Miracle-dz/UniFAR-FTUs huggingface dataset:
Geometric Discrepancy: An Illustrated Guide

1. Introduction 1.1 Discrepancy for Rectangles and Uniform Distribution 1.2 Geometric Discrepancy in a More General Setting 1.3 Combinatorial Discrepancy 1.4 On Applications and Connections 2. Low-Discrepancy Sets for Axis-Parallel Boxes 2.1 Sets with Good Worst-Case Discrepancy 2.2 Sets with Good Average Discrepancy 2.3 More Constructions: b-ary Nets 2.4 Scrambled Nets and Their Average Discrepancy 2.5 More Constructions: Lattice Sets 3. Upper Bounds in the Lebesgue-Measure Setting 3.1 Circular Discs: a Probabilistic Construction 3.2 A Surprise for the L 1-Discrepancy for Halfplanes 4. Combinatorial Discrepancy 4.1 Basic Upper Bounds for General Set Systems 4.2 Matrices, Lower Bounds, and Eigenvalues 4.3 Linear Discrepancy and More Lower Bounds 4.4 On Set Systems with Very Small Discrepancy 4.5 The Partial Coloring Method 4.6 The Entropy Method 5. VC-Dimension and Discrepancy 5.1 Discrepancy and Shatter Functions 5.2 Set Systems of Bounded VC-Dimension 5.3 Packing Lemma 5.4 Matchings with Low Crossing Number 5.5 Primal Shatter Function and Partial Colorings 6. Lower Bounds 6.1 Axis-Parallel Rectangles: L 2-Discrepancy 6.2 Axis-Parallel Rectangles: the Tight Bound 6.3 A Reduction: Squares from Rectangles 6.4 Halfplanes: the Combinatorial Discrepancy 6.5 Combinatorial Discrepancy for Halfplanes Revisited 6.6 Halfplanes: the Lebesgue-Measure Discrepancy 6.7 A Glimpse of Positive Definite Functions 7. More Lower Bounds and the Fourier Transform 7.1 Arbitrarily Rotated Squares 7.2 Axis-Parallel Cubes 7.3 An Excursion to Euclidean Ramsey Theory A. Tables of Selected Discrepancy Bounds Bibliography Index Hints
Low Dietary Diversity for Recommended Food Groups Increases the Risk of Obesity among Children: Evidence from a Chinese Longitudinal Study

The association between dietary diversity and childhood obesity remains unclear; therefore, this longitudinal study was conducted to analyze the effect of dietary diversity on childhood obesity. One year after the first investigation, a follow-up was completed in 2010. A total of 4538 participants were included for analysis. Dietary diversity scores were calculated based on the consumption of nine recommended food groups which were categorized in accordance with the 2013 United Nations Food and Agriculture Organization guidelines. After a one-year follow-up, the low-score group underwent a significantly more considerable change in weight, body mass index, and body fat percentage than the high-score group (4.62 vs. 4.06 kg, 0.76 vs. 0.51 kg/m2, and 1.99% vs. 1.13%, respectively). Furthermore, in the low-score group, the odds ratios for overweight, obese, and overweight and obese were 1.76 (95% CI: 1.17, 2.65), 0.99 (95% CI: 0.67, 1.46), and 1.35 (95% CI: 1.01, 1.81), and the relative risks were 1.81 (95% CI: 1.03, 3.19), 2.31 (95% CI: 0.81, 6.59), and 1.98 (95% CI: 1.20,3.28), respectively. Low dietary diversity for the recommended food groups was associated with a high weight, high body mass index, and high body fat, which was associated with an increased risk of being overweight or obese in Chinese children.
Three addressable spin qubits in a molecular single-ion magnet

We show that several qubits can be integrated in a single magnetic ion, using its internal electronic spin states with energies tuned by a suitably chosen molecular environment. This approach is illustrated with a nearly-isotropic Gd(III) ion entrapped in a polyoxometalate molecule. Experiments with microwave technologies, either three dimensional cavities or quantum superconducting circuits, show that this magnetic molecule possesses the number of spin states and the set of coherently addressable transitions connecting these states that are needed to perform a universal three-qubit processor or, equivalently, a d=8-level 'qudit'. Our findings open prospects for developing more sophisticated magnetic molecules which can result in more powerful and noise resilient quantum computation schemes.
Electro-optics of graphene: Field-modulated reflection and birefringence

