Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusion Tensor Imaging of Leukoaraiosis , Normal Appearing Brain Tissue , and Normal Brain Tissue

Diffusion Tensor Imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique. DTI provides quantitative information at microstuructural level via its parameter indices e.g. mean diffusivity (MD) and fractional anisotropy (FA). It also allows for visualization of neuron fibres through a specific technique called fibre tractography. Leukoaraiosis is an asymptomatic pathological condition of the brain white matter which appears hyperintense on T2-weighted MRI images. Association of leukoaraiosis with age and ischemic heart disease have been previously reported. The objective of this study is to compare MD and FA values measured in various areas of the brain white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) in humans using DTI. 30 subjects with leukoaraiosis and 12 subjects without leukoaraiosis underwent brain scan using GE 1.5 Tesla MRI system. Region of interests were located in the CSF and various WM and GM areas. Comparison of MD and FA values was made between leukoaraiosis tissue (LA) and normal appearing brain tissue (NABT) measured within the same leukoaraiosis subjects, and with normal brain tissue (CONTROL) of healthy control subjects. LA demonstrated a significantly higher MD and lower FA compared to NABT and CONTROL in frontal and occipital WM areas. No differences were observed in MD in any brain region between NABT and CONTROL. Whereas no differences were observed in FA between NABT and CONTROL except in the occipital WM. Fibre tractography showed 31.7% to 56.1% lesser fibre tracts in LA subjects compared to CONTROL subjects. Significant differences were found between pathological tissue compared to normal appearing brain tissue and normal brain tissue. Fibre tractography exposed reduced number of neural fibres in leukoaraiosis subjects as compared to normal subjects.
Java Performance Troubleshooting and Optimization at Alibaba

Alibaba is moving toward one of the most efficient cloud infrastructures for global online shopping. On the 2017 Double 11 Global Shopping Festival, Alibaba's cloud platform achieved total sales of more than 25 billion dollars and supported peak volumes of 325,000 transactions and 256,000 payments per second. Most of the cloud-based e-commerce transactions were processed by hundreds of thousands of Java applications with above a billion lines of code. It is challenging to achieve comprehensive and efficient performance troubleshooting and optimization for large-scale online Java applications in production. We proposed new approaches to method profiling and code warmup for Java performance tuning. Our fine-grained, low-overhead method profiler improves the efficiency of Java performance troubleshooting. Moreover, our approach to ahead-of-time code warmup significantly reduces the runtime overheads of just-in-time compiler to address the bursty traffic. Our approaches have been implemented in Alibaba JDK (AJDK), a customized version of OpenJDK, and have been rolled out to Alibaba's cloud platform to support online critical business.
Development of a Sonar for Underwater Sensor Platforms and Surface Vehicles

In the frame of a thesis project the authors have developed software and methodologies for a sonar prototype. The ultimate goal is the installation of the sonar prototype on the department’s sensor platforms, which include AUVs and ASVs. The thesis presents the intelligent sampling algorithms and DSP tools, e.g. a matched filter, that have been implemented. The sonar was successfully configured to work as an echo sounder. Tests were performed in the underwater laboratory at FOI and in-situ in the Stockholm archipelago. It was found that the sonar is capable of measuring distances with an average error of less than 1 cm in controlled experiments. The in-situ experiments in Baggensfjärden showed a echo detection rate of ≈90 %. Unfortunately, due to hardware limitations, attempts to implement DVL functions have failed. However, background theory and methodologies for velocity measurements, communication and positioning are briefly explained to provide a basis for future work. The electronics currently are subject to improvements and a new version is expected to be ready for use soon. Future work will include analysis and integration of velocity sensing, communication protocols and positioning concepts.
$Q: a super-quick, articulation-invariant stroke-gesture recognizer for low-resource devices

