Miracle-dz/UniFAR-FTUs huggingface dataset:
Fukomys mechowii (Rodentia: Bathyergidae)

Abstract: Fukomys mechowii (Peters, 1881), the giant mole-rat or Mechow's mole-rat, is a cooperatively breeding, tooth-digging, subterranean rodent. It is the largest representative of the genus Fukomys, which is part of the African mole-rat family Bathyergidae. It is found in mesic shrubland, savannah habitats, and agricultural lands in central Africa, its range extending through Angola, the Democratic Republic of Congo, and Zambia. Fukomys mechowii is hunted for its meat in rural areas but its population is considered to be stable. It is rarely housed in captivity and is listed as “Least Concern” (LC) on the International Union for Conservation of Nature Red List of Threatened Species.
On the Potential Self-Amplification of Aneurysms Due to Tissue Degradation and Blood Flow Revealed From FSI Simulations

Tissue degradation plays a crucial role in the formation and rupture of aneurysms. Using numerical computer simulations, we study the combined effects of blood flow and tissue degradation on intra-aneurysm hemodynamics. Our computational analysis reveals that the degradation-induced changes of the time-averaged wall shear stress (TAWSS) and oscillatory shear index (OSI) within the aneurysm dome are inversely correlated. Importantly, their correlation is enhanced in the process of tissue degradation. Regions with a low TAWSS and a high OSI experience still lower TAWSS and higher OSI during degradation. Furthermore, we observed that degradation leads to an increase of the endothelial cell activation potential index, in particular, at places experiencing low wall shear stress. These findings are robust and occur for different geometries, degradation intensities, heart rates and pressures. We interpret these findings in the context of recent literature and argue that the degradation-induced hemodynamic changes may lead to a self-amplification of the flow-induced progressive damage of the aneurysmal wall.
Alternative responses by two species of jumping spiders to unpalatability and toxicity in prey

Abstract. A key challenge for generalist predators is avoiding toxins in prey. Species-specific strategies range from total avoidance of distasteful (and potentially toxic) prey to the use of physiological mechanisms to metabolize toxins after consumption. We compare two species of jumping spiders, Habronattus trimaculatus Bryant, 1945 and Phidippus regius CL Koch, 1846. Based on several anecdotal observations and other aspects of their biology, we hypothesized a priori that H. trimaculatus would be (1) less willing to feed on unpalatable prey and (2) more susceptible to toxins that are consumed compared with P. regius. In Experiment 1, we presented spiders of both species with size-matched quinine-dipped crickets. Consistent with our hypothesis, all H. trimaculatus attacked and rejected them while all P. regius attacked and consumed them. In Experiments 2 and 3, we assigned spiders of both species to experimental feeding treatments with varying levels of toxicity (using toxic springtails, Folsomia candida) and assessed effects on their growth. Spiders of both species readily fed on the springtails. Collectively, results from these two experiments suggest that springtails have negative effects on both species, but that these effects are stronger in H. trimaculatus. Habronattus FO Pickard-Cambridge, 1901 has a unique red retinal filter pigment (not found in Phidippus CL Koch, 1846) that likely improves their ability to discriminate reds and oranges. The evolution of this unique visual system may have been driven by their heightened susceptibility to prey toxins, and thus the benefits of avoiding prey that advertise toxins with long-wavelength colors.
Modelling product-recovery processes in closed-loop supply-chain network design

Recent changes in environmental requirements have forced manufacturing operations to face a new challenge, which is to develop green strategies to design supply chains and their processes. This study describes the specific features of green supply-chain design considering end-of-life products. We propose a mixed integer linear programming model to obtain the optimal closed-loop supply-chain (CLSC) network design, in which recovery process occurs in three different ways: material recovery, component recovery, and product recovery. An extensive analysis is supported by numerical results which inform CLSC managers about the opportunities of enhancing product returns in terms of quality and quantity. To define a better CLSC strategy to increase system profitability, the volume of product returns and corresponding quality conditions should be considered in the design of a CLSC network. The numerical study provides information for us to discuss the potential benefits of product-recovery processes and the reaction of system profitability to the changes in specific CLSC parameters.
Use of Mobile-Based Application for Collection of Patient-Reported Outcomes in Cardiac Surgery

