Miracle-dz/UniFAR-FTUs huggingface dataset:
A Power-Efficient CMOS Multi-Band Phased-Array Receiver Covering 24–71-GHz Utilizing Harmonic-Selection Technique With 36-dB Inter-Band Blocker Tolerance for 5G NR

This article introduces a power-efficient 24.25– 71-GHz multi-band phased-array receiver supporting all allocated fifth-generation mobile network new radio (5G NR) frequency range 2 (FR2) bands at 24/28/39/47 GHz and the potential 5G NR-U bands in unlicensed 57–71 GHz. A novel harmonic-selection technique is introduced to extend the operating bandwidth with low power consumption. By switching between the fundamental-selected mode, the second-harmonic-selected mode, and the third-harmonic-selected mode, only signals in the desired bands can be preserved, while the unselected mixing components are rejected. A dual-mode multi-band low-noise amplifier (LNA) based on a configurable transformer is adopted to realize broadband operation with minimized power consumption and noise figure (NF). The Hartley architecture is employed to further improve the image rejection performance. A hybrid-type polyphase filter (PPF) with a detector-based high-precision calibration block is utilized in this work to realize the Hartley operation with reduced insertion loss (IL). The proposed phased-array receiver is fabricated in a standard 65-nm bulk CMOS process. With the concerted efforts of all components, the proposed multi-band receiver can support 5G standard-compliant OFDMA-mode modulated signals up to 256QAM with a 400-MHz channel bandwidth from 24 to 71 GHz. Better than 36-dB inter-band blocker rejections can be maintained by this work. With existing of 0-dBc inter-band blockers at worst case frequencies, this receiver shows EVMs of −33.3, −30.9, −31.6, and −28.5 dB at 28, 39, 47.2, and 60.1 GHz, respectively. The power consumptions for a single receiver channel are 36, 32, 51, and 71 mW at 28, 39, 47.2, and 60.1 GHz, respectively.
Unidirectional frequency conversion in microring resonators for on-chip frequency-multiplexed single-photon sources

Microring resonators are attractive for low-power frequency conversion via Bragg-scattering four-wave-mixing due to their comb-like resonance spectrum, which allows resonant enhancement of all four waves while maintaining energy and momentum conservation. However, the symmetry of such mode structures limits the conversion efficiency to 50% due to the equal probability of up- and down-conversion. Here, we demonstrate how two coupled microrings enable highly directional conversion between the spectral modes of one of the rings. An extinction between up- and down-conversion of more than 40 dB is experimentally observed. Based on this method, we propose a design for on-chip multiplexed single-photon sources that probabilistically generate photon pairs across many frequency modes of a ring resonator and subsequently convert them to a single frequency—thereby enabling quasi-deterministic photon emission. Our numerical analysis shows that once a photon is generated, it can be converted and emitted into a wave packet having a 90% overlap with a Gaussian with 99% efficiency for a ratio between intrinsic and coupling quality factors of 400.
PIMCA: A Programmable In-Memory Computing Accelerator for Energy-Efficient DNN Inference

This article presents a programmable in-memory computing accelerator (PIMCA) for low-precision (1–2 b) deep neural network (DNN) inference. The custom 10T1C bitcell in the in-memory computing (IMC) macro has four additional transistors and one capacitor to perform capacitive-coupling-based multiply and accumulation (MAC) in analog-mixed-signal (AMS) domain. A macro containing $256 \times 128$ bitcells can simultaneously activate all the rows, and as a result, it can perform a matrix-vector multiplication (VMM) in one cycle. PIMCA integrates 108 of such IMC static random-access memory (SRAM) macros with the custom six-stage pipeline and the custom instruction set architecture (ISA) for instruction-level programmability. The results of IMC macros are fed to a single-instruction-multiple-data (SIMD) processor for other computations such as partial sum accumulation, max-pooling, activation functions, etc. To effectively use the IMC and SIMD datapath, we customize the ISA especially by adding hardware loop support, which reduces the program size by up to 73%. The accelerator is prototyped in a 28-nm technology, and integrates a total of 3.4-Mb IMC SRAM and 1.5-Mb off-the-shelf activation SRAM, demonstrating one of the largest IMC accelerators to date. It achieves the system-level energy efficiency of 437 TOPS/W and the peak throughput of 49 TOPS at the 42-MHz clock frequency and 1-V supply for the VGG9 and the ResNet-18 on the CIFAR-10 dataset.
Type 2 diabetes mellitus induced autophagic response within pulmonary tissue in the rat model

