Miracle-dz/UniFAR-FTUs huggingface dataset:
JetScope: Reliable and Interactive Analytics at Cloud Scale

Interactive, reliable, and rich data analytics at cloud scale is a key capability to support low latency data exploration and experimentation over terabytes of data for a wide range of business scenarios. Besides the challenges in massive scalability and low latency distributed query processing, it is imperative to achieve all these requirements with effective fault tolerance and efficient recovery, as failures and fluctuations are the norm in such a distributed environment. We present a cloud scale interactive query processing system, called JetScope, developed at Microsoft. The system has a SQL-like declarative scripting language and delivers massive scalability and high performance through advanced optimizations. In order to achieve low latency, the system leverages various access methods, optimizes delivering first rows, and maximizes network and scheduling efficiency. The system also provides a fine-grained fault tolerance mechanism which is able to efficiently detect and mitigate failures without significantly impacting the query latency and user experience. JetScope has been deployed to hundreds of servers in production at Microsoft, serving a few million queries every day.
Section: Clustering Cluster Validation Background on Cluster Validation

Spacecrafts orbiting a selected suite of planets and moons of our solar system are continuously sending long sequences of data back to Earth. The availability of such data provides an opportunity to invoke tools from machine learning and pattern recognition to extract patterns that can help to understand geological processes shaping planetary surfaces. Due to the marked interest of the scientific community on this particular planet, we base our current discussion on Mars, where there are presently three spacecrafts in orbit (e.g., NASA’s Mars Odyssey Orbiter, Mars Reconnaissance Orbiter, ESA’s Mars Express). Despite the abundance of available data describing Martian surface, only a small fraction of the data is being analyzed in detail because current techniques for data analysis of planetary surfaces rely on a simple visual inspection and descriptive characterization of surface landforms (Wilhelms, 1990). The demand for automated analysis of Mars surface has prompted the use of machine learning and pattern recognition tools to generate geomorphic maps, which are thematic maps of landforms (or topographical expressions). Examples of landforms are craters, valley networks, hills, basins, etc. Machine learning can play a vital role in automating the process of geomorphic mapping. A learning system can be employed to either fully automate the process of discovering meaningful landform classes using clustering techniques; or it can be used instead to predict the class of unlabeled landforms (after an expert has manually labeled a representative sample of the landforms) using classification techniques. The impact of these techniques on the analysis of Mars topography can be of immense value due to the sheer size of the Martian surface that remains unmapped. While it is now clear that machine learning can greatly help in automating the detailed analysis of Mars’ surface (Stepinski et al., 2007; Stepinski et al., 2006; Bue and Stepinski, 2006; Stepinski and Vilalta, 2005), an interesting problem, however, arises when an automated data analysis has produced a novel classification of a specific site’s landforms. The problem lies on the interpretation of this new classification as compared to traditionally derived classifications generated through visual inspection by domain experts. Is the new classification novel in all senses? Is the new classification only partially novel, with many landforms matching existing classifications? This article discusses how to assess the value of clusters generated by machine learning tools as applied to the analysis of Mars’ surface.
Life satisfaction and aphasia: an integrative review with recommendations for future research

ABSTRACT Background: Recent legislation in the United States has called for greater use of patient-reported outcomes to assess treatment effectiveness. Life satisfaction is a patient-reported outcome that is only recently receiving attention in the aphasia literature. Understanding life satisfaction among persons with aphasia (PWA) is critical to developing strategies that will assist these individuals in managing their lives after experiencing aphasia. Aims: The aim of this paper is to review life satisfaction among PWA for the purpose of stimulating further discussion and research. Main Contribution: We identified five studies with mixed results relating to life satisfaction after aphasia. Understanding life satisfaction among PWA is important as it reflects the individual’s response to this life changing communication disorder. However, the influence of a range of issues remains unclear with regard to life satisfaction and aphasia, including (a) the contributions of the individual’s clinical and sociodemographic characteristics, (b) the effects of time and (c) the methods used for measuring life satisfaction after aphasia. This review explores the complex factors associated with life satisfaction after aphasia. Conclusions: Studies of life satisfaction among PWA are lacking. Much needs to be learned about the range of factors associated with life satisfaction after aphasia. Understanding these issues is key to facilitating optimal post-aphasia outcomes from the perspective of the patient.
Evaluating the Similarity Estimator component of the TWIN Personality-based Recommender System

