Miracle-dz/UniFAR-FTUs huggingface dataset:
PCA-based network-wide correlated anomaly event detection and diagnosis

High-performance computing environments supporting large-scale distributed computing applications need multi-domain network performance measurements from open frameworks such as perfSONAR. Network-wide correlated anomaly events that can potentially impact data throughput performance need to be quickly and accurately notified for smooth computing environment operations. Since network topology is not always available along with the measurements data, it is challenging to identify and locate network-wide correlated anomaly events that impact data throughput performance. In this paper, we present a novel PCA-based correlated anomaly event detection scheme that can fuse multiple time-series of measurements and transform them using principal component analysis. We demonstrate using actual perfSONAR one-way delay measurement datasets that our scheme can: (a) effectively distinguish between correlated and uncorrelated anomalies, (b) leverage a source-side vantage point to diagnose whether a correlated anomaly event location is local or in an external domain, (c) act as a “black-box” correlation analysis tool for key insights in eventual root-cause identification.
Identification and Characterization of thescl Gene Encoding a Group A StreptococcusExtracellular Protein Virulence Factor with Similarity to Human Collagen

ABSTRACT Group A Streptococcus (GAS) expresses cell surface proteins that mediate important biological functions such as resistance to phagocytosis, adherence to plasma and extracellular matrix proteins, and degradation of host proteins. An open reading frame encoding a protein of 348 amino acid residues was identified by analysis of the genome sequence available for a serotype M1 strain. The protein has an LPATGE sequence located near the carboxy terminus that matches the consensus sequence (LPXTGX) present in many gram-positive cell wall-anchored molecules. Importantly, the central region of this protein contains 50 contiguous Gly-X-X triplet amino acid motifs characteristic of the structure of human collagen. The structural gene (designated scl for streptococcal collagen-like) was present in all 50 GAS isolates tested, which together express 21 different M protein types and represent the breadth of genomic diversity in the species. DNA sequence analysis of the gene in these 50 isolates found that the number of contiguous Gly-X-X motifs ranged from 14 in serotype M6 isolates to 62 in a serotype M41 organism. M1 and M18 organisms had the identical allele, which indicates very recent horizontal gene transfer. The gene was transcribed abundantly in the logarithmic but not stationary phase of growth, a result consistent with the occurrence of a DNA sequence with substantial homology with a consensus Mga binding site immediately upstream of the sclopen reading frame. Two isogenic mutant M1 strains created by nonpolar mutagenesis of the scl structural gene were not attenuated for mouse virulence as assessed by intraperitoneal inoculation. In contrast, the isogenic mutant derivative made from the M1 strain representative of the subclone most frequently causing human infections was significantly less virulent when inoculated subcutaneously into mice. In addition, both isogenic mutant strains had significantly reduced adherence to human A549 epithelial cells grown in culture. These studies identify a new extracellular GAS virulence factor that is widely distributed in the species and participates in adherence to host cells and soft tissue pathology.
The Energy Landscape, Folding Pathways and the Kinetics of a Knotted Protein

The folding pathway and rate coefficients of the folding of a knotted protein are calculated for a potential energy function with minimal energetic frustration. A kinetic transition network is constructed using the discrete path sampling approach, and the resulting potential energy surface is visualized by constructing disconnectivity graphs. Owing to topological constraints, the low-lying portion of the landscape consists of three distinct regions, corresponding to the native knotted state and to configurations where either the N or C terminus is not yet folded into the knot. The fastest folding pathways from denatured states exhibit early formation of the N terminus portion of the knot and a rate-determining step where the C terminus is incorporated. The low-lying minima with the N terminus knotted and the C terminus free therefore constitute an off-pathway intermediate for this model. The insertion of both the N and C termini into the knot occurs late in the folding process, creating large energy barriers that are the rate limiting steps in the folding process. When compared to other protein folding proteins of a similar length, this system folds over six orders of magnitude more slowly.
The creative processes in video game development : a model set illustrating the creative processes with theoretical and practical implications

This thesis sets out to examine the creative process in developing large TV console video games. Using methods based on the philosophy of Grounded Theory, interviews were conducted at four game development studios. From these interviews and the extant literature, a Model Set was constructed to reflect the creative process. The underlying premise of the Model Set is that a Darwinian process of variation, selection, and retention, is the kernel of the creating process. The Model Set is comprised of four components: a rigorous domain specific definition of the creative process, a defined perspective, a Core Creating Model, and a Creative Continuum. The Core Creating Model is the mechanism of the creating process, while the Creative Continuum provides a platform to evaluate the video game in terms of the creative definition. Following from the Model Set are four key research findings as contributions to knowledge and current research directions. These findings are: 1) Creativity is not all about ideas, as commonly perceived. Decision-making is a fundamental element of creativity, 2) The Core Creating Mechanism provides a distinction between Creativity and Discovery, while placing both within an understandable context, 3) The Model Set challenges the common assumption that more creativity is better, 4) The creative process is structured in multiple ways. It is of critical importance to understand these difference structures when researching and managing the creative process. The creative process in video game development is not monotonic: it is bimodal, that is, there is creativity both at the beginning and at the conclusion of the development process. Not all creative processes follow this pattern. The Model Set and four key research findings are a contribution to knowledge as they expand and deepen our understanding of the creative process. From these findings, the thesis discusses the theoretical and practical implications of the research.
Usability Factors Assessment in Health Information System