Institute of Semiconductor Physics, NAS of Ukraine, Pr. Nauky 41, Kyiv, 03028, Ukraine(Dated: December 4, 2009)The elecrooptical response of graphene due to heating and drift of carriers is studied theoreti-cally. Real and imaginary parts of the dynamic conductivity tensor are calculated for the case ofeﬀective momentum relaxation, when anisotropic contributions are small. We use the quasiequilib-rium distribution of electrons and holes, characterized by the eﬀective temperature of carriers andby concentrations, which are controlled by gate voltage and in-plane electric ﬁeld. The geometryof normal propagation of probe radiation is considered, spectral and ﬁeld dependences of the re-ﬂection coeﬃcient and the relative absorption are analyzed. The ellipticity degree of the reﬂectedand transmitted radiation due to small birefringence of graphene sheet with current have also beendetermined.
High Sensitivity, Wide Range Pressure Sensor Based on Layer-by-Layer Self-Assembled MXene/Carbon Black@Polyurethane Sponge for Human Motion Monitoring and Intelligent Vehicle Control

Flexible pressure sensors with high sensitivity, low cost, lightweight, and convenience are of significance in the field of human movement monitoring and sensing. This article demonstrated a piezoresistive pressure sensor prepared by layer-by-layer (LbL) self-assembly of MXene and carbon black (CB) on a polyurethane (PU) sponge. The electronegativity of MXene and the electropositive of CB enable them to combine more stably. The assembled sensor achieves reliable repeatability (over 3700 cycle testing), high sensitivity (−5.26 kPa $^{-{1}}$ ), wide sensing range (0–240 kPa), acceptable response time (300/300 ms), and good reproducibility under various pressures. MXene and CB greatly increase the electrical conductivity and measurement range of the piezoresistive sensors. The existence of microcracks allows the sensor to sensitively capture micropressure signals, such as human radial artery pulse and respiration. In addition, the large-area conductive framework permits the sensor to maintain high responsiveness over a huge strain range and to distinguish various degrees of human movement. Furthermore, the sensor has shown excellent performance in controlling smart devices through external pressure as a human–machine interface. The pressure sensor based on LbL self-assembled MXene/CB on a PU sponge has potential applications in motion signal detection, artificial intelligence, and other fields.
Cold Positrons from Decaying Dark Matter

Many models of dark matter contain more than one new particle beyond those in the Standard Model. Often heavier particles decay into the lightest dark matter particle as the Universe evolves. Here we explore the possibilities that arise if one of the products in a (Heavy Particle) $$\rightarrow$$ (Dark Matter) decay is a positron, and the lifetime is shorter than the age of the Universe. The positrons cool down by scattering off the cosmic microwave background and eventually annihilate when they fall into Galactic potential wells. The resulting 511 keV flux not only places constraints on this class of models but might even be consistent with that observed by the INTEGRAL satellite.
Dissipative preparation of entangled states between two spatially separated nitrogen-vacancy centers

We present a novel scheme for the generation of entangled states of two spatially separated nitrogen-vacancy (NV) centers with two whispering-gallery-mode (WGM) microresonators, which are coupled either by an optical fiber-taper waveguide, or by the evanescent fields of the WGM. We show that, the steady state of the two NV centers can be steered into a singlet-like state through a dissipative quantum dynamical process, where the cavity decay plays a positive role and can help drive the system to the target state. The protocol may open up promising perspectives for quantum communications and computations with this solid-state cavity quantum electrodynamic system.
Memristive Neural Network with Efficient In-Situ Supervised Training

