Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Attack: Using Analytics to Unlock the Secrets of Successful Zone Entries in Hockey ⋆

In this paper, we use machine learning methods to see what types of offensive zone entries and their upcoming play sequence lead to shots with high xG values in hockey. Our results showed a clear difference in sequence characteristics regarding the length of the sequence, the type of zone entries, the number of events, and in what zones those events took place for good goal-scoring opportunities compared to worse ones.
Ultra-deep Subduction of Continental Crust: Evidence from Natural Rocks and Experimental Investigations

Much of what we know about the deep subduction of continental crust is gained from study of the mineralogy of ultrahigh-pressure metamorphic (UHPM) rocks incorporated within continent-continent collision belts. UHPM rocks of metasedimentary origin were only recently recognized due to discovery of coesite, diamond, titanite inferred to have contained six-fold coordinated Si before exsolution of coesite, and TiO2 with alpha-PbO2 structure. Modern seismic tomography provides remarkable images that suggest lithospheric plates are subducted to the core-mantle boundary and may remain there stagnated during long geological times; the presence of continental material within such plates cannot be excluded. The mineral phase transformations possible within deeply subducted continental crust have been the subject of intensive laboratory experimentation during the last decade. Though many new UHP minerals were synthesized at P~ 6 to >20 GPa (e.g., wadeite, topaz-OH, phase Egg, K-and Na-hollandite) in the KNASH, KASH and ASH chemical systems, none except topaz-OH has yet been identified in UHPM rocks. The microstructural evidence of former majoritic garnet decompression is proven only for garnet peridotite, whereas no evidence of such structures has been reported yet from diamondiferous felsic rocks. It is not clear if this is because the UHPM minerals of felsic rocks are easily lost during retrograde metamorphism, or if this is because garnets crystallized in the felsic systems do not contain a large majoritic component at high pressures. There is no clear indication of what portion of subducted continental crust is returned back to Earth$\prime$s surface, and what fraction may have become more dense than mantle rocks and sunk down to the mantle transition zone and even deeper. Is there any connection between mantle plumes and deeply subducted continental rocks? The UHPM discipline would also benefit from new experiments designed to reproduce decompression structures of UHP minerals and evaluation of melting in rocks of diverse crustal lithologies during very deep subduction to enable numerical modeling to predict what other phases or decompression products may yet be found in UHPM rocks.
Optimization of Geometric Multigrid for Emerging Multi-and Manycore Processors

In the past decades, continued increases in clock frequencies have delivered exponential improvements in computer system performance. However, this trend came to an abrupt end a few years ago as power consumption became the principal rate limiting factor. As a result, power constraints are driving architectural designs towards ever-increasing numbers of cores, wide data parallelism, potential heterogenous acceleration, and a decreasing trend in per-core memory bandwidth. Understanding how to leverage these technologies in the context of demanding numerical algorithms is likely the most urgent challenge in high-end computing. In this work, we explore the optimization of geometric multigrid (MG) — one of the most important algorithms for computational scientists — on a variety of leading multiand manycore architectural designs. Our primary contributions are:
Small Area Estimation with Application to Disease Mapping

Small Area Estimation is important in survey analysis when domain (subpopulation) sample sizes are too small to provide adequate precision for direct domain estimators. Small Area Estimation (SAE) is a mathematical technique for extracting more detailed information from existing data sources by statistical modeling. The estimates are often mapped, so the technique is often generically called mapping. These maps and estimates (together with estimates of accuracy) are key information in aid allocation within a country. They are also increasingly important inputs to negotiations on allocation of international aid to particular countries. This paper provides a critical review of the main advances in small area estimation (SAE) methods in recent years with application to disease mapping. The review discusses in detail earlier developments of small area estimation methods in the field of disease mapping which serve as a necessary background for the new studies in disease mapping of small areas which we termed "Extensions". Illustrative examples of the application of Small Area Estimation (SAE) to disease mapping are presented.
On the E(cid:14)cient Implementation of Massively Parallel Quicksort

Parallel Quicksort is one of the most promising parallel sorting algorithms from the point of view of scalability. However, actual implementations have been limited to very basic versions of the algorithm so far and su(cid:11)er from a number of de(cid:12)ciencies. We have implemented a high performance variant of parallel Quicksort which incorporates the following optimizations: Stop the recursion at the right time, sort locally (cid:12)rst, use accurate yet e(cid:14)cient pivot selection strategies, stream-line communication patterns, use locality preserving processor indexing schemes and work with multiple pivots at once. In particular, on mesh-connected computers, the resulting algorithm turns out to be among the best practical sorting methods. It is about three times faster than the basic algorithm and achieves a speedup of 810 on a 1024 processor Parsytec GCel for the NAS parallel sorting benchmark of size 2 24 . The optimized algorithm can also be shown to be asymptotically optimal on meshes.
Consensus formation in opinion dynamics with online and offline interactions at complex networks

