Miracle-dz/UniFAR-FTUs huggingface dataset:
SDSS J084539.17+225728.0: the first DBZ white dwarf with a metal‐rich gaseous debris disc

We report the discovery of a third white dwarf hosting a gaseous debris disc, SDSS J084539.17+225728.0. The typical double-peaked Ca II 8498,8542,8662 A emission lines can be modelled in terms of a Keplerian gas disc with a radial extent from ∼0.5 to ∼1.0 R� . The effective temperature of SDSS 0845+2257,T eff � 18 600 ± 500 K, is comparable to the two other white dwarfs with gaseous discs, SDSS 1043+0855 and SDSS 1228+1040, and hence substantially hotter than the bulk of white dwarfs where dusty debris discs were identified through the presence of infrared excess flux. This may suggest that the conditions to produce emission lines from debris discs in the optical wavelength range are only met for a relatively narrow range in T eff. The observed asymmetry in the line profiles indicates a substantial eccentricity in the disc. Two spectra obtained four years apart reveal a significant change in the shapes and equivalent widths of the line profiles, implying that the circumstellar disc evolves on relatively short time-scales. In contrast to SDSS 1043+0855 and SDSS 1228+1040, SDSS 0845+2257 has a helium-dominated atmosphere. We detect photospheric absorption lines of He, Ca, Mg and Si in the Sloan Digital Sky Survey spectrum, and hence classify SDSS 0845+2257 as DBZ white dwarf. The abundances for the three metals determined from model atmosphere fits are Ca/He � 1.3 × 10 −7 ,M g/He � 6.0 × 10 −6 and Si/He � 8.0 × 10 −6 . From the non-detection of Hα, we derive H/He < 3 × 10 −5 , which implies that the hydrogen-to-metal abundance ratio of the circumstellar material is 1000 times lower than in the Sun. This lends strong support to the hypothesis that the gaseous and dusty debris discs found around roughly a dozen white dwarfs originate from the disruption of rocky planetary material.
Finite-Size Scaling in Random $K$-Satisfiability Problems

We provide a comprehensive view of various phase transitions in random K-satisfiability problems solved by stochastic-local-search algorithms. In particular, we focus on the finite-size scaling (FSS) exponent, which is mathematically important and practically useful in analyzing finite systems. Using the FSS theory of nonequilibrium absorbing phase transitions, we show that the density of unsatisfied clauses clearly indicates the transition from the solvable (absorbing) phase to the unsolvable (active) phase as varying the noise parameter and the density of constraints. Based on the solution clustering (percolation-type) argument, we conjecture two possible values of the FSS exponent, which are confirmed reasonably well in numerical simulations for 2 ≤ K ≤ 3.
Object Recognition Using a Tree-Like Procedure Generated from 3-D Model

This paper presents a vision system which automatically generates an object recognition procedure from a 3-D model, and recognizes the object by executing this procedure. The change in object appearances due to the viewpoint is a main issue in 3-D model vision. In this system, the appearances of an object from various view points are described with visible 2-D figures, such as parallel lines and ellipses. These figures are projections of linear or circular visible elements in the model. Then, the appearance descriptions are compared. Similar figures are extracted and merged into a new description, which represents a common and general appearance of the old ones. This process is iterated and ends in a tree-like procedure. The system search the procedure tree and recognizes the object. At a visited node of the tree, figure is estimated by the recognition procedure and looked for in the image. If such figures are detected, a child of the current node is selected for the next visit. Detected figures are used for estimation at the next node. The number of object candidates increases as the number of detected figures increases, and propagated candidates construct a tree. The system searches the candidate tree in addition to the procedure tree. Experimental results show the efficiency of proposed system.
The AT(1)-type angiotensin receptor in oxidative stress and atherogenesis: part I: oxidative stress and atherogenesis.

Initial researchwith angiotensin II focused on its role in the pathogenesis ofhypertension; however, in the past decade, increasing evi-dence has accumulated to indicate that this octapeptide isinvolved in the development of atherosclerosis, myocardialinfarction, vascular and myocardial remodeling, and conges-tive heart failure.
Properties of the Cosmological Density Distribution Function