Artificial Neural Networks (ANNs) are trained and tested with empirical data in a supervised and unsupervised manner. During the learning of an ANN in hardware, matrix vector multiplication and the outer product of vectors are costly operations in terms of time and space. Memristor-based crossbars are one of the most prominent candidates for implementing these operations efficiently. Here, a memristive neural network is proposed where a synapse is realized by employing two memristors only. No transistor as a controlling element is associated at the cross point of the memristive crossbar. An in-situ training architecture to train a memristive multilayered neural network (MNN) is proposed where online supervised gradient descent back propagation is implemented and all the synaptic weights are updated in (1) time. The proposed training algorithm has been tested on simulated memristive MNN and single layer neural network (SNN) on the IRIS data set and Breast Cancer Wisconsin data set with a classification accuracy of 99.11% and 90.14%, respectively. Further, with 10% of the memristors stuck at maximum conductance state, a classification accuracy of 94.67% on the IRIS data-set shows the robustness of the proposed method.
MAP4: A Pragmatic Framework for In-Network Machine Learning Traffic Classification

Self-driving networks guided by machine-learning (ML) algorithms are the driving force for building networks of the future. ML is effective at making inferences about data that is too complex or too unpredictable for humans. The network softwarization enabled by a deep programmability approach opens up new opportunities to deploy ML at the programmable data plane. In this paper, we introduce the MAP4 as a framework that explores the feasibility of mapping ML models in programmable network devices. To achieve this, we rely on the P4 language to deploy a pre-trained model into a programmable switch, utilizing the ML model to accurately classify flows at line rate. Our approach demonstrates that ML models working as classifiers can better fit the data by using the new levels of network programmability from the P4 language. The results showed that with few packets, most of the flows are properly classified. In some use cases, with two packets in the flow, 97% of traffic can be correctly classified, and all classes are properly labeled with a maximum of four packets.
Systemic comparison of dielectric and plasmonic biosensors on a silicon photonics platform

Plasmonic and dielectric based waveguides are widely used for biosensing applications. However, the use of different sensing architectures and platforms hinders the fair comparison of their respective figures of merit. In this paper, plasmonic and dielectric-based photonic waveguide biosensors are compared in terms of attainable limit of detection, using in both cases a coherent-readout interferometric architecture and the same commercial manufacturing platform.
An embedded Hildreth-based model predictive control of an Elbow Joint Orthosis Robot

In this paper, we consider a constrained model predictive control design for an Elbow Joint Orthosis Robot. The challenge of the robotic device control is to achieve passive and resistive rehabilitation movements with hard and soft constraints. A fast quadratic programming solver based on the Hildreth method is developed to meet the short real-time implementation sampling time. The online optimization solver based on the Hildreth method is compared with two other solvers proving its superiority in terms of computation time in the simulation environment. Simulation results show successful set point tracking and constraints satisfaction. An embedded version of constrained model predictive control using the Hildreth quadratic programming solver is implemented on an Arduino Due microcontroller. The results are satisfactory, and motion tracking errors and inputs variance are minimized. Less effort, optimal performances, and absence of overshoot and control signal oscillations are considered to evaluate the different studied motions. A lower computational cost is obtained taking into account the trade-off between the control effort and the closed-loop performances.
Non-standard interactions and bimagic baseline for neutrino oscillations

For standard interactions of neutrinos with matter bimagic baseline of length about 2540 Km is known to be suitable for getting good discovery limits of neutrino mass hierarchy, $\sin^2 \theta_{13}$ and CP violation in the $\nu_e \rightarrow \nu_{\mu}$ oscillation channel. We discuss how even in presence of non-standard interactions (NSIs) of neutrinos with matter this baseline is found to be suitable for getting these discovery limits. This is because even in presence of NSIs one could get the $\nu_e \rightarrow \nu_\mu $ oscillation probability to be almost independent of CP violating phase $\delta$ and $\theta_{13}$ for one hierarchy and highly dependent on these two for the other hierarchy over certain parts of neutrino energy range. For another certain part of the energy range the reverse of this happens with respect to the hierarchies. We present the discovery limits of NSIs also in the same neutrino energy range. However, as with the increase of neutrino energy the NSI effect in the above oscillation probability gets relatively more pronounced in comparison to the vacuum oscillation parameters, so we consider higher neutrino energy range also for getting better discovery limits of NSIs. Analysis presented here for 2540 Km could also be implemented for longer bimagic baseline $> 6000$ Km.
Interplay of gas and ice during cloud evolution

