Miracle-dz/UniFAR-FTUs huggingface dataset:
The Type IIb SN 2011dh: Two years of observations and modelling of the lightcurves

We present optical and near-infrared (NIR) photometry and spectroscopy as well as modelling of the lightcurves of the Type IIb supernova (SN) 2011dh. Our extensive dataset, for which we present the observations obtained after day 100, spans two years, and complemented with Spitzer mid-infrared (MIR) data, we use it to build an optical-to-MIR bolometric lightcurve between days 3 and 732. To model the bolometric lightcurve before day 400 we use a grid of hydrodynamical SN models, which allows us to determine the errors in the derived quantities, and a bolometric correction determined with steady-state non-local thermodynamic equilibrium (NLTE) modelling. Using this method we find a helium core mass of 3.1^(+0.7)_(-0.4) M⊙ for SN 2011dh, consistent within error bars with previous results obtained using the bolometric lightcurve before day 80. We compute bolometric and broad-band lightcurves between days 100 and 500 from spectral steady-state NLTE models, presented and discussed in a companion paper. The preferred 12 M⊙ (initial mass) model, previously found to agree well with the observed spectra, shows a good overall agreement with the observed lightcurves, although some discrepancies exist. Time-dependent NLTE modelling shows that after day ~600 a steady-state assumption is no longer valid. The radioactive energy deposition in this phase is likely dominated by the positrons emitted in the decay of ^(56)Co, but seems insufficient to reproduce the lightcurves, and what energy source is dominating the emitted flux is unclear. We find an excess in the K and the MIR bands developing between days 100 and 250, during which an increase in the optical decline rate is also observed. A local origin of the excess is suggested by the depth of the He I 20 581 A absorption. Steady-state NLTE models with a modest dust opacity in the core (τ = 0.44), turned on during this period, reproduce the observed behaviour, but an additional excess in the Spitzer 4.5 μm band remains. Carbon-monoxide (CO) first-overtone band emission is detected at day 206, and possibly at day 89, and assuming the additional excess to bedominated by CO fundamental band emission, we find fundamental to first-overtone band ratios considerably higher than observed in SN 1987A. The profiles of the [O I] 6300 A and Mg I] 4571 A lines show a remarkable similarity, suggesting that these lines originate from a common nuclear burning zone (O/Ne/Mg), and using small scale fluctuations in the line profiles we estimate a filling factor of ≲0.07 for the emitting material. This paper concludes our extensive observational and modelling work on SN 2011dh. The results from hydrodynamical modelling, steady-state NLTE modelling, and stellar evolutionary progenitor analysis are all consistent, and suggest an initial mass of ~12 M⊙ for the progenitor.
Ubiquitous Semantic Applications: A Systematic Literature Review

Recently practical approaches for development of ubiquitous semantic applications have made quite some progress. In particular in the area of the ubiquitous access to the semantic data the authors recently observed a large number of approaches, systems and applications being described in the literature. With this survey the authors aim to provide an overview on the rapidly emerging field of Ubiquitous Semantic Applications (UbiSA). The authors conducted a systematic literature review comprising a thorough analysis of 48 primary studies out of 172 initially retrieved papers. The authors obtained a comprehensive set of quality attributes for UbiSA together with corresponding application features suggested for their realization. The quality attributes include aspects such as mobility, usability, heterogeneity, collaboration, customizability and evolvability. The primary studies were surveyed in the light of these quality attributes and the authors performed a thorough analysis of five ubiquitous semantic applications, six frameworks for UbiSA, three UbiSA specific ontologies, five ubiquitous semantic systems and nine general approaches. The proposed quality attributes facilitate the evaluation of existing approaches and the development of novel, more effective and intuitive UbiSA.
3D Model of Lamprey Estrogen Receptor with Estradiol and 15α-Hydroxy-Estradiol

