Miracle-dz/UniFAR-FTUs huggingface dataset:
Multitarget Enumeration and Localization in Distributed MIMO Radar Based on Energy Modeling and Compressive Sensing

Target localization is one of the most important research topics in the field of radar signal processing. In this article, the problem of multitarget enumeration and localization in the distributed multiple-input multiple-output radar with noncoherent processing mode is investigated. We first analyze the theoretical bound of the multitarget localization accuracy under the discrete time signal model and the Swerling 1 target model. It is determined by the Cram$\acute{\text{e}}$r–Rao lower bound at a low signal-to-noise ratio (SNR) and the sampling lower bound when the SNR is high. Furthermore, an innovative multitarget enumeration and localization scheme is developed, which is based on the energy modeling of the multiple transmitter–receiver paths and the compressive sensing theory. To solve the sparse vector recovery issue, we design a lightweight iterative greedy pursuit algorithm including the similarity evaluation strategy. In addition, an iterative-based target position refinement process is designed to alleviate the off-grid problem caused by the spatial discretization. The proposal utilizes the samples of the raw signals and belongs to the category of the direct localization. Nevertheless, it has significantly higher computational efficiency and lower data communication burden than the conventional direct localization methods, while avoiding the complex data association encountered by the indirect localization methods. Finally, the simulation results validate the effectiveness and robustness of the proposed method.
INDIAN MOBILE BANKING IN POST COVID-19: AN ANALYTICAL STUDY AND GRATIFICATION FROM THE ASPECT OF KANO MODEL

The purpose of the present research paper is to understand the research questions related to M-banking. It is the time call to take up Virtual Banking (VB) with Zero Contact Banking (ZCB) as a preventive measure to COVID-19. The study also admits the comparative analysis on the gratification of M-banking users considering factors/attributes of the Kano Model. The researcher has undertaken Integrative Approach (IA) for both, related to literature reviewed and survey so far observed. Both primary data through well-structured questionnaires from 900 M-banking users of SBI, HDFC, and Citi Bank (300 from each) and secondary data from published sources have been cantered and cited to understand the syntactic research gap. The researcher has followed Stratified Random Sampling for sample banks considering the date of establishment, volume and value of M-banking transactions, number of employees, and Convenient Random Sampling for M-banking users, to make the sample representative. The objectives were studied thoroughly and hypotheses were tested in SPSS. The researcher has used Kolmogorov-Smirnov (D-Statistic) and Shapiro-Wilk test (W-Statistic) to test data normality, Cronbachs’ Alpha to test Data Reliability, Descriptive Statistics i.e. frequency and per cent count to describe data and Chi-square to measure significant associations and differences if any. The researcher has drawn an epilogue purely on the basis of data collection and analysis. The researcher has conducted Pearson’s Product Movement Correlation, to suggest a correlation on Y-intercept Model to show an association between volume and value of M-banking transactions of SBI, HDFC, and Citi Bank and suggested a model fit to regression equation. This paper gives a unique insight into KANO model.
Boundary Element Analysis of Systems Using Interval Methods

In engineering, most governing partial differential equations of physical systems are solved using finite element or finite difference methods. Applications of interval methods have been explored in finite element analysis to model systems with uncertainty in parameters and to account for the impact truncation error on solutions. An alternative to finite element analysis is boundary element method. The boundary element method uses singular functions to reduce the dimension of the domain by transforming the domain variables to variables on the boundaries. In this work, new methods using interval variables are developed to enhance boundary element method for considering impreciseness such as uncertain boundary conditions, truncation errors, integration errors and discretization errors. Exemplars are presented to illustrate the effectiveness and potential of interval approach in boundary element method analysis. Keyword: boundary element method, interval analysis, truncation error, discretization errors
Indomethacin: Effect of Diffusionless Crystal Growth on Thermal Stability during Long-Term Storage

