Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Altitude of Anchors on Performance of UWB Real-Time Locating System

Ultra-wideband (UWB) technology has recently improved the performance of real-time locating systems (RTLS) to centimeter-level accuracy. One of commercially available integrated circuits (IC) for UWB RTLS is from Decawave. Its DW1000 IC can be used in two-way ranging (TWR) method to measure precise time of flight, thus accurate estimation of the distance between an anchor and a tag. A trilateration algorithm can then estimate the position of a tag in two-dimensional (2-D) and three-dimensional (3-D) space from the distance between the tag and three or more anchors. In this work, the impact of altitude of anchors above the tag on the performance of a TWR UWB RTLS was studied. In the experiments, the anchors and tag were first placed on the first floor of a building. Then, some of the anchors were raised or moved to higher floors. The results revealed that the error distances along x-, y-, and z-axis varied differently with increasing altitude of the anchors, thus changing their contribution to the 2-D and 3-D performance. The results indicated that altitude of anchors dramatically affected the performance, especially in 3-D. The results can help suggest how to find optimal positions of anchors for deployment of the RTLS.
A High Frequency Hydrogen-Terminated Diamond MISFET With  ${f}_{{\text{T}}}/{f}_{\max}$  of 70/80 GHz

A high frequency hydrogen-terminated diamond metal-insulator-semiconductor field-effect transistor (MISFET) with extremely small source-drain distance of about 350 nm was realized by self-aligned process on (001)-oriented single crystal diamond substrate. To suppress the gate leakage current, a low temperature Al<sub>2</sub>O<sub>3</sub> film was deposited as the gate insulator by inductance coupled plasma enhanced atomic layer deposition. A low ohmic contact resistance of <inline-formula> <tex-math notation="LaTeX">$1.84~\Omega \cdot $ </tex-math></inline-formula>mm was measured by using transmission line method. The fabricated 100 nm gate length MISFET shows a high current density of 585 mA/mm and a high transconductance of 206 mS/mm. By minimizing the parasitic parameters of the device, a high current gain cut-off frequency <inline-formula> <tex-math notation="LaTeX">${f} _{\textsf {T}}$ </tex-math></inline-formula> of 70 GHz and maximum frequency of oscillation <inline-formula> <tex-math notation="LaTeX">${f} _{\textsf {max}}$ </tex-math></inline-formula> of 80 GHz have been realized.
Microparasite dispersal in metapopulations: a boon or bane to the host population?

Although connectivity can promote host species persistence in a metapopulation, dispersal may also enable disease transmission, an effect further complicated by the impact that parasite distribution may have on host–parasite population dynamics. We investigated the effects of connectivity and initial parasite distribution (clustered or dispersed) on microparasite–host dynamics in experimental metapopulations, using guppies and Gyrodactylus turnbulli. We created metapopulations of guppies divided into four subpopulations and introduced either a low level of parasites to all subpopulations (dispersed) or a high level of parasites to one subpopulation (clustered). Controlled migration among subpopulations occurred every 10 days. In additional trials, we introduced low or high levels of parasites to isolated populations. Parasites persisted longer in metapopulations than in isolated populations. Mortality was lowest in isolated populations with low-level introductions. The interaction of connectivity and initial parasite distribution influenced parasite abundance. With low-level introductions, connectivity helped the parasite persist longer but had little effect on the hosts. With high levels, connectivity also benefited the hosts, lowering parasite burdens. These findings have implications for disease management and species conservation.
Seam Carving Detection Using Convolutional Neural Networks

Deep Learning techniques have been widely used in the recent years, primarily because of their efficiency in several applications, such as engineering, medicine, and data security. Seam carving is a content-aware image resizing method that can also be used for image tampering, being not straightforward to be identified. In this paper, we combine Convolutional Neural Networks and Local Binary Patterns to recognize whether an image has been modified automatically or not by seam carving. The experimental results show that the proposed approach can achieve accuracies within the range [81%-98%] depending on the severity of the tampering procedure.
Closed Humeral Fracture Complicated with Acute Hematogenous Osteomyelitis: A Case Report