The properties of the probability distribution function of the cosmological continuous density field are studied. We present further developments and compare dynamically motivated methods to derive the PDF. One of them is based on the Zel'dovich approximation (ZA). We extend this method for arbitrary initial conditions, regardless of whether they are Gaussian or not. The other approach is based on perturbation theory with Gaussian initial fluctuations. We include the smoothing effects in the PDFs. We examine the relationships between the shapes of the PDFs and the moments. It is found that formally there are no moments in the ZA, but a way to resolve this issue is proposed, based on the regularization of integrals. A closed form for the generating function of the moments in the ZA is also presented, including the smoothing effects. We suggest the methods to build PDFs out of the whole series of the moments, or out of a limited number of moments -- the Edgeworth expansion. The last approach gives us an alternative method to evaluate the skewness and kurtosis by measuring the PDF around its peak. We note a general connection between the generating function of moments for small r.m. s $\sigma$ and the non-linear evolution of the overdense spherical fluctuation in the dynamical models. All these approaches have been applied in 1D case where the ZA is exact, and simple analytical results are obtained. The 3D case is analyzed in the same manner and we found a mutual agreement in the PDFs derived by different methods in the the quasi-linear regime. Numerical CDM simulation was used to validate the accuracy of considered approximations. We explain the successful log-normal fit of the PDF from that simulation at moderate $\sigma$ as mere fortune, but not as a universal form of density PDF in general.
Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion

The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13. Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract
Model of Strengthening the Entrepreneurship Character Through Entrepreneurship Commitment

Objective - This study aims to determine the relationship between entrepreneurship character with entrepreneurship commitment. Methodology/Technique - 87 randomly selected undergraduate students studying Business Economics at the As-Syafi'iyah Islamic University Jakarta are surveyed and the data is analyzed using descriptive analysis, correlation and regression methods. Findings - The results show that entrepreneurship commitment has a strong positive influence on entrepreneurship character (0.66). Entrepreneurship commitment is therefore an important instrument to strengthen the character of entrepreneurship. Further, strengthening the character of entrepreneurship can be predicted by entrepreneurship commitment using a simple regression model: Ŷ = 0,658 + 0,823 X. Novelty - In addition, the contribution of entrepreneurship commitment towards the formation of character of entrepreneurship is 44%, with factors such as discipline, perseverance, honesty, fighting power etc. contributing the remaining 56%. Type of Paper: Empirical. Keywords: Entrepreneurship; Character; Entrepreneurship Commitment. JEL Classification: M10, M16, M19.
Toponym Resolution in Text: “Which Sheffield is it?”

Named entity tagging comprises the sub-tasks of identifying a text span and classifying it, but this view ignores the relationship between the entities and the world. Spatial and temporal entities ground events in space-time, and this relationship is vital for applications such as question answering and event tracking. There is much recent work regarding the temporal dimension [13, 10], but no extensive study of the spatial dimension. I propose to investigate how spatial named entities (which are often referentially ambiguous) can be automatically resolved with respect to an extensional coordinate model (toponym resolution), using hybrid heuristic/statistical methods. The major contributions of this research project are a corpus of text manually annotated for spatial named entities with their model correlates as a training/evaluation resource [4] and a novel method to spatially ground toponyms in text.
Wherever You Are, I'll Catch You Modeling the Identification of Location-Based Communities in Mobile Social Networks

Several community detection methods have been proposed in recent years and the majority of these methods ignore location properties and few of them handle mobile social networks. Over the last decade, mobile social networks have witnessed a significant use and a non-stop popularity thanks to smartphones, and thus location based social networks attract an increasing number of users. These tools offer a high accuracy of following and modeling usersâĂŹ movement and facilitating usersâĂŹ interactions. Several factors can influence usersâĂŹ interactions mainly the geographic distance that has an impact on the way users communicate. In this paper, we address the problem of detecting mobile social networks communities.
Low-power Spin Valve Logic using Spin-transfer Torque with Automotion of Domain Walls

A novel scheme for non-volatile digital computation is proposed using spin-transfer torque (STT) and automotion of magnetic domain walls (DWs). The basic computing element is composed of a lateral spin valve (SV) with two ferromagnetic (FM) wires served as interconnects, where DW automotion is used to propagate the information from one device to another. The non-reciprocity of both device and interconnect is realized by sizing different contact areas at the input and the output as well as enhancing the local damping mechanism. The proposed logic is suitable for scaling due to a high energy barrier provided by a long FM wire. Compared to the scheme based on non-local spin valves (NLSVs) in the previous proposal, the devices can be operated at lower current density due to utilizing all injected spins for local magnetization reversals, and thus improve both energy efficiency and resistance to electromigration. This device concept is justified by simulating a buffer, an inverter, and a 3-input majority gate with comprehensive numerical simulations, including spin transport through the FM/non-magnetic (NM) interfaces as well as the NM channel and stochastic magnetization dynamics inside FM wires. In addition to digital computing, the proposed framework can also be used as a transducer between DWs and spin currents for higher wiring flexibility in the interconnect network.
Update on the Chemical Composition Of Crystalline, Smectite, and Amorphous Components for Rocknest Soil and John Klein and Cumberland Mudstone Drill Fines at Gale Crater, Mars

