Miracle-dz/UniFAR-FTUs huggingface dataset:
Morphological changes in the mechanically unloaded myocardial cell

The role of stretch and/or tension in maintaining the structural integrity of the myocardial cell was investigated in 16 cats. Right ventricular papillary muscles were studied 1–28 days after transection of the chordae tendinae and compared to adjacent intact papillary muscles. A progressive atrophy, as shown by decreased mean cell cross‐sectional area, occurred; by the 28th day mean cardiocyte area was only 28% of the control value. The earliest ultrastructural changes (one day after surgery) were primarily focal and included disorientation of contractile filaments and loss of Z‐line substance. During the first week, vacuolation, loss of contractile filaments, and infiltration of macrophages and fibroblasts were characteristic. By the second week a massive loss of contractile substance, disappearance of the sarcoplasmic reticulum, and a marked increase in connective tissue occurred. Leptomere structures, membrane alterations, and phagocytosis were the most typical changes between the second and fourth week. Hydroxyproline assays on papillary muscles unloaded for three days showed a 38% increase in connective tissue, indicating an early increase in connective tissue/muscle mass associated with mechanical unloading.
Brain Mapping Based Stress Identification Using Portable EEG Based Device

A high amount of stress is experienced by people of all ages nowadays and is affecting their physical and mental health adversely. Traditionally, Perceived Stress Score (PSS-14) questionnaire is used to calculate the stress score, which requires manual intervention of people. In this work, we look into the usage of Electroencephalography (EEG) to help predict the stress level of people without manual intervention and recording by a Brain-Computer Interface(BCI) instrument. EEG can estimate and record the electrical signals in brains utilizing sensors exhibited over the scalp. We propose the design of a brain mapping based stress identification system using a single electrode EEG device. Here we have taken EEG recording of 63 students using a single electrode EEG device NeuroSky Mindwave Mobile. A novel feature combination of bandpower ratios of alpha, beta, delta and theta bands are extracted and fed to the classifiers. We evaluate the performance of Support Vector Machine and K-Nearest Neighbour machine learning algorithms. Target class of the training set is assigned using the stress score calculated from the response of the PSS-14 questionnaire. We achieve the highest average classification accuracy of 74.43 % using K-NN algorithm. We observe that there exist a correlation of bandpower ratios of different bands obtained from recorded EEG signals from the frontal portion of the brain with the stress level of subjects.
Differences in Relative Iron Bioavailability in Traditional Bangladeshi Meal Plans

Background Iron deficiency is the most common nutrient deficiency worldwide. Large intakes of micronutrient-poor staple crops, coupled with low intakes of highly bioavailable dietary iron, are a major cause of this deficiency. Objective To examine the concentration and relative bioavailability of iron in several models (n = 23) of traditional Bangladeshi meals (rice, lentils/dal, vegetable, and fish), as well as the effect of removal of the lentil seed coat on the nutritional quality of iron. Methods The relative bioavailability of iron was assessed by the in vitro/Caco-2 cell culture method, iron concentration by an inductively coupled argon-plasma emission spectrometer (ICAP-ES), and phytic acid concentration by colorimetric assay. The recipes contained 75% to 85% rice, 0% to 15% dal (containing whole or dehulled lentils), 0% to 15% vegetable curry, and 0% to 8% fish. Results While the iron concentrations of recipes containing dehulled dal were significantly lower than those of recipes containing whole dal (p = .005), seed coat removal doubled relative iron bioavailability and increased phytic acid concentration (p < .001). The addition of fish to the meals had no significant effect on relative iron bioavailability. Iron concentration and relative iron bioavailability were correlated in the recipes containing dehulled dal (r = 0.48, p = .03), but not whole dal (r = −0.047, p = .84). Conclusions The total amount of iron absorbed from traditional Bangladeshi meals is dependent upon iron concentration, and dehulling lentils removes inhibitory factors increasing iron uptake but also increases the density of phytic acid in the lentil sample. Thus, along with breeding for high iron concentration and bioavailability (i.e., biofortification), seed coat removal plus measures to lower phytic acid concentrations may be an important strategy to improve the bioavailability of iron in lentils and other pulse crops.
Choriocapillary blood propagation in normal volunteers and in patients with central serous chorioretinopathy