Introduction: Acute hematogenous osteomyelitis (AHO) has been noted mainly in open fractures injuring soft tissue immunological defenses and in immuneincompetent patients. Osteomyelitis complicating closed fractures in immunocompetent adult patients is, therefore, a rare clinical entity with scarce literature. Case Report: We report a case of primary Staphylococcus aureus bacterial infection of a closed, humeral shaft fracture occurring in a previously healthy 28-year-old male patient. The patient was involved in a motorcycle accident and was admitted to the surgical ward with a chest drain. While hospitalized, a peak of fever was noted, but no source was found. Diagnosis of the closed fracture infection was noted on primary open reduction and internal fixation (ORIF), and although the patient was treated with antibiotics, local osteomyelitis developed. Treatment including serial debridements utilizing gentamycin beads and an additional ORIF procedure until the full union was achieved. The patient regained full, painless, motion of the arm and shoulder. Conclusion: Although AHO complicating a closed fracture in immunocompetent adults is very rare, it should not be overlooked, and special attention should be sought in such cases. Meticulous debridement and rigid fixation are utmost for the eradication of infection and fracture union. Patients presenting with such infections should, therefore, be followed closely and treated promptly.
Pet Face Detection

The technology of human face recognition is very useful and important for man-machine communication and security. Then, many methods of face recognition have been developed and are used for a lot of systems such as digital camera, bank ATM (Automated Teller Machine), home security and so on. These days, most of human faces are precisely recognized with Haar-like features and AdaBoost classifiers. On the other hand, many people have pets such as dogs and cats, and they are friends or even family members for human beings. Then, surveillance cameras have been developed and used for monitoring pets, who are in houses while the owners are away from home. However, the recognition of pet faces is very difficult since there are a variety of patterns on the face. It is not sure that pet faces can be recognized with the same methods as the faces of human beings. Therefore, we have investigated the methods to detect pet faces, especially for cats and dogs. We have used Haar-like and HOG (Histogram of Oriented Gradients) features to construct the classifiers of pet faces. In addition, we have tried to investigate which is better for the pet face detection to use either whole face or parts of the face such as eyes and nose. Finally, we have applied our method to some pictures of cats and dogs, and confirmed that the classifiers have been able to detect the pet faces correctly.
Structural, functional, and symptom relations in painful distal symmetric polyneuropathies: a systematic review

Abstract The diagnosis of distal symmetric polyneuropathies (DSPs) relies on the presenting symptomatology and neurological sensory examination, supported by objectively quantified structural and functional changes in sensory nerves. Although these separate components have important diagnostic utility, the associations between the structural vs the symptomatic and functional findings in painful DSP are still unclear. It is assumed that delineation of the correlations, or lack of such, between structure, clinical presentation, and function will contribute to a better understanding and treatment of DSP. This systematic review assessed small fiber morphology in patients with different types of painful DSP, and compared it with symptoms, signs, and nerve fiber function. Overall, 111 papers met the inclusion criteria for the systematic review. The results indicate that epidermal nerve fiber loss, in isolation, is not a useful indicator of painful symptoms or their severity in DSP. Intraepidermal nerve fiber density correlated reasonably well with neuropathy scores on tools assessing signs and symptoms (such as the Michigan Neuropathy Screening Instrument and the Total Neuropathy Score), but less so with symptom measures only. Among various psychophysical sensory measures, warmth detection and heat pain thresholds correlated best with intraepidermal nerve fiber density, particularly when assessed at the same anatomical site. The observed sources of heterogeneity, and the lack of associations between structural and functional measures in several studies are discussed. A framework is proposed for uniform assessment of nerve fiber parameters for investigating clinically relevant mechanisms of neuropathic pain in DSP.
Association between angiopoietin-like protein 2 and lectin-like oxidized low-density lipoprotein receptor 1 ligand containing apolipoprotein B in patients with type 2 diabetes