Nowadays, with the development of information communication technology and Internet, more and more people receive information and exchange their opinions with others via online environments (e.g. Twitter, Facebook, Weibo, and WeChat). According to eMarketer Report [Worldwide Internet and Mobile Users: eMarketer’s Updated Estimates and Forecast for 2015–2020 (eMarketer Report). Published October 11, 2016, https://www.emarketer. com/Report/Worldwide-Internet-Mobile-Users-eMarketers-Updated-Estimates-Forecast-20152020/2001897 ). ], by the end of 2016, more than 3.2 billion individuals worldwide will use the Internet regularly, accounting for nearly 45% of the world population. By contrast, the other half of the global population still obtain information and regularly exchange their opinions in a more traditional way (e.g. face to face). Generally, the speed at which information spreads and opinions are exchanged and updated in an online environment is much faster than in an offline environment. This paper focuses on jointly investigating the challenge of consensus formation in opinion dynamics with online and offline interactions. Without loss of generality, we assume the speed at which information spreads and opinions are exchanged and updated in an online environment is [Formula: see text] times as fast as in an offline environment. We demonstrate that the update speed ratio in mixed online and offline environments (i.e. [Formula: see text]) strongly impacts the consensus formation at complex networks: a large update speed ratio of online and offline environments (i.e. [Formula: see text]) makes it difficult for all agents to reach consensus in opinion dynamics. Furthermore, these effects are often further intensified as the number of online participating agents increases.
Dynamically consistent noise infusion and partially synthetic data as confdentiality protection measures for related time-series

The Census Bureau's Quarterly Workforce Indicators (QWI) provide detailed quarterly statistics on employment measures such as worker and job ows, tabulated by detailed worker characteristics in various combinations. The data are released for detailed NAICS industries and for several levels of geography, the lowest aggregation of which are counties. OnTheMap, another Census Bureau product, provides a subset of these tabulations at the tract level. Disclosure avoidance methods are required to protect the information about individuals and businesses that contribute to the underlying data. The QWI disclosure avoidance mechanism we describe here relies heavily on the use of noise infusion through a permanent multiplicative noise distortion factor, used for magnitudes, counts, differences and ratios. There is minimal suppression and no complementary suppressions. To our knowledge, the release in 2003 of the QWI was the first large-scale use of noise infusion in any official statistical product. We show that the released statistics are analytically valid along several critical dimensions -measures are unbiased and time series properties are preserved. We provide an analysis of the degree to which con dentiality is protected. Furthermore, we show how the judicious use of synthetic data, injected into the tabulation process, can completely eliminate suppressions, maintain analytical validity, and increase the protection of the underlying con dential data.
AN AUTOMATIC SYSTEM FOR THE MEASUREMENT OF FLAT WORKPIECES

This paper reports on the development of an automatic photogrammetric system which is used for the dimensional control of large plain workpieces in industrial environments. The system consists of one or more standard video cameras, a video frame grabber and a NT workstation computer. A diffuse light source is used to illuminate the object space. Plain objects may be measured by single image techniques such as projective rectification. In this case at least 4 control points are given in object space and are used to determine the perspective transformation between cameras and object space. Due to the selected cameras significant variations of principle point coordinates and distortion values have to be considered. Using self-calibrating bundle adjustment the parameter of interior orientation are calculated iteratively in order to get distortion-free image for the perspective transformation. The measurement of the parts is performed by automatic line following using digital image processing. Approximate values of edge positions are calculated from existing CAD data of the object. The system has been implemented in a production environment for concrete ceilings. These parts have to be controlled with an accuracy of about 5-10mm. First results have shown that a system accuracy of less than 3mm is given under industrial conditions. The time for a complete measurement of object edges is less than 1 second.
Streaming Sparse Data on Architectures with Vector Extensions using Near Data Processing

