Miracle-dz/UniFAR-FTUs huggingface dataset:
Secular Evolution via Bar-driven Gas Inflow: Results from BIMA SONG

We present an analysis of the molecular gas distributions in the 29 barred and 15 unbarred spirals in the BIMA CO (J = 1-0) Survey of Nearby Galaxies (SONG). For galaxies that are bright in CO, we confirm the conclusion by Sakamoto et al. that barred spirals have higher molecular gas concentrations in the central kiloparsec. The SONG sample also includes 27 galaxies below the CO brightness limit used by Sakamoto et al. Even in these less CO-bright galaxies we show that high central gas concentrations are more common in barred galaxies, consistent with radial inflow driven by the bar. However, there is a significant population of early-type (Sa-Sbc) barred spirals (6 of 19) that have no molecular gas detected in the nuclear region and have very little out to the bar corotation radius. This suggests that in barred galaxies with gas-deficient nuclear regions, the bar has already driven most of the gas within the bar corotation radius to the nuclear region, where it has been consumed by star formation. The median mass of nuclear molecular gas is over 4 times higher in early-type bars than in late-type (Sc-Sdm) bars. Since previous work has shown that the gas consumption rate is an order of magnitude higher in early-type bars, this implies that the early types have significantly higher bar-driven inflows. The lower accretion rates in late-type bars can probably be attributed to the known differences in bar structure between early and late types. Despite the evidence for bar-driven inflows in both early and late Hubble-type spirals, the data indicate that it is highly unlikely for a late-type galaxy to evolve into an early type via bar-induced gas inflow. Nonetheless, secular evolutionary processes are undoubtedly present, and pseudobulges are inevitable; evidence for pseudobulges is likely to be clearest in early-type galaxies because of their high gas inflow rates and higher star formation activity.
Service User Satisfaction in a Low Secure Forensic Learning Disability Unit

Despite an increasing trend of service user involvement in psychiatric research, few studies involving the recipients of secure care, or individuals with learning disability, were identified. It was argued that service users with learning disabilities detained in a secure hospital setting were an important source of information about the care they received. It was predicted that this group would provide a valid and useful account of their experiences and that concerns would be raised in similar areas to those that have been reported in other groups of service users. These included concerns relating to environmental conditions, therapeutic activities, quality of available information about care, and concerns relating to living with others. Seven service users completed a semi-structured interview about their experiences of the care that they received. Data were analysed using content analysis in order to derive a series of key themes whilst acknowledging the individuality of participants’ experiences. Themes were identified relating to two areas: Detention and Treatment. Findings supported predictions that individuals with learning disability could give valid views about their treatment. There was overlap between the findings of this research and previous studies considering views of mental health/forensic and learning disabled service users.
Test Instructions Do Not Moderate the Indirect Effect of Perceived Test Importance on Test Performance in Low-Stakes Testing Contexts

Assessment specialists expend a great deal of energy to promote valid inferences from test scores gathered in low-stakes testing contexts. Given the indirect effect of perceived test importance on test performance via examinee effort, assessment practitioners have manipulated test instructions with the goal of increasing perceived test importance. Importantly, no studies have investigated the impact of test instructions on this indirect effect. In the current study, students were randomly assigned to one of three test instruction conditions intended to increase test relevance while keeping the test low-stakes to examinees. Test instructions did not impact average perceived test importance, examinee effort, or test performance. Furthermore, the indirect relationship between importance and performance via effort was not moderated by instructions. Thus, the effect of perceived test importance on test scores via expended effort appears consistent across different messages regarding the personal relevance of the test to examinees. The main implication for testing practice is that the effect of instructions may be negligible when reflective of authentic low-stakes test score use. Future studies should focus on uncovering instructions that increase the value of performance to the examinee yet remain truthful regarding score use.
Online Direct Density-Ratio Estimation Applied to Inlier-Based Outlier Detection

Many machine learning problems, such as nonstationarity adaptation, outlier detection, dimensionality reduction, and conditional density estimation, can be effectively solved by using the ratio of probability densities. Since the naive two-step procedure of first estimating the probability densities and then taking their ratio performs poorly, methods to directly estimate the density ratio from two sets of samples without density estimation have been extensively studied recently. However, these methods are batch algorithms that use the whole data set to estimate the density ratio, and they are inefficient in the online setup, where training samples are provided sequentially and solutions are updated incrementally without storing previous samples. In this letter, we propose two online density-ratio estimators based on the adaptive regularization of weight vectors. Through experiments on inlier-based outlier detection, we demonstrate the usefulness of the proposed methods.
A Fun and Engaging Interface for Crowdsourcing Named Entities