Objective This study was performed to evaluate the association of the serum level of angiopoietin-like protein 2 (ANGPTL2) with circulating inflammatory markers and oxidized and modified low-density lipoprotein (LDL) cholesterol as evaluated by lectin-like oxidized LDL receptor 1 ligand containing apolipoprotein B (LAB) in patients with type 2 diabetes. Methods The study included 70 patients with type 2 diabetes hospitalized for glycemic control and 9 control subjects. Results The serum level of ANGPTL2 was significantly higher in the patients with type 2 diabetes than in the healthy controls. There was a significant positive correlation between ANGPTL2 and the high-sensitivity C-reactive protein, fibrinogen, and LAB levels and a significant negative correlation between ANGPTL2 and the estimated glomerular filtration rate (eGFR). Conclusions These results suggest that the serum ANGPTL2 level has a close positive association with inflammatory markers, especially fibrinogen and oxidized and modified LDL as evaluated by LAB. The data also suggest that the serum ANGPTL2 level is influenced by renal function as reflected by the eGFR.
Correlation-Constrained and Sparsity-Controlled Vector Autoregressive Model for Spatio-Temporal Wind Power Forecasting

The ever-increasing number of wind farms has brought both challenges and opportunities in the development of wind power forecasting techniques to take advantage of interdependencies between tens or hundreds of spatially distributed wind farms, e.g., over a region. In this paper, a sparsity-controlled vector autoregressive (SC-VAR) model is introduced to obtain sparse model structures in a spatio-temporal wind power forecasting framework by reformulating the original VAR model into a constrained mixed integer nonlinear programming (MINLP) problem. It allows controlling the sparsity of the coefficient matrices in direct manner. However this original SC-VAR is difficult to implement due to its complicated constraints and the lack of guidelines for setting its parameters. To reduce the complexity of this MINLP and to make it possible to incorporate prior expert knowledge to benefit model building and forecasting, the original SC-VAR is modified and a correlation-constrained SC-VAR (CCSC-VAR) is proposed based on spatial correlation information about wind farms. Our approach is evaluated based on a case study of very-short-term forecasting for 25 wind farms in Denmark. Comparison is performed with a set of traditional local methods and spatio-temporal methods. The results obtained show the proposed CCSC-VAR has better overall performance than both the original SC-VAR and other benchmark methods, taking into account all evaluation indicators, including sparsity-control ability, sparsity, accuracy, and efficiency.
Development and Evaluation of a Personalized Computer-aided Question Generation for English Learners to Improve Proficiency and Correct Mistakes

In the last several years, the field of computer assisted language learning has increasingly focused on computer aided question generation. However, this approach often provides test takers with an exhaustive amount of questions that are not designed for any specific testing purpose. In this work, we present a personalized computer aided question generation that generates multiple choice questions at various difficulty levels and types, including vocabulary, grammar and reading comprehension. In order to improve the weaknesses of test takers, it selects questions depending on an estimated proficiency level and unclear concepts behind incorrect responses. This results show that the students with the personalized automatic quiz generation corrected their mistakes more frequently than ones only with computer aided question generation. Moreover, students demonstrated the most progress between the pretest and post test and correctly answered more difficult questions. Finally, we investigated the personalizing strategy and found that a student could make a significant progress if the proposed system offered the vocabulary questions at the same level of his or her proficiency level, and if the grammar and reading comprehension questions were at a level lower than his or her proficiency level.
Why is My Baby Crying? An In-Depth Analysis of Paralinguistic Features and Classical Machine Learning Algorithms for Baby Cry Classification

As human beings, we begin interacting with the world by expressing our basic needs through crying. Parents strive to identify and timely address these needs before hysterical crying sets in. However, first-time parents usually fail, and this leads to frustration and feelings of helplessness. In this context, our work focuses on creating an automatic system able to distinguish between different infant needs based on crying. We extract various sets of paralinguistic features from the baby-cry audio signals and we train various rule-based or statistical classifiers. We evaluate and in-depth compare the results and obtain up to 70% accuracy on the evaluation dataset.
Neonatal respiratory outcomes in pregnancy induced hypertension: introducing a novel index

