Miracle-dz/UniFAR-FTUs huggingface dataset:
Subthreshold CMOS Implementation of the Izhikevich Neuron Model

Neuromorphic computing seeks to build hardware systems that are similar to the brain in form and function. Such systems are composed of artificial neurons and synapses, both of which will have to operate with extreme energy efficiency to allow spiking neural networks to scale to the size of the brain. In this work, we present such a low-power subthreshold implementation of the Izhikevich neuron model, inspired by the circuit introduced by Wijekoon and Dudek. The circuit, designed in the UMC 65nm process, consumes 11.74fJ/spike at a 0.18V supply voltage, while operating on a biological timescale and allowing analog tunability of control voltages so as to exhibit different spiking behaviors. The circuit comprises an integrated digital spike transceiver that communicates with AER arbitration circuitry and generates reset pulses.
A Single-Inductor Triple-Output Buck-Boost Converter with Output Ripple Control for Wearable Devices

This paper presents a single-inductor triple-output (SITO) buck-boost converter for wearable devices. It converts a 2.8V to 4.8V Li-ion battery voltage to three regulated output voltages: 1.2 V, 1.8V, and 3.3V for different back-end circuits, such as digital circuits and analog circuits. The converter operates at discontinuous conduction mode (DCM) and regulates the output using pulse-skip modulation (PSM) to reduce cross-regulation. Furthermore, the converter includes an adaptive on-time (AOT) generator to improve the output power range at low input voltage and control the maximum output voltage ripple under different inputs. Furthermore, three self-tracking zero current detectors (ST-ZCD) provide appropriate off-time periods for power MOSFETs to reduce the reverse inductor current. The measurement results show that the proposed SITO buck-boost converter achieves a maximum peak power conversion efficiency of 75.8% under 315mW output power. In addition, the peak inductor current is well controlled under different input voltages.
A Highly Parallel Fine-Grained Sort-Merge Join on Near Memory Computing

In-time processing of database system is imperative to reveal the hidden information. JOIN operation is critical in data analysis, as it occupies almost half of the average execution time in the standard TPC-H benchmark for database processing. In modern databases, transferring data between computing engines and system memory has become one of the main performance challenges. Previous works of Near Memory Computing (NMC) alleviated the costly data transfer, however, the designs still pose inefficiency in terms of processing flow and data management. In this paper, we propose FG-SMJ: a highly parallel fine-grained sort-merge join on near memory computing. The novel data layout allows us to access data from memory chips with fine-grained chip-level parallelism and exploit memory bandwidth. Compared with previous NMC designs, the proposed FG-SMJ attains 3.08x speedup.
How soon after a zero-temperature quench is the fate of the Ising model sealed?

We study the transient between a fully disordered initial condition and a percolating structure in the low-temperature non-conserved order parameter dynamics of the two-dimensional Ising model. We show that a stable structure of spanning clusters establishes at a time . Our numerical results yield for the square and kagome lattices, for the triangular and for the bowtie-a lattices. We generalise the dynamic scaling hypothesis to take into account this new time-scale. We discuss the implications of these results for other non-equilibrium processes.
Oscillations in a flexible channel flow of a generalized Newtonian fluid

We study the flow of a generalized Newtonian fluid, characterized by a power-law model, through a channel consisting of a wall with a flexible membrane under longitudinal tension. It is assumed that at steady state the flow through the channel admits a constant flux unidirectional flow profile, while for the unsteady case, we employ the long wave approximation and use a set of reduced equations to describe the variation of the shape of the membrane (assumed to be massless and elastic) and the variation of the fluid-flux. By means of asymptotic expansion, multiscale analysis and full numerical solutions of the pertinent governing equations, we show that depending upon the Reynolds number and the membrane stress, the flow behaviour for a shear-thinning, shear-thickening and Newtonian fluid may be markedly different, being oscillatory for one while chaotic for the other. The results presented herein hold practical relevance for several biologically relevant processes involving transport of rheologically complex biofluids through flexible domains.
Design of Cyclic-Coupled Ring Oscillators with Guaranteed Maximal Phase Resolution

