference, which compromises spectral efficiency. This spectral efficiency loss can be avoided using superimposed pilots, where delay-Doppler (DD) bins in the OTFS frame carries both data and pilot symbols. In this paper, we propose a sparse superimposed pilot scheme for channel estimation, where all the DD bins in a frame carry data symbols and pilot symbols are superimposed over some of them, sparsely. The proposed scheme does not suffer spectral efficiency loss due to pilot/guard symbols. It also has the advantage of more localized pilot-data interference profile that leads to better performance. We derive the minimum mean square error (MMSE) channel estimator for the proposed scheme. We obtain optimum number of pilot symbols per frame and power distribution among data and pilot symbols through simulations. Simulation results show that the proposed scheme achieves better performance at a lesser complexity compared to existing superimposed pilot scheme. An iterative scheme that further improves performance is also proposed.
Low-Overhead Beam Selection for mmWave Massive MIMO Systems by Deep Learning

In 5G communication systems, massive multiple-input multiple-output (MIMO) technology could compensate for the severe path-loss of millimeter-wave by high-gain beams. However, the excessive overhead of beam measurement induces a significant challenge for practical systems. To reduce the measurement overhead and improve the accuracy of beam selection, deep learning (DL) is employed to predict the signal quality of all beam pairs by measuring a few selected beam pairs. The proposed beam prediction network is mainly composed of input module, residual module and multi-layer perceptron (MLP) module, therefore denoted as ReMBP net. After the preprocessing for the input signal quality of measured beam pairs, the designed residual module is adopted to extract the high-dimensional feature vector, then the signal quality of all beam pairs could be predicted by the designed MLP module. Moreover, to improve the generalization ability of the proposed ReMBP net for different communication environments, the input module with a flexible input size of signal quality data is designed. Experiment results indicate that a high-accuracy beam selection could be achieved with low overhead compared with other traditional artificial intelligence (AI) models.
PESTnet - Pre-IFFT PAPR Estimation using Neural Networks for Improved OFDM Systems

For the next generation of wireless technologies, Orthogonal Frequency Division Multiplexing (OFDM) remains a key signaling technique. Peak-to-Average Power Ratio (PAPR) reduction must be included with OFDM to reduce the detrimental high PAPR exhibited by OFDM. The cost of PAPR reduction techniques stems from adding multiple IFFT iterations, which are computationally expensive and increase latency. We propose a novel PAPR Estimation Technique called PESTNet which reduces the necessary IFFT operations for PAPR reduction techniques by using deep learning to estimate the PAPR before the IFFT is applied. This paper gives a brief background on PAPR in OFDM systems and describes the PESTNet algorithm and the training methodologies. A case study of the estimation model is provided where results demonstrate PESTNet is able to give an accurate estimate of PAPR and can compute large batches of resource grids up to 10 times faster than IFFT based techniques.
Heavy-traffic analysis of the M/G/1 queue with priority classes

We consider the M=G=1 queue with two priority classes, for the case that at least one of the service time distributions is regularly varying of index with 1 < < 2. It is shown for this heavy-tailed case that the waiting time distribution of the low-priority customers is regularly varying of index one degree higher than that of the service time distribution with the heaviest tail. We also prove a heavy-tra c limit theorem for the steady-state low-priority waiting time W2. When the low-priority tra c load 2 ! 1 1 ( 1 being the high-priority tra c load), the contracted low-priority waiting time ( 2)W2= 1 converges in distribution to the Mittag-Le er distribution R 1(t) where ( 2) is a particular function of 2 with the property that ( 2)! 0 for 2 ! 1 1, R 1(t) is a proper distribution with LaplaceStieltjes transform 1=(1+ s ) and 1 is the mean of class-1 service time. The heavy-tra c limit theorem gives rise to an approximation for the steady-state distribution of W2, which is extensively tested numerically. Mathematics Subject Classi cation Number: 60K25, 90B22.
Performance Analysis of Multiple Optical Reflecting Surfaces Assisted FSO Communication

