Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fast ECT Measurement Method for the Thickness of Metallic Plates

This contribution focuses on the nondestructive evaluation of the thickness of metallic plates, by means of eddy-current testing. Specifically, we present a method for reducing/optimizing the measurement time for the approach presented in (Yin and Peyton, 2007), while keeping a high accuracy suitable for industrial applications. In (Yin and Peyton, 2007), the key feature for estimating the thickness of plates is the value of the frequency where a proper quantity achieves its minimum value. To get a proper accuracy in measuring the thickness of the plate, this minimum needs to be located in an accurate manner. In turns, this requires “many” measurements at different frequencies, which make the approach time-consuming and not suitable for almost real-time applications, as those of interest for industry. The proposed patent pending strategy combines a multisine approach to collect the data onto a proper set of frequencies, plus proper techniques for interpolating the data at all the frequencies required to locate accurately the minimum of the response. The combination of the multisine to allocate efficiently the measurement frequencies with the data interpolation results in a reduction of the number of required measurements and, in ultimate analysis, of the overall measurement time. Specifically, the measurement time for a typical situation was reduced of a factor of about 4 (from 13 to 2.66 s) with the same accuracy level of the order of 3%. Finally, we highlight that both design and testing of the new measurement method were carried out by combining numerical simulations and experimental results.
Renal Denervation Reduces Blood Pressure and Improves Cardiac Function: Results from a 12-Month Study

Background Previous studies showed that a decline in BP can reverse pressure-overloaded left ventricular hypertrophy in the long term. Whether this structural remodeling and improved cardiac function were due to reduced BP levels or sympathetic tone is unclear. The aim of this study was to evaluate the efficacy of renal denervation (RDN) on cardiac function and left ventricular hypertrophy in patients diagnosed with resistant hypertension with systolic and diastolic dysfunction. Methods Thirteen patients diagnosed with resistant hypertension underwent bilateral RDN (RDN group), and 13 patients were selected as the control group (drug group) who received regular antihypertensive drugs for the first time. Demographic analysis and hematologic tests were performed to determine renal function as well as BNP levels. Echocardiogram was performed at baseline and 12 months after RDN. Results All the baseline characteristics are comparable in two groups. Both RDN and drug regiments resulted in significant reduction from baseline in SBP/DBP at 12-month follow-up (all P values < 0.01), and the decline due to two interventions showed no statistically significant difference (F = 1.64, P = 0.213 and F = 0.124, P = 0.853 for SBP and DBP, respectively). RDN significantly reduced mean LV mass index (LVMI) from 151.43 ± 46.91 g/m2 to 136.02 ± 37.76 g/m2 (P = 0.038) and ejection fraction (LVEF) increased from 57.15 ± 5.49% at baseline to 59.54 ± 4.18% at 12 months (P = 0.039). No similar changes were detected in the drug group (P values, 0.90 for EF and 0.38 for LVMI). Renal parameters including BUN, Cr, UA, and eGFR at baseline, 3 months, and 12 months showed no marked difference (P = 0.497, 0.223, 0.862, 0.075, respectively). Conclusions Our findings show that in addition to hypertension and its progression, elevated sympathetic hyperactivity is related to left ventricular hypertrophy and cardiac function.
The IMU Augment SLAM on Unmanned Vehicle for Detection of Protective Measures in COVID-19