Cyclic-coupled ring oscillators (CCRO), which consist of M ring oscillators each with N inverting stages, can be used in time-domain data converters to achieve sub-gate-delay resolution and improved phase noise performance compared to a single ring oscillator (RO). However, CCROs can oscillate in several different oscillation modes, where some modes contain overlapping phases. Such in-phase oscillations severely degrade the performance of a time-domain data converter by undermining the sub-gate-delay of the CCRO. This paper presents a design method to avoid the undesired in-phase oscillation modes, and thus achieve guaranteed maximal phase resolution regardless of the oscillation mode, by properly selecting the CCRO dimensions N and M. We show, both theoretically and with transistor-level simulations, that mode-agnostic maximum phase resolution can be ensured by selecting a prime M together with an N which is co-prime with M.
Low-Complexity Pseudo Direct Learning Digital Pre-Distortion Architecture for Nonlinearity and Memory Effect of Power Amplifier in mmWave Baseband Transmitter

In this paper, we design a power amplifier (PA) digital pre-distortion (DPD) module at the baseband transmitter to pre-compensate the nonlinearity and memory effect of the PA. In terms of DPD, we propose a low-complexity pseudo direct learning (PDL) DPD architecture based on the system level point of view according to the IEEE 802.11ad/ay specifications. The compensated error vector magnitude (EVM) performance of nonlinearity and memory effects can be improved from -12.8 dB to -21.7 dB at 16-QAM mode. The gain flatness of the -3 dB bandwidth can be extended from 0.3$\pi$ to 0.78$\pi$ with improving of 2.6 times. For the hardware implementation, we use TSMC 28-nm HPC_PLUS CMOS technology with four times parallelism to achieve 2.5 GHz chip rate. The gate counts and power of the proposed DPD design are 273.1 K and 98.0 mW, respectively.
A Flexible-Window Filtering Technique for Interference Suppression in SpO2 Monitoring

The peripheral oxygen saturation (SpO2) reflects the metabolic capacity of the human body, which can be used in assessing or screening symptoms such as pulmonary embolism. Photoplethysmography (PPG) is a common method for SpO2 monitoring, while it suffers from interferences such as ambient light scattering, reflections, and motion artifacts. These interferences significantly degrade the accuracy of SpO2 monitoring. Filtering techniques are widely used to suppress the interferences in PPG signals. However, conventional PPG filtering techniques use a fixed window, which is not able to handle interferences at different frequencies. In this paper, we propose a flexible-window filtering technique to suppress the interferences in SpO2 monitoring. To validate the proposed technique, we built a prototype to monitor the in-vivo SpO2 of the human body. Measurement results show that the proposed technique reduces the mean absolute percentage error (MAPE) of SpO2 by 46% compared to the conventional methods.
Augmented Reality for the Visually Impaired: Navigation Aid and Scene Semantics for Indoor Use Cases

With the Augmented Reality (AR) technology avail-able today, it is quite feasible to accommodate the needs of the visually impaired (VI) via AR. In this paper, a framework is introduced to help the VI navigate and explore unfamiliar indoor environments. In contrast to commonly used AR applications focused on visual augmentation, the proposed framework em-ploys auditory three-dimensional feedback (A3DF) for guiding the VI. Concretely, the current framework reads the pose of the user and helps the VI reach a target location via A3DF. The A3DF is implemented with the Unity game engine to provide the optimal user experience. After acquiring the environment mesh (EM), the optimal path from the user's location to the target location is calculated, while avoiding obstacles using Unity's navigation system. Moreover, the user is provided with semantic information about the unknown environment whilst exploring via auditory information. This framework is implemented on Microsoft HoloLens 2 and tested at an office environment with different locations of interest. Additionally, this framework potentially accelerates the learning curve since the user can be trained using Unity's simulation environment. Lastly, given different design parameters of the framework, the proposed method can be fine-tuned to fit the specific needs of the individual VI.
A SAR ADC with Reconfigurable Delay and Redundancy to Relax the Reference Driver