During the evolution of diffuse clouds to molecular clouds, gas-phase molecules freeze out on surfaces of small dust particles to form ices. On dust surfaces, water is the main constituent of the icy mantle in which a complex chemistry is taking place. We aim to study the formation pathways and the composition of the ices throughout the evolution of diffuse clouds. For this purpose, we used time-dependent rate equations to calculate the molecular abundances in the gas phase and on solid surfaces (onto dust grains). We fully considered the gas-dust interplay by including the details of freeze-out, chemical and thermal desorption, and the most important photo-processes on grain surfaces. The difference in binding energies of chemical species on bare and icy surfaces was also incorporated into our equations. Using the numerical code flash, we performed a hydrodynamical simulation of a gravitationally bound diffuse cloud and followed its contraction. We find that while the dust grains are still bare, water formation is enhanced by grain surface chemistry that is subsequently released into the gas phase, enriching the molecular medium. The CO molecules, on the other hand, tend to gradually freeze out on bare grains. This causes CO to be well mixed and strongly present within the first ice layer. Once one monolayer of water ice has formed, the binding energy of the grain surface changes significantly, and an immediate and strong depletion of gas-phase water and CO molecules occurs. While hydrogenation converts solid CO into formaldehyde (H2CO) and methanol (CH3OH), water ice becomes the main constituent of the icy grains. Inside molecular clumps formaldehyde is more abundant than water and methanol in the gas phase, owing its presence in part to chemical desorption.
A Novel Frequency Hopping-Aided FMCW Integrated Radar and Communication System

While the frequency-modulated continuous-wave (FMCW) based scheme has been considered as a candidate for realizing integrated radar-communication (RadCom) systems, it still suffers from the low transmission rate. To resolve this issue, we in this paper propose a frequency hopping-aided FMCW RadCom system along with the corresponding radar detection and communication signal demodulation approaches. Our proposed system can significantly improve the transmission rate with only slight degradation of the radar performance. Since the interference could degrade the system performance, we discuss the interference problem and the interference avoidance solution. By simulations, we validate the efficacy of the proposed system.
Design Single Phase Five Level Packed U-Cell Inverter For Standalone and Grid Connected Modes

The Packed U-Cell (PUC) inverter now has a new mode of operation is presented in this work. The PUC five levels inverter is a switching inverter that is integrated into the process, is designed using a sensor-free voltage control system that uses redundant switching states. The Voltage control without sensors maintains half the voltage of the DC source on the DC capacitor, resulting in a minimal harmonic distortion symmetric five-level voltage waveform at the output. The suggested converter’s voltage regulator with no sensors simplifies the control system’s complexity, making it suitable for industrial applications. The introduced sensor-less technology is being used in a grid-connected application PUC5In order to inject real and reactive power into the grid with a changeable power factor from the inverter, an external current controller was employed, The PUC auxiliary DC bus, on the other hand, is controlled solely by a sensor free controller and a new switching scheme. The proposed PUC5 inverter’s simulation results in grid-connected and stand-alone operation modes demonstrate the sensor free voltage control’s a quick response time and good dynamic performance in achieving the necessary DC capacitor voltage balance.
A TYPE Ia SUPERNOVA AT REDSHIFT 1.55 IN HUBBLE SPACE TELESCOPE INFRARED OBSERVATIONS FROM CANDELS

We report the discovery of a Type Ia supernova (SN Ia) at redshift z = 1.55 with the infrared detector of the Wide Field Camera 3 (WFC3-IR) on the Hubble Space Telescope (HST). This object was discovered in CANDELS imaging data of the Hubble Ultra Deep Field and followed as part of the CANDELS+CLASH Supernova project, comprising the SN search components from those two HST multi-cycle treasury programs. This is the highest redshift SN Ia with direct spectroscopic evidence for classification. It is also the first SN Ia at z > 1 found and followed in the infrared, providing a full light curve in rest-frame optical bands. The classification and redshift are securely defined from a combination of multi-band and multi-epoch photometry of the SN, ground-based spectroscopy of the host galaxy, and WFC3-IR grism spectroscopy of both the SN and host. This object is the first of a projected sample at z > 1.5 that will be discovered by the CANDELS and CLASH programs. The full CANDELS+CLASH SN Ia sample will enable unique tests for evolutionary effects that could arise due to differences in SN Ia progenitor systems as a function of redshift. This high-z sample will also allow measurement of the SN Ia rate out to z ≈ 2, providing a complementary constraint on SN Ia progenitor models.
The bimodal initial mass function in the Orion Nebula Cloud