Differential scanning calorimetry and Raman spectroscopy were used to study the nonisothermal and isothermal crystallization behavior of amorphous indomethacin powders (with particle sizes ranging from 50 to 1000 µm) and their dependence on long-term storage conditions, either 0–100 days stored freely at laboratory ambient temperatures and humidity or placed in a desiccator at 10 °C. Whereas the γ-form polymorph always dominated, the accelerated formation of the α-form was observed in situations of heightened mobility (higher temperature and heating rate), increased amounts of mechanically induced defects, and prolonged free-surface nucleation. A complex crystallization behavior with two separated crystal growth modes (originating from either the mechanical defects or the free surface) was identified both isothermally and nonisothermally. The diffusionless glass–crystal (GC) crystal growth was found to proceed during the long-term storage at 10 °C and zero humidity, at the rate of ~100 µm of the γ-form surface crystalline layer being formed in 100 days. Storage at the laboratory temperature (still below the glass transition temperature) and humidity led only to a negligible/nondetectable GC growth for the fine indomethacin powders (particle size below ~150 µm), indicating a marked suppression of GC growth by the high density of mechanical defects under these conditions. The freely stored bulk material with no mechanical damage and a smooth surface exhibited zero traces of GC growth (as confirmed by microscopy) after >150 days of storage. The accuracy of the kinetic predictions of the indomethacin crystallization behavior was rather poor due to the combined influences of the mechanical defects, competing nucleation, and crystal growth processes of the two polymorphic phases as well as the GC growth complex dependence on the storage conditions within the vicinity of the glass transition temperature. Performing paired isothermal and nonisothermal kinetic measurements is thus highly recommended in macroscopic crystallization studies of drugs with similarly complicated crystal growth behaviors.
Wideband 120-GHz CMOS I/Q Transmitter With Suppressed IMRR and LOFT for Wireless Short-Range High-Speed 6G IoT Applications

In this study, a wideband 120-GHz I/Q transmitter with suppressed image rejection ratio (IMRR) and LO feed through (LOFT) is presented using 40-nm complementary metal oxide semiconductor technology. For the up-conversion mixer, an NMOS/PMOS pair with resistive feedback is used during the transconductance stage to increase the input bandwidth with gain boosting, and a novel switching core without LO-RF coupling is used to suppress the LOFT effect. For the quadrature injection locked tripler, an I/Q calibration circuit is inserted to minimize the I/Q mismatch; accordingly, the measured IMRR is greatly improved. The peak conversion gain of the proposed transmitter was 10.8 dB, and the 3-dB gain bandwidth was 20 GHz. The measured IMD2 and IMD3 were above 40 dBc. Moreover, the IMRR was measured as 43.1 dBc, applying I/Q calibration. The measured LOFT was 33.7 dBc. The data rate of the proposed transmitter was measured up to 20 Gbps and at a distance of 5 cm. Subsequently, the error vector magnitudes were 13.4 dB for QPSK and −19.1 dB for 16-QAM modulation. It is expected that such wireless high-speed communication can be applied to wireless short-range high-speed 6G IoT applications.
Rapid Controllable Damper Design for Complex Structures with a Hybrid Reduced-Order Modeling/Simulation Approach

AbstractEvaluating controllable damping designs typically requires simulation of the resulting inherently nonlinear closed-loop system because linear design strategies cannot always be reliably used. These analyses typically require many simulations, each a function evaluation in a parameter study or optimization. For complex structural models, these simulations can require significant computational resources. Further, complex structural models requiring repeated solutions of high-order Riccati equations for each function evaluation further exacerbate the computational burden. This paper demonstrates that a reduced-order model for designing the control strategy, resulting in a low-order control law, coupled with the full model of the original system, falls in the class of systems that are mostly linear but with very localized nonlinearities. For such systems, the authors have previously developed an approach that reduces the equations of motion to a low-order nonlinear Volterra integral equation that can .
A visual framework for the study of cardiac motion

