Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding low-utility data structures

Many opportunities for easy, big-win, program optimizations are missed by compilers. This is especially true in highly layered Java applications. Often at the heart of these missed optimization opportunities lie computations that, with great expense, produce data values that have little impact on the program's final output. Constructing a new date formatter to format every date, or populating a large set full of expensively constructed structures only to check its size: these involve costs that are out of line with the benefits gained. This disparity between the formation costs and accrued benefits of data structures is at the heart of much runtime bloat. We introduce a run-time analysis to discover these low-utility data structures. The analysis employs dynamic thin slicing, which naturally associates costs with value flows rather than raw data flows. It constructs a model of the incremental, hop-to-hop, costs and benefits of each data structure. The analysis then identifies suspicious structures based on imbalances of its incremental costs and benefits. To decrease the memory requirements of slicing, we introduce abstract dynamic thin slicing, which performs thin slicing over bounded abstract domains. We have modified the IBM J9 commercial JVM to implement this approach. We demonstrate two client analyses: one that finds objects that are expensive to construct but are not necessary for the forward execution, and second that pinpoints ultimately-dead values. We have successfully applied them to large-scale and long-running Java applications. We show that these analyses are effective at detecting operations that have unbalanced costs and benefits.
Patients’ Experiences of Cancer Diagnosis as a Result of an Emergency Presentation: A Qualitative Study

Introduction Cancers diagnosed following visits to emergency departments (ED) or emergency admissions (emergency presentations) are associated with poor survival and may result from preventable diagnostic delay. To improve outcomes for these patients, a better understanding is needed about how emergency presentations arise. This study sought to capture patients' experiences of this diagnostic pathway in the English NHS. Methods Eligible patients were identified in a service evaluation of emergency presentations and invited to participate. Interviews, using an open-ended biographical structure, captured participants' experiences of healthcare services before diagnosis and were analysed thematically, informed by the Walter model of Pathways to Treatment and NICE guidance in an iterative process. Results Twenty-seven interviews were conducted. Three typologies were identified: A: Rapid investigation and diagnosis, and B: Repeated cycles of healthcare seeking and appraisal without resolution, with two variants where B1 appears consistent with guidance and B2 has evidence that management was not consistent with guidance. Most patients’ (23/27) experiences fitted types B1 and B2. Potentially avoidable breakdowns in diagnostic pathways caused delays when patients were conflicted by escalating symptoms and a benign diagnosis given earlier by doctors. ED was sometimes used as a conduit to rapid testing by primary care clinicians, although this pathway was not always successful. Conclusions This study draws on patients' experiences of their diagnosis to provide novel insights into how emergency presentations arise. Through these typologies, we show that the typical experience of patients diagnosed through an emergency presentation diverges significantly from normative pathways even when there is no evidence of serious service failures. Consultations were not a conduit to diagnosis when they inhibited patients’ capacity to appraise their own symptoms appropriately and when they resulted in a reluctance to seek further healthcare. Recommendations The findings also point to potentially avoidable breakdowns in the diagnostic process. In particular, to encourage patients to return to the GP if symptoms escalate, a stronger emphasis is needed on diagnostic uncertainty in discussions between patients and doctors in both primary and secondary care. To improve appropriate access to rapid investigations, systems are needed for primary care to communicate directly with secondary care at the time of referral.
Is Thermal Expansion Driving the Initial Gas Ejection in NGC 6251?

The relativistic jets in active galactic nuclei (AGNs) are probably driven by the action of supermassive, spinning black holes. There is very little direct evidence for this, however, since the nuclei of active galaxies are difficult to study. This is now changing with new, high-resolution multiwavelength observations of nearby sources such as Sgr A* at the Galactic center and the nucleus of NGC 6251 (hereafter called NGC 6251*). In this paper, we explore the possibility that the radiative properties of the most compact region in NGC 6251* may be understood in the same sense as Sgr A*, though with some telling differences that may hint at the nature of jet formation. We show that observations of this object with ASCA, ROSAT, HST, and VLBI together may be suggesting a picture in which Bondi-Hoyle accretion from an ambient ionized medium feeds a standard disk accreting at ~ 4.0 × 1022 g s-1. Somewhere near the event horizon, this plasma is heated to more than 1011 K, where it radiates via thermal synchrotron (producing a radio component) and self-Comptonization (accounting for a nonthermal X-ray flux). This temperature is much greater than its virial value and the hot cloud expands at roughly the sound speed (~0.1c), after which it begins to accelerate on a parsec scale to relativistic velocities. In earlier work, the emission from the extended jet has been modeled successfully using nonthermal synchrotron self-Compton processes, with a self-absorbed inner core. In the picture we are developing here, the initial ejection of matter is associated with a self-absorbed thermal radio component that dominates the core emission on the smallest scales. The nonthermal particle distributions responsible for the emission in the extended jet are then presumably energized, e.g., via shock acceleration, within the expanding, hot gas. The power associated with this plasma represents an accretion efficiency of about 0.54, requiring dissipation in a prograde disk around a rapidly spinning black hole (with spin parameter a ~ 1).
A collaborative filtering recommendation algorithm based on dynamic and reliable neighbors