Detecting protective measures (e.g., masks, goggles and protective clothing) is a momentous step in the fight against COVID-19. The detection mode of unmanned devices based on Simultaneous localization and mapping (SLAM) and fusion technology is more efficient, economical and safe than the traditional manual detection. In this paper, a tightly-coupled nonlinear optimization approach is used to augment the visual feature extraction of SLAM by the gyroscope of the IMU to obtain a high-precision visual inertial system for joint position and pose estimation. Based on the VINS-Mono frame, first, an LSD algorithm based on a conditional selection strategy is proposed to extract line features efficiently. Then, we propose recovering missing point features from line features. Moreover, we propose a strategy to recover vanishing point features from line features, and add residuals to the SLAM cost function based on optimization, which optimizes point-line features in real time to promote the tracking and matching accuracy. Second, the wavelet threshold denoising method based on the $3\sigma $ criterion is used to carry out real-time online denoising for gyroscope to improve the output precision. Our WD-PL-VINS was measured on publicly available EuRoC datasets, TUM VI datasets and evaluated and validated in lab testing with a unmanned vehicle (UV) based on the NVIDIA Jetson-TX2 development board. The results show that our method’s APE and RPE on MH_03_easy sequences are improved by 69.28% and 97.66%, respectively, compared with VINS-Mono.
Effect of Gum Acacia on the Intestinal Bioavailability of n-3 Polyunsaturated Fatty Acids in Rats

Lipid emulsification is a technique that is being explored for improving the bioavailability of omega 3 (n-3) long chain (LC) fatty acid (FA). The nature of the emulsifiers can differently impact the lipid bioavailability via a modification of the lipolysis step. Among natural emulsifiers, gum acacia (GA), an indigestible polysaccharide, provides protective encapsulation of n-3 by forming a specifically crown-like shape around lipid drops, which could also impact the digestion step. Despite the interest in lipolysis rate, the impact of GA on lipid bioavailability has never been explored in a complete physiological context. Thus, we followed in a kinetics study the n-3 bioavailability in rat lymph, orally administered DHA-rich oil, formulated based on GA compared to the bulk phase form of the oil. The AUC values were significantly improved by +121% for total TG and by 321% for n-3 PUFA, specifically for EPA (+244%) and for DHA (+345%). Benefits of GA have also been related to the transport of FA in lymph, which was 2 h earlier (Tmax = 4 h), compared to the Tmax (6 h) obtained with the bulk phase oil. All the data showed that GA is one of the most favorable candidates of natural emulsifiers to improve n-3 bioavailability and their rate of absorption for health targets.
A DFT-Based Quantitative and Geometric Analysis of the Effect of Pressure on Boron Arsenate

Boron arsenate, BAsO4, is a β-cristobalite-like crystal which has been reported to exhibit the rather unusual property of negative linear compressibility behaviour at elevated pressures, that is expanding rather than shrinking in a linear dimension when subjected to pressure. This work proposes a ‘geometry—deformation mechanism’-based mathematical model to aid the discernment of the manner how this anomalous pressure behaviour is achieved. The model makes use of data obtained from DFT simulations over an extended range of pressures, including extreme pressure conditions, and rigorously explains the macroscopic properties of this material in terms of the nanoscale deformations. More specifically, through this model, it was possible to decipher the different contributions to the deformation mechanism and compressibility properties of BAsO4. Moreover, for the first time, it was shown that a rule related to the sum of angles of tetrahedrally coordinated atoms is so robust that it applies at the extreme pressures studied here.
The Evolutionary Trends and Convergence of Cereal Yield in Europe and Central Asia

The state of food security in the world, including that of Europe and Central Asia (ECA), was highlighted in 2020 by the outbreak of the COVID-19 pandemic, when the fact that the food security status of millions of people in ECA, particularly the most vulnerable and those living in fragile contexts, would deteriorate if swift action was not taken as soon as possible became apparent. Improving cereal yield is the key for the ECA to achieve the Sustainable Development Goal (SDG) Target 2.1 to end hunger by 2030. Impressive cereal yield growth has been witnessed within the ECA from 1991 to 2020, but there is still significant variation across the five sub-regions. This paper aimed to analyze the evolutionary trends and convergence of cereal yield in countries of the ECA from 1991 to 2020 for four major cereals: wheat, maize, barley and oats. The findings show that there is strong evidence of σ-convergence and absolute and conditional β-convergence for cereal yield in the ECA, which indicates that countries with low yield in the initial stages have totally experienced higher growth rate, and yield in countries farther away from the steady-state have to have faster growth rate to converge to the steady-state. The presence of club convergence is also identified in terms of geographic location and income level, simultaneously. Therefore, cereal yield in the ECA has converged to the whole and to different groups at the same time, which provides some evidence of agricultural technology spillover effect in the region.
Racial differences in hospitalizations for acute cholangitis: a nationwide time trend analysis, 2008-2018

