Miracle-dz/UniFAR-FTUs huggingface dataset:
Gaze-Driven video streaming with saliency-based dual-stream switching

The ability of a person to perceive image details falls precipitously with larger angle away from his visual focus. At any given bitrate, perceived visual quality can be improved by employing region-of-interest (ROI) coding, where higher encoding quality is judiciously applied only to regions close to a viewer's focal point. Straight-forward matching of viewer's focal point with ROI coding using a live encoder, however, is computation-intensive. In this paper, we propose a system that supports ROI coding without the need of a live encoder. The system is based on dynamic switching between two pre-encoded streams of the same content: one at high quality (HQ), and the other at mixed quality (MQ), where quality of a spatial region depends on its pre-computed visual saliency values. Distributed source coding (DSC) frames are periodically inserted to facilitate switching. Using a Hidden Markov Model (HMM) to model a viewer's temporal gaze movement, MQ stream is pre-encoded based on ROI coding to minimize the expected streaming rate, while keeping the probability of a viewer observing low quality (LQ) spatial regions below an application-specific ϵ. At stream time, the viewer's gaze locations are collected and transmitted to server for intelligent stream switching. In particular, server employs MQ stream only if: i) viewer's tracked gaze location falls inside the high-saliency regions, and ii) the probability that a viewer's gaze point will soon move outside high-saliency regions, computed using tracked gaze data and updated saliency values, is below ϵ. Experiments showed that video streaming rate can be reduced by up to 44%, and subjective quality is noticeably better than a competing scheme at the same rate where the entire video is encoded using equal quantization.
Real-world experience with interferon-free, direct acting antiviral therapies in Asian Americans with chronic hepatitis C and advanced liver disease

Abstract Real-life data on interferon (IFN)-free direct acting antiviral (DAA) therapies for chronic hepatitis C (CHC) is limited for Asian Americans. To evaluate sustained virologic response (SVR) and adverse events (AE) in Asian Americans treated with sofosbuvir (SOF)-based, IFN-free DAA therapies. This is a retrospective study of 110 consecutive Asian Americans with HCV genotypes 1 to 3 or 6 treated with IFN-free SOF-based regimens for 8 to 24 weeks between February 2014 and March 2016 at a university center in Northern California. Mean age was 63 ± 12 years, mean BMI was 25 ± 6 (kg/m2), and about half (52%) were male. Most patients were infected with HCV genotype 1 (HCV-1, 64%), followed by HCV-2 (14%), HCV-6 (13%), and HCV-3 (8%). Half had cirrhosis, and the majority of these (67%) had decompensation. Overall SVR12 was 93% (102/110), and highest among patients without cirrhosis, liver transplant, or HCC (100%, 37/37). SVR12 was lower among patients with HCC (82%, 14/17), decompensated cirrhosis (84%, 31/37), or liver transplant (89%, 17/19), regardless of treatment and genotype. Most common AEs were anemia (25%), fatigue (20%), and headache (12%). Anemia was highest in patients receiving SOF/RBV (67%). There was 1 treatment-unrelated serious adverse effect (SAE). There were 7 dose reductions due to anemia or fatigue from RBV and 2 treatment discontinuations due to fatigue or loss of insurance authorization. This real-life cohort of Asian American CHC patients treated with IFN-free SOF-based therapies showed high overall treatment response and good tolerability, despite very high rates of advanced disease and prior treatment failure.
An Improved ART 2-A Model for Mixed Numeric and Categorical Data

Adaptive Resonance Theory (ART) architectures are important neural networks for unsupervised clustering. ART 2- A is one version of the ART family capable of clustering both binary and numeric data. However, real-world problems usually contain categorical data that cannot be processed by ART 2-A. A simple solution is using binary encoding to preprocess categorical data. Binary encoding is a simple and straightforward approach, but it suffers from two main drawbacks: increase of dimensionality and lack of scalability. Therefore this paper proposes ART 2a-M, an improved version over ART 2-A. ART 2a-M can deal with mixed numeric and categorical data. Experiments were carried out on KDD Cup 99 data set to compare ART 2a-M with ART 2-A. Results show that not only ART 2a-M overcomes the two drawbacks of binary encoding. but also runs about 10% faster than the original one, while keeping the same accuracy.
An innovative behavioral approach to worm detection