The deployment of intelligent reflecting surfaces (IRSs) in wireless communication systems have recently garnered much attention due to its potential to reduce blockages by providing an alternate propagation path and improving reliability. This paper reports the performance analysis of multiple optical reflecting surfaces (ORSs)-assisted free space optics (FSO) communication. Specifically, the performance is investigated by utilizing the selection of the best ORS from the multiple available ORSs. Firstly, we have derived the exact probability density function (PDF) of the end-to-end maximum instantaneous signal-to-noise ratio (SNR) among multiple ORSs-aided FSO links. Further, using the above PDF statistics, the outage and average symbol error rate (SER) expressions of the considered multiple ORSs system are derived in closed-form. Additionally, the asymptotic expressions, which are mathematically more tractable, for both outage and average SER are presented with the diversity gain analysis. Finally, numerical results along with Monte-Carlo simulation results are provided to corroborate the derived analytical results.
An 84dB-SNDR 1-0 Quasi-MASH NS SAR with LSB Repeating and 12-bit Bridge-Crossing Segmented CDAC

As the residue on the CDAC of a noise-shaping (NS) SAR ADC mainly contains quantization error $(\mathrm{n}_{\mathrm{q}})$ and comparator noise ($\mathrm{n}_{\text{comp}}$), it is desirable to reduce them simultaneously to boost the SNR by NS. However, reducing ncomp by 2x would increase the comparator’s power consumption by $\sim 4\mathrm{x}$. Therefore, many NS SAR ADCs adopt $8\sim 10\mathrm{~b}$ CDAC and low-power comparators for comparable $\mathrm{nq}_{\mathrm{q}}$ and ncomp. Then, the residue can be shaped by $1^{\text{st}}$-order NS with high OSR (25) [1] or $4^{\text{th}}$-order NS [2–3] to boost the SNR to over $85\mathrm{~dB}$, at the price of limited input BW or increased circuit complexity. Although pipelined NS SAR or MASH suppress the last-stage n comp effectively, amplifying the preceding stage’s residue requires either power-hungry amplifier or dynamic amplifier with intense calibration [4]. Alternatively, LSB repeating can suppress $n_{\text{comp}}$ power-efficiently [5]. The 78.4dB-SNDR NS SAR with 9bit CDAC in [6] suppress ncomp with 4-times LSB repeating and use the results to switch the CDAC after tri-level voting. However, the suppression effect of ncomp would be much limited for a precision CDAC (10 12bit) with more times LSB repeating, as it only translate the results into 3 different levels.
IRS-Aided Uplink Multi-Antenna NOMA Systems With Non-Ideal GSIC

Both intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) are considered as potential techniques for the next-generation mobile communication system. In this paper, we concentrate on the power minimization problem for a multi-antenna IRS-NOMA uplink system, which is addressed by alternatively optimizing transceivers and phase shifts. Particularly, the users are divided into one central group and one edge group according to their propagation distances to the base station, where the data transmission of the edge group is assisted by the IRS. Besides, from the perspective of practice, a non-ideal group-based successive interference cancellation (GSIC) is taken into account. To proceed, an iterative algorithm with the minimum mean square error equalizer is leveraged to design the transceivers and a sequential rotation algorithm is developed to optimize the phase shifts. Simulation results indicate the superiority of the proposed scheme compared with various benchmarks in terms of transmit power consumption.
Phase Controlled Electromagnetically Induced Transparency in a Closed Cyclic Lambda Atomic System

In this work, Electromagnetically Induced Transparency (EIT) has been studied in a microwave driven closed cyclic Lambda atomic system. It is observed that in the absence of microwave field a normal transparency window is obtained, but when a microwave field is also applied between hyperfine levels along with the optical fields an amplification and attenuation in EIT signal is observed depending upon the relative phase between fields driving the atomic system. In fact, a new probe field is generated by microwave and coupling field which interfere constructively or destructively with incident probe field leading to either amplification, attenuation or asymmetricity in probe transmission signal. Also, dependency of phase sensitive amplification on ground state decoherence is also studied. This novel, controllable and amplified EIT signal can be potentially used for the transfer of coherent microwave analog or digital message signal over larger distance using optical fibers where amplification is preliminary requirement.
Adaptive Online Time-Series Prediction for Virtual Metrology in Semiconductor Manufacturing