Background The data on racial epidemiologic trends for acute cholangitis (AC) are scarce. Therefore, we conducted a longitudinal assessment of the racial breakdown of AC-related hospitalizations in the United States (US) over 11 years (2008-2018). Methods Using the National Inpatient Sample, we retrieved adult (>18 years) patients with AC. The adjusted yearly hospitalization rate per 100,000 for each race category was calculated based on the US population estimate for July 1 of the corresponding year obtained from the US Census Bureau. We followed Healthcare Cost and Utilization Project recommendations to: (1) derive a time-interrupted trend (before and after 2015), after determining that the International Classification of Diseases coding change affected AC hospitalizations because of more specific coding in the tenth revision; and (2) generate proportionate estimates using revised trend weights. Results A total of 321,849 patients with AC were included in the analysis. Before 2015, the overall hospitalizations (per 100,000 persons) increased from 16.03 in 2008 to 20.76 in 2014 (P<0.001). Following 2015, the overall hospitalizations increased from 14.34 in 2016 to 14.70 in 2018 (P=0.04). After Whites, Asians represented the ethnic group with the highest race-specific AC hospitalizations per 100,000 persons. Conclusions This cohort study demonstrated an overall rising and disproportionate rate among different races for AC-related hospitalizations. Even though Asians constitute only 6.5% of the US population, they represent the ethnic minority with most hospitalizations for AC.
Effects of dissipative substrate on the performances of enhancement mode AlInN/GaN HEMTs

AlInN/GaN high electron mobility transistors (HEMTs) exhibit numerous advantages compared to other known semiconductor devices. However, it is more difficult to realize the enhancement mode (E‐mode) HEMTs of AlInN/GaN than those of the AlGaN/GaN heterostructure, because of the higher 2‐dimensional electron gas density at the AlInN/GaN interface. In this work, using simulations, it is shown that the E‐mode can be achieved in AlInN/GaN HEMTs by tuning the thickness of the AlInN barrier layer to less than 1.14 nm in our investigated structure. Based on the E‐mode structure, the device performance stability of Al0.83In0. 17N/GaN HEMTs with different heat dissipative substrates was evaluated to explore their effect on the suppression of the self‐heating behavior. The DC behavior, device temperature, lattice temperature distribution, current cutoff frequency (fT), unilateral power‐gain‐cutoff frequency (fmax), and transient response were investigated comparatively. The results indicate that the AlInN/GaN HEMTs with a free‐standing GaN substrate exhibit the best performance characteristics, ie, lowest lattice temperature, highest fT, and fastest transient response, in comparison with those using the flip‐chip substrate and sapphire substrate. Our simulation results suggest that the free‐standing GaN substrate can significantly improve the thermal stability and other basic performance characteristics of the E‐mode AlInN/GaN HEMTs.
Extending analyzed frequency range in interpretation of frequency responses measured on a distribution transformer

In the field of diagnosis of mechanical failures in power transformer’s active part, i.e., windings, leads and the core, the technique of Frequency Response Analysis (FRA) has been recently approved as the main application tool. Mechanical failures in transformer windings reflect changes on measured terminal frequency responses normally in medium frequency range, from several to hundreds of kHz, which is in fact not easy to interpret for diagnosis. The authors proposed a new method based on simulation of a lumped three-phase equivalent circuit of power transformers to interpret frequency responses effectively, but only within low frequency range. This limitation is due to the fact that, the circuit cannot reflect well physical phenomena at medium and higher frequencies. To improve the FRA performance of the proposed method at medium frequencies for transformer failure diagnosis purpose, the paper introduces an investigation on a distributed three-phase equivalent circuit of a 200 kVA 10.4/0.46 kV Yy6 distribution transformer. Result of the investigation is a simplified procedure in determination of electrical parameters associated with the distributed circuit for better simulation based FRA interpretation at medium frequencies.
Mixed THz/FSO Relaying Systems: Statistical Analysis and Performance Evaluation

