Miracle-dz/UniFAR-FTUs huggingface dataset:
Reference Standard for Digital Infrared Thermography of the Surface Temperature of the Lower Limbs

Digital infrared thermographic imaging (DITI) is a supplementary diagnostic technique to visualize the surface temperature of the human body. However, there is currently no reference standard for the lower limbs for accurate diagnosis. In this study, we performed DITI on the lower limbs of 905 healthy Korean volunteers (411 males and 494 females aged between 20 and 69 years) to obtain reference standard data. Thermography was conducted on the front, back, lateral sides, and sole area, and 188 regions of interest (ROIs) were analyzed. Additionally, subgroup analysis was conducted according to the proximity of ROIs, sex, and age groups. The mean temperatures of ROIs ranged from 24.60 ± 5.06 to 28.75 ± 5.76 °C and the absolute value of the temperature difference between both sides reached up to 1.06 ± 2.75 °C. According to subgroup analysis, the sole area had a significantly lower temperature than any other areas, men had higher temperatures than women, and the elderly had higher temperatures than the young adults except for the 20s age group (p < 0.001, respectively). This result could be used as a foundation for the establishment of a reference standard for DITI. Practical patient DITI can be accurately interpreted using these data, and it can serve as a basis for further scientific research.
Target high precision horizontal region detection based on improved faster R-CNN

Aiming at the multi-scale, multi-directional and deformation of targets in remote sensing images, a Fast R-CNN algorithm with deformable convolution is proposed in this paper, which can significantly improve the detection accuracy of ship targets and shorten the processing time.According to the characteristics of large aspect ratio of ships, the size and ratio of anchor frame are adjusted by the K-means clustering method , so that the improved algorithm is more suitable for detecting approximately vertical or horizontal objects, and can obtain high-precision horizontal region detection of ship targets.
Broadband measurements of the acoustic backscatter cross section of sand particles in suspension

A method using a broadband transducer to measure the acoustic backscatter cross section of suspended sand particles is investigated. The frequencies used range from 1.3 to 2.8 MHz, and the sand sizes from 100‐ to 350‐μm diameter. The measurements are made in the transducer near field. The measured form factor is compared with the theoretical result for the movable rigid sphere model, and with previous narrow‐band measurements.
Parametric Lyapunov function approach to H/sub 2/ analysis and control of linear parameter-dependent systems

The problems of H/sub 2/ analysis and control synthesis for linear continuous-time parameter-dependent systems are addressed. The admissible values of the parameters and their rates of variation are assumed to belong to a given polytope. Linear matrix inequality-based methods of H/sub 2/ performance analysis and state feedback control are developed. Both the design of gain-scheduled and robust controllers are addressed. The proposed methods have the feature that stability as well as the guaranteed H/sub 2/ performance cost are based on a parameter-dependent Lyapunov function which is quadratic on the system parameters. The controller implementation does not require online knowledge of the rate of variation of the parameters
Comparing Direct Measurements and Three-Dimensional (3D) Scans for Evaluating Facial Soft Tissue

The inspection of patients’ soft tissues and the effects of various dental procedures on their facial physiognomy are quite challenging. To minimise discomfort and simplify the process of manual measuring, we performed facial scanning and computer measurement of experimentally determined demarcation lines. Images were acquired using a low-cost 3D scanner. Two consecutive scans were obtained from 39 participants, to test the scanner repeatability. An additional ten persons were scanned before and after forward movement of the mandible (predicted treatment outcome). Sensor technology that combines red, green, and blue (RGB) data with depth information (RGBD) integration was used for merging frames into a 3D object. For proper comparison, the resulting images were registered together, which was performed with ICP (Iterative Closest Point)-based techniques. Measurements on 3D images were performed using the exact distance algorithm. One operator measured the same demarcation lines directly on participants; repeatability was tested (intra-class correlations). The results showed that the 3D face scans were reproducible with high accuracy (mean difference between repeated scans <1%); the actual measurements were repeatable to some extent (excellent only for the tragus-pogonion demarcation line); computational measurements were accurate, repeatable, and comparable to the actual measurements. Three dimensional (3D) facial scans can be used as a faster, more comfortable for patients, and more accurate technique to detect and quantify changes in facial soft tissue resulting from various dental procedures.
Few-Shot Class-Incremental SAR Target Recognition Based on Hierarchical Embedding and Incremental Evolutionary Network