Abstract Objective: To evaluate short-term respiratory outcomes, mortality and bronchopulmonary dysplasia (BPD) in preterm infants born to mothers with and without pregnancy induced hypertension (PIH). Methods: Exposed infants <33 weeks’ gestation were matched to controls in a 1:2 ratio, based on gestation, sex and antenatal steroid exposure in this retrospective cohort study. Primary outcomes were a novel cumulative respiratory index (cRI) (product of mean airway pressure-hours and FiO2-hours while on invasive ventilation during first 72 hours), mortality and BPD. Results: Seventy-nine exposed infants were matched with 158 controls. cRI was higher in exposed infants (median 1854; IQR 186–13,901) versus controls (median 1359; IQR 210–11,302) but not statistically significant (p = .63). On conditional regression analysis, PIH did not predict cRI (adjusted β = 0.96; 95% CI = 0.79–1.17; p = .712). No association between PIH and mortality (unadjusted odds ratio [OR] = 3.14; 95% CI = 0.76–13.0; p=.11) was identified. PIH was significantly associated with BPD on univariate analysis (OR = 2.29; 95% CI = 1.02–5.17; p=.046), but not after adjustment (aOR = 1.26; 95% CI = 0.38–4.19; p=.7). Conclusions: PIH was not associated with cRI, mortality or BPD in this study. Further validation of cRI and exploration of its relationship with PIH as well as neonatal outcomes is warranted.
Pharmacological Action of a Pregnane Glycoside, Russelioside B, in Dietary Obese Rats: Impact on Weight Gain and Energy Expenditure

Background and purpose: Russelioside B (RB) is a pregnane glycoside obtained from Caralluma quadrangula; a herb with antidiabetic, anti-inflammatory, and antihyperlipidemic activities. The present experiment tested the possible role of RB in controlling weight gain in rats fed on high fat (HF) diet. Methods: RB was separated from the n-butanol fraction of the crude methanolic extract by chromatographic separation on a Si gel column according to the procedures described previously. The experiment of the biological assessment of RB used 32 male Wistar rats (4 groups, n = 8). Group 1 rats were fed with a palatable normal diet. Group 2, 3, and 4 were fed on HF diet for 16 weeks. Group 2 served as the HF diet control group while Group 3 and 4 received daily oral doses of RB (25 and 50 mg/kg) during the last four weeks. Animals’ parameters like weight gain, fasting level of blood sugar, serum lipids, and serum liver enzyme activities were measured. Liver or adipose tissue weight was divided by the rat’s body weight and multiplied by 100 to obtain the liver or adipose tissue index, respectively. Adipose tissues were processed for histopathological examination, measurement of mRNA expression of visfatin, leptin, adiponectin, uncoupling protein-1 (UCP-1), and carnitine palmitoyl transferase-1 (CPT-1). Furthermore, serum levels of insulin, interleukin-6 (IL-6), IL-1β, tumor necrosis factor-α (TNF-α), leptin, resistin, and adiponectin were assessed using ELISA kits. Results: Rats fed with the HF diet exhibited significant body weight gain, abnormal liver function, disturbed lipid profile, and greater serum level of pro-inflammatory cytokines in addition to greater insulin resistance, adipose tissue and liver indices. Further, rats fed with the HF diet displayed upregulations in the expression of visfatin and leptin with downregulations in the expression of adiponectin, UCP-1, and CPT-1 compared to normal rats. Interestingly, RB (25 or 50 mg/kg) favorably modulated the measured parameters. Conclusion: Data from this study documented the beneficial role of RB in diminishing weight gain, improving the inflammatory perturbations and energy expenditure in HF diet fed rats. Therefore, RB might be a promising candidate for obesity.
A Line Tracking Algorithm Based on Image Processing