Systems’ usability is one of the critical attribute of any system’s quality. Medical prac-titioners usually encounter usability difficulties while using a health information system like other systems. There are different usability factors, which are expected to influence systems’ usability. Errors preventions, patient safety and privacy are vital usability factors and should not be ignored while developing a health information system. This study is based on a comprehensive analysis of published academic and industrial literature to provide the current status of health information systems’ usability. It also identifies different usability factors such as privacy, errors, design and efficiency. Usability factors are then assessed. Those factors are further examined through a questionnaire to study the priorities of them from medical practitioners’ point of view in Saudi Arabia. The statistical analysis shows that the privacy and errors are very critical than the other usability factors. The study results further revealed that availability and response time are the main challenges faced by the medical practitioners when using the HIS. However, flexibility and customizability were claimed to ease the use of the HIS. In addition, a number of statistical correlations were established. Overall, the study findings seemed helpful to designers and implementers to consider these factors for successful implementation of HIS.
Strategic information technology management: the city of Anaheim technological initiatives

This paper reports the findings of an exploratory study investigating the role of IT in a municipal-owned and operated public utility. Through the use of case study methodology, the paper finds a confluence of contextual factors fostering changes in an IT management strategy aimed at increasing efficiency and effectiveness of service delivery and improving customer/citizen satisfaction. These factors include changes in the regulatory policy environment, advances in technology, increasing citizen and customer knowledge and sophistication about IT, and managerial and elected official commitment to an IT strategy. The paper begins by proposing a model of the IT strategic planning process that occurs in municipal environments and then details several IT initiatives of the municipality in relation to the proposed model. The study finds that the complex nature of technology and its financial risk due to quick obsolescence poses political risks for the organization attempting to manage the IT infrastructure, which changes at a far faster pace than the organization's other types of infrastructure. The strategic management of IT must take into account the differing value sets among its organizational and political members and how these differing motivations impact the management of the IT infrastructure.
Visualizing Roles of Variables to Novice Programmers

Many students learning to write computer programs encounter considerable difficulties. For novices, one of the key problems is in understanding how the very basic programming constructs work. In this paper, we concentrate on visualizing the role of a variable, i.e., the dynamic character of a variable embodied by the sequence of its successive values as related to other variables. We present a classification of roles and introduce an animation system, PlanAni, that uses this approach.
Determination of thermal inactivation kinetics of Hepatitis A virus in blue mussel ( Mytilus 1 edulis ) homogenate 2 3 4 5

Determination of thermal inactivation kinetics of Hepatitis A virus in blue mussel (Mytilus 1 edulis) homogenate 2 3 4 5 Hayriye Bozkurt, Doris H. D’Souza, P. Michael Davidson 6 7 8 9 Department of Food Science and Technology, The University of Tennessee, Knoxville, TN, 10 USA. 11 12 13 Running Head: Thermal inactivation of Hepatitis A in blue mussels 14 15 16 Address correspondence to P. Michael Davidson, pmdavidson@utk.edu. 17
The effect of breakfast consumption prior to exercise on cognitive performance, mood and appetite

Exercise can improve mood and some facets of cognitive performance acutely and may suppress appetite transiently. Breakfast consumption is associated with mood and memory enhancement and superior control of appetite and body weight. Beneficial pre-exercise nutritional practices for those who exercise for mood, cognitive and appetite benefits, rather than to improve physical performance, have not been well established. Therefore, the current PhD programme aimed to uncover the potential effects of breakfast consumption prior to exercising on cognitive function, mood and appetite later in the day, with a particular focus on recreationally active females, an under-represented population in this area of research. The results from two intervention studies presented in this thesis determined that consuming, compared to omitting, breakfast prior to exercise reduced appetite until the next meal was consumed and abridged mental fatigue in the post-exercise recovery period in active males (Chapter 2) and females (Chapter 5). Active females may choose to undertake morning exercise in a fasted state to avoid discomfort during exercise and due to lack of time (Chapter 3), but postexercise, overall mood positively correlated, and mental fatigue inversely correlated with breakfast size prior to exercise in active females when assessed in a field setting (Chapter 4); however, consuming a lower energy dense breakfast still elicited the aforementioned positive effects, and was preferential to consuming a larger breakfast to avoid cognitive detriments in the afternoon when measured in a laboratory setting (Chapter 5). To conclude, the results from this thesis suggest that consuming breakfast prior to morning exercise is beneficial for post-exercise mood and appetite in both habitually active men and women, but consuming a large breakfast may impair cognitive function after exercise. Consuming a light breakfast pre-exercise may be a particularly beneficial practice for habitual female exercisers who chose to omit breakfast prior to exercise due to lack of time or to avoid discomfort during exercise.
Sybil attack detection based on signature vectors in VANETs