This paper proposes a novel highly accurate virtual metrology (VM) method based on adaptive online time-series learning. The method comprises a novel time-series prediction algorithm robust against data drifts and shifts observed in semi-conductor manufacturing. The prediction algorithm incorporates time-aware data normalization and adaptive online learning. The time-aware normalizer transforms the data to suppress the effect of drifts. The adaptive online learner captures the time-varying relationship between response and inputs caused by shifts. On both simulated and real process data our approach outperforms conventional VM approaches. When applied to advanced process control (APC) on high-volume production lines at a major semiconductor manufacturer, our VM method substantially reduced variability of process outcomes.
Thermoacoustic engines

Thermoacoustic engines (TAEs) can be used to pump heat using a sound wave or pump a sound wave using a temperature gradient. The basic arrangement is a gas-filled acoustic resonator with appropriately positioned thermoacoustic elements. Two types of thermoacoustic elements are used in these engines: (1) heat exchangers used to communicate heat between the gas and external heat reservoirs; and (2) the TAE, also known as a stack. The TAEs are sections of porous media that support the temperature gradient, transport heat on the acoustic wave between the exchangers, and produce or absorb acoustic power. Previous results have been developed for TAEs with circular or parallel slit pore geometries. The theory is extended for gas-filled TAEs to include pores of arbitrary cross-sectional geometry. An approximate analysis of energy flow and acoustical measurements of a thermoacoustic prime mover are given. <<ETX>>
Interference-Aware User Association and Beam Pair Link Allocation in mm-Wave Cellular Networks

We study the problem of joint user association and beam pair link (BPL) allocation in millimeter-wave (mm-wave) cellular networks. We propose two interference-aware strategies – a centralized and a distributed one – and evaluate their performance based on site-specific directional channel data and realistic antenna models. Our results show that using idealized sectored antenna models severely underestimates the spatial interference, considering the non-negligible sidelobes of realistic antenna arrays which strongly limit the achievable spatial separation of the allocated BPLs in mm-wave networks using beam codebooks. We also show that intra-cell interference is the dominant interference component for all allocated users, in contrast to assumptions in the prior literature. By exploiting non line-of-sight BPLs, our interference-aware strategies achieve significant performance gains over interference-agnostic 5G-NR default user association to the strongest base station and BPL, as well as outperforming a centralized, load-balancing literature benchmark. Our proposed strategies rely solely on downlink 5G-NR reference signals for channel state information updates, making them attractive for practical codebook-based mm-wave cellular networks.
Characteristics of Equatorial F-region Irregularities along the 90°E Meridian during High Solar Activity Phase

This study investigated the characteristics of the Equatorial ionospheric F-region Irregularities (EFIs) along the 90°E meridian using the phase fluctuations of Global Navigational Satellite System (GNSS) signals during the maximum phase of solar activity in the solar cycle 24. Results indicate that the occurrence of EFIs is related to the local time, season and magnetic latitude. The EFIs are usually observed during the post-sunset hours and are more pronounced before midnight. In the equinox seasons, EFIs are more common and intense around the magnetic equator and low latitude regions. The disappearance time of EFIs is late during the spring equinox season than the autumn equinox. The occurrence probability of severe EFIs is high in the equinox seasons than in the solstice seasons, especially in spring equinox. Moderate EFIs are observed more in the spring equinox season over the pole-ward edge of the Equatorial Ionization Anomaly (EIA) region in both the hemispheres. This study helps in understanding the spatio-temporal characteristics of EFIs and thereby mitigating the scintillation effects in highly precise and dynamic applications of satellite-based navigation systems over the equatorial and low latitude Indian sector.
DENOISING OF COMPUTER TOMOGRAPHY IMAGES USING CURVELET TRANSFORM