This paper presents a new approach to the automatic detection of worms using behavioral signature with sequential hypothesis testing. Characteristic patterns of worm behaviors in network traffic include 1) sending similar data from one machine to the next, 2) tree-like propagation and reconnaissance, and 3) changing a server into a client [1]. 4) infected hosts should meet the basic requirements [2]. This sequential hypothesis testing theory first developed by Wald [3] overcomes the hurdle that it's difficult to find a threshold of determining whether a host is infected when we build a tree of worm propagation. Besides, to slow down the propagation of worms we alter an existing method which is connection rate limiting to packet-sending rate limiting. Our results that show this approach successfully restricts the number of packets sent by worms, has a low false alarm rate and a low missing alarm rate.
Self-intersections with Cullide

We present an image-space technique, which can detect intersections and self-intersections among multiple moving and deforming objects. No preprocessing is needed and the shape of the objects are unconstrained and can be an arbitrarily polygon soup. Compared to other intersection detection algorithms running on graphics hardware the algorithm only make modest use of bandwidth between the CPU and GPU because no buffer readbacks are necessary.
Neurodegeneration and functional impairments associated with glycogen synthase accumulation in a mouse model of Lafora disease

Lafora disease (LD) is caused by mutations in either the laforin or malin gene. The hallmark of the disease is the accumulation of polyglucosan inclusions called Lafora Bodies (LBs). Malin knockout (KO) mice present polyglucosan accumulations in several brain areas, as do patients of LD. These structures are abundant in the cerebellum and hippocampus. Here, we report a large increase in glycogen synthase (GS) in these mice, in which the enzyme accumulates in LBs. Our study focused on the hippocampus where, under physiological conditions, astrocytes and parvalbumin‐positive (PV+) interneurons expressed GS and malin. Although LBs have been described only in neurons, we found this polyglucosan accumulation in the astrocytes of the KO mice. They also had LBs in the soma and some processes of PV+ interneurons. This phenomenon was accompanied by the progressive loss of these neuronal cells and, importantly, neurophysiological alterations potentially related to impairment of hippocampal function. Our results emphasize the relevance of the laforin–malin complex in the control of glycogen metabolism and highlight altered glycogen accumulation as a key contributor to neurodegeneration in LD.
Functional and Structural Substrates of Neural Modulation in Older Adults After Executive Control Training

The fronto-parietal control network (FPCN) and dorsal attention network (DAN) are critical for goal-directed cognition (GDC), which is known to decline with advancing age. Here, we investigated whether a strategy-based executive control training intervention (GOALS) would alter recruitment of the FPCN and DAN in healthy older adults. We also investigated whether functional brain changes would be associated with improvements in GDC and structural integrity of frontalposterior white matter tracts. Thirteen participants were randomly assigned to the five-week long GOALS training and 12 were randomly assigned to a time and intensity matched control intervention group. Both groups were tested before and after intervention on a goal-directed cognitive task while undergoing fMRI scanning. We observed post-training increases in activation within the FPCN during a selective working memory task requiring GDC in the GOALS training group as compared to the control group, p < . 001. These increases were positively correlated with the integrity of white matter pathways connecting frontal and posterior brain regions in the GOALS group, p < . 001. In conclusion, this study is the first to our knowledge to report changes in functional neural networks known to subserve GDC in older adults after training and relate these changes to the integrity of underlying white matter tracts.
Emission‐Line Helium Abundances in Highly Obscured Nebulae