It is difficult to realize effective synthetic aperture radar (SAR) automatic target recognition (ATR) in open scenarios because the ATR model cannot continuously learn from new classes with limited training samples. When adding new classes to the previously trained model, the capability of recognizing old classes may lose due to severe overfitting. To tackle this problem, a few-shot class-incremental SAR ATR method, namely, hierarchical embedding and incremental evolutionary network (HEIEN), is proposed in this article. First, a hierarchical embedding network and a hybrid distance-based classifier are constructed for basic feature extraction and classification. Then, in order to obtain more accurate decision boundaries, an adaptive class-incremental learning (ACIL) module is designed to adjust the weights of classifiers in all tasks by collecting context information from the past to the present. Finally, a pseudo-incremental training strategy is designed to enable effective model training with only a few samples. Experimental results on the moving and stationary target acquisition and recognition (MSTAR) benchmark data set have illustrated that HEIEN performs well with remarkable advantages in few-shot class-incremental SAR ATR tasks.
Intraday trading of cryptocurrencies using polynomial auto regression

This research attempts to fit a polynomial auto regression (PAR) model to intraday price data of four major cryptocurrencies and convert the model into a real-time profitable automated trading system. A PAR model was constructed to fit cryptocurrencies' behavior and to attempt to predict their short-term trends and trade them profitably. We used machine learning (ML) procedures enabling our system to train using minutes' data for six months and perform actual trading and reporting for the next six months. Results have shown that our system has dramatically outperformed the naive buy and hold (B & H) strategy for all four examined cryptocurrencies. Results show that our system's best performances were achieved trading Ethereum and Bitcoin and worse trading Cardano. The highest net profit (NP) for Bitcoin trades was 15.58%, achieved by using 67 minutes bars to form the prediction model, compared to −44.8% for the B & H strategy. Trading Ethereum, the system generated 16.98% NP, compared to −33.6% for the B & H strategy, 61 minutes bars. Moreover, the highest NPs achieved trading Binance Coin (BNB) and Cardano were 9.33% and 4.26%, compared to 0.28% and −41.8% for the B & H strategy, respectively. Furthermore, the system better predicted Ethereum and Cardano uptrends than downtrends while it better predicted Bitcoin and BNB downtrends than uptrends.
Fractal dynamics of spin glasses

The fractal structure of the free energy surface of a spin glass is used for a phenomenological description of the continuous hierarchy of relaxation times and the slow relaxation of the spin glass order parameter at long times. The quasi-power-like and logarithmic reduction of the order parameter has been obtained on the bases of the scaling properties of potential barriers of the free energy surface. The dynamical nature of the spin glass state is discussed.
A search for low-luminosity pulsars.

The results of Phase I of the Princeton-NRAO pulsar survey, carried out at 390 MHz using the 92 m telescope at Green Bank, West Virginia, are presented. This search discovered 34 new pulsars and detected 49 previously known ones. As has been the case with all previous surveys, no pulsars with intrinsic luminosities less than 0.3 mJy/sq kpc have been found. Because of the high sensitivity of the survey and its coverage of nearly 2 sr of sky, the present results imply that such low-luminosity pulsars do not constitute a large portion of the total active pulsar population in the Galaxy. Also in common with previous surveys, the sensitivity of this one deteriorates rather quickly for pulse periods less than a few tenths of a second. The extent to which this loss of sensitivity has biased the period distribution of known pulsars is discussed. 14 references.
Eliminating Obstacles in TPM Implimentation In Sugarmill Industry

In the dynamic scenario of technology, many technological innovations are available to contribute in the analysis of Equipment Efficiency, minimized input v/s optimized output, minimizing the overall consumption, effective use of machineries and finally increase in production rate by expenditure and consumption of sources. Since the starting of technological era, Scientists/ Researchers have put mammoth efforts to increase production rate. To embark with, many small inadequacies of equipments and machines can lead to the huge losses in small to medium scale industries. Implementation of TPM in various industries has contributed its effective role but not much work available with small to medium scale sugar mill industries in India.In Ajnala Cooperative Sugar Mill, Amritsar, the author has contributed that the mill management avoid doing the changes with traditional approaches of productivity for example changes in setup and maintenance scheduling. So to remove the obstacles, the author has suggested several steps to bring the minimum but necessary changes in maintenance and repairs. The author made an attempt to increase the Overall Equipment Efficiency and to decrease the high rejection rate, downtime, and setup time to compete with others similar industries by applying Total Productive Maintenance in the small scale industry by eliminating the upcoming obstacles successfully.
Internal multiple prediction and removal using marchenko autofocusing and seismic interferometry

Standard seismic processing steps such as velocity analysis and reverse time migration (imaging) usually assume that all reflections are primaries: Multiples represent a source of coherent noise and must be suppressed to avoid imaging artifacts. Many suppression methods are relatively ineffective for internal multiples. We show how to predict and remove internal multiples using Marchenko autofocusing and seismic interferometry. We first show how internal multiples can theoretically be reconstructed in convolutional interferometry by combining purely reflected, up- and downgoing Green’s functions from virtual sources in the subsurface. We then generate the relevant up- and downgoing wavefields at virtual sources along discrete subsurface boundaries using autofocusing. Then, we convolve purely scattered components of up- and downgoing Green’s functions to reconstruct only the internal multiple field, which is adaptively subtracted from the measured data. Crucially, this is all possible without detailed modeled information about the earth’s subsurface. The method only requires surface reflection data and estimates of direct (nonreflected) arrivals between subsurface virtual sources and the acquisition surface. The method is demostrated on a stratified synclinal model and shown to be particularly robust against errors in the reference velocity model used.
An Improved 2-D Subdomain Method Toward Electromagnetic-Performance Analysis of Line-Start Permanent Magnet Synchronous Motor