A special member of the emerging family of multiscale geometric transforms is the curvelet transform which was developed in the last few years in an attempt to overcome inherent limitations of traditional multistage representations such as wavelets. The Computer Tomography images were denoised using both wavelet and curvelet transform and results are presented in this paper. It has been found that the cuvelet transform outperforms the wavelet transform in terms of signal noise ratio.
Super-Adiabatic Cooling of Small Scale Magnetic Flux-Ropes in Inner Heliosphere: PSP Observation

Small scale magnetic flux-rope (SSMFR) is ubiquitous in space plasma and contributes to several plasma processes such as; plasma transport, wave activity, acceleration, etc. Here, we have investigated the thermodynamics of three SSMFRs close to the Sun. The polytropic indices for all three SMFRs were greater than two, suggesting that the plasma shows super-adiabatic properties. Additionally, the SSMFRs' work-to-heat-supply ratios are greater than -0.6. It shows that more than 60% of the heat delivered to the system is used to carry out work, while the remaining is used to boost internal energy. Thus, the discovered super-adiabatic process would be critical in understanding the energy transfer from the SSMFR to the surrounding plasma.
Marine Stratocumulus Convection. Part I: Governing Equations and Horizontally Homogeneous Solutions

Abstract A coupled, convective-radiative, boundary-layer model of marine stratocumulus clouds is presented. The model, which is a slight generalization of the cloud-topped, mixed-layer model of Lilly (1968), has as dependent variables the cloud-top height, cloud-base height, mixed-layer moist static energy and total water content, the turbulent fluxes of moist static energy and total water, the cloud-top jumps of moist static energy and total water, the cloud-top temperature, and the net radiative flux divergence at cloud top and in the mixed layer. Under horizontally homogeneous steady-state conditions the governing equations reduce to a system of algebraic equations which is easily solved. This system has been solved for sea surface temperatures between 13 and 18°C and large-scale divergences between 1×10−6 and 6×10−6 s−1. These calculations have been performed for the case when all the radiative cooling is confined to the cloud-top jump condition and for the case when some of the cooling is allowed to .
A Monolithic 3D Magnetic Sensor in 65nm CMOS with <10μTrms Noise and 14.8μW Power

Magnetic sensors have become increasingly ubiquitous as they constitute an integral part of several fast-growing sectors such as automotive, navigation, robotics, medical devices and consumer electronics [1] –[6]. Due to their compatibility with the standard CMOS process, Hall magnetic sensors are widely used. However, one of the key challenges of CMOS-based Hall sensors is their relatively low sensitivity, which is inevitable given the low Hall coefficient of Si. For better sensitivity, Hall sensors are biased at higher current levels which hinders their widescale use in low-power bioelectronics and other power-constrained applications. Another challenge is the difficulty in implementing high-sensitivity vertical Hall elements in planar CMOS processes for 3D sensing. This is often overcome by using ferromagnetic materials that require additional and expensive steps during fabrication, thus increasing the cost [2] [3].
GEOMETRIC MEAN LABELING OF SOME NEW DISCONNECTED GRAPHS

A Graph G = (V, E) with p vertices and q edges is said to be a Geometric mean graph if is possible to label the vertices xIV with distinct labels f(x) from 1,2…. q+1 is such a way that when each edge e=uv is labeled with.
Discrete event estimation of nonlinear hybrid dynamical systems using fuzzy clustering

Abstract Nonlinear hybrid dynamical systems change its continuous nonlinear dynamic due to occurrence of discrete events. In many applications of hybrid mechanical systems, discrete dynamic exists due to the change in magnitude of displacement and velocity which change its continuous dynamics. For model-based control of such systems, it is difficult to obtain first principle models due to unknown discrete events. In this work, clustering based fuzzy validation criteria is proposed to estimate the number of discrete event present in the hybrid mechanical systems along with identification of PieceWise Auto Regressive eXogenous model. The simulation results, on a mechanical hybrid system consist of discrete dynamics due to the magnitude of the velocity, which has nonlinear boundaries, are used to validate the proposed methodology.