Miracle-dz/UniFAR-FTUs huggingface dataset:
From Algorithm to Module: Adaptive and Energy-Efficient Quantization Method for Edge Artificial Intelligence in IoT Society

Next-generation industrial edge artificial intelligence (AI) applications will undoubtedly emerge on energy-efficient, highly-integrated platforms incorporating various sensors, processors, and functional modules. Embedding the data quantization module onto edge AI chips, connecting sensors, processors, and functional modules is critical to achieving adaptive transformation of diverse data representation formats. This paper proposes a novel adaptive and low-power quantization technique and systematically validates its effectiveness from algorithm to hardware module for industrial IoT applications, covering precise navigation for autonomous vehicles and accurate classification utilizing deep neural networks (DNNs). The proposed quantization method merges an adaptive conversion function from floating-point to fixed-point binaries and an adaptive radix-point determination function, ensuring adequate resolution and minimal error loss of the fixed-point inputs to the edge AI modules. The experimental results demonstrate that the quantization error in the proposed quantization technique contributes negligible errors to the navigation solutions of the strapdown inertial navigation system and the DNNs' top-1 and top-5 classification accuracy (on the order of 10<inline-formula><tex-math notation="LaTeX">$^{-8}$</tex-math></inline-formula> and 10<inline-formula><tex-math notation="LaTeX">$^{-7}$</tex-math></inline-formula>). Moreover, a quantization-on-multiplier (QoM) hardware module is designed, synthesized, and routed in accordance with the proposed quantization technique. The simulation results indicate that the QoM's power consumption and area are 0.1 mW and 649.552 <inline-formula><tex-math notation="LaTeX">$\mu \text{m}^{2}$</tex-math></inline-formula>, accounting for 5% and 14.15% of its total energy consumption and area, respectively. With our proposed on-chip quantization technique, the time required to quantize the parameters of DNNs is up to 1142 times shorter than with the existing benchmark off-chip quantization approaches.
OS‐in‐the‐Loop verification for multi‐tasking control software

Embedded control software that controls safety‐critical IoT devices requires systematic and comprehensive verification to ensure safe operation of the device. However, rigorous verification in this domain has not been feasible due to the high complexity of embedded control software, which is characterized by the frequent use of multi‐tasking, interrupts, and periodic alarms. Realizing that two major factors, scalability and exactness, are extremely difficult to achieve at the same time but critical for effective and efficient verification in this domain, this work introduces a domain‐specific compositional OS‐in‐the‐Loop (OiL) verification approach and sets out to push the boundary in achieving both factors. The suggested approach (1) models the behavior of the underlying operating system to limit the search space using the notion of controlled concurrency, (2) performs heterogeneous composition of controllers with the formal OS model to reduce verification complexity, and (3) utilizes state‐of‐the‐art verification techniques for the purpose of comprehensive verification up to a given search depth.
Gain compression and its dependence on output power in quantum dot lasers

The gain compression coefficient was evaluated by applying the frequency modulation/amplitude modulation technique in a distributed feedback InAs/InGaAs quantum dot laser. A strong dependence of the gain compression coefficient on the output power was found. Our analysis of the gain compression within the frame of the modified well-barrier hole burning model reveals that the gain compression coefficient decreases beyond the lasing threshold, which is in a good agreement with the experimental observations.
Consequences of the Pauli exclusion principle for the Bose-Einstein condensation of atoms and excitons

The bosonic atoms used in present day experiments on Bose-Einstein condensation are made up of fermionic electrons and nucleons. In this Letter we demonstrate how the Pauli exclusion principle for these constituents puts an upper limit on the Bose-Einstein-condensed fraction. Detailed numerical results are presented for hydrogen atoms in a cubic volume and for excitons in semiconductors and semiconductor bilayer systems. The resulting condensate depletion scales differently from what one expects for bosons with a repulsive hard-core interaction. At high densities, Pauli exclusion results in significantly more condensate depletion. These results also shed a new light on the low condensed fraction in liquid helium II.
Glycated Soy β-Conglycinin Nanoparticle for Efficient Nanocarrier of Curcumin: Formation Mechanism, Thermal Stability, and Storage Stability

