Miracle-dz/UniFAR-FTUs huggingface dataset:
Grace: Safe and Efficient Concurrent Programming

The shift from single to multiple core architectures means that, in order to increase application performance, programmers must write concurrent, multithreaded programs. Unfortunately, multithreaded applications are susceptible to numerous errors, including deadlocks, race conditions, atomicity violations, and order violations. These errors are notoriously difficult for programmers to debug. We present Grace, a runtime system for multithreaded programs written in C/C++ that provides good scalability and performance while eliminating a range of concurrency errors. With Grace, multithreaded programs behave as if all threads were run sequentially. Grace exploits available CPU resources by combining speculative thread execution, supported by a novel virtual memory based transactional memory system, together with a sequential commit protocol that guarantees sequential semantics. We show that Grace ensures the correctness of otherwise-buggy multithreaded programs. Across a suite of CPU-intensive multithreaded applications, Grace often achieves performance and scalability comparable to unsafe thread libraries.
Towards a Scalable Representation of Run-time Information: The Challenge and Proposed Solution

An important issue in application modernization is the time and effort needed to understand existing applications. Understanding the dynamic aspects of software is a difficult task, further complicated by the lack of a scalable way of representing the extracted knowledge. The behavior of a software system is typically represented in the form of execution traces. Traces, however, can be extraordinary large. Existing metamodels such as the Knowledge Discovery Metamodel and the UML metamodel provide limited support for handling large execution traces. In this paper, we describe a metamodel called the Compact Trace Format (CTF) for efficient modeling of traces of routine (method) calls generated from multi-threaded systems. CTF is intended to facilitate the interoperability among modernization tools that focus on the analysis of the behavior of software systems. CTF is designed to be easily extensible to support other types of traces.
- 1-AN UPDATE ON INPATIENT GLYCEMIC CONTROL IN U . S . HOSPITALS

Objective: To provide data on glucose control in US hospitals, analyzing measurements from the largest number of facilities to date. Methods: Point-of-care bedside glucose (POC-BG) tests were extracted from 575 hospitals from January 2009 to December 2009 using a laboratory information management system. Glycemic control for patients in the intensive care unit (ICU) and non-ICU areas was assessed by calculating patient-day-weighted mean POC-BG values and rates of hypoglycemia and hyperglycemia. The relationship of POC-BG levels with hospital characteristics was determined. Results: A total of 49,191,313 POC-BG measurements (12,176,299 ICU; 37,015,014 non-ICU) were obtained from 3,484,795 patients (653,359 ICU; 2,831,436 non-ICU). The mean POC-BG was 167 mg/dL for ICU patients and 166 mg/dL for nonICU patients. The prevalence of hyperglycemia (>180 mg/dL) was 32.2% in ICU patients and 32.0% in non-ICU patients. The prevalence of hypoglycemia (<70 mg/dL) was 6.3% in ICU patients and 5.7% in non-ICU patients. Patient-day-weighted mean POC-BG levels varied according to hospital size (P<.01), type (P<.01), and geographic location (P<.01) for ICU and non-ICU patients, with larger (≥400 beds), academic, and Western hospitals having the lowest mean POC-BG. The percentage of patient days in the ICU characterized by hypoglycemia was highest among larger and academic hospitals (P<.05) and least among hospitals in the Northeast (P<.001). Conclusions: Hyperglycemia is common in US hospitals, and glycemic control may vary according to hospital characteristics. Increased hospital participation in data warehousing may support a national benchmarking process for the development of best practices to manage inpatient hyperglycemia.
Intracellular Site of Sr 2 + and Ba 2 + Accumulation in Frog Twitch Muscle Fibres as Determined by Electron Probe X-ray