Objective Application-based (app) technology has been studied for patient engagement and collecting patient-reported outcomes (PROs) in several surgical specialties with limited research in cardiac surgery. The aim of study was to determine the effectiveness of app-based technology for collecting PROs, improving the patient experience, and reducing health services utilization in a cardiac surgery center. Methods Patients accessed an interactive app via smartphones. Patients were guided from 4 weeks preoperative to 4 weeks postoperative via reminders, tasks, PRO surveys, and evidence-based education. In the postoperative period, patients were engaged with daily health surveys to track warning signs and recovery milestones. Based on the patient's signs and symptoms, the app escalated lower risk issues to self-care education or higher risk issues to the care team (e.g., phone call to a nurse). Results Sixty-six percent of patients (730 of 1,108) activated their app account. Two hundred seventy-seven patients completed an end-of-program feedback survey, with 94% of patients recommending the app and 98% of patients finding the app was helpful in recovery. Patients also reported using the app to avoid unnecessary health services utilization, with 45% of patients using the app to avoid at least 1 phone call and 28% of patients using the app to avoid at least 1 hospital visit. Conclusions App-based technology for patient engagement is an effective modality to enhance the patient experience, better understand the trajectory of recovery, and reduce unnecessary health services utilization in cardiac surgery.
The Paradigm Design of a Novel 2-class Unilateral Upper Limb Motor Imagery Tasks and its EEG Signal Classification

Multitasking motor imagery (MI) of the unilateral upper limb is potentially more valuable in stroke rehabilitation than the current conventional MI in both hands. In this paper, a novel experimental paradigm was designed to imagine two motions of unilateral upper limb, which is hand gripping and releasing, and elbow reciprocating left and right. During this experiment, the electroencephalogram (EEG) signals were collected from 10 subjects. The time and frequency domains of the EEG signals were analyzed and visualized, indicating the presence of different Event-Related Desynchronization (ERD) or Event-Related Synchronization (ERS) for the two tasks. Then the two tasks were classified through three different EEG decoding methods, in which the optimized convolutional neural network (CNN) based on FBCNet achieved an average accuracy of 67.8%, obtaining a good recognition result. This work not only can advance the studies of MI decoding of unilateral upper limb, but also can provide a basis for better upper limb stroke rehabilitation in MI-BCI.
Throughput and Delay Performance of Cooperative HARQ in Satellite-HAP-Vehicle FSO Systems

This paper addresses the link-layer error-control solutions of high platform altitude (HAP)-aided relaying satellite free-space optical (FSO) systems for the Internet of Vehicles. Specifically, we propose a design of cooperative incremental redundancy (IR) hybrid automatic repeat request (HARQ) protocol to mitigate the transmission errors over the turbulence fading channels. The performance metrics, including average throughput and average frame delay, are analytically derived. The numerical results confirm the effectiveness of our proposed cooperative IR-HARQ protocol in FSO-based satellite-HAP-vehicle systems and support the proper selection of parameters. Monte-Carlo simulations are also performed to validate the correctness of theoretical results.
Analysis of SEB and SEGR in super-junction MOSFETs

The electric field distribution in the super-junction power MOSFET is analyzed using analytical modeling and numerical simulations in this paper. The single-event burnout (SEB) and single-event gate rupture (SEGR) phenomena in this device are studied in detail. It is demonstrated that the super-junction device is much less sensitive to SEB and SEGR compared to the standard power MOSFET. The physical mechanism is explained.
Hybrid Antenna Array Predistorter for 5G mm Band