We have previously calculated the chemical compositions of the X-ray-diffraction (XRD) amorphous component of three solid samples (Rocknest (RN) soil, John Klein (JK) drill fines, and Cumberland (CB) drill fines) using major-element chemistry (APXS), volatile-element chemistry (SAM), and crystalline- phase mineralogy (CheMin) obtained by the Curiosity rover as a part of the ongoing Mars Science Laboratory mission in Gale Crater. According to CheMin analysis, the RN and the JK and CB samples are mineralogically distinct in that RN has no detectable clay minerals and both JK and CB have significant concentrations of high-Fe saponite. The chemical composition of the XRD amorphous component is the composition remaining after mathematical removal of the compositions of crystalline components, including phyllosilicates if present. Subsequent to, we have improved the unit cell parameters for Fe-forsterite, augite, and pigeonite, resulting in revised chemical compositions for the XRD-derived crystalline component (excluding clay minerals). We update here the calculated compositions of amorphous components using these revised mineral compositions.
New Zealand lawyers and conveyancers disciplinary tribunal cases involving vulnerable clients, 2011–2017*

ABSTRACT This research analyses disciplinary decisions of the New Zealand Lawyers and Conveyancers Disciplinary Tribunal (NZLCDT) from 2011 to 2017 that involve vulnerable clients. Increasingly, scholarship discusses vulnerability as an ethical concept, including in the legal context. Based on published decisions, the present study inquires whether some legal clients’ vulnerability warrants special attention. Twenty-five of the 193 clients in the NZLCDT decisions qualified as vulnerable based upon age, gender, mental health/neuro-disability or immigrant status. The results may inform disciplinary bodies and inspire preventive strategies by lawyers, educators and regulatory bodies. Ultimately, this evidence-based analysis magnifies the importance of client-centred approaches to risk reduction in legal practice.
Automating XML documents transformations with structuring mapping result

This paper describes a transformation of XML documents from one structure to another could be generated on previously established mappings introduced in our earlier work. That work characterized certain general conditions under which a semi-automatic transformation is possible. The system generates a transformation between two structures of the same document class. We begin by introducing the chosen structure of the mapping result. Then we describe how we generate automatically a transformation script based on such structured mapping result.
1 Cached Guaranteed-Timer Random Drop ( Cached GT-RD ) for Protecting Web Servers

This paper proposes a new method and algorithm to efficiently protect web servers against SYN-flooding denial-of-service attacks and flash crowds. The method proposes use of cache to avoid preemption of legitimate SYN messages from the TCP backlog queue in Random Drop (RD) method during SYN-flooding attacks. A new algorithm, the Cached Guaranteed Timer Random Drop (Cached GT-RD), was designed to maximize the effect of the cache during flash crowds. Performance of the Cached GT-RD was evaluated and compared to an existing solution, the Probabilistic Pre-filtering Random Drop (PPRD), using the simulation method. The experiments demonstrated that Cached GT-RD improved the connection rate and throughput by 67.4 and 73.2% from PP-RD. Cached GT-RD also improved the fairness for slowconnection clients, who most suffer from SYN-flooding attacks and flash crowds. For small TCP backlog queue, the successful connection rate of slow-connection clients became four times better than PP-RD. The proposed solution does not require any modification in either hardware or software for existing data transmissions using TCP/IP. The results of simulation experiments suggest that use of cache will be an efficient and practical solution for both SYN-flooding attacks and flash crowds and Cached GT-RD will be effective in improving fairness in connections.
Local Linearizability for Concurrent Container-Type Data Structures

The semantics of concurrent data structures is usually given by a sequential specification and a consistency condition. Linearizability is the most popular consistency condition due to its simplicity and general applicability. Nevertheless, for applications that do not require all guarantees offered by linearizability, recent research has focused on improving performance and scalability of concurrent data structures by relaxing their semantics. In this paper, we present local linearizability, a relaxed consistency condition that is applicable to container-type concurrent data structures like pools, queues, and stacks. While linearizability requires that the effect of each operation is observed by all threads at the same time, local linearizability only requires that for each thread T, the effects of its local insertion operations and the effects of those removal operations that remove values inserted by T are observed by all threads at the same time. We investigate theoretical and practical properties of local linearizability and its relationship to many existing consistency conditions. We present a generic implementation method for locally linearizable data structures that uses existing linearizable data structures as building blocks. Our implementations show performance and scalability improvements over the original building blocks and outperform the fastest existing container-type implementations.
On Feynman-Kac Perturbation of Symmetric Markov Processes