With the constant increase in the amount of information available in online communities, the task of building an appropriate Recommender System to support the user in her decision making process is becoming more and more challenging. In addition to the classical collaborative filtering and content based approaches, taking into account ratings, preferences and demographic characteristics of the users, a new type of Recommender System, based on personality parameters, has been emerging recently. In this paper we describe the TWIN (Tell Me What I Need) Personality Based Recommender System, and report on our experiments and experiences of utilizing techniques which allow the extraction of the personality type from text (following the Big Five model popular in the psychological research). We estimate the possibility of constructing the personality-based Recommender System that does not require users to fill in personality questionnaires. We are applying the proposed system in the online travelling domain to perform TripAdvisor hotels recommendation by analysing the text of user generated reviews, which are freely accessible from the community website.
Software Architecture Decoupling at Ericsson

In order to evaluate and increase modularity this paper combines a method for visualizing and measuring software architectures and two algorithms for decoupling. The combination is tested on a software system at Ericsson. Our analysis show that the system has one large cluster of components (18% of the system, a Core), all interacting with each other. By employing cluster and dominator analysis we suggest 19 dependencies to be removed in order to decouple the Core. Validating the analysis output with experts at Ericsson six of the suggested dependencies where deemed impossible to remove. By removing the remaining 13 dependencies Ericsson would improve the architecture of their system considerably, e.g. core size would go down to 5%.
PDF: A Probabilistic Data Fusion Framework for Retrieval and Ranking

Data fusion has been shown to be a simple and effective way to improve retrieval results. Most existing data fusion methods combine ranked lists from different retrieval functions for a single given query. But in many real search settings, the diversity of retrieval functions required to achieve good fusion performance is not available. Researchers are typically limited to a few variants on a scoring function used by the engine of their choice, with these variants often producing similar results due to being based on the same underlying term statistics. This paper presents a framework for data fusion based on combining ranked lists from different queries that users could have entered for their information need. If we can identify a set of "possible queries" for an information need, and estimate probability distributions concerning the probability of generating those queries, the probability of retrieving certain documents for those queries, and the probability of documents being relevant to that information need, we have the potential to dramatically improve results over a baseline system given a single user query. Our framework is based on several component models that can be mixed and matched. We present several simple estimation methods for components. In order to demonstrate effectiveness, we present experimental results on 5 different datasets covering tasks such as ad-hoc search, novelty and diversity search, and search in the presence of implicit user feedback. Our results show strong performances for our method; it is competitive with state-of-the-art methods on the same datasets, and in some cases outperforms them.
A ug 2 01 7 Diminishable Parameterized Problems and Strict Polynomial Kernelization

Kernelization—a mathematical key concept for provably effective polynomial-time preprocessing of NP-hard problems—plays a central role in parameterized complexity and has triggered an extensive line of research. This is in part due to a lower bounds framework that allows to exclude polynomial-size kernels under the assumption of NP * coNP/poly. In this paper we consider a restricted yet natural variant of kernelization, namely strict kernelization, where one is not allowed to increase the parameter of the reduced instance (the kernel) by more than an additive constant. Building on earlier work of Chen, Flum, and Müller [Theory Comput. Syst. 2011] and developing a general and remarkably simple framework, we show that a variety of FPT problems does not admit strict polynomial kernels under the weaker assumption of P 6= NP. In particular, we show that various (multicolored) graph problems and Turing machine computation problems do not admit strict polynomial kernels unless P = NP. To this end, a key concept we use are diminishable problems ; these are parameterized problems that allow to decrease the parameter of the input instance by at least one in polynomial time, thereby outputting an equivalent problem instance. Finally, we study a relaxation of the notion of strict kernels and reveal its limitations.
Thread prioritization: a thread scheduling mechanism for multiple-context parallel processors

Multiple-context processors provide register resources that allow rapid context switching between several threads as a means of tolerating long communication and synchronization latencies. When scheduling threads on such a processor, we must first decide which threads should have their state loaded into the multiple contexts, and second, which loaded thread is to execute instructions at any given time. In this paper we show that both decisions are important, and that incorrect choices can lead to serious performance degradation. We propose thread prioritization as a means of guiding both levels of scheduling. Each thread has a priority that can change dynamically, and that the scheduler uses to allocate as many computation resources as possible to critical threads. We briefly describe its implementation, and we show simulation performance results for a number of simple benchmarks in which synchronization performance is critical. <<ETX>>
An Energy Efficient Dynamic Clustering Protocol Based on Weight in Wireless Sensor Networks