We introduce $Q, a super-quick, articulation-invariant point-cloud stroke-gesture recognizer for mobile, wearable, and embedded devices with low computing resources. $Q ran up to 142X faster than its predecessor $P in our benchmark evaluations on several mobile CPUs, and executed in less than 3% of $P's computations without any accuracy loss. In our most extreme evaluation demanding over 99% user-independent recognition accuracy, $P required 9.4s to run a single classification, while $Q completed in just 191ms (a 49X speed-up) on a Cortex-A7, one of the most widespread CPUs on the mobile market. $Q was even faster on a low-end 600-MHz processor, on which it executed in only 0.7% of $P's computations (a 142X speed-up), reducing classification time from two minutes to less than one second. $Q is the next major step for the "$-family" of gesture recognizers: articulation-invariant, extremely fast, accurate, and implementable on top of $P with just 30 extra lines of code.
Reducing Component Contract Overhead by Offloading Enforcement [ Extended Abstract ]

In recent years, component technology has been a successful methodology for large-scale commercial software development. It is also becoming increasingly popular for large-scale scientific computing in helping to tame the software complexity required in coupling multiple disciplines, multiple scales, and/or multiple physical phenomena. The Common Component Architecture (CCA) [1] is a component model that was designed to fit the needs of the scientific computing community by imposing low overhead and supporting parallel components. CCA has already been used in several scientific domains, creating components for large simulations involving accelerator design, climate modeling, combustion, and accidental fires and explosions [6]. Executable interface contracts present a way to better specify interfaces through which components interact, and to dynamically verify whether this specification is adhered to by an executing application. In this way, composability of applications and the quality of software components is improved. Contracts uncover both errors which would have resulted in the application being killed by the OS and errors where the application produces incorrect results, which are more difficult to trace. Although they present a performance overhead, in order to be most effective contracts need
ANONYMIZING TRANSACTION DATA PUBLICATION USING SLICING

Slicing technique has been proposed as a mechanism for protecting privacy in microdata publishing. To hide certain customer specific information while releasing the transaction data to a third party. Several anonymization techniques have been used for data publishing. Generalization technique loses considerable amount of information, especially for high dimensional data. Bucketization technique does not have a clear separation between quasiidentifying attributes and sensitive attributes. Slicing preserves better data utility than generalization and bucketization. This technique partitions the data both horizontally and vertically. Slicing can handle high dimensional data.
Validation of a Natural Language Processing Algorithm for Detecting Infectious Disease Symptoms in Primary Care Electronic Medical Records in Singapore

Background Free-text clinical records provide a source of information that complements traditional disease surveillance. To electronically harness these records, they need to be transformed into codified fields by natural language processing algorithms. Objective The aim of this study was to develop, train, and validate Clinical History Extractor for Syndromic Surveillance (CHESS), an natural language processing algorithm to extract clinical information from free-text primary care records. Methods CHESS is a keyword-based natural language processing algorithm to extract 48 signs and symptoms suggesting respiratory infections, gastrointestinal infections, constitutional, as well as other signs and symptoms potentially associated with infectious diseases. The algorithm also captured the assertion status (affirmed, negated, or suspected) and symptom duration. Electronic medical records from the National Healthcare Group Polyclinics, a major public sector primary care provider in Singapore, were randomly extracted and manually reviewed by 2 human reviewers, with a third reviewer as the adjudicator. The algorithm was evaluated based on 1680 notes against the human-coded result as the reference standard, with half of the data used for training and the other half for validation. Results The symptoms most commonly present within the 1680 clinical records at the episode level were those typically present in respiratory infections such as cough (744/7703, 9.66%), sore throat (591/7703, 7.67%), rhinorrhea (552/7703, 7.17%), and fever (928/7703, 12.04%). At the episode level, CHESS had an overall performance of 96.7% precision and 97.6% recall on the training dataset and 96.0% precision and 93.1% recall on the validation dataset. Symptoms suggesting respiratory and gastrointestinal infections were all detected with more than 90% precision and recall. CHESS correctly assigned the assertion status in 97.3%, 97.9%, and 89.8% of affirmed, negated, and suspected signs and symptoms, respectively (97.6% overall accuracy). Symptom episode duration was correctly identified in 81.2% of records with known duration status. Conclusions We have developed an natural language processing algorithm dubbed CHESS that achieves good performance in extracting signs and symptoms from primary care free-text clinical records. In addition to the presence of symptoms, our algorithm can also accurately distinguish affirmed, negated, and suspected assertion statuses and extract symptom durations.
BIOMETRIC TECHNIQUES AND FACIAL EXPRESSION RECOGNITION-A REVIEW