Background Lamprey, basal vertebrate, is an important model system for understanding early events in vertebrate evolution. Lamprey contains orthologs of the estrogen receptor [ER], progesterone receptor and corticoid receptor. A perplexing property of lamprey is that 15α-hydroxy-steroids are active steroids. For example, 15α-hydroxy-estradiol [15α-OH-E2] is the estrogen, instead of estradiol [E2]. To investigate how 15α-OH-E2 binds lamprey ER, we constructed a 3D model of the lamprey ER with E2 and 15α-OH-E2. Methodology We used the 3D structure of human ERα as a template to construct a 3D model of lamprey ER. E2 and 15α-OH-E2 were inserted into the 3D model of lamprey ER and 15α-OH-E2 was inserted into human ERα. Then the each steroid-protein complex was refined using Discover 3 from Insight II software. To determine if lamprey ER had some regions that were unique among vertebrate ERs, we used the ligand-binding domain of lamprey ER as a query for a BLAST search of GenBank. Principal Findings Our 3D model of lamprey ER with 15α-OH-E2 shows that Sδ on Met-409 can form a hydrogen bond with the 15α-hydroxyl on 15α-OH-E2. In human ERα, the corresponding residue Ile-424 has a van der Waals contact with 15α-OH-E2. BLAST analysis of GenBank indicates that among vertebrate ERs, only lamprey ER contains a methionine at this position. Thus, the contact between Sδ on Met-409 and 15α-OH-E2 is unique. Interestingly, BLAST finds that five New World monkeys and a sturgeon contain a valine instead of isoleucine. Significance In addition to shedding light on the structure of the ER in a basal vertebrate, our 3D model of lamprey ER should prove useful in virtual screening of chemical libraries to identify compounds for controlling reproduction in sea lamprey, an environmental pest in Lake Michigan.
Buer Occupancy Asymptotics in Networks with Heterogeneous Long-tailed Inputs

In this paper, we consider a network in which sessions with long-tailed session lengths arrive as Poisson processes. In particular, we assume that a session of type n transmits rn cells per unit time and lasts for a random time n with a generalized Pareto distribution given by IP(n >x ) nx (1+n) for large x ,w heren ,n > 0. The network is assumed to be loop-free with respect to source-destination routes. We characterize the order asymptotics of the complementary buer occupancy distribution at each node in terms of the input characteristics of the sessions. In particular, we show that the distributions obey a power law whose exponent can be calculated via solving a fixed point and deterministic knapsack problem. The paper concludes with some canonical examples.
Comparative Analysis of Clustering Algorithms for Outlier Detection in Data Streams

Nowadays, data mining has become one of the most popular research areas in the field of computer science, because data mining techniques are used for extracting the hidden knowledge from the large databases. In data mining, most of the work is emphasized over knowledge discovery and data stream mining is becoming an active research area in this domain. A data stream is a similar to river, it means continuous and massive sequence of data elements are in and out generated at a rapid rate and the analysis of data stream has been recently attracted attention over in data mining research community. When the amount of data is very huge, it leads to a numerous computational and mining challenges due to shortage of hardware and software limitations. Data mining techniques are newly proposed for data streams they are highly helpful to mine are data stream clustering, data stream classification, frequent pattern technique, sliding window techniques and so on. For outlier detection data stream clustering algorithm is highly needed. This main objective of this research work is to perform the clustering process in data streams and detecting the outliers in data streams. In this research work, two clustering algorithms namely BIRCH with CLARANS and CURE with CLARANS are used for finding the outliers in data streams. Different types, sizes of data sets and two performance factors such as clustering accuracy and outlier detection accuracy are used for analysis. By analyzing the experimental results, it is observed that the CURE with CLARANS clustering algorithm performance is more accurate than the BIRCH with CLARANS.
A Lexicalized Ontology for Spatial Semantics

This paper presents an ontology of lexicalized spatial concepts designed for text processing. The ontology draws on existing linguistic resources and is experimentally shown to improve the automatic extraction of ACE spatial relations, PropBank locative arguments and FrameNet spatial frame elements. We will use the ontology for corpus annotation and automatic inference in the spatial semantic domain.
Symbiotic intelligence: Self-organizing knowledge on distributed networks, driven by human interaction

This work addresses how human societies, and other diverse and distributed systems, solve collective challenges that are not approachable from the level of the individual, and how the Internet will change the way societies and organizations view problem solving. The authors apply the ideas developed in self-organizing systems to understand self-organization in informational systems. The simplest explanation as to why animals (for example, ants, wolves, and humans) are organized into societies is that these societies enhance the survival of the individuals which make up the populations. Individuals contribute to, as well as adapt to, these societies because they make life easier in one way or another, even though they may not always understand the process, either individually or collectively. Despite the lack of understanding of the how of the process, society during its existence as a species has changed significantly, from separate, small hunting tribes to a highly technological, globally integrated society. The authors combine this understanding of societal dynamics with self-organization on the Internet (the Net). The unique capability of the Net is that it combines, in a common medium, the entire human-technological system in both breadth and depth: breadth in the integration of heterogeneous systems of machines, information and people; and depth in the detailed capturing of the entire complexity of human use and creation of information. When the full diversity of societal dynamics is combined with the accuracy of communication on the Net, a phase transition is argued to occur in problem solving capability. Through conceptual examples, an experiment of collective decision making on the Net and a simulation showing the effect of noise and loss on collective decision making, the authors argue that the resulting symbiotic structure of humans and the Net will evolve as an alternative problem solving approach for groups, organizations and society. Self-organizing knowledge formation from this symbiotic intelligence exemplifies a new type of self-organizing system, one without dissipation and not constrained by limited resources.
Structural Segmentation of Musical Audio by Constrained Clustering