Due to its youth, proximity and richness the Orion Nebula Cloud (ONC) is an ideal testbed to obtain a comprehensive view on the Initial Mass Function (IMF) down to the planetary mass regime. Using the HAWK-I camera at the VLT, we have obtained an unprecedented deep and wide near-infrared JHK mosaic of the ONC (90% completeness at K~19.0mag, 22'x28). Applying the most recent isochrones and accounting for the contamination of background stars and galaxies, we find that ONC's IMF is bimodal with distinct peaks at about 0.25 and 0.025 M_sun separated by a pronounced dip at the hydrogen burning limit (0.08 M_sun), with a depth of about a factor 2-3 below the log-normal distribution. Apart from ~920 low-mass stars (M 0.005 M_sun, hence about ten times more substellar candidates than known before. The substellar IMF peak at 0.025 M_sun could be caused by BDs and IPMOs which have been ejected from multiple systems during the early star-formation process or from circumstellar disks.
The Optimization Design for Suppression of CRAFT TF Magnet Power Converter Switching Overvoltage

The switching overvoltage due to the operation of the switching device is considered to be one of the important research contents during the design phase of a high-power supply system based on thyristor rectifier topology in the comprehensive research facility for fusion technology (CRAFT). Switching peak overvoltage is suppressed by resistors–capacitors (RC) snubber circuit generally; however, the traditional RC design often relies on some simple empirical formulas and blind amplification margins, which is unable to meet the precision requirements of engineering design. All the work that has been done is based on the cophase counter parallel connection structure of the converter module, and a new strategy is proposed to optimize the RC snubber circuit in order to suppress the operating peak overvoltage better. First, the no-load transformer breaking overvoltage is analyzed, then RC parameters are designed based on a new strategy. Compared with traditional methods, the RC parameters selected by this strategy are more accurate, which meets the accuracy requirements of engineering design and suppresses switching better than before.
Accuracy Evaluation of the Landsat 9 Land Surface Temperature Product

Having a good knowledge of the uncertainty in the land surface temperature (LST) product will help to encourage its use in a wide number of applications, including urban heat islands, geothermal detection, and surface energy balance. Landsat 9 was launched on 27 September 2021 and provides an LST product, which is generated by the radiative transfer equation algorithm and has a spatial resolution of 30 m. In this article, we evaluated the performance of the Landsat 9 LST product by using a temperature-based (T-based) method and cross-validation. The T-based validation results showed that the average bias at the surface radiation budget network and baseline surface radiation network sites was 0.24 K and that the corresponding root mean square error (RMSE) was 3.42 K. The Landsat 9 LST product was in good agreement with the Landsat 7/8 LSTs, with an average bias of 0.25/0.08 K, an RMSE of 0.51/1.04 K, and a mean absolute error of 0.38/0.64 K. The comparable performance of the Landsat 7/8/9 LST products can be explained by the consistent LST retrieval algorithm. The absolute differences in the LST between Landsat 9 LST and MOD11 (MOD21) LST images were between 0.01 (0.65) and 2.50 K (1.76 K), whereas the RMSE values were between 1.40 (1.80) and 3.65 K (3.26 K). The specific heat capacity and thermal inertia of the different land surface covers can explain the significant biases. The above evaluation results are consistent with the initial performance testing of thermal infrared sensor-2 (TIRS-2) by the National Aeronautics and Space Administration and the U.S. Geological Survey. Although the released Landsat 9 LST product showed good performance in the preliminary evaluation, the split-window algorithm may be a better option for Landsat 9 LST retrieval, as the TIRS-2 data addressed stray light incursion. Since there are no official validation results that have been published, this article provides a third-party performance evaluation of the Landsat 9 LST product and will benefit research fields that require Landsat series LST products.