Collaborative filtering algorithm is currently the most widely used and a very efficient technology in personalized recommendation system. To overcome several defects in the research of the traditional Item-based collaborative filtering algorithm, this paper presents a optimized algorithm in two aspects, which are the selection of neighbors and the prediction of ratings. Firstly, different numbers of neighbors for the items and users are dynamically selected according to the similarity threshold, then the reliability of neighbors of both items and users are calculated. Finally, the more reliable neighbors was selected to predict the results. Experimental with MovieLens data set shows that the new algorithm outperforms the traditional Item-based algorithms significantly on accuracy of predictions.
The Bayes Tree: Enabling Incremental Reordering and Fluid Relinearization for Online Mapping

Abstract : In this paper we present a novel data structure, the Bayes tree, which exploits the connections between graphical model inference and sparse linear algebra. The proposed data structure provides a new perspective on an entire class of simultaneous localization and mapping (SLAM) algorithms. Similar to a junction tree, a Bayes tree encodes a factored probability density, but unlike the junction tree it is directed and maps more naturally to the square root information matrix of the SLAM problem. This makes it eminently suited to encode the sparse nature of the problem, especially in a smoothing and mapping (SAM) context. The inherent sparsity of SAM has already been exploited in the literature to produce efficient solutions in both batch and online mapping. The graphical model perspective allows us to develop a novel incremental algorithm that seamlessly incorporates reordering and relinearization. This obviates the need for expensive periodic batch operations from previous approaches, which negatively affect the performance and detract from the intended online nature of the algorithm. The new method is evaluated using simulated and real-world datasets in both landmark and pose SLAM settings.
Robust Machine Learning Applied to Astronomical Data Sets. III. Probabilistic Photometric Redshifts for Galaxies and Quasars in the SDSS and GALEX

We apply machine learning in the form of a nearest neighbor instance-based algorithm (NN) to generate full photometric redshift probability density functions (PDFs) for objects in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS DR5). We use a conceptually simple but novel application of NN to generate the PDFs, perturbing the object colors by their measurement error and using the resulting instances of nearest neighbor distributions to generate numerous individual redshifts. When the redshifts are compared to existing SDSS spectroscopic data, we find that the mean value of each PDF has a dispersion between the photometric and spectroscopic redshift consistent with other machine learning techniques, being σ = 0.0207 ± 0.0001 for main sample galaxies to r < 17.77 mag, σ = 0.0243 ± 0.0002 for luminous red galaxies to r≲ 19.2 mag, and σ = 0.343 ± 0.005 for quasars to i < 20.3 mag. The PDFs allow the selection of subsets with improved statistics. For quasars, the improvement is dramatic: for those with a single peak in their probability distribution, the dispersion is reduced from 0.343 to σ = 0.117 ± 0.010, and the photometric redshift is within 0.3 of the spectroscopic redshift for 99.3% ± 0.1% of the objects. Thus, for this optical quasar sample, we can virtually eliminate “catastrophic” photometric redshift estimates. In addition to the SDSS sample, we incorporate ultraviolet photometry from the Third Data Release of the Galaxy Evolution Explorer All-Sky Imaging Survey (GALEX AIS GR3) to create PDFs for objects seen in both surveys. For quasars, the increased coverage of the observed-frame UV of the SED results in significant improvement over the full SDSS sample, with σ = 0.234 ± 0.010. We demonstrate that this improvement is genuine and not an artifact of the SDSS-GALEX matching process.
Temporal Segmentation of Facial Behavior in Static Images Using HOG & Piecewise Linear SVM