The 2-D subdomain method (SDM) has proven to be a time-efficient approach suited for determining the magnetic field of permanent magnet synchronous motor (PMSM); however, further application of this method into the field analysis for the line-start PMSM (LSPMSM) is limited by its natural defects, including 1) inability to consider the saturation effect of iron material and 2) failure to deal with the rotor eddy currents allowing self-start. In this work, the step-by-step or iterative numerical calculation using the finite difference method (FDM) is embedded into the execution of conventional 2-D SDM, through which an enhanced version addressing all issues as stated above is obtained. The improved SDM avoids the limitations of the pure analytical method and possesses higher calculation efficiency than that of the pure numerical method. The reliability of the presented method is validated by the finite element analysis (FEA) and tests.
Health Monitoring Using Smart Home Technologies: Scoping Review

Background The Internet of Things (IoT) has become integrated into everyday life, with devices becoming permanent fixtures in many homes. As countries face increasing pressure on their health care systems, smart home technologies have the potential to support population health through continuous behavioral monitoring. Objective This scoping review aims to provide insight into this evolving field of research by surveying the current technologies and applications for in-home health monitoring. Methods Peer-reviewed papers from 2008 to 2021 related to smart home technologies for health care were extracted from 4 databases (PubMed, Scopus, ScienceDirect, and CINAHL); 49 papers met the inclusion criteria and were analyzed. Results Most of the studies were from Europe and North America. The largest proportion of the studies were proof of concept or pilot studies. Approximately 78% (38/49) of the studies used real human participants, most of whom were older females. Demographic data were often missing. Nearly 60% (29/49) of the studies reported on the health status of the participants. Results were primarily reported in engineering and technology journals. Almost 62% (30/49) of the studies used passive infrared sensors to report on motion detection where data were primarily binary. There were numerous data analysis, management, and machine learning techniques employed. The primary challenges reported by authors were differentiating between multiple participants in a single space, technology interoperability, and data security and privacy. Conclusions This scoping review synthesizes the current state of research on smart home technologies for health care. We were able to identify multiple trends and knowledge gaps—in particular, the lack of collaboration across disciplines. Technological development dominates over the human-centric part of the equation. During the preparation of this scoping review, we noted that the health care research papers lacked a concrete definition of a smart home, and based on the available evidence and the identified gaps, we propose a new definition for a smart home for health care. Smart home technology is growing rapidly, and interdisciplinary approaches will be needed to ensure integration into the health sector.
Iterative Edge Enhancing Framework for Building Change Detection

The building change detection (BCD) task serves urban planning by monitoring land use. However, due to the complexity of remote-sensing images and high foreground–background similarity, it leads to inaccurate detection of building edge regions. Existing methods deal with this problem by fusing features of different layers. But the fusing operation cannot separate details information from the overall information of buildings, resulting in inaccurate detection of building edge area. To address the above challenges, we propose an iterative edge-enhancing framework (IEEF). The IEEF alleviates the building edge detection difficulty by densely implementing a detail semantic enhancement module (DSEM) in the decoding part. This module takes differential features between adjacent scales to explicitly represent the building edge information. Simultaneously, to deal with the class imbalance problem, a Density-Guided Sampling method dedicated to change detection is proposed to increase the proportion of positive samples during training. Our proposed method achieves state-of-the-art performance on the LEarning, VIsion and Remote sensing laboratory building Change Detection (LEVIR-CD) dataset and the Wuhan University (WHU) dataset and obtains accurate changed building edges.
On the use of the magnetic vector potential in the nodal and edge finite element analysis of 3D magnetostatic problems

An overview of various finite element techniques based on the magnetic vector potential for the solution of three-dimensional magnetostatic problems is presented. If nodal finite elements are used for the approximation of the vector potential, a lack of gauging results in an ill-conditioned system. The implicit enforcement of the Coulomb gauge dramatically improves the numerical stability, but the normal component of the vector potential must be allowed to be discontinuous on iron/air interfaces. If the vector potential is is interpolated with the aid of edge finite elements and no gauge is enforced, a singular system results. It can be solved efficiently by conjugate gradient methods, provided care is taken to ensure that the current density is divergence free. Finally, if a tree-cotree gauging of the vector potential is introduced, the numerical stability depends on how the tree is selected with no obvious optimal choice available.
Modelling forces of infection by using monotone local polynomials