The type of authentication, the one relies on measurable physical characteristics that can be automatically checked, and is becoming more popular and demanded. It is called biometrics. This study aims to give the basic review on the biometric techniques and discussion to facial expression recognization in still images and in videos also and to discuss both the techniques for intelligent computers or robots that are mind implemented. An automatic system for the recognition of facial expressions is based on a representation of the expression, learned from a training set of preselected meaningful features. As a first we investigate the emotionally intelligent computers which can perceive human emotions. Biometric uses a variety of processes and techniques to analyze the authentication of the living person. Biometrics is the science and technology of measuring and analyzing biological data. In information technology, biometrics refers to technologies that measure and analyze human body characteristics such as fingerprints, eye retinas, irises, voice patterns, facial patterns and hand measurements, for authentication purposes. In this research paper there is a stress on biometric and techniques of biometric also we have discussed facial expression recognition for both static and dynamic techniques to recognize human facial expression to recognize universally recognized five principal emotions namely angry, disgust, happy, sad and surprise along with neutral in still images and also in video sequence.
Powertrain architectures of electri fi ed vehicles : Review , classi fi cation and comparison

Increasingly stringent regulations and customers' demand for high fuel economy led to rapid developments of distinct alternative powertrain solutions, especially electrified vehicles. Fusion of electric machines into powertrain greatly diversifies powertrain architectures and enriches means to save energy. In this review work, conventional classification of hybrid electric vehicle (Series, Parallel and Power-split HEVs) is expanded to all electrified vehicles (xEV) by including Pure Electric Vehicle (PEV) as the fourth primary type of electrified powertrain architecture; In addition, electrification level of powertrain is analyzed and incorporated into new classification method as the second index; different variants of PEV, Series, Parallel and Power-split HEVs are presented with corresponding patents or products; more complex electrified powertrains are also illustrated by decomposing them into two or more of the four fundamental types and sub-types. This review work is based on comprehensive and up-to-date summary of current development in this field. & 2014 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Reorganization of Destabilized Nodes of Ranvier in βIV Spectrin Mutants Uncovers Critical Timelines for Nodal Restoration and Prevention of Motor Paresis

Disorganization of nodes of Ranvier is associated with motor and sensory dysfunctions. Mechanisms that allow nodal recovery during pathological processes remain poorly understood. A highly enriched nodal cytoskeletal protein βIV spectrin anchors and stabilizes the nodal complex to actin cytoskeleton. Loss of murine βIV spectrin allows the initial nodal organization, but causes gradual nodal destabilization. Mutations in human βIV spectrin cause auditory neuropathy and impairment in motor coordination. Similar phenotypes are caused by nodal disruption due to demyelination. Here we report on the precise timelines of nodal disorganization and reorganization by following disassembly and reassembly of key nodal proteins in βIV spectrin mice of both sexes before and after βIV spectrin re-expression at specifically chosen developmental time points. We show that the timeline of nodal restoration has different outcomes in the PNS and CNS with respect to nodal reassembly and functional restoration. In the PNS, restoration of nodes occurs within 1 month regardless of the time of βIV spectrin re-expression. In contrast, the CNS nodal reorganization and functional restoration occurs within a critical time window; after that, nodal reorganization diminishes, leading to less efficient motor recovery. We demonstrate that timely restoration of nodes can improve both the functional properties and the ultrastructure of myelinated fibers affected by long-term nodal disorganization. Our studies, which indicate a critical timeline for nodal restoration together with overall motor performance and prolonged life span, further support the idea that nodal restoration is more beneficial if initiated before any axonal damage, which is critically relevant to demyelinating disorders. SIGNIFICANCE STATEMENT Nodes of Ranvier are integral to efficient and rapid signal transmission along myelinated fibers. Various demyelinating disorders are characterized by destabilization of the nodal molecular complex, accompanied by severe reduction in nerve conduction and the onset of motor and sensory dysfunctions. This study is the first to report in vivo reassembly of destabilized nodes with sequential improvement in overall motor performance. Our study reveals that nodal restoration is achievable before any axonal damage, and that long-term nodal destabilization causes irreversible axonal structural changes that prevent functional restoration. Our studies provide significant insights into timely restoration of nodal domains as a potential therapeutic approach in treatment of demyelinating disorders.
Knowledge Sharing by Older Adults: An Empirical Study