Introduction: The current experiment aimed to address the impact of type 2 diabetes mellitus on autophagy status in the rat pulmonary tissue. Methods: In this study, 20 male Wistar rats were randomly allocated into two groups as follows: control and diabetic groups. To induce type 2 diabetes mellitus, rats received a combination of streptozotocin (STZ) and a high-fat diet. After confirmation of diabetic condition, rats were maintained for 8 weeks and euthanized for further analyses. The pathological changes were assessed using H&E staining. We also measured transforming growth factor-β (TGF-β), bronchoalveolar lavage fluid (BALF), and tumor necrosis factor-α (TNF-α) in the lungs using ELISA and real-time PCR analyses, respectively. Malondialdehyde (MDA) and superoxide dismutase (SOD) levels were monitored in diabetic lungs to assess oxidative status. We also measured the expression of becline-1, LC3, and P62 to show autophagic response under diabetic conditions. Using immunofluorescence staining, protein levels of LC3 was also monitored. Results: H&E staining showed pathological changes in diabetic rats coincided with the increase of TNF-α (~1.4-fold) and TGF-β (~1.3-fold) compared to those in the normal rats (P<0.05). The levels of MDA (5.6 ± 0.4 versus 6.4 ± 0.27 nM/mg protein) were increased while SOD (4.2 ± 0.28 versus 3.8 ± 0.13 U/mL) activity decreased in the diabetic rats (P<0.05). Real-time polymerase chain reaction (PCR) analysis showed the up-regulation of Becline-1 (~1.35-fold) and LC3 (~2-fold) and down-regulation of P62 (~0.8-fold) (P<0.05), showing incomplete autophagic flux. We noted the increase of LC3+ cells in diabetic condition compared to that in the control samples. Conclusion: The prolonged diabetic condition could inhibit the normal activity of autophagy flux, thereby increasing pathological outcomes.
Multi-Modality Diversity Fusion Network with Swintransformer for RGB-D Salient Object Detection

Multi-modality complementary information brings new impetus and innovation to saliency object detection (SOD). However, most existing RGB-D SOD methods either indiscriminately handle RGB features and depth features or only take depth features as additional information of RGB subnet-work, ignoring the different roles of two modalities for SOD tasks. To tackle this issue, we propose a novel multi-modality diversity fusion network with SwinTransformer (M2DFNet) for RGB-D SOD from the perspective of the different status of multi-modality, which adequately explores the roles of RGB and depth modalities. To this end, a triple-diversity supervision mechanism (TDSM) and a diversity fusion module (DFM) are designed to parse the function of different modalities. Besides, we designed a dense decoder (DSD) to integrate multi-scale features and transfer gain information from top to bottom, which can improve the performance of SOD. Extensive experiments on five benchmark datasets demonstrate that the proposed M2DFNet outperforms 17 other state-of-the-art (SOTA) RGB-D SOD methods.
Nonresonant leptoquark with multigeneration couplings for 
μμjj
 and 
μνjj
 at the LHC

CMS has recently reported a moderate excess in the $\mu\nu jj$ final state in a second generation Leptoquark search, but they have disregarded it because the excess is not present in the $\mu\mu jj$ final state and because they do not observe the expected resonant peak in the distributions. As a proof of concept we show that a simple Leptoquark model including second and third generation couplings with non-negligible single- and non-resonant production in addition to usual pair production could explain the data: excess ($\mu\nu jj$), lack of excess ($\mu\mu jj$) and missing peak in the distributions; while being in agreement with collider constraints. We take this result and analysis as a starting point of a reconsideration of the ATLAS and CMS second generation Leptoquark searches. We also discuss which would be the consequences and modifications that should be performed in the searches to test if this deviation would correspond to a New Physics signal. We observe that low-energy flavor constraints can be avoided by adding heavier particles to the model.
Systematic ab initio study of curvature effects in carbon nanotubes