Strontium and barium can substitute for calcium at different levels of the excitation-contraction-relaxation cycle. The problem of sequestration of these ions in cellular microcompartments may be settled only by direct evidence obtained with analytical methods. Isolated frog twitch muscle fibres were perfused with increasing concentrations of potassium in Ca-free solution supplemented with Sr + (10mmol/l) or Ba (5mmol/l). After equilibration in a Ca-free Ringer with Sr f or Ba for 30 to 60 min the fibres were frozen in liquid propane (at 80 K) to immobilise ions. Ultrathin (150nm) cryosections were cut at 170K, freeze-dried, carbon-coated and analysed in an electron microscope equipped with an X-ray spectrometer. The ultrastructure of the superficial layer of the fibres was satisfactorily preserved. The terminal cisternae (t. c.) of the sarcoplasmic reticulum (SR) were dark and contained various amounts of Sr or Ba in addition to Ca. In Sr loaded fibres the longitudinal SR occasionally showed electron dense content with significant amounts of Ca; no Sr was present. The results suggest that t. c. is the common sequestering compartment for Ca, Sr and Ba. Essentially the same distribution pattern of Sr was found following precipitation of Sr with a solution containing digitonin and Koxalate.
Increasing Inequality: The Effect of GOTV Mobilization on the Composition of the Electorate

Numerous get-out-the-vote (GOTV) interventions are successful in raising voter turnout. However, these increases may not be evenly distributed across the electorate and could potentially increase the differences between voters and nonvoters. By analyzing individual level-data, we reassess previous GOTV experiments to determine which interventions mobilize under-represented citizens versus those who regularly turn out. We develop a generalized and exportable test which indicates whether a particular intervention reduces or exacerbates disparities in political participation and apply it to 24 previous experimental interventions. On average, current mobilization strategies significantly widen disparities in participation by mobilizing high-propensity individuals more than the under-represented, low-propensity citizens. The results hold troubling implications for the study and improvement of political inequality, but the methodological procedures laid out in this study may assist the development and testing o.
Myocardial Infarction Detection Using Hybrid BSS Method

This paper introduces a new technique for detecting myocardial infarction (MI) from patients ECGs. Nowadays MI is one of the major cause of death worldwide. MI is a minor stage in lifelong cardiac disease, which is often unnoticed and leads to sudden death. MI is the first symptom of coronary artery disease. So it is very important to detect MI in an earlier stage. To detect MI from ECG, several methods are employed. But the problem is to detect MI in an earlier stage and efficiently from noisy signal. The problem is in data acquisition. Several noises are mixed with ECG at the time of data acquisition and this make the extraction difficult. The noises are due to respiration, EMG etc. The inefficiency of low pass filters in ECG machine add these signals to ECG. So a perfect denoising technique for getting good input data is required. This is inevitable for the detection of small variations. The existing techniques use filters like notch and adaptive for denoising since they are not considering this raw ECG. It is proved that Independent Component Analysis (ICA) based on blind source seperation (BSS) algorithms, is the effective tool for extracting ECG from mixed raw signal. Better denoising gives better results in earlier detection of MI. Thus the main aim of this work is to detect myocardial infarction in an earlier stage. The classification is done using naïve bayes classifier. Our algorithm gives 96.77% accuracy on PhysioNet ECG database, which is supported by the National Institute of General Medical Sciences (NIGMS) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB). Keywords—Myocardial Infarction, ECG, Polynomial fitting, Bayesian classifier, Naïve bayes classifier, fastICA, EFICA, WASOBI
ATINER ' s Conference Paper Series EDU 2015-1634