In this study, soy β-conglycinin (7S) was glycated with dextran of different molecular masses (40, 70, 150, 500 kDa) by the dry-heating method to synthesize soy β-conglycinin-dextran (7S-DEX) conjugates. The curcumin (Cur) loaded nanocomplexes were prepared based on 7S-DEX conjugates by a pH-driven self-assemble strategy to enhance the solubility and thermal stability of curcumin. Results showed that the 7S-150 conjugates (glycated from 7S with dextran (150 kDa)) could remain stable in the pH 3.0–pH 8.0 range and during the heat treatment. The results of fluorescence quenching and FT-IR indicated that glycated 7S were combined with curcumin mainly by hydrogen bonding and hydrophobic interaction, and 7S-150 conjugates had higher binding affinity than natural 7S for curcumin. The loading capacity (μg/mg) and encapsulation efficiency (EE%) of 7S-150-Cur were 16.06 μg/mg and 87.51%, respectively, significantly higher than that of 7S-Cur (12.41 μg/mg, 51.15%). The XRD spectrum showed that curcumin was exhibited in an amorphous state within the 7S-150-Cur nanocomplexes. After heating at 65 °C for 30 min, the curcumin retention of the 7S-150-Cur nanocomplexes was about 1.4 times higher than that of free curcumin. The particle size of 7S-150-Cur nanocomplexes was stable (in the range of 10–100 nm) during the long storage time (21 days).
Electron avalanche and surface charging on alumina insulators during pulsed high‐voltage stress

This paper describes a model for insulator surface charging in high‐voltage ceramic vacuum diodes. The model involves electron emission from the insulator‐cathode‐vacuum junction followed by electron avalanches on the insulator surface which leave the wall positively charged. Experiments were performed to measure (i) the triple‐junction (cathode‐vacuum‐insulator interface) emission and its relation to the initiation of the avalanche, (ii) the dynamic current in the avalanche, and (iii) the saturated surface charge resulting from the avalanche. The experimental results were interpreted by computer simulation in terms of the model and were found to be in close agreement with the predictions.
A Review on the Use of Computer Vision and Artificial Intelligence for Fish Recognition, Monitoring, and Management

Computer vision has been applied to fish recognition for at least three decades. With the inception of deep learning techniques in the early 2010s, the use of digital images grew strongly, and this trend is likely to continue. As the number of articles published grows, it becomes harder to keep track of the current state of the art and to determine the best course of action for new studies. In this context, this article characterizes the current state of the art by identifying the main studies on the subject and briefly describing their approach. In contrast with most previous reviews related to technology applied to fish recognition, monitoring, and management, rather than providing a detailed overview of the techniques being proposed, this work focuses heavily on the main challenges and research gaps that still remain. Emphasis is given to prevalent weaknesses that prevent more widespread use of this type of technology in practical operations under real-world conditions. Some possible solutions and potential directions for future research are suggested, as an effort to bring the techniques developed in the academy closer to meeting the requirements found in practice.
A Study on the Factors Influencing the Teaching Effect of Moral and Social Courses in Primary Schools

Taking the influence of various factors on the teaching effect of moral and social courses of primary school students as the research content, a unified examination was conducted on third-grade students from 413 primary schools in Kunming, and 1270 valid questionnaires were obtained from their teachers. A questionnaire was innovatively designed with 52 dimensions, and the data were analyzed using the SPSS big data analysis platform to find the most influential factors in the teaching and learning of moral and social courses and to propose suggestions for improving the teaching effectiveness of moral and social courses.
Kinematic coupling‐based trajectory planning for rotary crane system with double‐pendulum effects and output constraints