Let X be an m-symmetric right process on Luzin space E and (E, F) be its associated quasi-regular Dirichlet form. Let µ be a signed smooth measure of X and A µ be the continuous additive functional (CAF in abbreviation) of X with signed Revuz measure µ. It defines a symmetric Feynman-Kac semigroup T t f (x) := E x [exp(A µ t)f (X t)] for t > 0 and f ≥ 0. (1) Define a symmetric quadratic form (E µ , D(E µ)) by D(E µ) := u ∈ F : u ∈ L 2 (E, |µ|) , E µ (u, v) = E(u, v) − E u(x)v(x)µ(dx) for u, v ∈ D(C). We say that the form (E µ , D(E µ)) is bounded from below if there is some α 0 ≥ 0 such that E µ α 0 (u, u) := E µ (u, u) + α 0 (u, u) ≥ 0 for every u ∈ D(E µ). For a non-negative smooth measure ν, we say it is in the Kato class of X if lim t→0 sup x∈E [A ν t ] = 0. that if ν is in the Kato class of X, then for every ε > 0, there is some constant A ε > 0 such that E u(x) 2 ν(dx) ≤ ε E(u, u) + A ε E u(x) 2 m(dx) for every u ∈ F.
An Obstacle Extraction Method Using Virtual Disparity Image

The driving support system is one of most important research field in intelligent transport system (ITS). In this paper, we address an obstacle extraction method for driving support system. The stereovision system is one of most suit sensor to recognize details of environment. On the other hand, a disparity image obtained by stereovision system has quite a lot of information. Therefore an efficient algorithm to analyze obtained disparity image is strongly demanded. If the road surface is extracted, obstacles can be easily extracted by evaluating whether one object touch on a road or not. In this paper, we propose a novel method to estimate three-dimensional road surface position by using virtual disparity image. Moreover, an obstacle extraction method is expressed.
Average effort and average mastery in the identification of the Zone of Proximal Development

We propose a set of formal definitions aiming to address the personalization and adaptivity of courses in e-learning environments. We build on a developing framework which relies on pedagogical foundations of the Vygotskij Theory, and formalize requirements to meet, in order to support its implementation within e-learning software systems.
Fast, scalable and accurate differential expression analysis for single cells

Analysis of single-cell RNA-seq data is challenging due to technical variability, high noise levels and massive sample sizes. Here, we describe a normalization technique that substantially reduces technical variability and improves the quality of downstream analyses. We also introduce a nonparametric method for detecting differentially expressed genes that scales to > 1,000 cells and is both more accurate and ~10 times faster than existing parametric approaches.
Hilbert-Schmidt Lower Bounds for Estimators on Matrix Lie Groups for ATR

Deformable template representations of observed imagery model the variability of target pose via the actions of the matrix Lie groups on rigid templates. In this paper, we study the construction of minimum mean squared error estimators on the special orthogonal group, SO(n), for pose estimation. Due to the nonflat geometry of SO(n), the standard Bayesian formulation of optimal estimators and their characteristics requires modifications. By utilizing Hilbert-Schmidt metric defined on GL(n), a larger group containing SO(n), a mean squared criterion is defined on SO(n). The Hilbert-Schmidt estimate (HSE) is defined to be a minimum mean squared error estimator, restricted to SO(n). The expected error associated with the HSE is shown to be a lower bound, called the Hilbert-Schmidt bound (HSB), on the error incurred by any other estimator. Analysis and algorithms are presented for evaluating the HSE and the HSB in cases of both ground-based and airborne targets.
Characterization of human translesion DNA synthesis across a UV-induced DNA lesion

Translesion DNA synthesis (TLS) during S-phase uses specialized TLS DNA polymerases to replicate a DNA lesion, allowing stringent DNA synthesis to resume beyond the offending damage. Human TLS involves the conjugation of ubiquitin to PCNA clamps encircling damaged DNA and the role of this post-translational modification is under scrutiny. A widely-accepted model purports that ubiquitinated PCNA recruits TLS polymerases such as pol η to sites of DNA damage where they may also displace a blocked replicative polymerase. We provide extensive quantitative evidence that the binding of pol η to PCNA and the ensuing TLS are both independent of PCNA ubiquitination. Rather, the unique properties of pols η and δ are attuned to promote an efficient and passive exchange of polymerases during TLS on the lagging strand. DOI: http://dx.doi. org/10.7554/eLife.19788. 001
Predicting Cardiovascular Risks - Using POSSUM, PPOSSUM and Neural Net Techniques

Neural Networks are broadly applied in a number of fields such as cognitive science, diagnosis, and forecasting. Medical decision support is one area of increasing research interest. Ongoing collaborations between cardiovascular clinicians and computer science are looking at the application of neural networks (and other data mining techniques) to the area of individual patient diagnosis, based on clinical records (from Hull and Dundee sites). The current research looks to advance initial investigations in a number of ways. Firstly, through a rigorous analysis of the clinical data, using data mining and statistical tools, we hope to be able to extend the usefulness of much of the clinical data set. Problems with the data include differences in attribute presence and use across different sites, and missing values. Secondly we look to advance the classification of referred patients with different outcome through the rigorous use of POSSUM, PPOSSUM and both supervised and unsupervised neural net techniques. Through the use of different classifiers, a better clinical diagnostic support model may be built.