Sybil attack is one of the serious threats in vehicular ad hoc networks (VANETs) because drivers may receive wrong information, which could lead to injury the lives of the drivers and passengers, when they are under Sybil attack. This paper, therefore, presents a novel solution named Sybil attack detection based on signature vectors (SADSIV) in VANETs. Each node gathers the digital signatures in their moving; then our algorithm detects Sybil attack by analysing and comparing vehicle nodes' signature vectors independently under the condition of inadequate infrastructures. We improve the feasibility of our approach through the limited infrastructures at the early deployment stages of VANETs. In addition, the independency and feasibility of our algorithm are more robust than the existing solutions which rely on collaboration of neighbouring nodes. Simulation results show that our method outperforms the existing detection schemes in terms of robustness, detection rate and lower system requirements.
The challenge of the proteome dynamic range and its implications for in‐depth proteomics

The dynamic range of the cellular proteome approaches seven orders of magnitude—from one copy per cell to ten million copies per cell. Since a proteome's abundance distribution represents a nearly symmetric bell‐shape curve on the logarithmic copy number scale, detection of half of the expressed cellular proteome, i.e. approximately 5000 proteins, should be a relatively straightforward task with modern mass spectrometric instrumentation that exhibits four orders of magnitude of the dynamic range, while deeper proteome analysis should be progressively more difficult. Indeed, metaanalysis of 15 recent papers that claim detection of >5000 protein groups reveals that the half‐proteome analyses currently requires ≈5 h of chromatographic separation, while deeper analyses yield on average ≤20 new proteins per hour of chromatographic gradient. Therefore, a typical proteomics experiment consists of a “high‐content” part, with the detection rate of approximately 1000 proteins/h, and a “low‐content” tail with much lower rate of discovery and respectively, lower cost efficiency. This result calls for disruptive innovation in deep proteomics analysis.
2 Basic Notions from Learning

An easy example of a concept class is the set of emails and functions mapping emails to spam or not spam. Another example is the set of points and a line `, and a single function determining which side of the line ` the points are on. PAC learning is the following problem. We are given a concept class H, a function f ∈ H, and a hidden distribution D on X. The algorithm is allowed to get m labeled examples (xi, f(xi)) for 1 ≤ i ≤ m, by drawing each xi ∈ X according to the distribution D. We want that for any constants , δ, after getting these m examples, with probability 1 − δ, the algorithm should ensure that the error on future examples drawn from the distribution D is ≤ . The δ denotes the probably, and the denotes the approximately in the name PAC learning. Our final definition here will be a weak learner. Definition 2. A weak learner is one that has error at most 1 2 − η for some η > 0.
A practical example of increasing net transfer capacity (NTC) by modifying the power system topology

The construction of new transmission facilities, or enhancing transmission network, increases the reliability and security of the power system. Enhancing transmission network increases the amount of power that can be transmitted through the system, which, in most cases, allows the increase of electricity trading volume. However, in practice there may be cases, primary due to methods used for congestion management, where construction of new transmission facility, which was built in order to increase the reliability and security of the system, reduces the amount of power available to market participants for electricity trading. This paper is an example of one such case, as well as the proposal on how changing of the topology of transmission network can counteract this phenomenon, and take advantage of newly constructed transmission facilities.
Non-governmental organisations and the Truth and Reconciliation Commission: an impact assessment

Abstract This article examines the relationship between Non‐Governmental Organisations (NGOs) and the Truth and Reconciliation Commission (TRC). Based mainly on interviews with NGO and TRC staff, the article outlines the various ways that NGOs participated in the development of the TRC legislation and engaged with TRC structures. The shape of this engagement was very uneven depending on the stage of the TRC process: the strongest input came at the point of lobbying in response to draft legislation. Different NGO sectors (human rights, conflict resolution, mental health) also had different levels of engagement at different stages of the process. The article evaluates the impact that NGOs had on the TRC (and vice versa), and critically evaluates the general failure of NGOs to effectively mobilise around the principles and strategic concerns raised by the TRC. The constraints on the development of an effective relationship are found to be located both in the structure and processes of the TRC, as well as wit.
Finding Frequent Patterns Based On Quantitative Binary Attributes Using FP-Growth Algorithm