With the increasing proportion of aging population worldwide, online communities that supports knowledge sharing * among older adults have received special attention for the host of psychological benefits they could bring [1-4]. However, despite the above-mentioned beneficial outcomes of using online knowledge sharing virtual communities (KSVCs) for older adults, the two types of user activities, i.e. knowledge contribution (KC) and knowledge seeking (KS), are often examined together as “social interactions” in the context of older adults [5]. There is a paucity of literature that examines how each type of activity affects older adults’ satisfaction in its respective way. Moreover, older adults may react to the aging process differently, and accordingly differ in their psychological and emotional states based on their individual coping strategy [6-8]. It is possible that KC and KS activities have different effects on older adults’ satisfaction, depending on their emotional states. Therefore, the aim of this study is to address the key research question: How do socioemotional aspects pertinent to the aging phenomenon influence older adult’s satisfaction derived from knowledge contribution and knowledge seeking activities in knowledge sharing virtual communities?
THE 5.25 AND 5.7 μm ASTRONOMICAL POLYCYCLIC AROMATIC HYDROCARBON EMISSION FEATURES

Astronomical mid-IR spectra show two minor polycyclic aromatic hydrocarbon (PAH) features at 5.25 and 5.7 μm (1905 and 1754 cm−1) that hitherto have been little studied, but contain information about the astronomical PAH population that complements that of the major emission bands. Here, we report a study involving both laboratory and theoretical analysis of the fundamentals of PAH spectroscopy that produce features in this region and use these to analyze the astronomical spectra. The Infrared Space Observatory Short Wavelength Spectrograph spectra of 15 objects showing these PAH features were considered for this study, however only four (HD 44179; NGC 7027; Orion Bar, two positions) have sufficient signal-to-noise between 5 and 6 μm to allow for an in-depth analysis. All four astronomical spectra show similar peak positions and profiles. The 5.25 μm feature is peaked and asymmetric, with an FWHM of about 0.12 ± 0.01 μm (∼40 ± 6.5 cm−1), while the 5.7 μm feature is broader and flatter, with an FWHM of about 0.17 ± 0.02 μm (50 ± 5.6 cm−1). Detailed analysis of the laboratory spectra and quantum-chemical calculations show that the astronomical 5.25 and 5.7 μm bands are a blend of combination, difference and overtone bands primarily involving CH stretching and CH in-plane and CH out-of-plane bending fundamental vibrations. The experimental and computational spectra show that, of all the hydrogen adjacency classes that are possible on PAHs, solo and duo hydrogens consistently produce prominent bands at the observed positions, whereas quartet hydrogens do not. In all, this study supports the picture that astronomical PAHs are large with compact, regular structures. From the coupling with primarily strong CH out-of-plane bending modes, one might surmise that the 5.25 and 5.7 μm bands track the neutral PAH population. However, theory suggests that the role of charge in these astronomical bands might also be important.
Variational total curvature model for multiplicative noise removal