When the payload is too large or the hook mass cannot be ignored, the double‐pendulum phenomenon may happen in rotary cranes practical applications. The increase in dynamic complexity makes it more difficult to fast and accurate positioning while suppressing swing during cargo transportation. Moreover, output constraints should be considered in actual crane systems. In this paper, a novel kinematic coupling‐based trajectory planning method is proposed for double‐pendulum rotary cranes with the constraints on angular acceleration and velocity of the boom. The proposed trajectory consists of two parts: a positioning reference component and a swing‐eliminating component. The positioning reference trajectory takes into account the physical constraints of the actuator. The swing‐eliminating trajectory is designed based on the kinematic coupling relationship among the boom luffing, the hook swing and the payload swing. Lyapunov techniques and Barbalat lemma are used for stability analysis. Numerical simulation and real experiments verify the superior control performance and robustness of the proposed control method.
Fingerprinting Smartphones Based on Microphone Characteristics From Environment Affected Recordings

Fingerprinting devices based on unique characteristics of their sensors is an important research direction nowadays due to its immediate impact on non-interactive authentications and no less due to privacy implications. In this work, we investigate smartphone fingerprints obtained from microphone data based on recordings containing human speech, environmental sounds and several live recordings performed outdoors. We record a total of 19,200 samples using distinct devices as well as identical microphones placed on the same device in order to check the limits of the approach. To comply with real-world circumstances, we also consider the presence of several types of noise that is specific to the scenarios which we address, e.g., traffic and market noise at distinct volumes, and may reduce the reliability of the data. We analyze several classification techniques based on traditional machine learning algorithms and more advanced deep learning architectures that are put to test in recognizing devices from the recordings they made. The results indicate that the classical Linear Discriminant classifier and a deep-learning Convolutional Neural Network have comparable success rates while outperforming all the rest of the classifiers.
K-/Ka-Band Shared-Aperture Phased Array With Wide Bandwidth and Wide Beam Coverage for LEO Satellite Communication

A K-/Ka-band shared-aperture endfire phased array antenna is presented in this article. The antenna has the properties of dual wide bandwidths, orthogonal circular polarizations (CPs), wide beam coverage, and high isolation between the K-band and Ka-band channels. In this work, a new array topology is proposed to enhance the design freedom and the periodicity of the antenna array. Then, the filtering structures used to reflect the crossband coupled power also enhance the isolation between the K-band and Ka-band channels. The crossband mutual coupling is reflected and reradiated to generate the wideband CP beams. The high-order parallel plate waveguide (PPW) mode is suppressed to realize the wide CP beam coverage. The working bands at the boresight are 17.7–21.2 and 27.5–31.0 GHz, respectively. The polarizations are right-hand CP (RHCP) in K-band and left-hand CP (LHCP) in Ka-band. The maximal scan angles are ±60°. The axial ratios (ARs) are below 3 dB at boresight and below 5 dB when the beam scans to ±60°. The isolation between the K-band and Ka-band channels is higher than 40 dB.
Land Cover Change Detection With Heterogeneous Remote Sensing Images: Review, Progress, and Perspective

With the fast development of remote sensing platforms and sensors technology, change detection with heterogeneous remote sensing images (Hete-CD) has become an attractive topic in recent years and plays a vital role in land cover change detection for responding to natural disaster emergencies when homogeneous images are unavailable. Although Hete-CD has been developed for about three decades, and various related methods have been developed and applied successfully in practice, a systematic and comprehensive review of the current achievements regarding Hete-CD remains lacking. Therefore, in this article, we first present an overview of Hete-CD in terms of the related literature. Second, the major techniques of Hete-CD are reviewed in terms of publicly available datasets, the taxonomy of major techniques, results, performance, and quantitative evaluation. Then, some classical methods are selected for comparison and discussion. Finally, based on the discussion and literature review, challenges, opportunities, and future directions for Hete-CD are concluded. The review aims to provide a “one-stop-shop” understanding of the problems with the categories of existing approaches, open opportunities and challenges, and potential future directions for Hete-CD.
Determinants of Major Body Morphometric Traits of Khari Goat Kids (Capra hircus L.) in Nawalpur District, Nepal