Temporal segmentation of facial gestures in spontaneous facial behavior recorded in real-world settings is an important, unsolved, and relatively unexplored problem in facial image analysis. Several issues contribute to the challenge of this task. These include non-frontal pose, moderate to large out-of-plane head motion, large variability in the temporal scale of facial gestures, and the exponential nature of possible facial action combinations. To address these challenges, we propose a two-step approach to temporally segment facial behavior. The first step uses spectral graph techniques to cluster shape and appearance features invariant to some geometric transformations. The second step groups the clusters into temporally coherent facial gestures. We evaluated this method in facial behavior recorded during face-to-face interactions. The video data were originally collected to answer substantive questions in psychology without concern for algorithm development. The method achieved moderate convergent validity with manual FACS (Facial Action Coding System) annotation. Further, when used to preprocess video for manual FACS annotation, the method significantly improves productivity, thus addressing the need for ground-truth data for facial image analysis. Moreover, we were also able to detect unusual facial behavior. This paper consists of efficient facial detection in static images using Histogram of Oriented Gradients (HOG) for local feature extraction and linear piecewise support vector machine (PL-SVM) classifiers. Histogram of oriented gradient (HOG) gives an accurate description of the contour of image. HOG features are calculated by taking orientation of histogram of edge intensity in a local region. PL-SVM is nonlinear classifier that can discriminate multi-view and multi-posture from the images in high dimensional feature space. Each PL-SVM model forms the subspace, corresponding to the cluster of special view. This paper consists of comparison of PL-SVM and several recent SVM methods in terms of cross validation accuracy.
The effects of PWM voltage source inverters on the mechanical performance of rolling bearings

Modern power inverters provide the industrial control industry with significant advantages. Faster switching devices have increased drive performance, but with some recently discovered disadvantages. One disadvantage, rotor shaft voltage and resulting bearing current, has become an industry concern. The oil film in a bearing acts as a capacitor and provides a charging mechanism for rotor shaft voltage buildup. Electrical breakdown of the film can damage the bearing. The paper examines the mechanical and electrical characteristics of the bearing and converts them into models. The mechanical model for the bearing contact area establishes an allowable bearing current density, which is used to estimate the effect of electrical life of a mechanical bearing. The electrical model for the bearing provides a significant advancement to aid bearing design and in the analysis of electrically induced bearing damage. Finally, the paper presents quantitative results on one solution to the shaft voltage and bearing current problem.
Preclinical Vascular Cognitive Impairment and Alzheimer Disease: Neuropsychological Test Performance 5 Years Before Diagnosis

Background and Purpose— Neuropsychological changes that precede a diagnosis of vascular cognitive impairment (VCI) and the differences between preclinical VCI and Alzheimer disease (AD) are not well understood. We compared the neuropsychological performances of people with incident VCI, incident AD, and no cognitive impairment (NCI) 5 years before their clinical diagnoses. Methods— The Canadian Study of Health and Aging is a prospective, cohort study of 10 263 randomly selected persons age 65 years or older. We studied 332 individuals who had completed a battery of neuropsychological tests and were diagnosed with NCI at baseline. After 5 years, 41 were diagnosed with VCI, 25 with AD, and 266 with NCI. Results— At baseline, the incident-VCI group performed worse on a wide range of neuropsychological tests compared with the NCI group. A test of abstract reasoning was selectively low in the incident-VCI group, relative to both the incident-AD and NCI groups. The incident-AD group performed worse at baseline on memory tests compared with incident-VCI and NCI groups. Conclusions— This study suggests a preclinical phase may exist in VCI that differs from that in AD. Neuropsychological measures may aid the design of preventive strategies for VCI.
Information retrieval in context: IRiX

IR research is now conducted in multi-media, multi-lingual, and multi-modal environments but largely in a context-free manner (Ingwersen & Jäärvelin, 2005). However, the retrieval of such information depends on time, place, history of interaction, task in hand, and a range of other factors that are not given explicitly but are implicit in the interaction and ambient environment, namely the context. Such contextual data can be used effectively to constrain retrieval of information thereby reducing the complexity of the retrieval process.
Catastrophic failure and fault-tolerant design of IGBT power electronic converters - an overview

Reliability is one of the key issues for the application of Insulated Gate Bipolar Transistors (IGBTs) in power electronic converters. Many efforts have been devoted to the reduction of IGBT wear out failure induced by accumulated degradation and catastrophic failure triggered by single-event overstress. The wear out failure under field operation could be mitigated by scheduled maintenances based on lifetime prediction and condition monitoring. However, the catastrophic failure is difficult to be predicted and thus may lead to serious consequence of power electronic converters. To obtain a better understanding of catastrophic failure of IGBTs, the state-of-the-art research on their failure behaviors and failure mechanisms is presented in this paper. Moreover, various fault-tolerant design methods, to prevent converter level malfunctions in the event of IGBT failure, are also reviewed.
Bounded degree cosystolic expanders of every dimension