Nodes in most wireless sensor networks (WSNs) are powered by batteries with limited energy. Prolonging network lifetime and saving energy are two critical issues for WSNs. Clustering is an effective technique to improve the energy efficiency and prolong network lifetime of wireless sensor networks. In this paper, an energy efficient dynamic clustering protocol (EEDCP) based on weight for wireless sensor networks is proposed, which is able to dramatically prolong network lifetime and save energy. In the EEDCP, we introduce the typical energy model to compute energy consumption, virtual grid technology to construct cluster and a long sleeping state to reduce energy consumption. In addition, we use the value of weight to measure the size of residual energy instead of voting, which can significant reduce the voting times and the number of transmitting information. Further, simulation experiments are conducted to compare the EEDCP with some well-known clustering algorithms and simulation results show that the proposed method overcomes the existing methods in the aspects of energy consumption and network lifetime in wireless sensor networks.
Therapeutic Writing: An Exploratory Speech–Language Pathology Counseling Technique

This exploratory qualitative study investigated the use of therapeutic writing for counseling long-term caregivers of spouses with brain injury and neurogenic communication disorders. Three participants wrote an average of six single-spaced pages of text. After analysis of the written text, the common themes of onset of diagnosis, anger, grief, and similarities in coping mechanisms were identified. Additional information about the value of therapeutic writing was obtained. Therapeutic writing appears to be a promising technique to use for counseling caregivers. On the basis of the caregiver's written text, the counseling needs related to neurogenic communication disorders can be addressed more efficiently.
Integrating Animal Models and In Vitro Tissue Models to Elucidate the Role of Desmosomal Proteins in Diseases

Abstract Desmosomes are intercellular junctions that provide tissues with structural stability. These junctions might also act as signaling centers that transmit environmental clues to the cell, thereby affecting cell differentiation, migration, and proliferation. The importance of desmosomes is underscored by devastating skin and heart diseases caused by mutations in desmosomal genes. Recent observations suggest that abnormal desmosomal protein expression might indirectly contribute to skin disorders previously not linked to these proteins. For example, it has been postulated that reduced desmosomal protein expression occurs in patients affected by Ankyloblepharon-ectodermal defects-cleft lip/palate syndrome (AEC), a skin fragility disorder caused by mutations in the transcription factor TP63. Currently, it is not clear how these changes in desmosomal gene expression contribute to AEC. We will discuss new approaches that combine in vitro and in vivo models to elucidate the role of desmosomal gene deregulation in human skin diseases such as AEC.
Information and Communication Technologies

Abstract Information and Communications Technology (ICT) can reduce poverty by improving poor people's access to education, health, government and financial services. ICT can also help small farmers and artisans by connecting them to markets. India has been a breeding ground of such innovative ICT projects in the rural areas by the government and private enterprises. But these projects have either been geographically restricted to certain areas or have not been successful in reaching out to every individual in the social pyramid. This paper analyses some of the initiatives taken up by the institutions and organizations, and identifies the problems faced by these initiatives in achieving the targeted objectives, respectively. The paper then identifies technological solutions to the various problems experienced and gives an insight into the ways ICT technologies can be successfully and efficiently implemented in achieving the social objectives with which they are identified.
Serologic and virologic evidence of a Prospect Hill-like hantavirus in Wisconsin and Minnesota.

The purposes of this study were to determine if hantaviruses were present in the Great Lakes port areas of Wisconsin and Minnesota and if so, to identify which virus and which rodent host species were involved. Rodents were trapped in Duluth, Minnesota, Superior, Green Bay, and Milwaukee, Wisconsin, all ports of call for international maritime shipping. A total of 675 wild rodents were captured and tested, including 310 meadow voles (Microtus pennsylvanicus), 173 Norway rats (Rattus norvegicus), 179 Peromyscus spp. , (including white footed mice [P. leucopus] and deer mice [P. maniculatus gracilis and P. maniculatus bairdii]), and 13 house mice (Mus musculus). Twenty percent of the rats, 17% of the meadow voles, 8% of the house mice, and 3% of the Peromyscus spp. had antibody to a hantavirus by immunofluorescent antibody assay (IFA). By the plaque-reduction neutralization test (PRNT), nine of 36 meadow voles, one of 4 P. leucopus, and one of 34 rats had hantavirus antibody, with the highest titers to Prospect Hill (PH) virus. All of the PRNT-seropositive individuals were from the twin cities of Superior and Duluth. Hantavirus antigen was detected in lung tissue by IFA in M. pennsylvanicus and Peromyscus spp. , but not in rats. Two hantaviruses, designated SD-1 and SD-2, were isolated from M. pennsylvanicus captured in Duluth and found to be very similar to prototype PH virus by cross-IFA and cross-PRNT. Virus isolation attempts were unsuccessful from tissues of the Peromyscus spp. and the rats.
Perceived Social Support and the Voluntary, Mixed, or Pressured Use of Mental Health Services