This work presents a reconfigurable delay and redundancy technique, which relaxes the reference driver requirements for a charge-redistribution SAR ADC. By selectively adding delay to the most critical SAR cycle, the overall speed of the ADC is only slightly degraded, while the output impedance of the driver or the amount of decoupling capacitance can be reduced substantially. In a simulated 10-bit 10 MS/s SAR ADC prototype, the proposed technique reduces the decoupling capacitance by 16× while maintaining 59.2 dB SNDR and 71.2 dB SFDR at a power consumption of $32 \mu \mathrm{W}$. The estimated area is 0.002 mm2 including decoupling capacitors.
Evidence for Chiral d-Wave Superconductivity in URu2Si2 from the Field-Angle Variation of Its Specific Heat

Low-energy quasiparticle (QP) excitations in the heavy-fermion superconductor URu2Si2 were investigated by specific-heat \(C(T,H,\phi ,\theta )\) measurements of a high-quality single crystal. The occurrence of QP excitations due to the Doppler-shift effect was detected regardless of the field direction in C(H) of the present clean sample, which is in sharp contrast to a previous report. Furthermore, the polar-angle-dependent C(θ) measured under a rotating magnetic field within the ac plane exhibits a shoulder-like anomaly at θ ∼ 45° and a sharp dip at θ = 90° (H || a) in the moderate-field region. These features are supported by theoretical analyses based on microscopic calculations assuming the gap symmetry of \(k_{z}(k_{x} + ik_{y})\), whose gap structure is characterized by a combination of a horizontal line node at the equator and point nodes at the poles. The present results have settled the previous controversy over the gap structure of URu2Si2 and have authenticated its chiral d-wave superconducti.
Rapidity Correlation Structure in Nuclear Collisions

We show that measurements of the rapidity dependence of transverse momentum correlations can be used to determine the characteristic time ${\ensuremath{\tau}}_{\ensuremath{\pi}}$ that dictates the rate of isotropization of the stress energy tensor, as well as the shear viscosity $\ensuremath{\nu}=\ensuremath{\eta}/sT$. We formulate methods for computing these correlations using second-order dissipative hydrodynamics with noise. Current data are consistent with ${\ensuremath{\tau}}_{\ensuremath{\pi}}/\ensuremath{\nu}\ensuremath{\sim}10$, but targeted measurements can improve this precision.
The SLH framework for modeling quantum input-output networks

Abstract Many emerging quantum technologies demand precise engineering and control over networks consisting of quantum mechanical degrees of freedom connected by propagating electromagnetic fields, or quantum input-output networks. Here we review recent progress in theory and experiment related to such quantum input-output networks, with a focus on the SLH framework, a powerful modeling framework for networked quantum systems that is naturally endowed with properties such as modularity and hierarchy. We begin by explaining the physical approximations required to represent any individual node of a network, e.g. atoms in cavity or a mechanical oscillator, and its coupling to quantum fields by an operator triple (S,L,H). Then we explain how these nodes can be composed into a network with arbitrary connectivity, including coherent feedback channels, using algebraic rules, and how to derive the dynamics of network components and output fields. The second part of the review discusses several extensions to the basic SLH framework that expand its modeling capabilities, and the prospects for modeling integrated implementations of quantum input-output networks. In addition to summarizing major results and recent literature, we discuss the potential applications and limitations of the SLH framework and quantum input-output networks, with the intention of providing context to a reader unfamiliar with the field. Graphical Abstract
Errors and pseudothresholds for incoherent and coherent noise

We compare the effect of single qubit incoherent and coherent errors on the logical error rate of the Steane [[7,1,3]] quantum error correction code by performing an exact full-density-matrix simulation of an error correction step. We find that the effective 1-qubit process matrix at the logical level reveals the key differences between the error models and provides insight into why the Pauli twirling approximation is a good approximation for incoherent errors and a poor approximation for coherent ones. Approximate channels composed of Clifford operations and Pauli measurement operators that are pessimistic at the physical level result in pessimistic error rates at the logical level. In addition, we observe that the pseudo-threshold can differ by a factor of five depending on whether the error is calculated using the fidelity or the distance.
Cosmological Perturbations: Vorticity, Isocurvature and Magnetic Fields