The main focus of this paper is the hybrid antenna subarray linearization with digital predistorter and its practical implementation. During the experiments two alternative predistorter architectures have been evaluated in terms of EVM and ACLR. The experimental results for 5G/NR system @ 28 GHz show that predistorter with the complex anti-beamforming feedback requires an intensive RF calibration in order to achieve EVM and ACLR levels required for 256-QAM transmission. In contrast, the newly proposed predistorter with low-complexity timely shared feedback provides the same performances without any costly and labor-intensive RF calibration and looks a better alternative during the plant manufacturing where cost became the main driver of the commercial success.
Factors governing burr formation during high-speed slot milling of wrought aluminum alloys

Burr formation and edge finishing are research topics with high relevance to industrial applications. To remove burrs, however, a secondary operation known as deburring is usually required. Deburring is more complex and costly when dealing with milled parts, because multiple burrs form at different locations with various sizes. Therefore, proper selection of process parameters to minimize the burr size is strongly recommended. Therefore, this requires an understanding of milling burr formation mechanism and the governing cutting parameters on milling burrs. In this article, a multilevel experimental study is arranged to investigate the effects of machining conditions, tooling and workpiece materials on burr size (height and thickness). Statistical tools are then used to determine the dominant cutting parameters on burr size and to effectively prescribe an operational window to control and minimize burr formation. It was found that optimum setting levels of process parameters to minimize each burr are different. The analysis of results shows the significant effects of cutting tool, feed per tooth and depth of cut on slot milling burrs.
IExchange: Asynchronous Communication and Termination Detection for Iterative Algorithms

Iterative parallel algorithms can be implemented by synchronizing after each round. This bulk-synchronous parallel (BSP) pattern is inefficient when strict synchronization is not required: global synchronization is costly at scale and prohibits amortizing load imbalance over the entire execution, and termination detection is challenging with irregular data-dependent communication. We present an asynchronous communication protocol that efficiently interleaves communication with computation. The protocol includes global termination detection without obstructing computation and communication between nodes. The user's computational primitive only needs to indicate when local work is done; our algorithm detects when all processors reach this state. We do not assume that global work decreases monotonically, allowing processors to createnew work. We illustrate the utility of our solution through experiments, including two large data analysis and visualization codes: parallel particle advection and distributed union-find. Our asynchronous algorithm is several times faster with better strong scaling efficiency than the synchronous approach.
Examining the Influence of Spatial Smoothing on Spatiotemporal Features of Intrinsic Connectivity Networks at Low ICA Model Order

Using a relatively high model order of independent component analysis (ICA with 75 ICs) of functional magnetic resonance imaging (fMRI) data, we have reported a clear effect of spatial smoothing Gaussian kernel size on spatiotemporal properties of intrinsic connectivity networks (ICNs). However, many if not the majority of ICA fMRI studies are usually performed at low model order, e.g., 20-IC decomposition, as such low order is generally enough to extract the few networks of interest such as the default-mode network (DMN). The aim of this study is to investigate if we can replicate the spatial smoothing effects on spatiotemporal features of ICNs at low ICA model order. Same resting state fMRI data that we used with 75-IC analysis were used here. Spatial smoothing using an isotropic Gaussian filter kernel with full width at half maximum (FWHM) of 4, 8, and 12 mm was applied during preprocessing. ICNs were identified from 20-IC decomposition and evaluated in terms of three primary features: spatial map intensity, functional network connectivity (FNC), and power spectra. The results identified similar effects of spatial smoothing on spatial map intensities and power spectra at p < 0.01, false discovery rate (FDR) corrected for multiple comparisons. Reduced spatial smoothing kernel size resulted in decreased spatial map intensities as well as a generally decreased low-frequency power (0.01 – 0.10 Hz) but increased high-frequency power (0.15 – 0.25 Hz). FNC, however, did not show a uniform change in correlation values with the size of smoothing kernel. Notably, FNC between DMNs decreased but FNC between central executive and visual networks increased with an increase in smoothing kernel size. These preliminary findings confirm spatial smoothing influences ICN features regardless of model order. The discussion focuses on differences between observed changes at low and high ICA model orders.
In-the-loop validation of fuel cell vehicle control