Background/aims To evaluate early choroidal vascular dye-filling and dye propagation patterns in normal subjects and in patients with central serous chorioretinopathy (CSC) using indocyanine green (ICG) angiography. Methods Seventeen healthy volunteers (21–81 years old) and six patients with CSC were included. ICG angiography was performed using a modified Topcon ICG video-camera system. Subtracted images were made using the early ICG frames at a time interval of 0.12 s. Ninety frames of time-sequential images for 3 s starting from the initial dye appearance in the choroid were prepared to construct an animated video. Results The animated video demonstrated dye-filling and propagation patterns at the level of the choroid–choriocapillaris. In normal young volunteers, the initial phase of dye filling appeared as a uniform patchy fluorescence in the sub-foveal area, and then spread evenly in a centrifugal manner in all directions in a wave-like, pulsed fashion towards the equator. In normal older volunteers, the initial phase was similar to that in young volunteers, but centrifugal flow propagation of fluorescence towards the periphery showed an uneven progression and border. In patients with CSC, the initial dye showed a multiple patchy dye appearance with a significant time delay and loss of the centrifugal extension pattern. Conclusion Using this new approach, various choroidal dye propagation patterns were observed in normal volunteers and in patients with CSC. A video of subtracted images allowed evaluation of the dynamics of dye propagation in the choroid–choriocapillaris.
Critical appraisal of emergency medicine educational research: the best publications of 2011.

OBJECTIVES The objective was to critically appraise and highlight medical education research studies published in 2011 that were methodologically superior and whose outcomes were pertinent to teaching and education in emergency medicine (EM). METHODS A search of the English language literature in 2011 querying PubMed, Scopus, Education Resources Information Center (ERIC), and PsychInfo identified EM studies that used hypothesis-testing or observational investigations of educational interventions. Six reviewers independently ranked all publications based on 10 criteria, including four related to methodology, that were chosen a priori to standardize evaluation by reviewers. This method was used previously to appraise medical education published in 2008, 2009, and 2010. RESULTS Forty-eight educational research papers were identified. Comparing the literature of 2011 to that of 2008 through 2010, the number of published educational research papers meeting the criteria increased over time from 30, to 36, to 41, and now to 48. Five medical education research studies met the a priori criteria for inclusion as exemplary and are reviewed and summarized in this article. The number of funded studies remained fairly stable over the past 3 years, at 13 (2008), 16 (2009), 9 (2010), and 13 (2011). As in past years, research involving the use of technology accounted for almost half (n = 22) of the publications. Observational study designs accounted for 28 of the papers, while nine studies featured an experimental design. CONCLUSIONS Forty-eight EM educational studies published in 2011 and meeting the criteria were identified. This critical appraisal reviews and highlights five studies that met a priori quality indicators. Current trends and common methodologic pitfalls in the 2011 papers are noted.
Agent-Based Models for Opinion Formation: A Bibliographic Survey

Agent-based models are now largely adopted to describe how opinions emerge in a group of people. This survey provides an analysis of the literature on the subject, highlighting the major characteristics of such models. Over the last decade, the number of papers has grown at an overall annual rate of 16%, though not continually. Two communities contribute to the research effort: physics and control systems. However, their mutual awareness and collaboration are rather low. The prevailing mechanism adopted to describe the interaction among the agents is bilateral, but not symmetric. In most cases, the opinion is described by a continuous variable. Just a few papers consider a utility function for the agents.
Low-cost IMU Data Denoising using Savitzky-Golay Filters

MEMS sensors have been used in many applications including navigation systems. However, these sensors suffer from highly noisy measurements. If left untreated, these errors will significantly degrade the ultimate navigational solution. Hence, applying a pre-filtering technique becomes a necessity to de-noise these sensor signals to improve the overall system performance. While wavelet denoising is the most common technique for sensor data pre-filtering, it may not be suitable for real-time implementations. This paper explores another method; namely, Savitzky-Golay filters, which can provide competitive denoising performance with a less computationally demanding algorithm. The purpose of the paper is to examine the performance of the new method against wavelet de-noising with respect to both positioning and attitude accuracy and computations time. We applied the filter to denoise MEMS-based inertial sensors data in a tightly coupled integrated INS/GPS system. Our results showed that the new method outperformed the wavelet denoising approach. Moreover, the new method demands much less computations time, which makes it more suitable for embedded systems and real-time applications.
A Binary Learning Framework for Hyperdimensional Computing

Brain-inspired Hyperdimensional (HD) computing is a computing paradigm emulating a neuron’s activity in high-dimensional space. In practice, HD first encodes all data points to high-dimensional vectors, called hypervectors, and then performs the classification task in an efficient way using a well-defined set of operations. In order to provide acceptable classification accuracy, the current HD computing algorithms need to map data points to hypervectors with non-binary elements. However, working with non-binary vectors significantly increases the HD computation cost and the amount of memory requirement for both training and inference. In this paper, we propose BinHD, a novel learning framework which enables HD computing to be trained and tested using binary hypervectors. BinHD encodes data points to binary hypervectors and provides a framework which enables HD to perform the training task with significantly low resources and memory footprint. In inference, BinHD binarizes the model and simplifies the costly Cosine similarity used in existing HD computing algorithms to a hardware-friendly Hamming distance metric. In addition, for the first time, BinHD introduces the concept of learning rate in HD computing which gives an extra knob to the HD in order to control the training efficiency and accuracy. We accordingly design a digital hardware to accelerate BinHD computation. Our evaluations on four practical classification applications show that BinHD in training (inference) can achieve 12.4× and 6.3× (13.8× and 9.9×) energy efficiency and speedup as compared to the state-of-the-art HD computing algorithm while providing the similar classification accuracy.
Fast Transient Analysis of Next-Generation Interconnects Based on Carbon Nanotubes