This paper outlines a way to determine the ionization correction factor (ICF) using only infrared data. We identify four line pairs, [Ne iii] 36 μm/[Ne ii] 12.8 μm, [Ne iii] 15.6 μm /[Ne ii] 12.8 μm, [Ar iii] 9 μm/[Ar ii] 6.9 μm, and [Ar iii] 21 μm/[Ar ii] 6.9 μm, that are sensitive to the He ICF. This happens because the ions cover a wide range of ionization, the line pairs are not sensitive to electron temperature, they have similar critical densities, and they are formed within the He+/H+ region of the nebula. We compute a very wide range of photoionization models appropriate for galactic H ii regions. The models cover a wide range of densities, ionization parameters, and stellar temperatures and use continua from four very different stellar atmospheres. The results show that each line pair has a critical intensity ratio above which the He ICF is always small. Below these values the ICF depends very strongly on details of the models for three of the ratios, and so other information would be needed to determine the helium abundance. The [Ar iii] 9 μm/[Ar ii] 6.9 μm ratio can indicate the ICF directly as a result of the near exact match in the critical densities of the two lines. Finally, continua predicted by the latest generation of stellar atmospheres are sufficiently hard that they routinely produce significantly negative ICFs.
A New Approach for Locating Mobile Stations under the Statistical Directional Propagation Model

Recently, mobile location estimation is drawing considerable attention in the field of wireless communications. Among different mobile location estimation methods, the one which estimates the location of mobile stations with reference to the wave propagation model is drawing much attention on the grounds that it is applicable to different kinds of cellular network. However the estimation accuracy of the signal propagation model deteriorates as the distance between the mobile station and the receiving base station increases. In view of this, we have designed a new location estimation approach which has divided the location estimation into two phases, the data collection phase and the location estimation phase. In this paper, we report our study of the new location estimation approach. We tested the approach with real life data collected from a major mobile operator of Hong Kong. Results show that the new location estimation approach has improved the existing statistical signal propagation model by 30.94%. This improvement can be further enhanced if more data are collected
SVD-based universal DNN modeling for multiple scenarios

Speech recognition scenarios (aka tasks) differ from each other in acoustic transducers, acoustic environments, and speaking style etc. Building one acoustic model per task is one common practice in industry. However, this limits training data sharing across scenarios thus may not give highest possible accuracy. Based on the deep neural network (DNN) technique, we propose to build a universal acoustic model for all scenarios by utilizing all the data together. Two advantages are obtained: 1) leveraging more data sources to improve the recognition accuracy, 2) reducing substantially service deployment and maintenance costs. We achieve this by extending the singular value decomposition (SVD) structure of DNNs. The data from all scenarios are used to first train a single SVD-DNN model. Then a series of scenario-dependent linear square matrices are added on top of each SVD layer and updated with only scenario-related data. At the recognition time, a flag indicates different scenarios and guides the recognizer to use the scenario-dependent matrices together with the scenario-independent matrices in the universal DNN for acoustic score evaluation. In our experiments on Microsoft Winphone/Skype/Xbox data sets, the universal DNN model is better than traditional trained isolated models, with up to 15.5% relative word error rate reduction.
Oil and fat in broiler nutrition

The terms "fat" and "oil" refer to triglycerides of several profiles of fatty acids. Fatty acids that are not bound to other organic components as glycerol are the so-called free fatty acids. Lipids constitute the main energetic source for animals and they have the highest caloric value among all the nutrients. Linoleic acid is the only fatty acid whose dietetic requirement has been demonstrated. Besides supplying energy, the addition of fat to animal diets improves the absorption of fat-soluble vitamins, decreases pulverulence, increases diet palatability, and the efficiency of utilization of the consumed energy. Furthermore, it reduces the rate of food passage through the gastrointestinal tract, which allows a better absorption of all nutrients present in the diet. The energetic value of oils and fats depend on the following: the length of the carbonic chain, the number of double bonds, the presence or absence of ester bonds (triglycerides or free fatty acids), the specific arrangements of the saturated and unsaturated fatty acids on the glycerol backbone, the composition of the free fatty acid, the composition of the diet, the quantity and the type of the triglycerides supplemented in the diet, the intestinal flora, the sex and the age of the birds. In birds, body fat composition is similar to the composition of the fat from the diet. The apparent digestibility of unsaturated fats is high in the first days of life of birds, whereas apparent digestibility of saturated fats is low. The quantity of oils or fats is assessed by the following methods: titration, moisture, impurities, unsaponifiable, saponification value, percentage of fat, percentage of free fatty acids/acidity and the profile of fatty acids. The methods initial peroxide value, active oxygen method, osi, iodine value, and analysis of the thiobarbituric acid (TBARS) are specific to evaluate the oxidative stability. Considering diets with the same nutritive values, birds fed with rations containing oil present better performance than birds fed no oil. Moreover, the use of oil or fat in diets for broilers may change both the composition and the quality of the carcass.
Performance characterization of the Alpha 21164 microprocessor using TP and SPEC workloads