The intricate cultural, social, economic and developmental diversity as well as the policy shift from dual track systems to inclusive education systems characterising contemporary classrooms challenge teachers to explore more effective teaching methods to suit all learning needs. As a plethora of literature suggests, acquiring more knowledge and mastering skills is not enough for competency acquisition to successfully implement and sustain change in the long-term. One’s sense of efficacy impacts aspirations, attitudes and behaviours regarding the ability to bring about change. Thus, to encourage the adoption of effective, sustainable methodological approaches teachers need to embark on an exploratory journey of what Bourdieu (1984) coined as habitus; the expression for deeply embodied ways of doing and thinking that is strongly affected by the dynamic interplay of personal, behavioural and environmental factors (Bandura, 1986). Since the early 1900s, reflective practice has been identified and advocated as meaningful and expected instructional practice for professional development and lifelong learning. However, critical approaches to reflection may often create discomforts when what has become ‘secondnature’ is questioned. As Sibilio (2014) postulated, the simplifying principles and properties identified in the theory of simplexity (Berthoz, 2012) may offer a constructive and creative starting point to reflect on one’s practices and ultimately face this complexity with a new mindset.
Predictions , Surprise , and Predictions of Surprise in General Value Function Architectures

Effective life-long deployment of an autonomous agent in a complex environment demands that the agent has some model of itself and its environment. Such models are inherently predictive, allowing an agent to predict the consequences of its actions. In this paper, we demonstrate the use of General Value Functions (GVFs) for learning and representing such a predictive model on a robotic arm. Our model is composed of three types of signals: (1) predictions of sensorimotor signals, (2) measures of surprise using Unexpected Demon Error (UDE) and (3) predictions of surprise. In a proof-ofprinciple experiment, where the robot arm is manually perturbed in a recurring pattern, we show that each perturbation is detected as a jump in the surprise signal. We demonstrate that the recurrence of these perturbations not only can be learned, but can be anticipated. We propose that introspective signals like surprise and predictions of surprise might serve as a rich substrate for more abstract predictive models, improving an agent’s abilitypredictive models, improving an agent’s ability to continually and independently learn about itself and its environment to fulfill its goals.
Automatic Refactoring of Single and Multiple-view UML Models using Artificial Intelligence Algorithms

The majority of articles that discuss software refactoring are focusing on software code (Fowler and Beck, 1999, O'Keeffe and Cinnéide, 2008, Alkhalid et al., 2011b). Recently, a slight increase in the interest of refactoring at the design level emerged(Misbhauddin and Alshayeb, 2015). Different methods have been applied to refactor UML diagrams namely: pattern-based (Song et al., 2002a), formal rules (Massoni et al., 2005) and graph transformation (Mens, 2006). Refactoring UML diagrams is favorable since designing activity precedes coding and as such abnormalities, ill-structure or potential bugs can be detected and corrected early (Sunyé et al., 2001). Each UML diagram has different design smells and requires different refactoring operations. Refactoring UML design smells for each diagram manually exhibits some drawbacks such as: it’s costly in terms of cost and time and it requires domain experts. Automating the refactoring process surely will save time and cost and will help software practioners to improve their designs. Most of the other refactoring approaches are carried out on single instances of UML diagrams (Ghannem et al., 2011, Issa, 2007). In this research, we are extending the field by applying AI refactoring on a multiple-view UML model and comparing the results with individual UML diagrams. This will show the advantages of adopting multiple-view refactoring.
Quintessential Starobinsky inflation and swampland criteria

A simple model for the late-time cosmic acceleration problem is presented in the Starobinsky inflation with a negative bare cosmological constant as well as a non-minimal coupling to Higgs boson. After electroweak symmetry breaking, the Starobinsky inflaton is frozen until very recently becoming a thawing quintessence, and a comparable magnitude to the observed dark energy density can be achieved without fine-tuning. Our proposal essentially links the cosmological constant problem to the electroweak hierarchy problem, and it is also consistent with the recently proposed swampland criteria.
Shallow Seismicity Forecast for the India‐Eurasia Collision Zone Based on Geodetic Strain Rates