In this paper, the performance of a mixed Terahertz/free-space optical (THz/FSO) wireless transmission system is studied, where the joint effects of channel fading and pointing errors are considered for both THz and FSO links. Employing the semi-blind amplify-and-forward protocol, we derive the cumulative distribution function and probability density function of the end-to-end signal-to-noise ratio. By applying the derived statistics, exact expressions for the outage probability (OP), average bit error rate (BER), and average channel capacity are obtained. In order to attain useful physical insights, asymptotic OP and average BER expressions are also presented. Based on them, the diversity gain is determined, which is shown to depend on channel fading and pointing errors of both links. In addition, by taking into account the hardware impairments, the OP of the non-ideal hardware system is derived. Moreover, the analysis is extended to multi-antenna scenarios and the asymptotic OP is obtained. Finally, illustrative numerical results are plotted and it can be observed that the path loss, channel fading, pointing errors and hardware impairments lead to a considerable degradation in system performance.
Analysis of the Flux Density and Back EMF in Eccentric Permanent Magnet Machines Based on 2-D Air-Gap Modulation Theory

In this article, the unified 2-D air-gap field modulation (AFM) model is established to analyze the flux density and back electromagnetic force (EMF) in both rotor-permanent magnet (PM) and stator-PM machines under eccentricity. For the temporal distribution of flux density, the static eccentricity (SE) causes amplitude unbalance, while the dynamic eccentricity (DE) leads to sideband harmonic components. The sideband harmonic is commonly regarded as a double-sideband (DSB) modulation effect, but it may be a single sideband (SSB) modulation effect in some specific cases, which is analytically and experimentally proved in this article. More importantly, a quantitative description of how eccentricity influences the phase back EMF is provided, which is only qualitatively expressed in the existing literature. A standardized analysis process is also given, which can be used for different machine topologies. The aforementioned conclusions are validated by the simulations and experiments on two prototyped machines, namely, an 18-slot 20-pole (18s/20p) surface-mounted PM (SPM) machine and a 12s/10p flux-switching PM (FSPM) machine.
Increasing Energy Capture From Partially Shaded PV String Using Differential Power Processing

In photovoltaic (PV) strings based on series-connected PV modules, mismatches among the modules due to partial shading will cause power loss either due to series connection constraint or bypass diodes. This paper proposes a new distributed maximum power point tracking (DMPPT) scheme using multiwinding forward-based converter, which acts as a current balancing differential power processing converter. The converter is configured in the way that each converter port is connected in parallel with individual PV module to enable module-level maximum power extraction. The proposed architecture operates in two modes: local maximum power point tracking (MPPT) mode and current balancing mode. The new maximum power points (MPPs) at module levels are tracked in a local MPPT mode and then dispatched to start current balancing mode of operation. In the current balancing mode, this paper proposes a simple control approach to maximize the output power from partially shaded PV string by maintaining an effective MPPT at module levels and directly transferring the compensation currents toward the shaded modules from modules under normal conditions without any intermediary. The proposed DMPPT scheme is validated by the simulation and experimental results. The results show that using the proposed scheme, the system efficiency is significantly improved compared to other existing topologies.
A Novel Approach for Vehicle Identification based on Image Registration and Deep Learning

Fine-grained vehicle type recognition using on-road cameras is among interesting topics in machine vision. It has several challenges like inter-class similarity, different viewing angles, and different lighting and weather conditions. This paper presents a novel approach for vehicle classification based on a novel augmentation method and deep learning. In the proposed smart augmentation, the vehicle images of each class are registered on the reference vehicles of all other classes and then added to the training set of that class. In this way, we will have a lot of new images which are very similar to both reference and target classes. This helps the CNN model to handle inter-class similarities very well. In the test phase, the input image is registered on every reference image in parallel and applied to the model. Finally, the winner is determined by summing up the provided scores of all models. The targeted data augmentation along with the proposed classification strategy has high recognition power and is capable of providing high accuracy using small CNNs or any other classification method without the need for large datasets. The proposed method achieved a recognition rate of 99.8% with only 150K parameters.
Reynolds-stress turbulence model in the KIVA code for engine simulation