This paper compares the performance characteristics of the Alpha 21164 to the previous-generation 21064 microprocessor. Measurements on the 21164-based AlphaServer 8200 system are compared to the 21064-based DEC 7000 server using several commercial and technical workloads. The data analyzed includes cycles per instruction, multiple-issued instructions, branch predictions, stall components, cache misses, and instruction frequencies. The AlphaServer 8200 provides 2 to 3 times the performance of the DEC 7000 server based on the faster clock, larger on-chip cache, expanded multiple-issuing, and lower cache/memory latencies and higher bandwidth.
Historical and paleo-tsunami deposits on Kamchatka, Russia: long-term chronologies and long-distance correlations

Abstract. Along the eastern coast of Kamchatka, at a number of localities, we have identified and attempted to assign ages to deposits of both historic and prehistoric (paleo-) tsunamis. These deposits are dated and correlated using tephrochronology from Holocene marker tephra and local volcanic ash layers. Because the historical record of earthquakes and tsunamis on Kamchatka is so short, these investigations can make important contributions to evaluating tsunami hazards. Moreover, because even the historical record is spotty, our work helps add to and evaluate tsunami catalogues for Kamchatka. Furthermore, tsunami deposits provide a proxy record for large earthquakes and thus are important paleoseismological tools. The combined, preserved record of tsunami deposits and of numerous marker tephra on Kamchatka offers an unprecedented opportunity to study tsunami frequency. Using combined stratigraphic sections, we can examine both the average frequency of events for each locality, and also changes in frequency through time. Moreover, using key marker tephra as time lines, we can compare tsunami frequency and intensity records along the Kamchatka subduction zone. Preliminary results suggest real variations in frequency on a millennial time scale, with the period from about 0 to 1000 A.D. being particularly active at some localities.
OpenFab

3D printing hardware is rapidly scaling up to output continuous mixtures of multiple materials at increasing resolution over ever larger print volumes. This poses an enormous computational challenge: large high-resolution prints comprise trillions of voxels and petabytes of data and simply modeling and describing the input with spatially varying material mixtures at this scale is challenging. Existing 3D printing software is insufficient; in particular, most software is designed to support only a few million primitives, with discrete material choices per object. We present OpenFab, a programmable pipeline for synthesis of multi-material 3D printed objects that is inspired by RenderMan and modern GPU pipelines. The pipeline supports procedural evaluation of geometric detail and material composition, using shader-like fablets, allowing models to be specified easily and efficiently. We describe a streaming architecture for OpenFab; only a small fraction of the final volume is stored in memory and output is fed to the printer with little startup delay. We demonstrate it on a variety of multi-material objects.
Murine B Cell Response to TLR7 Ligands Depends on an IFN-β Feedback Loop1