Geodetic strain rates from increasing Global Positioning System data provide a promising approach for seismicity forecast. With the strain rate field presented in Zheng et al. (2017, https://doi.org/10.1002/2017JB014465) derived from the most complete and up‐to‐date Global Positioning System data set in the India‐Eurasia collision zone, we forecast the shallow seismicity of this region, and infer that about 11 Mw ≥ 7.5, 36 Mw ≥ 7.0, 109 Mw ≥ 6.5, and 326 Mw ≥ 6.0 earthquakes may occur here every 100 years. We indicate that shallow seismicity forecast may be able to help us distinguish between block and continuum models, and block model cannot well describe the kinematics of the Tibetan Plateau, Tien Shan, West Mongolia, North China, and Myanmar. We suggest that the regions with high forecasted earthquake rates but lack of historical earthquakes are undergoing high seismic risk, such as the west‐central Himalaya (overdue for Mw ≥ 7.5 earthquakes, possibly Mw ≥ 8.0) and the central Altyn Tagh fault (overdue for Mw ≥ 7.0 and Mw ≥ 7.5 earthquakes).
Robust finite horizon MPC without terminal constraints

In this paper a procedure for obtaining the parameters of a finite horizon model predictive controller to make it equivalent to an H/sub /spl infin// normalised left coprime factorisation controller in the unconstrained case, is considered. The procedure is based on a linear matrix inequality approach to the solution of the discrete-time H/sub /spl infin// control problem and is solved by first considering the solution when the state is available for measurement.
Understanding the faint red galaxy population using large-scale clustering measurements from SDSS DR7

We use data from the SDSS to investigate the evolution of the large-scale galaxy bias as a function of luminosity for red galaxies. We carefully consider correlation functions of galaxies selected from both photometric and spectroscopic data, and cross-correlations between them, to obtain multiple measurements of the large-scale bias. We find, for our most robust analyses, a strong increase in bias with luminosity for the most luminous galaxies, an intermediate regime where bias does not evolve strongly over a range of two magnitudes in galaxy luminosity, and no evidence for an upturn in bias for fainter red galaxies. Previous work has found an increase in bias to low luminosities that has been widely interpreted as being caused by a strong preference for red dwarf galaxies to be satellites in the most massive haloes. We can recover such an upturn in bias to faint luminosities if we push our measurements to small scales, and include galaxy clustering measurements along the line of sight, where we expect non-linear effects to be the strongest. The results that we expect to be most robust suggest that the low-luminosity population of red galaxies is not dominated by satellite galaxies occupying the most massive haloes.
Instability mechanisms in swirling flows

We investigate the stability of the screened Rankine vortex with added plug flow where the azimuthal velocity decreases abruptly outside the core of the vortex. The jump in circulation is known to induce centrifugal and azimuthal Kelvin–Helmholtz instabilities. Their effect on the stability of the different azimuthal wave number m is discussed using physical considerations associated with asymptotic expansions and numerical computations of the dispersion relation. It is shown that the axial shear and centrifugal instability are active for all m, and that modes with |m|⩾2 are also destabilized by azimuthal shear. In contrast, the bending modes m=±1 are stabilized by a coupling with Kelvin waves in the core. Effects of rotation on the absolute/convective transition are also discussed. The absolute instability of positive helical modes is seen to be promoted by centrifugal instability and azimuthal shear.
Change in Dysfunctional Beliefs and Symptoms during Cognitive Behavior Therapy for Resistant Obsessive Compulsive Disorder

A central question in the field of Obsessive-Compulsive Disorder (OCD) is the role of symptom-related dysfunctional beliefs thought to underlie symptoms. This study examines change in symptoms and related dysfunctional beliefs during Cognitive Behavior Therapy (CBT) with 32 previously treatment resistant OCD patients. Three questions were examined: (a) What is the relationship between dysfunctional beliefs and symptoms at pre-treatment; (b) How much change occurs in symptoms, and related beliefs, during specialized CBT; and (c) What is the relationship between change in cognitive and symptom variables. On average, symptoms and related beliefs of symptomatic-responders resolved to within normallimits following treatment. Beliefs of patients whose symptoms did not improve remained unchanged. Pre-treatment strength of overestimation of threat and response to unpredictability were significant predictors of symptomatic improvement. Change in overcontrol of intrusive thoughts and overestimation of threat significantly predicted change in symptoms. Theoretical and treatment implications of the findings are discussed .
New Hope for Corporate Governance in China?