We investigate curvature effects on geometric parameters, energetics, and electronic structure of zigzag nanotubes with fully optimized geometries from first-principle calculations. The calculated curvature energies, which are inversely proportional to the square of radius, are in good agreement with the classical elasticity theory. The variation of the band gap with radius is found to differ from simple rules based on the zone folded graphene bands. Large discrepancies between tight binding and first-principles calculations of the band gap values of small nanotubes are discussed in detail.
An Optical-Infrared Jet in 3C 133

We report the discovery of a new optical-IR synchrotron jet in the radio galaxy 3C 133 from our HST NICMOS snapshot survey. The jet and eastern hot spot are well resolved and visible at both optical and IR wavelengths. The IR jet follows the morphology of the inner part of the radio jet, with three distinct knots identified with features in the radio. The radio-IR SEDs of the knots are examined, along with those of two more distant hot spots at the eastern extreme of the radio feature. The detected emission appears to be synchrotron, with peaks in the NIR for all except one case, which exhibits a power-law spectrum throughout.
Semiclassical theory of front propagation and front equilibration following an inhomogeneous quantum quench

We use a semiclassical approach to study out of equilibrium dynamics and transport in quantum systems with massive quasiparticle excitations having internal quantum numbers. In the universal limit of low energy quasiparticles, the system is described in terms of a classical gas of colored hard-core particles. Starting from an inhomogeneous initial state, in this limit we give analytic expressions for the space and time dependent spin density and spin current profiles. Depending on the initial state, the spin transport is found to be ballistic or diffusive. In the ballistic case we identify a "second front" that moves more slowly than the maximal quasiparticle velocity. Our analytic results also capture the diffusive broadening of this ballistically propagating front. To go beyond the universal limit, we study the effect of non-trivial scattering processes in the $O(3)$ non-linear sigma model by performing Monte Carlo simulations, and observe local equilibration around the second front in terms of the densities of the particle species.
Black hole formation in the first stellar clusters

The early Universe was composed almost entirely of hydrogen and helium, with only trace amounts of heavy elements. It was only after the first generation of star formation that the Universe became sufficiently polluted to produce a second generation (Population II) of stars which are similar to those in our local Universe. Evidence of massive star cluster formation is nearly ubiquitous among the observed galaxy population and if this mode of star formation occurred at early enough epochs, the higher densities in the early Universe may have caused many of the stars in the cluster to strongly interact. In this scenario, it may be possible to form a very massive star by repeated stellar collisions that may directly collapse into a black hole and form a supermassive black hole seed. In this chapter, we will explore this scenario in detail to understand the dynamics which allow for this process to ensue and measure the probability for this type of seed to represent the supermassive black hole population observed at z > 6.
THE KINETIC SUNYAEV–ZEL’DOVICH EFFECT FROM REIONIZATION: SIMULATED FULL-SKY MAPS AT ARCMINUTE RESOLUTION

The kinetic Sunyaev–Zel’dovich (kSZ) effect results from Thomson scattering by coherent flows in the reionized intergalactic medium. We present new results based on ray-tracing an 8 Gpc/h realization of reionization with resolution elements 2 Mpc/h (subtending ′ at z = 6) on a side to create a full-sky kSZ map. The realization includes, self-consistently, the effects of reionization on scales corresponding to multipoles . We separate the kSZ map into Doppler ( ), Ostriker–Vishniac ( ), patchy ( ), and third-order ( ) components, and compute explicitly all the auto- and cross-correlations (e.g., , , etc.) that contribute to the total power. We find a complex and nonmonotonic dependence on the duration of reionization at and evidence for a non-negligible (10%–30%) contribution from connected four-point correlations, , usually neglected in analytical models. We also investigate the cross-correlation of linear matter and large-scale kSZ temperature fluctuations, focusing on (1) cross-power spectra with biased tracers of the matter density and (2) cold spots from infall onto large, rare H ii regions centered on peaks in the matter distribution at redshifts that are a generic non-Gaussian feature of patchy reionization. Finally, we show that the reionization history can be reconstructed at 5σ–10σ significance by correlating full-sky 21 cm maps stacked in bins with with existing cosmic microwave background (CMB) temperature maps at , raising the prospects for probing reionization by correlating CMB and LSS measurements. The resulting kSZ maps have been made publicly available at www.cita. utoronto.ca/~malvarez/research/ksz-data/.
SAZyzz: Scaling AZyzzyva to Meet Blockchain Requirements