A visual framework is presented to solve the problem of left ventricle motion using cardiac image time sequences. A method for the estimation of the displacement field of the left ventricle boundary is proposed. Physical constraints, such as spatial smoothness of the displacement field and shape correspondence, are studied. The information contained in the estimated motion field is rendered explicit so that it can be utilized by medical experts (or for high level symbolic processing). With this aim in mind, a segmentation procedure of the left ventricle outline into line segments with homogeneous motion and deformation features is developed. The application of the method in X-ray cardiac imaging is illustrated. <<ETX>>
Resveratrol‐Induced Suppression of C‐type Natriuretic Peptide Associates With Increased Vertebral Bone Density in Postmenopausal Women

C‐type natriuretic peptide (CNP) is a paracrine growth factor essential in driving endochondral bone growth in mammals including humans. Despite evidence from animal experiments and tissues that CNP signaling stimulates osteoblast proliferation and osteoclast activity, whether CNP participates in bone remodeling in the mature skeleton is unknown. Using stored plasma samples from a previous randomized controlled clinical trial (RESHAW) of resveratrol supplementation in postmenopausal women exhibiting mild osteopenia, we have studied changes in plasma aminoterminal proCNP (NTproCNP) and concurrent change in bone turnover markers of formation (osteocalcin [OC] and alkaline phosphatase [ALP]) and resorption (C‐terminal telopeptide type 1 collagen [CTX]) with bone mineral density (BMD) over a 2‐year period of study in 125 subjects. In year one, subjects received placebo or resveratrol, switching to resveratrol or placebo, respectively, in year two. Across all time points, there were no significant associations of NTproCNP with CTX, ALP, or OC. During year one, plasma NTproCNP declined significantly in both groups. In the crossover comparison, analysis of change within individuals showed that, compared with placebo, NTproCNP declined after resveratrol (p = 0.011) and ALP increased (p = 0.008), whereas CTX and OC were unchanged. Inverse association of NTproCNP (r = −0.31; p = 0.025) and positive association of OC (r = 0.32, p = 0.022) with BMD at the lumbar spine were identified after resveratrol but not found after placebo. Decline in NTproCNP was independently associated with resveratrol treatment. This is the first evidence that CNP is modulated during a period of increasing BMD in postmenopausal women. Further study of NTproCNP and associations with drivers of bone formation or resorption can be expected to clarify CNP's role during other interventions directed to bone health in adults. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
Comparative study of turbulence models on highly constricted plasma cutting arc

Plasma cutting arc characteristics are investigated for different turbulence models, i.e. the Reynolds stress model (RSM), the k–ϵ model and its variants, the renormalization group (RNG) k–ϵ model, the RNG k–ϵ model taking into account the low Reynolds number effect and the realizable k–ϵ model. The results of the RSM and the RNG k–ϵ model taking into account the low Reynolds number effect are in reasonable agreement with experiment. They both predict very close voltage, shock wave location and temperature variation along the axis to experiment. On the other hand, the other three models overestimate the turbulence effects and predict much lower velocity and temperature, especially the standard k–ϵ model, which predicts that the temperature is about 10 000 K lower than the experiment in certain plasma jet regions.
Emerging Technology for Healthy Lifestyle of the Middle-Age and Elderly: A Scoping Review

Background: Emerging technology research focusing on promoting healthy lifestyles for the middle-aged and elderly is paramount in recent literature. However, limited evidence is available for the middle-aged population. This paper reviews how emerging technologies can help in promoting a healthy lifestyle for the middle-aged and elderly. Methods: A scoping literature review method was employed. Articles were extracted from online databases published within 2010–2021. Overall, 3,152 articles related to the topic were obtained and 2979 articles were archived via different search procedures. Moreover, 173 articles that met the inclusion criteria underwent qualitative synthesize for conclusive inferences. Results: Most studies focused on people aged 60 and up, leaving the middle-aged population under-studied and unprepared to age. Older adults have high technology anxiety and resistance to change. Limited studies are available to support technology-based healthy lifestyle promotion for middle-aged people. The emerging technologies that are useful in promoting healthy lifestyle behavior among middle-aged people include: robotics, virtual reality, wearables, artificial intelligence, smart textiles, as well as centralized health information systems. Conclusion: This review sets as a pace-setter for future research on how emerging technologies can aid in the development of healthy lifestyles for the middle-aged and elderly population, allowing them to live a quality life as they age.
A Lattice-Boltzmann Model for Visco-Elasticity