Discovery of frequent patterns from a large database is considered as an important aspect of data mining. There is always an ever increasing demand to find the frequent patterns. This paper introduces a method to handle the categorical attributes and numerical attributes in an efficient way. In the proposed methodology, ordinary database is converted in to quantitative database and hence it is converted in to binary values depending on the condition of the student database. From the binary patterns of all attributes presented in the student database, the frequent patterns are identified using FP growth,The conversion reveals all the frequent patterns in the student database.
Effect of a Health Belief Model-based nursing intervention on Chinese patients with moderate to severe chronic obstructive pulmonary disease: a randomised controlled trial.

AIMS AND OBJECTIVES To test the effect of a Health Belief Model-based nursing intervention on healthcare outcomes in Chinese patients with moderate to severe COPD. BACKGROUND The Health Belief Model (HBM) has been internationally validated in a variety of chronic conditions. However, nursing intervention based on the HBM is less explored in Chinese patients with COPD. DESIGN A randomised controlled trial. METHODS Enrolled patients were randomly assigned to the intervention and control groups. Patients in the intervention group received a 20- to 30-minute HBM-based nursing intervention every 2 days during the hospitalisation period after disease conditions were stable, with additional follow-ups after discharge. Patients in the control group received routine nursing care. RESULTS Patients had significantly increased scores of health belief and self-efficacy after receiving the HBM-based nursing intervention. After receiving the 3-month follow-up, patients in the intervention group had significantly higher mean total scores in the Health Belief Scale and the COPD Self-Efficacy Scale, as well as in all the subscales, than those in the control group except the perceived disease seriousness. Results showed that the value of FEV1 /FVC ratio had a significant difference between study groups before and after the intervention. Results also indicated that mean scores of the Dyspnea Scale, 6-minute walking distance and ADL were significantly different between the groups and between the study time-points. CONCLUSIONS Among patients with moderate to severe COPD, nursing intervention based on the HBM can enhance their health belief and self-efficacy towards the disease management, decrease dyspnoea and improve exercise tolerance and ADL. RELEVANCE TO CLINICAL PRACTICE Nurses can use the HBM-based intervention to enhance patients' health belief and self-efficacy towards the management of COPD, and subsequently benefit healthcare outcomes.
Localizing and Estimating Causal Relations of Interacting Brain Rhythms

Estimating brain connectivity and especially causality between different brain regions from EEG or MEG is limited by the fact that the data are a largely unknown superposition of the actual brain activities. Any method, which is not robust to mixing artifacts, is prone to yield false positive results. We here review a number of methods that allow for addressing this problem. They are all based on the insight that the imaginary part of the cross-spectra cannot be explained as a mixing artifact. First, a joined decomposition of these imaginary parts into pairwise activities separates subsystems containing different rhythmic activities. Second, assuming that the respective source estimates are least overlapping, yields a separation of the rhythmic interacting subsystem into the source topographies themselves. Finally, a causal relation between these sources can be estimated using the newly proposed measure Phase Slope Index (PSI). This work, for the first time, presents the above methods in combination; all illustrated using a single, simulated data set.
Cluster correlations in redshift space

We test an analytic model for the two-point correlations of galaxy clusters in redshift space using the Hubble volume N-body simulations. The correlation function of clusters shows no enhancement along the line of sight, owing to the lack of any virialized structures in the cluster distribution. However, the distortion of the clustering pattern arising from coherent bulk motions is clearly visible. The distribution of cluster peculiar motions is well described by a Gaussian, except in the extreme high-velocity tails. The simulations produce a small but significant number of clusters with large peculiar motions. The form of the redshift-space power spectrum is strongly influenced by errors in measured cluster redshifts in extant surveys. When these errors are taken into account, the model reproduces the power spectrum recovered from the simulation to an accuracy of 15 per cent or better over a decade in wavenumber. We compare our analytic predictions with the power spectrum measured from the APM cluster redshift survey. The cluster power spectrum constrains the amplitude of density fluctuations, as measured by the linear rms variance in spheres of radius 8 h - Mpc, denoted by σ 8 . When combined with the constraints on σ 8 and the density parameter Ω derived from the local abundance of clusters, we find a best-fitting cold dark matter model with σ 8 1.25 and Ω 0.2, for a power spectrum shape that matches that measured for galaxies. However, for the best-fitting value of Ω and given the value of Hubble's constant from recent measurements, the assumed shape of the power spectrum is incompatible with the most readily motivated predictions from the cold dark matter paradigm.