We present SAZyzz, a leader-based Byzantine Fault Tolerant consensus protocol for partially synchronous networks. SAZyzz exhibits better performance/scalability when compared to the state-of-the-art leader-based BFT consensus protocols. It is built on top of AZyzzyva and has adopted a tree-based communication model that enhances AZyzzyva's scalability. Additionally, SAZyzz reduces the communication complexity in the two protocol's paths to <inline-formula><tex-math notation="LaTeX">$O(\log {N})$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>O</mml:mi><mml:mo>(</mml:mo><mml:mo form="prefix">log</mml:mo><mml:mi>N</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="sohrabi-ieq1-3214976.gif"/></alternatives></inline-formula>. The tree-based topology, however, is argued to have shortcomings when used to design BFT consensus protocols. This refers to the strong assumption that all the internal nodes of the tree are honest, which leads to a trade-off between tolerating Byzantine faults and better performance/scalability. This paper shows that, with the current technological infrastructures available for industrial systems, such as Trusted Execution Environment (TEE) and Public Key Infrastructure (PKI), this assumption is realistic. SAZyzz comprises of fast-path and backup-path, each of which has two modes: <italic>simple mode</italic> and <italic>scalable mode</italic>. To demonstrate the efficiency and feasibility of SAZyzz's adoption for blockchain systems, we designed and implemented the ZyConChain blockchain system based on SAZyzz. The evaluation results show that SAZyzz can significantly improve the performance/scalability of blockchain systems.
Isolation And Purification of Hyaluronic Acid Like Components From Manihot esculenta ( tapioca )

Hyaluronic acid is a substance that is present in the human body. It is found in the most elevated fixations in liquids in the eyes and joints. Individuals take hyaluronic acid for different joint issue problems, including osteoarthritis. Hyaluronic acid is utilized in certain eye surgeries like, corneal transplantation, and repair of a disengaged retina and other eye wounds. Hyaluronic acid is additionally utilized as a lip filler in plastic surgery. A few people apply hyaluronic acid to the skin for mending wounds, cosmetics, skin ulcers, and as a lotion. Hyaluronic acid has been advanced as a wellspring of youth. In the present investigation Manihot esculenta (tapioca) was chosen for the study. The sample was extracted with methanol and chloroform. Goat brain and Visceral fluid were chosen as standard for the study. Estimation was carried out to check the presence of total carbohydrates, proteins and reducing sugars. Qualitative and quantitative studies were carried out which indicated the presence of hyaluronic acid like components in tapioca in comparison to visceral fluid and brain. Further ion exchange chromatography was carried using DEAE-Sepharose. The elution obtained from ion exchange showed a peak at 230nm which indicates the presence of hyaluronic acid like components. The peak eluents were further purified by gel permeation chromatography using Sephadex G100. The result confirmed the presence of hyaluronic acid like components. The results of the present work suggested that hyaluronic acid like components could be present in Tapioca.
Probing Seismogenic Faults with Machine Learning

We analyze continuous seismic data with a variety of classical machine learning (ML) and deep learning (DL) models with the goal of identifying hidden signals connected to the earthquake cycle. In the laboratory, we find that continuous seismic waves originating in the fault zone are imprinted with fundamental information regarding the physics of the fault. Statistics of these low-amplitude, noise-like signals identified with supervised ML approaches can be used to estimate fault friction, fault displacement, and forecast upcoming failure with great accuracy. These results hold true for both stick-slip and slow-slip frictional regimes. Similarly, when we scale the approach to study slow-slip events in the Cascadia subduction zone and the San Andreas Fault, we find that continuous seismic waves contain information about the instantaneous fault displacement at all times. Direct application of these approaches to seismogenic faults in Earth is highly challenging to date. As a result, we are developing more generalized DL approaches where the model is trained on fault simulations and applied to laboratory fault data.
Instance and Feature Selection Using Fuzzy Rough Sets: A Bi-Selection Approach for Data Reduction