The classical lattice-Boltzmann scheme is extended in an attempt to represent visco-elastic fluids in two dimensions. At each lattice site, two new quantities are added. A suitable coupling of these quantities with the viscous stress tensor leads to a nonzero shear modulus and visco-elastic effects. A Chapman–Enskog expansion gives us the equilibrium populations and conditions for isotropy of the model. A finite wave vector analysis is needed to study the relaxation of sound waves and to determine the dependence of the transport coefficients upon the frequency.
Unified particle simulation technique for the plasma bulk and the cathode sheath of a dc glow discharge

The unified particle simulation of the entire glow discharge including plasma bulk and electrode sheaths suffers from the bad representation of particles in the cathode fall and/or from expensive computing time. To improve the efficiency and reliability of such simulations we develop a splitting procedure for the simulation particles that increases the sampling rate in critical phase space regions. The technique is demonstrated with the help of a simplified model of a dc glow discharge. Simulation particles representing ions and electrons are traced from electrode to electrode by moving the particles in self‐consistent fields. For comparison, the same model of the discharge is analyzed in the framework of transport equations. To improve the spatial density profiles of the macroscopic equations, we accounted for nonlocal effects by adjusting the Townsend ionization coefficient with the help of the particle simulation.
Binary Magnetic Structures in HoEr

The magnetic structure of a single crystal of the rare earth random alloy Ho50%Er50% has been investigated by elastic neutron diffraction measurements in the temperature range 120-10 K. Three distinct magnetic phases are indentified below the N? el temperature of 104 K. The high- temperature phase observed between 104 K and 47.5 K is a binary magnetic structure where the holmium and erbium moments belong to different modulated c-axis spirals. The intermediate-temperature phase between 47.5 K and 35 K is a simple basal plane spiral. Below 35 K, the measurements suggest a ferrimagnetic stucture in which the holmium and erbium moments are indistinguishable and form a conical spiral with a half-cone angle of 20?
Investigation of Paraoxonase-1 Genotype and Enzyme-Kinetic Parameters in the Context of Cognitive Impairment in Parkinson’s Disease

Cognitive impairment is a common non-motor symptom of Parkinson’s disease (PD), which often progresses to PD dementia. PD patients with and without dementia may differ in certain biochemical parameters, which could thus be used as biomarkers for PD dementia. The enzyme paraoxonase 1 (PON1) has previously been investigated as a potential biomarker in the context of other types of dementia. In a cohort of PD patients, we compared a group of 89 patients with cognitive impairment with a group of 118 patients with normal cognition. We determined the kinetic parameters Km and Vmax for PON1 for the reaction with dihydrocoumarin and the genotype of four single nucleotide polymorphisms in PON1. We found that no genotype or kinetic parameter correlated significantly with cognitive impairment in PD patients. However, we observed associations between PON1 rs662 and PON1 Km (p < 10−10), between PON1 rs662 and PON1 Vmax (p = 9.33 × 10−7), and between PON1 rs705379 and PON1 Vmax (p = 2.21 × 10−10). The present study is novel in three main aspects. (1) It is the first study to investigate associations between the PON1 genotype and enzyme kinetics in a large number of subjects. (2) It is the first study to report kinetic parameters of PON1 in a large number of subjects and to use time-concentration progress curves instead of initial velocities to determine Km and Vmax in a clinical context. (3) It is also the first study to calculate enzyme-kinetic parameters in a clinical context with a new algorithm for data point removal from progress curves, dubbed iFIT. Although our results suggest that in the context of PD, there is no clinically useful correlation between cognitive status on the one hand and PON1 genetic and enzyme-kinetic parameters on the other hand, this should not discourage future investigation into PON1’s potential associations with other types of dementia.
Surface plasmon resonance biosensors for detection of foodborne pathogens and toxins