This study was carried out aiming at studying the non-genetic determinants affecting three major body morphological traits of Khari goats in Nawalparasi, Nepal. Body length, wither height and heart girth at the age of birth, weaning, nine months and fifteen months of 1260 kids born from 1005 does were measured and analyzed using fixed effect Least Square Mixed Model and Maximum Likelihood Computer Program (LSMMML PC-2). Significantly different means of body length, wither height and heart girth were between different sub-classes of non-genetic factors compared using Duncan’s Multiple Range Test (DMRT) computer software. Findings revealed that overall mean wither height of kids ranged from 28.84±0.59 cm at birth to 61.95±1.03 cm at fifteen months, respectively. Similarly, overall mean hearth girth of kids varied from 29.62±0.58 cm at to 65.04±1.17 cm at fifteen months’ age, respectively. Overall mean body length of Khari goat kids was at birth, weaning, nine months and fifteen months’ age was determined 28.09±0.67 cm at birth and reached to 59.96±0.98 cm at fifteen months’ age. Altitude, coat color, kidding season, dam’s parity, dam’s size, sex and birth type of kids were the important sources of variation (p<0.05 to <0.001) with respect to wither height, hearth girth and body length of kids at most of the stages of growth in case Nepalese hill goats. Thus, the results of present study help describe indigenous Khari goat breed using the phenotypic values of morphometric traits such as body length, heart girth and wither height which may be useful to estimate the phenological variations within breed.
Exploring active ingredients of anti-osteoarthritis in raw and wine-processed Dipsaci Radix based on spectrum-effect relationship combined with chemometrics.

ETHNOPHARMACOLOGICAL RELEVANCE Dipsaci Radix (DR) is the dry root of the Dipsacus asper Wall. ex DC. , which has the function of tonifying the liver and kidney, continuing tendons and bones, and regulating blood vessels. However, there are few reports on the main active ingredients. AIM OF THE STUDY This study aimed to find the main active components of DR in the treatment of osteoarthritis (OA) by spectrum-effect relationship and compare the differences between RDR and WDR. MATERIALS AND METHODS Firstly, the high-performance liquid chromatography (HPLC) method was used to establish the fingerprint of DR, and 10 peaks of them were determined by UPLC-Q-TOF/MS. Then, the OA rat model was established by injecting sodium iodoacetate to study the effect of DR on OA. The spectrum-effect relationship was analyzed by grey relational analysis (GRA) and Pearson correlation analysis. RESULTS According to the pharmacological results, compared with the model group, the cartilage score, tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6), and Mankin score of rats in low, medium and high dose groups were decreased, and the therapeutic effect of wine-processed DR tended to be better than raw DR at the same dose. Finally, the active components of DR were preliminarily determined as 4 (loganic acid), 6 (chlorogenic acid), 8 (caffeic acid), 14 (dipsanoside B), 16, and 17 (asperosaponin VI) which had a large correlation in GRA and Pearson correlation analysis. CONCLUSION This study established the spectrum-effect relationship between the raw and wine-processed DR for the first time, which provided a theoretical basis for the study of the pharmacodynamic substance basis of DR before and after processing. This research provided a reference for the subsequent study of DR.
Asteroseismology of 16,000 Kepler Red Giants: Global Oscillation Parameters, Masses, and Radii

The Kepler mission has provided exquisite data to perform an ensemble asteroseismic analysis on evolved stars. In this work we systematically characterize solar-like oscillations and granulation for 16,094 oscillating red giants, using end-of-mission long-cadence data. We produced a homogeneous catalog of the frequency of maximum power (typical uncertainty ), the mean large frequency separation ( ), oscillation amplitude ( ), granulation power ( ), power excess width ( ), seismically derived stellar mass ( ), radius ( ), and thus surface gravity ( dex). Thanks to the large red giant sample, we confirm that red-giant-branch (RGB) and helium-core-burning (HeB) stars collectively differ in the distribution of oscillation amplitude, granulation power, and width of power excess, which is mainly due to the mass difference. The distribution of oscillation amplitudes shows an extremely sharp upper edge at fixed , which might hold clues for understanding the excitation and damping mechanisms of the oscillation modes. We find that both oscillation amplitude and granulation power depend on metallicity, causing a spread of 15% in oscillation amplitudes and a spread of 25% in granulation power from [Fe/H] = −0.7 to 0.5 dex. Our asteroseismic stellar properties can be used as reliable distance indicators and age proxies for mapping and dating galactic stellar populations observed by Kepler. They will also provide an excellent opportunity to test asteroseismology using Gaia parallaxes, and lift degeneracies in deriving atmospheric parameters in large spectroscopic surveys such as APOGEE and LAMOST.
Local Approximations in Renormalizable and Nonrenormalizable Theories. II