The scaling of copper wires and the increase in signal switching speed produce transient crosstalk coupling between interconnect lines, which causes overshoots and additional time delay. The time-domain analysis of CMOS gates driving next-generation interconnects consisting of single wall carbon nanotube (SWCNT) bundles or multiwall carbon nanotubes (MWCNTs) is carried out. Accurate simulation models of SWCNT bundles and MWCNTs are proposed in the frequency domain by using both the multiconductor transmission line (MTL) formulation and the multiequivalent single conductor (MESC) approach. The fast transient voltage responses of two coupled nanointerconnects of 14 and 22 nm technologies to a pulsed input are computed by means of both the MTL and the MESC models. The obtained results are in good agreement. The same agreement is achieved by computing the 50% time delay of the output voltages.
A Low-Complexity QR-based Precoding for Massive MIMO Systems with Channel Update

In this paper, we investigate the precoding design for massive multiple-input multiple-output (MIMO) system after a new channel changes for a given user, i.e., channel update. Specifically, we develop a modified two-stage precoding based on channel extension to balance the multi-user interference and noise effect. Additionally, utilizing the matrix transform method of the QR decomposition, a low-complexity precoding algorithm is proposed with channel update into three cases of position. The computation complexity analysis and simulation results in terms of the system capacity are evaluated to demonstrate performance gains of the proposed algorithms.
An Adaptive Hash-Based Text Deduplication for ADS-B Data-Dependent Trajectory Clustering Problem

The Automatic Dependent Surveillance-Broadcast (ADS-B) protocol is equipped in aircraft as an alternative to secondary radar. This emerging technology produces such a prospective type of data to effectively broadcast the aircraft's status (location, velocity, etc.,) in a specific area, which is very useful in air traffic management (ATM). However, there is still a limited number of advanced studies from machine learning/data mining perspectives relying on this kind of data in ATM research. On the other hand, Locality Sensitive Hashing (LSH) is a data mining technique often used to find similar items in the data with high-dimension properties. It is thus relatively suitable for handling with trajectories data to group similar flight paths. From these factors, we reveal in this paper an adaptive LSH- based algorithm, used in near-duplicated documents detection, for the problem of clustering the nearest trajectories by representing the trajectories as a bag-of-words used popularly in text mining. To illustrate our proposed method, an experiment is designed and carried out in thirty successive days, employing the raw ADS-B data collected from FlightAware for the case of Changi International Airport, Singapore. The evaluation based on Silhouette score shows promising results of measuring the clustering performance.
Estimation based Maximum Power Point Control of DFIG based Wind Turbine Systems

The majority of the control schemes of doubly fed induction generator (DFIG) wind turbine systems for the maximum power capture are dependent on its internal states or functions based on these states. Thus, the availability of these states is required to implement such a control scheme in practical. But sometimes some of the states are not available (measurable) to formulate the control law. Hence, this paper recommends the estimation of such unobservable states to implement the maximum extraction control of DFIG based wind energy conversion system in practice. It is based on the estimation based control of the DFIG for the active power control for MPPT as well as the control of the stator terminal voltage. The estimation of the unobservable states have been carried out by Unscented Kalman Filter (UKF), a discrete-time nonlinear estimator. The active power and stator voltage control has been implemented through the rotor flux control approach.
Comparison of Spectral Efficiency Techniques in Device-to-Device Communication for 5G

Future generation networks will accommodate a large amount of data traffic and lower latency. In order to meet these demands, it is essential to look over current spectral use or introduce new frequency bands. Introduction of new frequency bands requires a partial or complete change of already deployed infrastructure, which will have high operation expenditure and capital expenditure. It is more convenient to find other solutions by concentrating on device-related solutions. One of the solutions to achieve higher spectra efficiency is through device-to-device (D2D) communication. This paper presents and compares recent spectral efficiency techniques in 5G through D2D communication. The main focus is on the utilization of different techniques to improve spectrum efficiency. Furthermore, the challenges in interference management, resource utilization, power control, and mode selection of the proposed work are compared.
Motor Fault Diagnosis Using CNN Based Deep Learning Algorithm Considering Motor Rotating Speed