In the last decade surface plasmon resonance (SPR) biosensors have made great strides both in terms of technology and its applications. SPR biosensors have become a central tool for study of molecular interactions and have been widely used for detection of chemical and biological analytes. Food analysis belongs to major areas of potential applications of SPR biosensors. Therefore, numerous SPR biosensors for detection of analytes implicated in food safety (e.g. pathogens, toxins, drug residues, vitamins, hormones, chemical contaminants, and allergens) have been developed. This paper reviews recent developments in the field of SPR biosensors for food safety, in particular, for detection of foodborne pathogens and toxins.
Some Results on Symmetric Stable Distributions and Processes.

Abstract : For symmetric stable random variables, a condition equivalent to linear regression is obtained and moments of certain monomials are computed. For stochastic processes of random variables with p-th moments, p1, a function space approach is developed and applied to the system identification problem. Conditions for measurable modifications and for integrable or absolutely continuous sample paths are given.
Identify the Virus-like Models for COVID-19 as Bio-Threats: Combining Phage Display, Spectral Detection and Algorithms Analysis

The rapid identification and recognition of COVID-19 have been challenging since its outbreak. Multiple methods were developed to realize fast monitoring early to prevent and control the pandemic. In addition, it is difficult and unrealistic to apply the actual virus to study and research because of the highly infectious and pathogenic SARS-CoV-2. In this study, the virus-like models were designed and produced to replace the original virus as bio-threats. Three-dimensional excitation-emission matrix fluorescence and Raman spectroscopy were employed for differentiation and recognition among the produced bio-threats and other viruses, proteins, and bacteria. Combined with PCA and LDA analysis, the identification of the models for SARS-CoV-2 was achieved, reaching a correction of 88.9% and 96.3% after cross-validation, respectively. This idea might provide a possible pattern for detecting and controlling SARS-CoV-2 from the perspective of combining optics and algorithms, which could be applied in the early-warning system against COVID-19 or other bio-threats in the future.
Drug Dissolution Enhancement by Salt Formation: Current Prospects

Salt formation is the most common and effective method of increasing solubility and dissolution rates of acidic and basic drugs. The physicochemical principles of salt solubility and the influence of PH solubility profiles of acidic and basic drugs on salt formation and dissolution are discussed. The solubility of salts of acidic or basic drugs depends on how easily they dissociate into their free acid or base forms and on interrelationships of several factors, such as intrinsic solubility, PH, Pka, solubility product and maximum solubility in different dissolution media of varying PH. The interrelationships of these factors are elaborated and their influence on salt screening and the selection of optimal salt forms for development are explained. Salt screening is increasingly being adapted to high throughput experimentation, to shortlist the potential salt(s) for a comprehensive biopharmaceutical characterization at the scale up stage. The suitable salt form is then processed to the next stage of drug development.
Evidence of pre-launch characterization problem of Meteosat-7 visible spectral response

Since the early 1980s, the geostationary Meteosat instruments have been observing the earth at a high temporal and spatial resolution. The data record contains more than 30 years of observations and has become very useful for climate monitoring. With a compilation of 10 satellites, it is crucial to reach the highest possible consistency between the instruments. However, the quality of the level 1 data records is still far from what is needed to generate homogeneous climate data records, due to both temporal ageing as well as discontinuities between successive instruments. In this letter, a method is proposed to assess the pre-launch Meteosat-7 visible spectral response curve and a model of its ageing. The results not only validate the ageing model, but also provide evidence that the official pre-launch spectral response curve of Meteosat-7 poorly represents the sensitivity of the instrument in the blue part of the visible spectrum. Until the Meteosat-7 visible spectral response curve has been reassessed, it is suggested to replace the Meteosat-7 curve with the curve of the high resolution visible channel of Meteosat-8. Quantitatively, the error introduced when unfiltering the data (i.e. conversion from filtered to unfiltered radiance), due to the uncertainty on the Meteosat-7 spectral response, is estimated at 4.5% using the Meteosat-7 spectral response curve, but could be reduced to 2.1% by following the recommendations in this letter.