Advanced powertrain development is accelerated with increased safety using model-based design tools and in-the-loop validation. The effective application of a 'Hardware-in-the-Loop' (HIL) and 'Software-in-the-Loop' (SIL) simulation system for the development of the safety and hybrid control algorithms for a hydrogen fuel cell hybrid passenger vehicle are described in this work. Models of the powertrain subsystems are assembled from vehicle test data. SIL simulation is used to test initial code integrity and to validate the HIL vehicle models. Battery charging control and hybrid control strategies are tested in HIL and the results are then validated in real-world application.
Understanding the Reliability of Ferroelectric Tunnel Junction Operations using an Advanced Small-Signal Model

Ferroelectric technology is becoming ever more appealing for a variety of applications, especially analog neuromorphic computing. In this respect, elucidating the physical mechanisms occurring during device operation is of key importance to improve the reliability of ferroelectric devices. In this work, we investigate ferroelectric tunnel junctions (FTJs) consisting of a ferroelectric hafnium zirconium oxide (HZO) layer and an alumina (Al2O3) layer by means of C-f and G-f measurements performed at multiple voltages and temperatures. For a dependable interpretation of the results, a new small signal model is introduced that goes beyond the state of the art by i) separating the role of the leakage in the two layers; ii) including the significant impact of the series impedance (that depends on the samples layout); iii) including the frequency dependence of the dielectric permittivity; iv) accounting for the fact that likely not the whole HZO volume crystallizes in the orthorhombic ferroelectric phase. The model correctly reproduces measurements taken on different devices in different conditions. Results highlight that the typical estimation method for interface trap density may be misleading.
8.3.1 Certainty, Risk and Gambling in the Development of Complex Systems

One of the few things certain about development of complex systems is the requirements for the system will remain uncertain late into the development program. Even though we recognize this, why do many programs assume that requirements will not change (gambling) or treat requirement change as a risk rather than a certainty? An analysis of gas turbine engine control systems requirements shows that typically 50% will change between Critical Design Review and Entry into Service. This requirements uncertainty manifests as technical risk to the programme. This paper evaluates the impact of not managing these uncertainties and describes how applying Systems Engineering principles can reduce this effect.
Stratification of carotid atheromatous plaque using interpretable deep learning methods on B-mode ultrasound images

Carotid atherosclerosis is the major cause of ischemic stroke resulting in significant rates of mortality and disability annually. Early diagnosis of such cases is of great importance, since it enables clinicians to apply a more effective treatment strategy. This paper introduces an interpretable classification approach of carotid ultrasound images for the risk assessment and stratification of patients with carotid atheromatous plaque. To address the highly imbalanced distribution of patients between the symptomatic and asymptomatic classes (16 vs 58, respectively), an ensemble learning scheme based on a sub-sampling approach was applied along with a two-phase, cost-sensitive strategy of learning, that uses the original and a resampled data set. Convolutional Neural Networks (CNNs) were utilized for building the primary models of the ensemble. A six-layer deep CNN was used to automatically extract features from the images, followed by a classification stage of two fully connected layers. The obtained results (Area Under the ROC Curve (AUC): 73%, sensitivity: 75%, specificity: 70%) indicate that the proposed approach achieved acceptable discrimination performance. Finally, interpretability methods were applied on the model’s predictions in order to reveal insights on the model’s decision process as well as to enable the identification of novel image biomarkers for the stratification of patients with carotid atheromatous plaque.Clinical Relevance—The integration of interpretability methods with deep learning strategies can facilitate the identification of novel ultrasound image biomarkers for the stratification of patients with carotid atheromatous plaque.
Integrated Weed Management in Kharif Sesamum