Most scientific and AI applications rely on data that is usually sparse. Sparsity is sometimes deliberately introduced with pruning of insignificant and redundant connections in the neural network layers. This sparse data can efficiently be represented through various compression formats, thereby, reducing storage footprint and eliminating computations with zero values. However, accessing nonzero values introduces extra computational overhead. Considersparsematrix-densevectormultiplication(spMV),where the sparse matrix data is represented in CSR format. The irregular memory loads caused by CSR format are particularly vexing for vectorized computations (e.g., modern CPUs with SVE or AVX extensions, GPUs) because they do not exploit spatial and temporal localities. In this work, we propose a memory-side accelerator known as MAID (Memory-side Acceleration for Irregular Data), which is a simple integer unit that performs these irregular memory accesses and streams the aligned data to the primary core. The primary vectorized CPU focuses on only fetching these aligned values and computing multiply-accumulate operations concurrently alongside our MAID accelerator. To accurately evaluate the performance effects of our proposed accelerator in a CPU-MAID-memory system, we used a Gem5 extension that permits simulating near data processing (NDP) accelerators close to memory devices at various levels of the memory hierarchy. Our experimental evaluations show that when MAID is placed close to L2 or LLC, minimizes data transfer to L1 cache, eliminates cache conflicts, and thus increases energy savings. We observed performance gains ranging between 2.76 and 3.56 times over in-order SIMD-CPU and an average of 2 times for out-of-order SIMD-CPU for sparse matrix * dense vector (spMV) algorithm. We also evaluated our MAID with sparse matrix * sparse vector (spMspV) and observed gains as high as 5.3 times over SIMD baseline.
Forecasting Factors for Skier-Triggered Avalanches at a Helicopter Skiing Operation

To forecast skier-triggered avalanches, stability, snowpack and meteorological variables, and records of previous avalanche activity are typically used. The relative importance of, and interaction between, variables used to forecast skier-triggered avalanches have received little attention. This study analyzes the influence of forecasting variables at a heli-skiing operation in the Columbia Mountains of British Columbia, Canada. Forecasting variables are individually assessed using rank correlations to identify which are most relevant for forecasting the potential for skier-triggered slab avalanches. The variables showing the strongest forecasting potential include: the largest skier-triggered avalanche observed on the previous one and two days, 24-hour snowfall and precipitation, storm snow, height of snowpack, and the number of days since December 1. The physical processes that relate these variables to skier-triggered avalanches are discussed. The predictive potential of combined forecasting variables is assessed using a classification tree model. Verification of the model with the last two years of data shows that the model predicts relatively large avalanches approximately two-thirds of the time.
Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR Sequences

Scene understanding is crucial for autonomous systems to reliably navigate in the real world. Panoptic segmentation of 3D LiDAR scans allows us to semantically describe a vehicle's environment by predicting semantic classes for each 3D point and to identify individual instances through different instance IDs. To describe the dynamics of the surroundings, 4D panoptic segmentation further extends this information with temporarily consistent instance IDs to identify the different instances in the scans consistently over whole sequences. Previous approaches for 4D panoptic segmentation rely on post-processing steps and are often not end-to-end trainable. In this paper, we propose a novel approach that can be trained end-to-end and directly predicts a set of non-overlapping masks along with their semantic classes and instance IDs that are consistent over time without any post-processing like clustering or associations between predictions. We extend a mask-based 3D panoptic segmentation model to 4D by reusing queries that decoded instances in previous scans. This way, each query decodes the same instance over time, carries its ID and the tracking is performed implicitly. This enables us to jointly optimize segmentation and tracking and directly supervise for 4D panoptic segmentation.
Heat Transfer Coefficient Estimation for Turbulent Boundary Layers

Convective heat transfer in rough wall-bounded turbulent ﬂows is prevalent in many engineering applications, such as in gas turbines and heat exchangers. At present, engineers lack the design tools to accurately predict the convective heat transfer in the presence of non-smooth boundaries. Accordingly, a new turbulent boundary layer facility has been commissioned, where the temperature of an interchangeable test surface can be precisely controlled, and conductive heat losses are minimized. Using this facility, we can estimate the heat transfer coefﬁcient (Stan-ton number, St ), through measurement of the power supplied to the electrical heaters and also from measurements of the thermal and momentum boundary layers evolving over this surface. These methods have been initially investigated over a shorter smooth prototype heated surface and compared with existing St prediction models. Preliminary results suggest that we can accurately estimate St in this facility.
Relationships between dead wood and arthropods in the southeastern United States