Abstract China's recent revisions to its Company Law and Securities Law have brought new attention to issues of corporate governance in Chinese companies and financial markets. Among the chief criticisms of the earlier laws – in both their provisions and application – were the lack of protection for minority shareholders, the paucity of independent directors, the absence of transparency and inadequate financial disclosure. The acknowledged need for greater congruence between Chinese law and practice and that of countries with more developed capital markets led to the proposal of amendments to China's legislation during the first half of this decade. This article highlights several improvements resulting from the revisions as well as remaining weaknesses in the regulatory framework for corporate enterprises in China.
My Dad's A Birdman

Lizzie and her dad worked all day and into the night, gathering feathers and string and thread and bits of cloth and coat-hangers and ribbons and buttons and beads. They stitched and snipped and stuck. By the next morning, Lizzie’s wings and her beak and her crest were just about done. Lizzie and Dad stood together at the door, both of them wearing their wings. They were worn out, but they were so happy, so proud of themselves. Lizzie leaned on her dad and said he was right, they were a fantastic team. Brilliant sunlight slanted over the rooftops and through the trees onto their happy and excited faces. Birds tweeted and whirled all around. The city traffic rumbled and roared. Dad giggled as he thought of what they could do next. ‘We need a nest, Lizzie,’ he said. ‘A nest? ’ ‘Aye. To make it all proper. To make us like proper birds. ’ Lizzie looked into his eyes. ‘Go on,’ he said. ‘It’ll make me happy. ’ She smiled and shrugged and said, ‘OK, Dad. What’ll we need? ’ Well, they needed grass and twigs and straw and leaves and string and ripped up tea towels, and bits of old shirt and bits of old jumper, and dusters and holey socks, and feathers, and carpet fluff. They carried all the bits and pieces into the kitchen, and they knelt on the floor and put everything together into the shape of a nest. Lizzie smiled and hummed as they worked. Dad tweeted and whistled and cawed. ‘Isn’t it lovely? ’ He said. ‘A proper little home for us. ’
Application of Texture Analysis Algorithm for Data Extraction in Dental X-Ray Images

: This paper presented an appropriate approach for the robust estimation of noise statistic in dental x-rays images. To achieve maximum image quality after denoising, a new, low order, local adaptive Gaussian Scale Mixture model is presented, which accomplishes nonlinearities from scattering. State of art methods use multi scale filtering of images to reduce the irrelevant part of information, based on generic estimation of noise. The usual assumption of a distribution of Gaussian and Poisson statistics only lead to overestimation of the noise variance in regions of low intensity (small photon counts), but to underestimation in regions of high intensity and therefore to non-optional results. In this paper, prominent constraints are firstly preservation of image's overall look; secondly preservation of the diagnostic content in the image and thirdly detection of small low contrast details in diagnostic content of the image. As shown in previously, state of the art methods provide non-convincing results. The new approach is funded on an attempt to interpret the problem from the view of blind source separation (BSS), thus to see the panoramic image as a simple mixture of (unwanted) background information, diagnostic information and noise.
Varied & Bespoke Needs of Caregivers: Organizing and Communicating Diabetes Care for Children in Era of DIY

Type 1 diabetes in children is a complex chronic condition that requires high levels of coordination among a range of caregivers in order to communicate and organize care for best health outcomes. We examined three types of care, at home, at school, and at the clinic, to explore the communication needs of a range of caregivers. Not only were there differences between types of caregiver, but there were also varied personal preferences for communication, different levels of knowledge regarding caregiving that required different forms of communication, and changes in child health leading to different care needs and communication styles. We frame these findings within the new trend of diabetes technologies that allow for cloud connected communication in order to show the need to respect varied and individual communication practices. Technologies that link current health data over the cloud may not have a one-size-fits-all solution for all caregivers, however, open-source DIY health trends may be a way towards supporting personalized communication needs.