Data reduction, aiming to reduce the original data by selecting the most representative information, is an important technique of preprocessing data. At present, large-scale or huge data are very common and the development of data reduction techniques for such data has attracted much attention. As a powerful tool for handling uncertainty in real-valued data, the fuzzy rough set theory has been widely applied to data reduction including extensive feature selection methods and some instance selection approaches. Nevertheless, not much work has been devoted to the simultaneous selection of feature and instance based on fuzzy rough sets. In this article, we investigate the fuzzy rough set-based bi-selection issue for data reduction. Specifically, the unified concepts of the importance degrees of fuzzy granules are presented to select the representative instances first and then the critical features. An instance selection algorithm with a noise elimination technique is provided to firstly remove the noise and then select the representative instances according to the importance degrees of fuzzy granules. Then, the importance-degree-preserved attribute reduction is proposed, and a corresponding feature selection algorithm with a wrapper technique is given to search for a best feature subset. Last, the bi-selection method based on fuzzy rough sets (BSFRS) is presented for data reduction by integrating the instance selection and the feature selection methods. Moreover, some numerical experiments are conducted to assess the performance of BSFRS, and the results show that BSFRS performs well in terms of the effectiveness.
Heavy Metal Rules. I. Exoplanet Incidence and Metallicity

The discovery of only a handful of exoplanets required establishing a correlation between giant planet occurrence and metallicity of their host stars. More than 20 years have already passed from that discovery, however, many questions are still under lively debate: (1) What is the origin of that relation? ; (2) What is the exact functional form of the giant planet–metallicity relation (in the metal-poor regime)? ; and (3) Does such a relation exist for terrestrial planets? All of these questions are very important for our understanding of the formation and evolution of (exo)planets of different types around different types of stars and are the subject of the present manuscript. Besides making a comprehensive literature review about the role of metallicity on the formation of exoplanets, I also revisited most of the planet–metallicity related correlations reported in the literature using a large and homogeneous data provided by the SWEET-Cat catalog. This study led to several new results and conclusions, two of which I believe deserve to be highlighted in the abstract: (i) the hosts of sub-Jupiter mass planets (∼0.6–0.9 M♃) are systematically less metallic than the hosts of Jupiter-mass planets. This result might be related to the longer disk lifetime and the higher amount of planet building materials available at high metallicities, which allow a formation of more massive Jupiter-like planets; (ii) contrary to the previous claims, our data and results do not support the existence of a breakpoint planetary mass at 4 M♃ above and below which planet formation channels are different. However, the results also suggest that planets of the same (high) mass can be formed through different channels depending on the (disk) stellar mass i.e., environmental conditions.
Hybrid Absorber With Dual-Band Performance and High Absorption Rate

Low-profile absorbers are of interest for compact shielded enclosures for making antenna measurements. Furthermore, the cost should be minimized for practical systems since massive production is required. In this work, a novel dual-band hybrid absorber based on structured resonators and lossy dielectric material is proposed to meet these requirements. The lossy material enables improvement in the absorption rate and operating bandwidth. The proposed absorber operates at 2.4- and 5.0-GHz Wi-Fi spectra and covers the low-frequency bands with a reflection coefficient lower than <inline-formula><tex-math notation="LaTeX">$-$</tex-math></inline-formula>25 dB and a large part of the high-frequency ones with reflection lower than <inline-formula><tex-math notation="LaTeX">$-$</tex-math></inline-formula>20 dB. Moreover, some of the Wi-Fi bands are covered with a reflection coefficient better than <inline-formula><tex-math notation="LaTeX">$-$</tex-math></inline-formula>30 dB. In order to validate the proposed concept, the dual-band absorber is manufactured and tested, and the agreement between the simulation and measurement results is good. The presented structure is cost-effective since it only uses conventional printed circuit board (PCB) technology for manufacturing and commercial lossy dielectric material.