Type I IFNs play an important, yet poorly characterized, role in systemic lupus erythematosus. To better understand the interplay between type I IFNs and the activation of autoreactive B cells, we evaluated the effect of type I IFN receptor (IFNAR) deficiency in murine B cell responses to common TLR ligands. In comparison to wild-type B cells, TLR7-stimulated IFNAR−/− B cells proliferated significantly less well and did not up-regulate costimulatory molecules. By contrast, IFNAR1−/− B cells did not produce cytokines, but did proliferate and up-regulate activation markers in response to other TLR ligands. These defects were not due to a difference in the distribution of B cell populations or a failure to produce a soluble factor other than a type I IFN. Instead, the compromised response pattern reflected the disruption of an IFN-β feedback loop and constitutively low expression of TLR7 in the IFNAR1−/− B cells. These results highlight subtle differences in the IFN dependence of TLR7 responses compared with other TLR-mediated B cell responses.
Circulating Biomarkers for Duchenne Muscular Dystrophy

Abstract Duchenne muscular dystrophy is the most common form of muscular dystrophy. Genetic and biochemical research over the years has characterized the cause, pathophysiology and development of the disease providing several potential therapeutic targets and/or biomarkers. High throughput – omic technologies have provided a comprehensive understanding of the changes occurring in dystrophic muscles. Murine and canine animal models have been a valuable source to profile muscles and body fluids, thus providing candidate biomarkers that can be evaluated in patients. This review will illustrate known circulating biomarkers that could track disease progression and response to therapy in patients affected by Duchenne muscular dystrophy. We present an overview of the transcriptomic, proteomic, metabolomics and lipidomic biomarkers described in literature. We show how studies in muscle tissue have led to the identification of serum and urine biomarkers and we highlight the importance of evaluating biomarkers as possible surrogate endpoints to facilitate regulatory processes for new medicinal products.
Short Cycle Covers of Graphs with Minimum Degree Three

The shortest cycle cover conjecture of Alon and Tarsi asserts that the edges of every bridgeless graph with $m$ edges can be covered by cycles of total length at most $7m/5=1.400m$. We show that every cubic bridgeless graph has a cycle cover of total length at most $34m/21\approx1.619m$, and every bridgeless graph with minimum degree three has a cycle cover of total length at most $44m/27\approx1.630m$.
Prenatal exposure to selenium may protect against wheezing in children by the age of 3

It has been suggested that human in utero exposure to heavy metals such as selenium can reduce the prevalence of childhood asthma and allergic diseases. However, data on this topic are scarce. The objective of the present study was to assess the putative associations between maternal selenium level during pregnancy and the risk of asthma, wheezing, allergic rhinitis, and atopic dermatitis in children from the EDEN birth cohort by the age of 1 and 3 years.
Modeling Software Components Using Behavior Protocols

This thesis proposes a novel approach for a description of a software component’s behavior. The behavior is specified by using behavior protocols –a notation similar to regular expressions, which is easy to read and comprehend. Based on an abstract model of communication between software components, the thesis introduces a notion of component behavior and defines a compliance relation of a component behavior and a protocol-based component specification. The concept of the behavior resp. protocol compliance can be used for reasoning about the specification refining correctness that can be verified at design time and adherence of a component’s implementation to its specification to be checked at run time. Further, the behavior compliance forms the basis for a definition of the a component dynamic update correctness. As a proof of the concept, the behavior protocols are used in the SOFA architecture description language at multiple levels of component abstraction. The application of the abstract communication model to SOFA allows to define a relationship among component descriptions at different abstraction levels and also a component implementation.
Virtual internet communities and commercial success: individual and community-level theory grounded in the atypical case of TimeZone.com

One potentially powerful way of organizing in the new Internet world is through the medium of the virtual Internet community. An effectively managed virtual community provides economic gains to the community organizer and to its members. We attempt to build theory grounded in the study of TimeZone.com, a virtual Internet community devoted to wristwatch hobbyists and enthusiasts. We argue that a member’s off-site communication, experience, perceived value of site management, content, and collectively held knowledge are positively associated with a member’s e-based economic transactions within this virtual community. Building on our theorizing attempts at the individual level, we develop propositions at the organizational level that relate characteristics of virtual Internet communities (membership size, scalability, and level of site management) to commercial success.