The multiplicative noise removal problem has received considerable attention recently. To solve this problem, various variational models have been proposed, which minimise an energy functional composed of the data term and the regularisation term. Regarding the regularisation term, a first-order model is frequently used to remove multiplicative noise, which may cause staircase effect and loss of contrast in the output image. In this study, the authors use a second-order model, the total curvature (TC), to solve the above problem. The TC model has the benefit of removing the staircase effect and maintaining image edges, contrasts and corners. The augmented Lagrange method is utilised to solve the proposed TC model by introducing auxiliary variables, Lagrange multipliers and using alternating optimisation strategy. In each loop of optimisation, the fast Fourier transform, generalised soft threshold formulas, projection method and gradient descent method are integrated effectively. The experimental results show that the TC model can effectively remove staircase effect and preserve smoothness, via comparison with the first-order model (total variation regularisation and Perona-Malik regularisation). Furthermore, the TC model is better than another second-order model based on bounded Hessian regularisation in preserving contrast and corner.
On-Orbit Optical Camera Self-Calibration for Cislunar Explorers

This manuscript describes a method for estimating an optical camera’s intrinsic parameters as well as lens distortion parameters from two or more images with relative point correspondences. The method uses a nonlinear least squares algorithm with optional constraints and requires no inertial information such as star positions. This is known as self-calibration, since the method relies on relative rather than inertial point correspondences for calibration. This approach is applied to the specific problem of on-orbit camera calibration for the optical navigation subsystem of Cislunar Explorers; however, it can be extended to applications beyond spacecraft imaging such as calibration of general stereo-vision systems. Through simulated images, the algorithm in this manuscript demonstrates fast convergence from large initial deviations in intrinsic and lens distortion parameters. Sensitivity analysis using image noise is conducted to test the robustness of the algorithm.
Secondary hyperparathyroidism among end-stage renal disease patients in Beharlou hospital, Tehran province, Iran

Introduction: The importance of secondary hyperparathyroidism (SHPT) are frequently neglected in hemodialysis (HD) centers.Objectives: The aim of this study is to determine the prevalence of SHPT in a group of ESRD patients under routine HD.Patients and Methods: From May 2016 to August 2016, this cross sectional study was conducted on ESRD patients undergoing HD in our HD center in Beharlou hospital, Tehran province, Iran. Blood samples were obtained prior to HD session to assess laboratory parameters including intact PTH level, serum calcium, phosphorus, and alkaline phosphatase. Immunoradiometric assay was used to measure serum intact PTH (iPTH) level.Results: Forty-five HD patients, including 19 females (42.2%) with mean age of 60±14.3 years were enrolled to the study. According to the Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines for mineral metabolism, 60% of our patients (n = 27) had accepted normal range of serum calcium (8.4 to 9.5 mg/dL) while 28.9% of patients had serum calcium of below 8.4 mg/dL. Around 60% of our patients (n = 27) had accepted normal range of serum phosphorus (3.5 to 5.5 mg/dL) while serum phosphorus above 5.5 mg/dL was detected in 31.1% of HD patients. Sixteen patients (35.55%) had iPTH levels between 150-300 ρg/mL which was in the accepted ranges for iPTH levels among HD patients. Seventeen patients (37.78%) had iPTH levels above accepted range.Conclusion: This study showed that PTH abnormalities and disorders of mineral metabolism are common among patients with ESRD. It is crucial to better understand the pathogenesis and treatment of these disorders among ESRD patients.Keywords: Hemodialysis, Parathyroid hormone, Secondary hyperparathyroidism, End-stage renal disease, Parathormone, Chronic kidney disease, Parathormone
In Silico Modeling ofMalaria and Sickle-Cell Disease

In silico modeling of hematologic diseases and disorders (e.g., malaria, sickle cell anemia) has proved to make a significant contribution to the understanding of various disease processes and their progression. This review presents a general computational framework for modeling blood flow on a single cell level applied here to malaria and sickle cell disease. The computational disease model is validated using a number of independent experimental results. The simulation approach is general enough to address a broad range of issues related to hematologic diseases and disorders with implications for diagnostics and treatment.