In recent years a high dimensional theory of expanders has emerged. The notion of combinatorial expansion of graphs (i.e. the Cheeger constant of a graph) has seen two generalizations to high dimensional simplicial complexes. One generalization, known as coboundary expansion, is due to Linial and Meshulem; the other, which we term here cosystolic expansion, is due to Gromov, who showed that cosystolic expanders have the topological overlapping property. No construction (either random or explicit) of bounded degree combinational expanders (according to either definition) were known until a recent work of Kaufman, Kazhdan and Lubotzky, which provided the first bounded degree cosystolic expanders of dimension two. No bounded degree combinatorial expanders are known in higher dimensions. In this work we present explicit bounded degree cosystolic expanders of every dimension. This solves affirmatively an open question raised by Gromov, who asked whether there exist bounded degree complexes with the topological overlapping property in every dimension. Moreover, we provide a local to global criterion on a complex that implies cosystolic expansion: Namely, for a d-dimensional complex, X, if its underlying graph is a good expander, and all its links are both coboundary expanders and good expander graphs, then the (d-1)-dimensional skeleton of the complex is a cosystolic expander.
Environmental DNA from Residual Saliva for Efficient Noninvasive Genetic Monitoring of Brown Bears (Ursus arctos)

Noninvasive genetic sampling is an important tool in wildlife ecology and management, typically relying on hair snaring or scat sampling techniques, but hair snaring is labor and cost intensive, and scats yield relatively low quality DNA. New approaches utilizing environmental DNA (eDNA) may provide supplementary, cost-effective tools for noninvasive genetic sampling. We tested whether eDNA from residual saliva on partially-consumed Pacific salmon (Oncorhynchus spp.) carcasses might yield suitable DNA quality for noninvasive monitoring of brown bears (Ursus arctos). We compared the efficiency of monitoring brown bear populations using both fecal DNA and salivary eDNA collected from partially-consumed salmon carcasses in Southeast Alaska. We swabbed a range of tissue types from 156 partially-consumed salmon carcasses from a midseason run of lakeshore-spawning sockeye (O. nerka) and a late season run of stream-spawning chum (O. keta) salmon in 2014. We also swabbed a total of 272 scats from the same locations. Saliva swabs collected from the braincases of salmon had the best amplification rate, followed by swabs taken from individual bite holes. Saliva collected from salmon carcasses identified unique individuals more quickly and required much less labor to locate than scat samples. Salmon carcass swabbing is a promising method to aid in efficient and affordable monitoring of bear populations, and suggests that the swabbing of food remains or consumed baits from other animals may be an additional cost-effective and valuable tool in the study of the ecology and population biology of many elusive and/or wide-ranging species.
Optimizing Multi-Processor Operating Systems Software Research Review

1 In this paper we review general purpose multiprocessor operating systems research that is relevant to maximizing performance, focusing on the exploitation of locality in large scale systems. We cover three areas in particular: 1. A historical review of multiprocessor operating systems research. 2. A discussion of disciplined approaches to applying distributed data structures to systems construction. 3. A review of modern operating systems research that addresses the unique characteristics of scalable hardware platforms. Utilizing concurrency to improve performance is not new and certainly not restricted to the domain of operating systems. Many of the features introduced into microprocessor architectures attempt to extract parallelism at the instruction level in order to hide latencies and improve the number of instructions executed per cycle. Increasingly scientific users split their calculations into independent components which can be executed in parallel in order to decrease absolute runtime. Operating systems are unique, from a software perspective, in their requirement to support and enable parallelism rather than exploiting it to improve their own performance. An operating system (OS) must ensure good overall system utilization and high degrees of parallelism for those applications which demand it. To do this, operating systems must: 1) utilize the characteristics of the hardware to exploit concurrency in general purpose workloads and 2) facilitate concurrent applications , which include providing models and facilities for applications to exploit the concurrency available in the hardware. It is critical that an OS reflect the parallelism of the workloads and individual applications to ensure that the OS facilities do not hinder overall system or individual application performance. This is often overlooked. Smith[117] alludes to the individual application requirements, noting that the tension between protection and performance is particularly salient and difficult in a parallel system and that the parallelism in one protection domain must be reflected in another. In other words, to ensure that a parallel application within one protection domain can realize its potential performance, all services in the system domains that the concurrent application depends on, must be provided in an equally parallel fashion. It is worth noting that this is true not only for individual applications but also for all applications forming the current workload on a parallel system: the demands of all concurrently executing applications must be satisfied with equal parallelism in order to ensure good overall system performance. Much of the research into multiprocessor operating systems has been concerned with how …