There are many current problems in natural language processing that are best solved by training algorithms on an annotated in-language, in-domain corpus. The more representative the training corpus is of the test data, the better the algorithm will perform, but also the less likely it is that such a corpus has already been annotated. Annotating corpora for natural language processing tasks is typically a time consuming and expensive process. In this paper, we provide a case study in using crowd sourcing to curate an in-domain corpus for named entity recognition, a common problem in natural language processing. In particular, we present our use of fun, engaging user interfaces as a way to entice workers to partake in our crowd sourcing task while avoiding inflating our payments in a way that would attract more mercenary workers than conscientious ones. Additionally, we provide a survey of alternate interfaces for collecting annotations of named entities and compare our approach to those systems.
Detection of Dot Matrix Printed Documents Using Component Analysis

Document Quality Analysis is one of the most prominent areas of interest these days. It is used for managing of huge number of documents, detection of fraud document, recognizing identity documents etc. A lot of work has been done in the areas of coloured photograph recognition, improving the quality of documents and printing technology. However, to the best of our knowledge no work has been done to recognize the dot matrix prints from other high quality prints using principle component analysis. This is useful for automatically recognizing the text on a certain print. Post the detection of the quality of the print, recognition of the text can be easily done using specific algorithm for each quality. In this paper, the above objective is achieved by applying principle component analysis before and after smearing of the text on a particular print and then classifying it into dot matrix or non-dot matrix print. Moreover, this approach has also been compared with prior works related to classification and detection of print quality.
Improving P2P IPTV random peers search through user similarity

With internet services to the end users becoming more homogenous, thus providing high bandwidth for all users, multimedia services such as IPTV to the public as a whole will finally become a reality, but even given the more abundant resources, IPTV architecture is far from being highly available due to technical limitations, we aim to provide a meaningful optimization in the P2P distribution model, which is currently based on a random structure bounded by high delays and low performance, by using channel probability, user's habits studies and users' similarity, in order to optimize one of the key aspects of IPTV which is the peers management, which directly reflects on resources and user's Quality of Experience.
Neuroglian-mediated cell adhesion induces assembly of the membrane skeleton at cell contact sites

The protein ankyrin links integral membrane proteins to the spectrin- based membrane skeleton. Ankyrin is often concentrated within restricted membrane domains of polarized epithelia and neurons, but the mechanisms responsible for membrane targeting and its segregation within a continuous lipid bilayer remain unexplained. We provide evidence that neuroglian, a cell adhesion molecule related to L1 and neurofascin, can transmit positional information directly to ankyrin and thereby polarize its distribution in Drosophila S2 tissue culture cells. Ankyrin was not normally associated with the plasma membrane of these cells. Upon expression of an inducible neuroglian minigene, however, cells aggregated into large clusters and ankyrin became concentrated at sites of cell-cell contact. Spectrin was also recruited to sites of cell contact in response to neuroglian expression. The accumulation of ankyrin at cell contacts required the presence of the cytoplasmic domain of neuroglian since a glycosyl phosphatidylinositol- linked form of neuroglian failed to recruit ankyrin to sites of cell- cell contact. Double-labeling experiments revealed that, whereas ankyrin was strictly associated with sites of cell-cell contact, neuroglian was more broadly distributed over the cell surface. A direct interaction between neuroglian and ankyrin was demonstrated using yeast two-hybrid analysis. Thus, neuroglian appears to be activated by extracellular adhesion so that ankyrin and the membrane skeleton selectively associate with sites of cell contact and not with other regions of the plasma membrane.
Molecular-weight-dependent mobilities in regioregular poly(3-hexyl-thiophene) diodes

We have investigated the transport properties in the direction perpendicular to the substrate of regioregular poly(3-hexyl-thiophene) of different molecular weights (MW) in a diode geometry. In these devices, which exhibit space-charge-limited behavior, we find that the mobility values at room temperature increase from 1.33×10−5cm2∕Vsto3.30×10−4cm2∕Vs as the MW is increased from 2.9to31. 1kg∕mol. The mobility is found to be field independent for high MW films, but field dependent for the low MW films. The current–voltage characteristics of the diodes are also studied as a function of temperature from 160Kto300K. The activation energy for carrier transport, extracted from the Arrhenius plot, is found to decrease gradually from 143meVto126meV as the MW is increased.
Research on the Influence of Doctor-Patient Relationship on Physicians’ Citizenship Behavior