In this paper I review some recent, interlinked, work undertaken using cosmological perturbation theory -- a powerful technique for modelling inhomogeneities in the Universe. The common theme which underpins these pieces of work is the presence of non-adiabatic pressure, or entropy, perturbations. After a brief introduction covering the standard techniques of describing inhomogeneities in both Newtonian and relativistic cosmology, I discuss the generation of vorticity. As in classical fluid mechanics, vorticity is not present in linearized perturbation theory (unless included as an initial condition). Allowing for entropy perturbations, and working to second order in perturbation theory, I show that vorticity is generated, even in the absence of vector perturbations, by purely scalar perturbations, the source term being quadratic in the gradients of first order energy density and isocurvature, or non-adiabatic pressure perturbations. This generalizes Crocco's theorem to a cosmological setting. I then introduce isocurvature perturbations in different models, focusing on the entropy perturbation in standard, concordance cosmology, and in inflationary models involving two scalar fields. As the final topic, I investigate magnetic fields, which are a potential observational consequence of vorticity in the early universe. I briefly review some recent work on including magnetic fields in perturbation theory in a consistent way. I show, using solely analytical techniques, that magnetic fields can be generated by higher order perturbations, albeit too small to provide the entire primordial seed field, in agreement with some numerical studies. I close with a summary and some potential extensions of this work.
Dynamics of anchored oscillating nanomenisci

We present a self-contained study of the dynamics of oscillating nanomenisci anchored on nanometric topographical defects around a cylindrical nanofiber -- radius below 100 nm. Using frequency-modulation atomic force microscopy (FM-AFM), we show that the friction coefficient surges as the contact angle is decreased. We propose a theoretical model within the lubrification approximation that reproduces the experimental data and provides a comprehensive description of the dynamics of the nanomeniscus. The dissipation pattern in the vicinity of the contact line and the anchoring properties are discussed as a function of liquid and surface properties in addition to the sollicitation conditions.
Variability and stability in blazar jets on time-scales of years: optical polarization monitoring of OJ 287 in 2005–2009

OJ 287 is a BL Lac object at redshift z = 0.306 that has shown double-peaked bursts at regular intervals of similar to 12 yr during the last similar to 40 yr. We analyse optical photopolarimetric monitoring data from 2005 to 2009, during which the latest double-peaked outburst occurred. The aim of this study is twofold: firstly, we aim to analyse variability patterns and statistical properties of the optical polarization light curve. We find a strong preferred position angle in optical polarization. The preferred position angle can be explained by separating the jet emission into two components: an optical polarization core and chaotic jet emission. The optical polarization core is stable on time-scales of years and can be explained as emission from an underlying quiescent jet component. The chaotic jet emission sometimes exhibits a circular movement in the Stokes plane. We find six such events, all on the time-scales of 10-20 d. We interpret these events as a shock front moving forwards and backwards in the jet, swiping through a helical magnetic field. Secondly, we use our data to assess different binary black hole models proposed to explain the regularly appearing double-peaked bursts in OJ 287. We compose a list of requirements a model has to fulfil to explain the mysterious behaviour observed in OJ 287. The list includes not only characteristics of the light curve but also other properties of OJ 287, such as the black hole mass and restrictions on accretion flow properties. We rate all existing models using this list and conclude that none of the models is able to explain all observations. We discuss possible new explanations and propose a new approach to understanding OJ 287. We suggest that both the double-peaked bursts and the evolution of the optical polarization position angle could be explained as a sign of resonant accretion of magnetic field lines, a 'magnetic breathing' of the disc.
Improved inference for the signal significance