We describe a method of segmenting musical audio into structural sections based on a hierarchical labeling of spectral features. Frames of audio are first labeled as belonging to one of a number of discrete states using a hidden Markov model trained on the features. Histograms of neighboring frames are then clustered into segment-types representing distinct distributions of states, using a clustering algorithm in which temporal continuity is expressed as a set of constraints modeled by a hidden Markov random field. We give experimental results which show that in many cases the resulting segmentations correspond well to conventional notions of musical form. We show further how the constrained clustering approach can easily be extended to include prior musical knowledge, input from other machine approaches, or semi-supervision.
Consistent Volumetric Discretizations Inside Self‐Intersecting Surfaces

Decades of research have culminated in a robust geometry processing pipeline for surfaces. Most steps in this pipeline, like deformation, smoothing, subdivision and decimation, may create self‐intersections. Volumetric processing of solid shapes then becomes difficult, because obtaining a correct volumetric discretization is impossible: existing tet‐meshing methods require watertight input. We propose an algorithm that produces a tetrahedral mesh that overlaps itself consistently with the self‐intersections in the input surface. This enables volumetric processing on self‐intersecting models. We leverage conformalized mean‐curvature flow, which removes self‐intersections, and define an intrinsically similar reverse flow, which prevents them. We tetrahedralize the resulting surface and map the mesh inside the original surface. We demonstrate the effectiveness of our method with applications to automatic skinning weight computation, physically based simulation and geodesic distance computation.
HandLog: a deformable tangible device for continuous input through finger flexion

We introduce HandLog, a novel handheld interaction device that supports single handed deformation through finger flexion as a continuous digital input. It consists of a 3D printed core inserted within a foam sleeve embedded with conductive foam columns. By measuring resistance changes across the columns during deformation, whole hand or individual finger flexion motions can be mapped to digital data in real-time. We conducted a user study that demonstrated the successful use of the device for game input. The results indicated that users could quickly become competent with the device and that when compared with discrete controls its supported interactions created a more engaging experience. HandLog has great potential for other application domains, including hand exercise for rehabilitation and handheld controllers for smart homes in ubiquitous computing.
Counter ow Pipeline Processor ArchitectureRobert

The counterrow pipeline processor architecture (cfpp) is a proposal for a family of micro-architectures for risc processors. The architecture derives its name from its fundamental feature, namely that instructions and results ow in opposite directions within a pipeline and interact as they pass. The architecture seeks geometric regularity in processor chip layout, purely local control to avoid performance limitations of complex global pipeline stall signals, and simplicity that might lead to provably correct processor designs. Moreover, cfpp designs allow asynchronous implementations, in contrast to conventional pipeline designs where the synchronization required for operand forwarding makes asynchronous designs unattractive. This paper presents the cfpp architecture and a proposal for an asynchronous implementation. Detailed performance simulations of a complete processor design are not yet available.
Two-View Label Propagation to Semi-supervised Reader Emotion Classification

In the literature, various supervised learning approaches have been adopted to address the task of reader emotion classification. However, the classification performance greatly suffers when the size of the labeled data is limited. In this paper, we propose a two-view label propagation approach to semi-supervised reader emotion classification by exploiting two views, namely source text and response text in a label propagation algorithm. Specifically, our approach depends on two word-document bipartite graphs to model the relationship among the samples in the two views respectively. Besides, the two bipartite graphs are integrated by linking each source text sample with its corresponding response text sample via a length-sensitive transition probability. In this way, our two-view label propagation approach to semi-supervised reader emotion classification largely alleviates the reliance on the strong sufficiency and independence assumptions of the two views, as required in co-training. Empirical evaluation demonstrates the effectiveness of our two-view label propagation approach to semi-supervised reader emotion classification.
Initial delay vs. interruptions: Between the devil and the deep blue sea

End user quality perception in the context of Internet applications is often characterized by waiting times before service consumption as well as interruptions during service consumption. In particular in case of bad network conditions, network and service providers have to trade off between these two impairment types, i.e. between the devil and the deep blue sea. In this paper we investigate this tradeoff in order to guide the design and development of Internet applications and network management approaches. The contribution of this paper is twofold. Firstly, we quantify the impact of initial delays on the user perceived Quality of Experience (QoE) for different application scenarios by means of subjective laboratory and crowdsourcing studies. We show that QoE for a given waiting time strongly depends on the concrete application at hand but that rating diversity remains fairly application-invariant. Secondly, using the example of YouTube video streaming we compare the influence of initial delays and interruptions (stallings) during watching. Our results demonstrate that users are extremely sensitive to interruptions and that services should be designed accordingly e.g. by increasing initial delay for prebuffering to overcome lack of resources.
Use of 3 CAPS Architecture to Simulate InhibitionProcesses in Grammatical