The importance of dead wood to maintaining forest diversity is now widely recognized. However, the habitat associations and sensitivities of many species associated with dead wood remain unknown, making it difficult to develop conservation plans for managed forests. The purpose of this research, conducted on the upper coastal plain of South Carolina, was to better understand the relationships between dead wood and arthropods in the southeastern United States. In a comparison of forest types, more beetle species emerged from logs collected in upland pine-dominated stands than in bottomland hardwood forests. This difference was most pronounced for Quercus nigra L. , a species of tree uncommon in upland forests. In a comparison of wood postures, more beetle species emerged from logs than from snags, but a number of species appear to be dependent on snags including several canopy specialists. In a study of saproxylic beetle succession, species richness peaked within the first year of death and declined steadily thereafter. However, a number of species appear to be dependent on highly decayed logs, underscoring the importance of protecting wood at all stages of decay. In a study comparing litter-dwelling arthropod abundance at different distances from dead wood, arthropods were more abundant near dead wood than away from it. In another study, ground-dwelling arthropods and saproxylic beetles were little affected by large-scale manipulations of dead wood in upland pine-dominated forests, possibly due to the suitability of the forests surrounding the plots.
Representation of Urban Geometry Evolution Through Space-Time Cube

Visualizing and understanding the evolution of neighbourhoods in cities is crucial to the understanding of urban areas. While data exists to document the evolution of the urban places, we lack methods to clearly visualize the evolution of a city or a neighbourhood in time. We propose a new representation of the city that integrates 3D urban data with time, inspired by the Space-Time Cube concept. Our representation allows the visualization and comparison of different versions of the city in a single interactive 3D space, based on a graph model of the data. In addition to displaying the 3D geometry, we also integrate a direct visualization of the type of changes between each version and provide several ways to interact with the visualization. We apply our visualization technique on real urban data and show that it allows quickly apprehending the evolution of a neighbourhood.
Water Resources Impacts

Models are used to estimate potential physical and biological impacts, efficient adaptations, and residual damages from climate change. The contributors cover a broad array of climate change impacts on affected market sectors (including water supply, agriculture, coastal resources, timber, and energy demand) as well as ecosystems and biodiversity. An integrated hydrologic-agriculture model is developed to explore how the region would adapt to changes in water flows. Interactions between climate impacts and population and economic growth, urbanization, and technological change are also explored. For example, the study examines how both climate change and projected land development affect the region’s terrestrial ecosystems and biodiversity.
UvA-DARE (Digital Academic Translating socioemotional selectivity theory Into persuasive communication: Conceptualizing and operationalizing emotionally-meaningful versus knowledge-related appeals

messages, whereas younger adults lack this bias. However, potentially due to multivocality in conceptualizations and operationalizations of these appeals, previous studies found no uniform support for these age differences. Consequently, this article aims to provide a conceptualization and operationalization of emotionally-meaningful versus knowledge-related appeals that can be used in future research. The study consists of a conceptualization phase (literature review; expert meetings) and an operationalization phase (content analysis of persuasive messages). We developed a theoretically valid and reliable coding instrument, outlining three dimensions of emotionally-meaningful appeals (emotion regulation, optimizing the present, close social relationships) and three dimensions of knowledge-related appeals (knowledge acquisition, optimizing the future, novel social relationships). This instrument is intended to guide the selection and design of persuasive messages in effect studies that aim to test hypotheses derived from SST.
Enabling high-accuracy long-read amplicon sequences using unique molecular identifiers and Nanopore sequencing

High-throughput amplicon sequencing of large genomic regions represents a challenge for existing short-read technologies. Long-read technologies can in theory sequence large genomic regions, but they currently suffer from high error rates. Here, we report a high-throughput amplicon sequencing approach that combines unique molecular identifiers (UMIs) with Oxford Nanopore sequencing to generate single-molecule consensus sequences of large genomic regions. We demonstrate the approach by generating nearly 10,000 full-length ribosomal RNA (rRNA) operons of roughly 4,400 bp in length from a mock microbial community consisting of eight bacterial species using a single Oxford Nanopore MinION flowcell. The mean error rate of the consensus sequences was 0.03%, with no detectable chimeras due to a rigorous UMI-barcode filtering strategy. The simplicity and accessibility of this method paves way for widespread use of high-accuracy amplicon sequencing in a variety of genomic applications.
Arctic Char Salvelinus alpinus can enhance fisheries in reservoirs with trophic constraints

ii ACKNOWLDEGEMENTS . iv Introduction . 1 Methods . 3 Study area . 3 Fish sampling . 4 Growth and energy density . 5 Char origin . 6 Diet . 7 Population modeling . 8 Bioenergetics modeling . 10 Results . 11 Fish sampling . 11 Char origin . 12 Diet . 12 Population dynamics . 13 Consumptive demand . 14 Discussion . 15 References . 31 Appendix A . 38 Introduction . 39 Methods . 39