We study the properties of several likelihood-based statistics commonly used in testing for the presence of a known signal under a mixture model with known background, but unknown signal fraction. Under the null hypothesis of no signal, all statistics follow a standard normal distribution in large samples, but substantial deviations can occur at practically relevant sample sizes. Approximations for respective p-values are derived to various orders of accuracy using the methodology of Edgeworth expansions. Adherence to normality is studied, and the magnitude of deviations is quantified according to resulting p-value inflation or deflation. We find that approximations to third-order accuracy are generally sufficient to guarantee p-values with nominal false positive error rates in the 5σ range (p-value =2.87 × 10−7) for the classic Wald, score, and likelihood ratio (LR) statistics at relatively low sample sizes. Not only does LR have better adherence to normality, but it also consistently outperforms all other statistics in terms of false negative error rates. The reasons for this are shown to be connected with high-order cumulant behavior gleaned from fourth order Edgeworth expansions. Finally, a conservative procedure is suggested for making finite sample adjustments while accounting for the look elsewhere effect via the theory of random fields.
POLARIMETRY OF THE SUPERLUMINOUS SUPERNOVA LSQ14MO: NO EVIDENCE FOR SIGNIFICANT DEVIATIONS FROM SPHERICAL SYMMETRY

We present the first polarimetric observations of a Type I superluminous supernova (SLSN). LSQ14mo was observed with VLT/FORS2 at five different epochs in the V band, with the observations starting before maximum light and spanning 26 days in the rest frame (z = 0.256). During this period, we do not detect any statistically significant evolution ( < 2 &sgr; ? > ) in the Stokes parameters. The average values we obtain, corrected for interstellar polarization in the Galaxy, are Q = −0.01% (±0.15%) and U = −0.50% (±0.14%). This low polarization can be entirely due to interstellar polarization in the SN host galaxy. We conclude that, at least during the period of observations and at the optical depths probed, the photosphere of LSQ14mo does not present significant asymmetries, unlike most lower-luminosity hydrogen-poor SNe Ib/c. Alternatively, it is possible that we may have observed LSQ14mo from a special viewing angle. Supporting spectroscopy and photometry confirm that LSQ14mo is a typical SLSN I. Further studies of the polarization of Type I SLSNe are required to determine whether the low levels of polarization are a characteristic of the entire class and to also study the implications for the proposed explosion models.
SHORT TERM ELECTRICITY LOAD FORECASTING FOR TUMAKURU CITY BASED ON ANN, LSTM AND RANDOM FOREST

: Due to the ongoing integration of renewable energy sources (RES) into the energy mix and the transformation of the conventional electric grid into a more intelligent, flexible, and interactive system, electrical load forecasting is now a crucial part of smart grid planning and management. It is challenging to anticipate the electric load due to its high volatility and uncertainty, whether the load is applied to the distribution system or a single residence. The main idea behind the proposed methodology is to optimise the hyper-parameters of the neural network by using the statistical properties of each time series dataset, as well as to arrange the dataset to maximise the advantages of the ANN algorithm. One of the three models is long short term memory. Random Forest and Artificial Neural Network are contrasted. An evaluation of algorithms was done for the smart city Tumakuru in Karnataka.
Pictorial Strucutures for Articulated Human Pose Estimation Technical Report

In this report we describe a framework to efficiently solve part matching problems in the form a pictorial structure. The framework can be used to solve a range of problems in Computer Vision including object detection, recognition and 2D pose estimation. The problem of human pose estimation which we are going to focus on in this report is, given a set of images of humans with annotated parts, find the location of these parts in novel images. Figure 1 shows a sample image from our dataset with annotations. As you can see each image in the training set comes with 10 bounding boxes outlining the major parts of the body. The aspect ratio of the bounding boxes are assumed to be fixed, therefore we only need to find 4 parameters including the position (x, and y), angle, and scale of the parts.
Quantum scalar fields in de Sitter space from the nonperturbative renormalization group

We investigate scalar field theories in de Sitter space by means of nonperturbative renormalization group techniques. We compute the functional flow equation for the effective potential of O(N) theories in the local potential approximation and we study the onset of curvature-induced effects as quantum fluctuations are progressively integrated out from subhorizon to superhorizon scales. This results in a dimensional reduction of the original action to an effective zero-dimensional Euclidean theory. We show that the latter is equivalent both to the late-time equilibrium state of the stochastic approach of Starobinsky and Yokoyama and to the effective theory for the zero mode on Euclidean de Sitter space. We investigate the immediate consequences of this dimensional reduction: symmetry restoration and dynamical mass generation.