Motor fault is a major problem in unmanned oriented systems such as smart factories. Recently, some studies have been actively carried out to make such a fault diagnosis unattended by a deep learning algorithm. However, these studies do not take into account the speed at which motors are driven, and therefore they are not appropriate for the actual system. In this paper, the experiment was performed to develop a deep learning algorithm that considered the motor speed. The method is that regard the vibration signal as an image and uses the algorithm, CNN, which is suitable for this processing. Adopting the suitable model reduced over-fitting and increased accuracy by reducing the model complexity. As a result, it is shown that fault diagnosis can be performed considering the motor driving speed by using the deep learning algorithm.
Viroids: self‐replicating, mobile, and fast‐evolving noncoding regulatory RNAs

Viroids are small, circular, and noncoding RNAs that infect plants. They replicate in the nucleus or chloroplast and then traffic from cell to cell and from organ to organ to establish systemic infection. Viroids achieve nearly all of the biological functions by directly interacting with host cellular factors. Viroid replication, together with replication of human hepatitis delta virus, demonstrates the biological novelty and significance of RNA‐dependent RNA polymerase activities of DNA‐dependent RNA polymerases. Viroid systemic infection uncovers a new biological principle—the role of three‐dimensional RNA structural motifs mediating RNA trafficking between specific cells. Viroid diseases are virtually the consequences of host gene regulation by noncoding RNAs. A viroid RNA has the highest in vivo mutation rate among all known nucleic acid replicons. The host range of many viroids is expanding, essentially as a result of continuing and fast evolution of noncoding sequences/structures to gain new biological functions. Here, I discuss recent progress in these areas, emphasizing the broad significance of viroid research to the discovery of fundamental biological principles. Copyright © 2010 John Wiley & Sons, Ltd.
Testicular relapse in childhood acute lymphoblastic leukemia: the challenges and lessons.

BACKGROUND Relapse of disease is documented in 15-20% of children with acute lymphoblastic leukemia (ALL). Although testicular relapse is rare with modern risk-adapted treatment protocols, earlier, the testes were a frequently encountered site of relapse and were designated as "drug sanctuaries". PURPOSE This descriptive study was designed to assess the pattern of testicular relapse and to identify high-risk factors. MATERIALS AND METHODS Data obtained from case records of 407 boys with ALL were analyzed. Fine needle aspiration cytology was carried out in children presenting with painless enlargement of testi(e)s. Bone marrow aspiration and cerebrospinal fluid examination were performed concomitantly to confirm or exclude disease at these sites. RESULTS Testicular relapse was documented in 30 boys. It was isolated in 17 patients and associated with bone marrow and/or central nervous system relapse in 13. At relapse, nine boys were over the age of 10 years. The majority were very early and early relapsers. Hyperleucocytosis was documented in five of 30 and seven of 137 relapsers and nonrelapsers, respectively (P = 0.04). Twelve of the 30 boys with testicular relapse were treated with testicular irradiation, reinduction and maintenance therapy. The estimated median overall survival was 33 months. CONCLUSION Testicular relapse, which depends on the therapy administered, may manifest several months/years after completion of treatment. The high incidence of testicular relapse in our series implicates the need of revaluation of our protocol and incorporation of high/intermediate dose methotrexate therapy upfront.
Conditional Disclosure on Pathways to Care: Coping Preferences of Young People at Risk of Psychosis

The interrelationship between stigma and help-seeking is under-researched among children and adolescents. This study explored stigma in relation to pathways to care among young people putatively in an early stage of increased risk of developing psychotic disorders. “Pathways to care” was defined as help-seeking and support from informal and formal resources, and increased risk was determined through the presence of persistent psychotic-like experiences and internalizing/externalizing psychopathology. Twenty-nine qualitative interviews were analyzed using thematic analysis. We defined the superordinate theme in these data as “conditional disclosure,” a concept reflecting the rules and prerequisites that influenced how/whether participants sought help. Through parallels between these findings and established stigma theory, we examined how these conditions could be interpreted as influenced by stigma. Our findings demonstrate the influence of stigma on young people’s perceptions of a range of pre-clinical symptoms, and on how they seek support for these symptoms.
Emotional State Classification: An Additional Step in Emotion Classification through Face Detection

Emotions play an important role in human relations, especially between companies and their customers. Facial expressions are factors that makes emotions recognizable. Paul Ekman identified six (6) core emotions, namely, joy, surprise, sadness, anger, disgust, and fear. These emotions can be categorized into two (2) emotional states, positive and negative. Joy and surprise are classified as positive emotional states while sadness, anger, disgust, and fear are classified as negative emotional states. Among the core emotions, confusion between surprise and fear has been present in multiple researches. This denotes that these emotions are frequently confused with each other due to their similar characteristics. This paper aims to implement an additional step which would categorize the emotional state before identifying the core emotion.