Summary. On the basis of serological data from prevalence studies of rubella, mumps and hepatitis A, the paper describes a flexible local maximum likelihood method for the estimation of the rate at which susceptible individuals acquire infection at different ages. In contrast with parametric models that have been used before in the literature, the local polynomial likelihood method allows this age‐dependent force of infection to be modelled without making any assumptions about the parametric structure. Moreover, this method allows for simultaneous nonparametric estimation of age‐specific incidence and prevalence. Unconstrained models may lead to negative estimates for the force of infection at certain ages. To overcome this problem and to guarantee maximal flexibility, the local smoother can be constrained to be monotone. It turns out that different parametric and nonparametric estimates of the force of infection can exhibit considerably different qualitative features like location and the number of maxima, emphasizing the importance of a well‐chosen flexible statistical model.
Caseins: Versatility of Their Micellar Organization in Relation to the Functional and Nutritional Properties of Milk

The milk of mammals is a complex fluid mixture of various proteins, minerals, lipids, and other micronutrients that play a critical role in providing nutrition and immunity to newborns. Casein proteins together with calcium phosphate form large colloidal particles, called casein micelles. Caseins and their micelles have received great scientific interest, but their versatility and role in the functional and nutritional properties of milk from different animal species are not fully understood. Caseins belong to a class of proteins that exhibit open and flexible conformations. Here, we discuss the key features that maintain the structures of the protein sequences in four selected animal species: cow, camel, human, and African elephant. The primary sequences of these proteins and their posttranslational modifications (phosphorylation and glycosylation) that determine their secondary structures have distinctively evolved in these different animal species, leading to differences in their structural, functional, and nutritional properties. The variability in the structures of milk caseins influence the properties of their dairy products, such as cheese and yogurt, as well as their digestibility and allergic properties. Such differences are beneficial to the development of different functionally improved casein molecules with variable biological and industrial utilities.
Continuous-time random-walk simulation of H~2 formation on interstellar grains

The formation of molecular hydrogen via the recombination of hydrogen atoms on interstellar grain surfaces has been investigated anew. A detailed Monte Carlo procedure known as the continuous-time random-walk method has been used. This Monte Carlo approach has two advantages over the stochastic master equation method: it treats random walk on a surface correctly, and it can easily be used for inhomogeneous surfaces. The recombination efficiency for H2 formation as a function of surface temperature and grain size has been calculated for a variety of grain surfaces with a flux of hydrogen atoms repre- sentative of diffuse interstellar clouds. The surfaces studied include homogeneous olivine and amorphous carbon, characterized by single energies for the diffusion barrier and binding energy of H atoms, inhomogeneous versions of these two surfaces with distributions of H-atom diffusion barriers and binding energies, and a variety of mixed surfaces of olivine and carbon. For the homogeneous surfaces, we confirm that the temperature range for efficient formation of H2 is very small. At temperatures near peak efficiency, there is little dependence on grain size. At temperatures higher than those of peak efficiency, the Monte Carlo procedure exhibits smaller efficiencies for molecular hydrogen formation than the master equation method in the limit of large grain sizes. For various types of inhomogeneous and mixed surfaces, the major effect we find is an increase in the temperature range over which the efficiency of molecular hydrogen formation is high. Efficient formation of H2 in diffuse interstellar clouds now seems possible with inhomogeneous grains.
Coupling and radiation through "V-shaped" narrow slots using the FDTD method

A "V-shaped" slot in the narrow wall of a rectangular waveguide is presented as a coupling element. Three- and four-port coupler parameters and the radiation characteristics of the slot were investigated using the finite-difference time-domain (FDTD) method. Two approximate numerical-analytical procedures are proposed to reduce the computer requirements and predict multislot device characteristics. A clear improvement in four-port coupler parameters was observed following the incorporation of a thin dielectric layer.
Resolution of Seismic-Moment Tensor Inversions from a Single Array of Receivers

Moment tensor inversion techniques are widely used in global and regional seismic applications. When the ray-path trajectories are confined in a single plane (e.g., in isotropic media using a vertical array of receivers or an array that deviates from the vertical in the direction of wave propagation) only five out of six elements of the moment tensor are resolvable. This study investigates the resolvability of the complete seismic moment tensor for single-well monitoring geometries. By analyzing the resolution matrix, we demonstrate that a correct representation of the five resolvable elements of the moment tensor is only possible in a local reference system. For a vertical array of receivers, a suitable choice of condition number can assist the acquisition design. For a non-vertical array, our numerical modeling experi- ments suggest that the required distance and orientation of receivers for a full moment tensor inversion can be satisfied in a deviated well. In this case, information embedded in the condition number is valuable for determining the required distribution of receivers along the well.