The paper aims to investigate what happens to grammatical assignment processes after a Noun Phrase (NP) had received its speciic grammatical function in sentence comprehension. It postulates that inhibition processes should play a signiicant role during this post{assignment stage, especially when multiple assignments are required, such as in center{embedding construction (e.g. The judge that ignored the doctor watched the movie. .). More precisely, two kinds of inhibition processes are assumed to come into play: 1. First, passive inhibition processes are supposed to play a part, as a mere consequence of the passage of time. They would lead to a decrease in the activation of a given grammatical function during the post{assignment stage. They are supposed to have little, if not, cost in working memory. 2. Secondly, active inhibition processes are assumed to be required when a new grammatical assignment has to be performed in the course of processing. They should be particularly important in case an NP has to receive two diierent functions in the same sentence such as with object relative clauses (e.g. The judge that the doctor ignored watched the movie. .). They are supposed to have some cost in working memory and to be tied to individual diierences both in working memory capacities and in inhibitory capacities. The paper presents rst human data obtained when testing the above-mentioned hypotheses in self-paced reading tasks. Secondly it explores how CCREADER (Just & Carpenter, 1992) would be used to implement these passive and active inhibition processes. CCREADER is an implemented cognitive model whose architecture, named 3CAPS, is speciically designed to simulate eeects of working memory limitations on symbolic language processing together with activation / inhibition processes during sentence comprehension.
Integrating Deoxyribozymes into Colorimetric Sensing Platforms

Biosensors are analytical devices that have found a variety of applications in medical diagnostics, food quality control, environmental monitoring and biodefense. In recent years, functional nucleic acids, such as aptamers and nucleic acid enzymes, have shown great potential in biosensor development due to their excellent ability in target recognition and catalysis. Deoxyribozymes (or DNAzymes) are single-stranded DNA molecules with catalytic activity and can be isolated to recognize a wide range of analytes through the process of in vitro selection. By using various signal transduction mechanisms, DNAzymes can be engineered into fluorescent, colorimetric, electrochemical and chemiluminescent biosensors. Among them, colorimetric sensors represent an attractive option as the signal can be easily detected by the naked eye. This reduces reliance on complex and expensive equipment. In this review, we will discuss the recent progress in the development of colorimetric biosensors that make use of DNAzymes and the prospect of employing these sensors in a range of chemical and biological applications.
Decomposition by Successive Convex Approximation: A Unifying Approach for Linear Transceiver Design in Heterogeneous Networks

We study the downlink linear precoder design problem in a multicell dense heterogeneous network (HetNet). The problem is formulated as a general sum-utility maximization (SUM) problem, which includes as special cases many practical precoder design problems such as multicell coordinated linear precoding, full and partial per-cell coordinated multipoint transmission, zero-forcing precoding, and joint BS clustering and beamforming/precoding. The SUM problem is difficult due to its nonconvexity and the tight coupling of the users' precoders. In this paper, we propose a novel convex approximation technique to approximate the original problem by a series of convex subproblems, each of which decomposes across all the cells. The convexity of the subproblems allows for efficient computation, while their decomposability leads to distributed implementation. Our approach hinges upon the identification of certain key convexity properties of the sum-utility objective, which allows us to transform the problem into a form that can be solved using a popular algorithmic framework called block successive upper-bound minimization (BSUM). Simulation experiments show that the proposed framework is effective for solving interference management problems in large HetNet.
Visigoth fault tolerance

We present a new technique for designing distributed protocols for building reliable stateful services called Visigoth Fault Tolerance (VFT). VFT introduces the Visigoth model, which makes it possible to calibrate the timing assumptions of a system using a threshold of slow processes or messages, and also to distinguish between non-malicious arbitrary faults and correlated attack scenarios. This enables solutions that leverage the characteristics of data center systems, namely their secure environment and predictable performance, in order to allow replicated systems to be more efficient with respect to the utilization of resources than those designed under asynchrony and Byzantine assumptions, while avoiding the need to make a system synchronous, or to restrict failure modes to silent crashes. We implemented a VFT protocol for a state machine replication library, and ran several benchmarks. Our evaluation shows that VFT has comparable performance to existing schemes and brings significant benefits in terms of the throughput per dollar, i.e., the server cost for sustaining a certain level of request execution.