Although the doctor-patient relationship (DPR) is a predictor of organizational citizenship behavior (OCB), the relations between DPR and OCB is not well understood. This study was designed to investigate the specific dimensions of OCB among physicians in China and determine the effects of DPR on OCB. The subjects were physicians at five large general hospitals in China, who were selected by random sampling methodology. Then, using empirical study methods, factor analysis and regression analysis for data collecting from 958 samples were made. Finally, we find that OCB consists of four dimensions including civic virtue, sportsmanship, altruism, and conscientiousness. DPR has significant negative impact on the civic virtue, sportsmanship, altruism, and conscientiousness behaviors, respectively. This finding suggests that effective strategies should be applied to promote physicians’ OCB by improving DPR, which can enhance their job performances and improve the quality of health care delivery.
Secure Multiple Deployment in Wireless Sensor Networks

As a fundamental requirement for providing security functionality in sensor networks, key management plays a central role in authentication and encryption. In this paper, we propose the adaptive key selection (AKS) scheme and the adaptive key selection algorithm for secure multiple deployment in sensor networks that target at providing high connectivity between different deployment sets of sensor nodes. Our simulation shows that the AKS scheme can greatly improve the connectivity of sensor nodes while maintaining the security of an existing multiple deployment scheme at the same time.
Model predictive control for the operation of building cooling systems

A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reduction in the central plant electricity cost and improvement of its efficiency.
Māori women leading local sustainable food systems

The article explores how Māori women in Aotearoa (New Zealand) are defining their own food system and the values of the women at the heart of their community food initiatives. Using a blend of participatory and kaupapa Māori (Māori principles) research methodologies, the study took place over the course of 3 years, involving four women or case studies who manage community food initiatives, with three located in the North Island and one in the South Island of New Zealand. The article discusses the benefits of community gardens and farms, noting how they are counteracting food poverty through promoting access to local food while bringing more attention to the essential role that Indigenous women play in addressing food security issues. The case studies exemplify how Māori women are leading the way within their own whānau (families) and communities, promoting local solutions to global food issues, solutions based on their own knowledge and Māori cultural values.
Communicatively Constructing Birth Family Relationships in Open Adoptive Families: Naming, Connecting, and Relational Functioning

ABSTRACT Open adoption (i.e., involving ongoing communication between birth and adoptive families) has become the predominant form of private domestic adoption. As such, an understanding of the communicative structures that create and sustain these families is needed. Grounded in discourse dependent family theorizing, we explored open adoptive parents’ (n = 298) construction of the birth family relationship through naming and connecting. Thematic analysis illuminated six address terms: identical derivative, familiar, cultural derivative, parallel derivative, first name, and no address term. Cluster and discriminant function analysis revealed four open adoption contact types: controlled, social, constant, and concise, which predict relational functioning.
From visual semantic parameterization to graphic visualization

Visualizing natural language description is a difficult and complex task. When dealing with the process of generating images from natural language descriptions, we firstly should consider the real world and find out what key visual information can be extracted from the sentences which represents the most fundament concepts in both virtual and real environments. In this paper, we present the result of a prototype system called 3DSV (3D Story Visualiser) that generates a virtual scene by using simplified story-based descriptions. In particular, we describe the methodology used to parameterize the visual and describable words into XML formatted data structure. Then we discuss how to interpret the parameterized data and create an interactive real-time 3D virtual environment.
Quarkonia decays into two photons induced by space-time noncommutativity

In this article we propose standard model strictly forbidden decay modes, quarkonia (QQ{sub 1{sup -}{sup -}}=J/{psi},{upsilon}) decays into two photons, as a possible signature of space-time noncommutativity. An experimental discovery of J/{psi}{yields}{gamma}{gamma} and/or {upsilon}{yields}{gamma}{gamma} processes would certainly indicate a violation of the Landau-Pomeranchuk-Yang theorem and a definitive appearance of new physics.
HDU: Cross-lingual Textual Entailment with SMT Features

We describe the Heidelberg University system for the Cross-lingual Textual Entailment task at SemEval-2012. The system relies on features extracted with statistical machine translation methods and tools, combining monolingual and cross-lingual word alignments as well as standard textual entailment distance and bag-of-words features in a statistical learning framework. We learn separate binary classifiers for each entailment direction and combine them to obtain four entailment relations. Our system yielded the best overall score for three out of four language pairs.
An Overview of Rescue Robots