The investigations of a previous paper are generalized to two‐point matrix elements. A principle is formulated, which yields unique finite Feynman rules in the renormalizable case, i.e., permits a unique separation of counterterms. For nonrenormalizable theories this principle yields uniqueness up to a ``scaling'' parameter. The results are generalized to a large class of Feynman graphs. For this subset of graphs, field‐theoretical principles do not determine this scaling parameter.
Prediction of Nusselt Number and Flow Rate of Buoyancy Driven Flow Between Vertical Parallel Plates

Literature on buoyancy driven flow in vertical channels have been reviewed in order to investigate formulas for Nusselt number and flow rate, which can he used in fast calculations of temperature rise in electrical apparatuses. The Rayleigh number range spans from fully developed duct flow to isolated plate boundary layer flow; and both uniform heat flux and uniform wall temperature boundary conditions are considered. Several heat transfer formulas are compared, and, for uniform temperature, an improved formula is presented that indicates the existence of an optimum plate separation. Flow rate formulas are proposed based on asymptotic estimates and adaptation to data available in the literature. Based on the flow rate formulas, the influence on flow rate of Rayleigh number and plate separation is discussed.
Detection of Hand Poses with a Single-Channel Optical Fiber Force Myography Sensor: A Proof-of-Concept Study

Force myography (FMG) detects hand gestures based on muscular contractions, featuring as an alternative to surface electromyography. However, typical FMG systems rely on spatially-distributed arrays of force-sensing resistors to resolve ambiguities. The aim of this proof-of-concept study is to develop a method for identifying hand poses from the static and dynamic components of FMG waveforms based on a compact, single-channel optical fiber sensor. As the user performs a gesture, a micro-bending transducer positioned on the belly of the forearm muscles registers the dynamic optical signals resulting from the exerted forces. A Raspberry Pi 3 minicomputer performs data acquisition and processing. Then, convolutional neural networks correlate the FMG waveforms with the target postures, yielding a classification accuracy of (93.98 ± 1.54)% for eight postures, based on the interrogation of a single fiber transducer.
Bounds on stringy quantum gravity from low energy existing data

We show that existing low energy experiments, searching for the breaking of local Lorentz invariance, set bounds upon string theory inspired quantum gravity models that induce corrections to the propagation of fields. Using the standard observer Lorentz transformations in the D-particle recoil model we find $Mg~1.2\ifmmode\times\else\texttimes\fi{}{10}^{5}{M}_{P}$ and $vl~2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}27}c$ for the mass and recoil speed of the D particle, respectively. These bounds are $\ensuremath{\sim}{10}^{8}$ times stronger than the latest astrophysical bounds. These results indicate that the stringy scenario for modified dispersion relations is as vulnerable to these types of tests as the loop quantum gravity schemes.
Healthcare scenario: a new task scheduling algorithm in cloud computing environment

Makespan and cost are the major factors in the current scenario and they generally upgrade the results to optimize the upcoming task processing by implementing the scheduling within the specified cloud platform. A new proposed agenda is being considered for a health care system to make the world healthier. The paper is designed to identify prior work as a health evaluator for the end user and act accordingly. It also satisfies the end user by providing demanded results and can establish trust between the system and the customer within a global era. By analyzing the COVID-pandemic situation in the digital world, things should be implemented in conjunction with healthcare and technology to serve things better. The proposed algorithm works on priority basis by analyzing the current patient condition and then implemented in CloudSim Toolkit. As per the results, the proposed steps are performing 50-70% better in terms of makespan and cost. Notable optimization has been accomplished by the proposed healthcare evaluator.