The network-episode model of service utilization and self-labeling theory underscore the importance of significant others in averting or prompting individuals’ entry into mental health treatment. Drawing from these approaches, three hypotheses are tested: (1) Social support generally reduces the likelihood of treatment entry, but (2) when individuals’ mental conditions are more serious, supportive relationships instead raise the probability of mental health utilization, and (3) for persons with greater social support, the more severe their mental disorders, the more likely they will enter treatment under pressure or with mixed volition. Data from the National Comorbidity Survey Replication are used to test these hypotheses (N = 5,692). Results confirm expectations. Findings also show that persons with greater social support perceived less need for mental health services, suggesting that supportive relationships might substitute for formal treatment or perhaps delay treatment seeking. Unmet need for psychiatric services may not be as great as indicated by low rates of service utilization among persons with disorders.
SimProgramming : the development of an integrated teaching approach for computer programming in higher education

Computer programming courses in higher education tend to have high rates of academic failure and students struggle, particularly so in the transition from entry-level programming to advanced programming. Some of the reasons given in the literature relate to the type of teaching approach and the strategies used by students and their attitudes towards computer programming. The literature also mentions that educational approaches are not always appropriate to the needs of students and to the development of skills required in the job market. We developed a teaching approach to try to address some of these issues and support students learning computer programming in the transition from entry-level to advanced computer programming: the SimProgramming approach. This approach was introduced at the University of Tras-os-Montes e Alto Douro (Portugal), within the scope of the course “Programming Methodologies III”, part of the second curricular year of the programmes of studies in Informatics Engineering and in Information & Communication Technologies. We present in detail the origins of the SimProgramming approach, starting from the first trials that introduced, in two iterations, learning activities based on problem-based learning, and up to the third iteration where the current SimProgramming approach was implemented. We describe the reasoning, design and implementation of these three iterations, to show how the approach evolved. The SimProgramming approach is based in four conceptual foundations: business-like learning environment, self-regulated learning, co-regulated learning and formative assessment. For each of these conceptual foundations, we explain the teaching strategies adopted. In SimProgramming, the learning activity process develops in four phases, and students have specific tasks in each phase. We analyse interview data regarding student perceptions about the SimProgramming approach, and registration grids data on team work dynamics and final assessment of the assignment, noting the impact of SimProgramming in student grades. The application of SimProgramming revealed promising evidences in the overall results of student learning in the activities proposed in this approach. The average grades improved, and did the number of students regularly submitting their tasks on schedule. The perceptions of students regarding the SimProgramming approach are very positive: they recommend using it in the following years, and provided some suggestions to improve the approach. We conclude with reflections and recommendations for subsequent development of the SimProgramming approach in its application to the teaching of computer programming and potential for using it in other educational contexts.
The Journey Between There and Here: Stories of a Faculty Writing Group

Reflecting, sharing, and producing knowledge about the process of writing and collaboration in a writing group is the focus of this qualitative project, in which we explore a complex weaving of knowledge, subjectivity, and representation. In this group are eight women faculty, all of whom are individually working on writing projects in their own areas of expertise. Using a method of writing as inquiry, each person was asked to keep a reflective journal; an autoethnographic account of their experiences of writing during a three-month period. The group met weekly and each individual shared their reflections and writing experiences. In this project, our intention is to decentre notions of the alienated, isolated academic by writing and constructing knowledge as a collective. Using the metaphor of here and there, we ask how can a relational culture grow out of writing? How can competitive, hidden barriers be broken down and replaced by open, encouraging spaces?
Performance and Energy Evaluation of ARM Cortex Variants for Smart Cardiac Pacemaker Application

Embedding microprocessors in implantable devices such as cardiac pacemakers improved their ability to treat complex heart conditions effectively. Future cardiac pacemakers are expected to evolve in features, gaining secure wireless connectivity, longer battery life, and increased operational reliability. Implementing such features in a power constrained pacemaker requires a deep understanding of the power consumption behavior of the underlying processor, especially for computing the expected workloads. In this paper, the popular ARM Cortex series of processors are evaluated against anticipated future workloads of a smart cardiac pacemaker. Simulation results are analyzed to understand the tradeoffs in instruction set design and the importance of a dedicated floating point calculation unit. The simulation results are backed by data collected from the execution of the programs on an actual Cortex-M4 processor with a floating point unit. The instantaneous power consumed by the processor is monitored, and possible improvement techniques are discussed. Execution time and total energy per operation are summarized to conclude the feasibility of existing embedded processors for future cardiac pacemaker application.