Field experiment was carried out on the medium black calcareous soil of Gujarat Agricultural University, Junagadh (Gujarat) during kharif seasons of 2000, 2001 and 2002. Four herbicides as sole application and its lower rate integrated with an interculturing were compared with interculture with weeding at 20 DAS, two intercultures with weeding at 20 and 40 DAS, weed-free (weeding at 15, 30, 45 and 60 DAS) and unweeded control. The results revealed that two intercultures with weeding at 20 and 40 DAS proved its superiority over rest of the weed management treatments in sesamum. Among herbicidal treatments, integration of herbicides with an interculturing proved better than their sole application.
Simulation of Head-Disk Interface and Ramp/Lift-Tab Interfaces During Load/Unload Process of Hard Disk Drive

A 2-D dynamic model was proposed to describe the dynamic behavior of the ramp/lift-tab interface of a one-inch hard disk drive with consideration of the air bearing force and contact stages during the unloading process. The contribution of the geometric parameters of the ramp/lift-tab interface on the dynamic performance of the suspension lift-tab was studied through simulation. A modified Reynolds equation and an iterative formulation for numerical scheme were presented considering continuum Poiseuille flows. The dynamic model developed for the lift-tab motion was extended to simulate the contact and separation stages of head-disk interface. The contact forces and deformation at the ramp/lift-tab contact interface were calculated. The effect of the horizontal velocity of the suspension lift-tab on the dynamic performance of the slider was analyzed. The results show that the dynamic characteristics of slider were independent on the geometric parameters of the ramp and the velocity of the suspension lift-tab. The calculation method to solve the Reynolds Equation proposed in the paper is with enough precision and high efficiency.
A new synchronous rectifier using bipolar transistor driven by current transformer

A new synchronous rectifier (SR) unit is proposed. SR has low offset voltage, which improves the efficiency oflow-voltage power supplies. The SR consists of a bipolar junction transistor (BJT) with a low on-resistance and a current transformer (CT). It is turned on by the free-wheeling current due to positive feedback through the CT. This unit needs no extra drive-circuit for BJT. Analysis and practical design considerations for the SR are presented. The lower offset voltage and higher conversion efficiency are obtained experimentally, and the proposed SR is compared with the case of Schottky diode for a 2 V power supply. <<ETX>>
Harmonic analysis of PWM converters

A nonlinear vector differential equation of periodically time-variant system is applied to the harmonic analysis of pulsewidth modulation (PWM) converters. The differential equation is solved by a combination of harmonic balance and small parameter methods. This results in an equivalent system of algebraic equations from which a steady-state solution required for the harmonic analysis is obtained. The first three equations of this system usually suffice for the practical analysis of PWM converters. The analysis may be formalized and simplified if the first equation is used to obtain dc components, and the inductor current and capacitor voltage harmonic content are obtained from two subsequent equations. An example (three-switch converter) is given.
Space-oriented Label Partitioning for Multi-object Tracking

The problem of tracking multiple objects has been investigated in various research and industrial fields. Among existing methods, random finite set (RFS) solutions such as the generalized labeled multi-Bernoulli (GLMB) filter has provided efficient solutions with solid theoretical justifications. Furthermore, implementations show that the GLMB approach is efficient under challenging scenarios. In this paper, we study an RFS-based method for multi-object tracking (MOT) through a simple data structure for label partitioning. Specifically, grid index structure based techniques for splitting a label space and a label-partitioned GLMB tracker are investigated. We finally evaluate the performance of label partitioning and the GLMB filter via various means such as visualization, execution time, and MOT metrics.
On Sum-Rate and Fairness of MIMO Downlink Communications

The tradeoff between sum-rate and fairness for MIMO downlink communications employing dirty paper coding (DPC) is investigated in this paper. More specifically, we first apply the luml1 -norm fairness measure to formulate the tradeoff as a certain optimization problem, which is unfortunately nonconvex and cannot be efficiently solved. To overcome the difficulty, we make use of the uplink-downlink duality to transform the problem back and forth between uplink and downlink communications. An efficient, iterative waterfilling based algorithm is then provided to yield achievable points on the sum rate-fairness tradeoff. Simulation results show surprisingly that the proposed DPC-based approach offers a significant gain in the achievable sum-rates for a wide range of fairness values, when compared to successive zero-forcing DPC-based coding schemes.