The technical innovations increases in our society, so do robots. Looking back a decade, we would never imagine that the society will look like it do today, with principle every device containing a small computer. Rescue robots are one of these things, containing a computer that react with the robots hardware to become a lifesaving tool. The possibilities is high and the limitations are few. With the help of rescue robots, looking over recently used robots, the purpose of them helping us to save life and do general rescue work has gone mostly as wanted and with accomplished results. Still, like always, there are things to improve. This paper gives an overview of the development of where rescue robotics stands today and what might be the future for them. It will also give a briefly introduction to the concept of rescue robotics and what is important to think about when working with it. To be able to manage all possible obstacles and be dynamic we have to know in which environmental conditions the robots have to manage. Often it is an unpredictable environment which make the navigation hard, therefor it need smart systems and well thought-out plans of how to manage every situation.
A new framework of hyperspectral image classification based on spatial spectral interest point

With the development of the hyperspectral sensor technologies, the spatial and spectral resolution of Hyperspectral Image (HSI) have been improved largely. In this case, objects are made up of several pixels which may belong to different materials. It is difficult to separate hyperspectral data with the traditional hyperspectral image classification algorithms. Therefore, based on spatial spectral interest point (SSIP), a new parallel framework of hyperspectral image classification is proposed. The experimental results show that the classification accuracy of our proposed algorithm is effective and dramatically higher than that of existing classification algorithms for 2D pseudo color images.
The Growth of Bacterial Cultures

The study of the growth of bacterial cultures does not constitute a specialized subject or branch of research: it is the basic method of Microbiology. It would be a foolish enterprise, and doomed to failure, to attempt reviewing briefly a "subject" which covers actually our whole discipline. Unless, of course, we considered the formal laws of growth for their own sake, an approach which has repeatedly proved sterile. In the present review we shall consider bacterial growth as a method for the study of bacterial physiology and biochemistry. More precisely, we shall concern ourselves with the quantitative aspects of the method, with the interpretation of quantitative data referring to bacterial growth. Furthermore, we shall considerz exclusively the positive phases of growth, since the study of bacterial "death," i.e., of the negative phases of growth, involves distinct problems and methods. The discussion will be limited to populations considered genetically homogeneous. The problems of mutation and selection in growing cultures have been excellently dealt with in recent review articles by Delbriick (1) and Luria (2). No attempt is made at reviewing the literature on a subject which, as we have just seen, is not really a subject at all. The papers and results quoted have been selected as illustrations of the points discussed.
Analyzing trends by symbolic episode representation and sequence alignment

Data analysis is often associated with quantitative techniques because of the large amount of data and easy-to-use statistical tools. Qualitative trend analysis (QTA) techniques always have to be guided with some data reduction method, e.g. principal component analysis (PCA) or segmentation, and the preprocessed, lowered size data can be analyzed for further aims. Derivative-based segmentation methods are presented which are popular in fault diagnosis. If there is an adequate distance measure, one is able to qualify, compare or classify different time series. This article proposes segmentation-based alignment techniques based on dynamic distance measure: time warping (DTW) and a developed one, which uses pairwise sequence alignment -a common tool in bioinformatics -to align triangular episode sequences. Both techniques highly depend on the pre-defined distance or similarity measure between the trends because they try to find the minimal distance or maximal similarity path. These two techniques are compared and qualified on handwriting data based case study. It has been shown that symbolic episode segmentation based sequence alignment aided by prior knowledge of the operators can handle qualitative trend analysis and thus it is able to monitor and qualify operating processes.
Optical Flow Templates for Superpixel Labeling in Autonomous Robot Navigation

Instantaneous image motion in a camera on-board a mobile robot contains rich information about the structure of the environment. We present a new framework, optical flow templates, for capturing this information and an experimental proof-of-concept that labels superpixels using them. Optical flow templates encode the possible optical flow fields due to egomotion for a specific environment shape and robot attitude. We label optical flow in superpixels with the environment shape they image according to how consistent they are with each template. Specifically, in this paper we employ templates highly relevant to mobile robot navigation. Image regions consistent with ground plane and distant structure templates likely indicate free and traversable space, while image regions consistent with neither of these are likely to be nearby objects that are obstacles. We evaluate our method qualitatively and quantitatively in an urban driving scenario, labeling the ground plane, and obstacles such as passing cars, lamp posts, and parked cars. One key advantage of this framework is low computational complexity, and we demonstrate per-frame computation times of 20ms, excluding optical flow and superpixel calculation.