Line follower robots can be used for many important robotic and industrial tasks. One of the most important factors in these methods is the computational requirement of the algorithm. The paper presents a novel method for the line following problem using image processing technique. Our main goal is to find an efficient way with real-time computing to track a line using a camera-equipped robot. To measure the effectiveness of the presented method, we compare two line following robots with the line tracking method being the only difference between them. The first robot uses the proposed camera-based method and the other robot has reflective optical sensors in order to determine the position of the line. These real life experiments demonstrate the efficiency of the presented method.
Aesthetic outcome following breast‐conserving surgery assessed by three evaluation modalities in relation to health‐related quality of life

The aim of this study was to compare the agreement between three different methods for evaluation of aesthetic outcome following breast‐conserving surgery and adjuvant radiotherapy: a patient questionnaire, panel evaluation of photographs and the software BCCT.core. A further aim was to examine how these modalities predict health‐related quality of life as measured by the validated Breast‐Q™ questionnaire.
Performance enhancement of ultraviolet light emitting diode incorporating Al nanohole arrays

Enhanced photoluminescence and improved internal quantum efficiency were demonstrated for ultraviolet light emitting diodes (UV-LEDs) with Al nanohole arrays deposited on the top surface. The effects of the thickness and periodicity of the plasmonic structures on the optical properties of UV-LEDs were studied, and an optimized nanohole array parameter was illustrated. Classical electrodynamic simulations showed that the radiated power is mostly concentrated along the edge of the Al nanohole arrays. Even though no obvious dip was observed in the transmission spectra associated with localized surface plasmon resonance, significant improvements in radiatiative recombination and light extraction efficiency were demonstrated, indicating the influence of Al nanohole arrays on the light emission control of UV-LEDs. It is anticipated that the enhanced luminescence can be obtained for various emitting wavelengths by directly adjusting the periodicity and morphology of the Al nanohole arrays and this new technology can alleviate crystal quality requirements of III-nitride thin films in the development of high efficiency UV optoelectronic devices.
Analysis of Ensemble Models for Aging Related Bug Prediction in Software Systems

With the evolution of the software industry, the growing software complexity led to the increase in the number of software faults. According to the study, the software faults are responsible for many unplanned system outages and affects the reputation of the company. Many techniques are proposed in order to avoid the software failures but still software failures are common. Many software faults and failures are outcomes of a phenomenon, called software aging. In this work, we have presented the use of various ensemble models for development of approach to predict the Aging Related Bugs (ARB). A comparative analysis of different ensemble techniques, bagging, boosting and stacking have been presented with their comparison with the base learning techniques which has not been explored in the prediction of ARBs. The experimental study has been performed on the LINUX and MYSQL bug datasets collected from Software Aging and Rejuvenation Repository.
Zero-shot Transfer Learning for Semantic Parsing

While neural networks have shown impressive performance on large datasets, applying these models to tasks where little data is available remains a challenging problem. In this paper we propose to use feature transfer in a zero-shot experimental setting on the task of semantic parsing. We first introduce a new method for learning the shared space between multiple domains based on the prediction of the domain label for each example. Our experiments support the superiority of this method in a zero-shot experimental setting in terms of accuracy metrics compared to state-of-the-art techniques. In the second part of this paper we study the impact of individual domains and examples on semantic parsing performance. We use influence functions to this aim and investigate the sensitivity of domain-label classification loss on each example. Our findings reveal that cross-domain adversarial attacks identify useful examples for training even from the domains the least similar to the target domain. Augmenting our training data with these influential examples further boosts our accuracy at both the token and the sequence level.
A Stochastic Method for Ultrasound Despeckling in Images Via Dynamic Weight Allocation

Medical and biological imaging modalities like ultrasound often contain noise that is non-linear in nature. Noise reduction via linear filtering algorithms often produce unimpressive results. Multiplicative noise like speckle noise is inherently present in medical ultrasound images, and it usually reduces the contrast between region of interest and the background. Recent algorithms like Bayesian methods have been used with some degree of success but they are computationally intensive. This paper presents an iterative algorithm for noise reduction in ultrasound images via dynamic weight allocation. Proposed method is fast and performs better in comparison to state-of-art techniques.