A Reynolds-Stress Turbulence Model has been incorporated with success into the KIVA code, a computational fluid dynamics hydrocode for three-dimensional simulation of fluid flow in engines. The newly implemented Reynolds-stress turbulence model greatly improves the robustness of KIVA, which in its original version has only eddy-viscosity turbulence models. Validation of the Reynolds-stress turbulence model is accomplished by conducting pipe-flow and channel-flow simulations, and comparing the computed results with experimental and direct numerical simulation data. Flows in engines of various geometry and operating conditions are calculated using the model, to study the complex flow fields as well as confirm the model’s validity. Results show that the Reynolds-stress turbulence model is able to resolve flow details such as swirl and recirculation bubbles. The model is proven to be an appropriate choice for engine simulations, with consistency and robustness, while requiring relatively low computational effort.
Near-Complete Suppression of Harmonic Currents in SPMSMs Caused by Back EMF and Dead Time

This article introduces a novel algorithm for suppression of phase current harmonics in three-phase sinusoidal surface-mounted permanent magnet synchronous machines (SPMSMs) caused by nonideal back EMF waveform and dead time effects. Proposed feedback acquisition chain obtains an exact information on all the relevant harmonics within each period of the fundamental. Design of the harmonic current controller based on the internal model control principle is given. The article outlines the relevant details of implementation and the results of verification performed by both computer simulations and experimentally, using a laboratory prototype machine. Experimental results, obtained in the presence of nonsinusoidal back-EMF and with erroneous dead time compensation, prove the ability of the proposed solution to remove the stator current harmonics quickly, in just two fundamental periods, and thus, eliminate torque ripple.
Business model innovation for resilient international growth

ABSTRACT Our knowledge concerning the link between internationalization and business model innovation remains limited. This study investigates the change in small and medium-sized enterprises (SMEs) searching for organizational resilience. It particularly focuses on discovering how SMEs innovate their business models when seeking organisational resilience through international growth. In order to answer this research question, we conducted a multiple-case study of three Finnish SMEs. The critical sources of resilience were digitalization, strategic collaboration, customer intimacy, agile use of resources/expertise, and an improved revenue model. For all the case firms, significant business model innovation was required for resilient international growth. Based on the study findings, a new concept is proposed for future research: SME international resilience.
Magphi: Sequence extraction tool from FASTA and GFF3 files using seed pairs

Researchers working with genomes originating from microorganisms often work with multiple genomes in a single analysis. The number of genomes in datasets can pose challenges when it comes to extracting specific regions of interest from multiple genomes. Manual extraction of regions becomes impractical and time consuming when datasets exceed 10-20 genomes. The complexity of this task increases when working within complex regions of genomes that may not assemble into a single contiguous sequence using some existing technologies such as short read-based sequencing technologies. Therefore, automation is required as datasets of microbial genomes routinely consist of tens or hundreds of genomes. Here we present Magphi, a BLAST (Altschul et al., 1990; Mount, 2007) based contig aware genome extraction tool utilising seed sequences to identify and extract regions of interest.
Sharp thresholds for stopping times of Markov Chains (I)

Motivated by the problem of characterizing cuto phenomena in Markov chains , and that of proving sharp thresholds for dynamic graph models, we investigate threshold properties for stopping times of Markov Chains. We propose an approach to this problem, extending results from the theory of thresholds of random graphs to stopping rules in Markov Chains. We give two such extensions: 1. We show that every monotonic stopping time has a threshold. 2. We give an extension (based on group representation theory) of Russo’s lemma to stopping times.