Miracle-dz/UniFAR-FTUs huggingface dataset:
Scoring attitudes to abortion

We show how to score binary responses to seven items to give a measure of approval for abortion, using a latent variable approach. Three models are suggested to cope with item non-response. The methods are exemplified with the use of a selection of data from the 1986 British Social Attitudes Panel Survey. This paper will use simple latent variable modelling of binary response to try to extract a common factor from expressed attitudes to abortion. The common factor is then used to score the response patterns. We shall also fit models. to allow for item non-response, both in a neutral fashion, and with an attempted recovery of information from the pattern of non-response. The impetus for this work came from the wish to produce a scoring for use in multilevel modelling work (see Wiggins et al., 1990).
Differences in Knowledge, Stress, Sensation Seeking, and Locus of Control Linked to Dietary Adherence in Hemodialysis Patients

Patients with chronic kidney disease (CKD) often require regular hemodialysis (HD) to prolong life. However, between HD sessions, patients have to restrict their diets carefully to avoid excess accumulation of potassium, phosphate, sodium, and fluid, which their diseased kidneys can no longer regulate. Failure to adhere to their renal dietary regimes can be fatal; nevertheless, non-adherence is common, and yet little is known about the psychological variables that might predict this dietary behavior. Thus, this study aimed to assess whether dietary adherence might be affected by a variety of psychological factors including stress, personality, and health locus of control, as well as dietary knowledge, in chronic HD patients. Fifty-one patients (30 men; age range 25–85) who had undergone HD for at least 3 months and had been asked to restrict at least one of potassium, phosphate or fluid, were recruited from a hospital renal unit. Measures of adherence to each of potassium, phosphate, and fluid were derived from standard criteria for these physiological indices in renal patients. Knowledge of food/drink sources of these dietary factors, and their medical implications in relation to HD and CKD were assessed by a bespoke questionnaire. Psychological factors including stress, personality and health locus of control beliefs were measured by standardized questionnaires. Having to restrict a particular nutrient was associated with better knowledge of both food sources and medical complications for that nutrient; however, greater dietary knowledge was not linked to adherence, and knowledge of medical complications tended to be associated with poorer adherence to potassium and phosphate levels. Adherence to these two nutrient requirements was also associated with lower reported stress in the past week. Adherence was associated with differences in locus of control: these differences varied across indices although there was a tendency to believe in external loci. For potassium, phosphate, and fluid restriction, adherers were less likely to be sensation seekers but did not differ from non-adherers on impulsivity, anxiety sensitivity, or hopelessness. In conclusion, the links between dietary adherence and stress, locus of control and personality suggests that screening for such psychological factors may assist in managing adherence in HD patients.
Fish consumption, fish oil, omega-3 fatty acids, and cardiovascular disease.

fatty acids affect cardiac function (including antiarrhythmic effects), hemodynamics (cardiac mechanics), and arterial endothelial function have helped clarify potential mechanisms of action. The present Statement will address distinctions between plant-derived (-linolenic acid, C18:3n-3) and marine-derived (eicosapentaenoic acid, C20:5n-3 [EPA] and docosahexaenoic acid, C22:6n-3 [DHA]) omega-3 fatty acids. (Unless otherwise noted, the term omega-3 fatty acids will refer to the latter.) Evidence from epidemiological studies and RCTs will be reviewed, and recommendations reflecting the current state of knowledge will be made with regard to both fish consumption and omega-3 fatty acid (plant- and marine-derived) supplementation. This will be done in the context of recent guidance issued by the US Environmental Protection Agency and the Food and Drug Administration (FDA) about the presence of environmental contaminants in certain species of fish.
SEAL: Spatio-Textual Similarity Search

Location-based services (LBS) have become more and more ubiquitous recently. Existing methods focus on finding relevant points-of-interest (POIs) based on users' locations and query keywords. Nowadays, modern LBS applications generate a new kind of spatio-textual data, regions-of-interest (ROIs), containing region-based spatial information and textual description, e.g., mobile user profiles with active regions and interest tags. To satisfy search requirements on ROIs, we study a new research problem, called spatio-textual similarity search: Given a set of ROIs and a query ROI, we find the similar ROIs by considering spatial overlap and textual similarity. Spatio-textual similarity search has many important applications, e.g., social marketing in location-aware social networks. It calls for an efficient search method to support large scales of spatio-textual data in LBS systems. To this end, we introduce a filter-and-verification framework to compute the answers. In the filter step, we generate signatures for the ROIs and the query, and utilize the signatures to generate candidates whose signatures are similar to that of the query. In the verification step, we verify the candidates and identify the final answers. To achieve high performance, we generate effective high-quality signatures, and devise efficient filtering algorithms as well as pruning techniques. Experimental results on real and synthetic datasets show that our method achieves high performance.
Online multi-modal distance learning for scalable multimedia retrieval

In many real-word scenarios, e.g., multimedia applications, data often originates from multiple heterogeneous sources or are represented by diverse types of representation, which is often referred to as "multi-modal data". The definition of distance between any two objects/items on multi-modal data is a key challenge encountered by many real-world applications, including multimedia retrieval. In this paper, we present a novel online learning framework for learning distance functions on multi-modal data through the combination of multiple kernels. In order to attack large-scale multimedia applications, we propose Online Multi-modal Distance Learning (OMDL) algorithms, which are significantly more efficient and scalable than the state-of-the-art techniques. We conducted an extensive set of experiments on multi-modal image retrieval applications, in which encouraging results validate the efficacy of the proposed technique.
DBMiner: A System for Mining Knowledge in Large Relational Databases

A data mining system, DBMiner, has been developed for interactive mining of multiple-level knowledge in large relational databases. The system implements a wide spectrum of data mining functions, including generalization, characterization, association, classification, and prediction. By incorporating several interesting data mining techniques, including attribute-oriented induction, statistical analysis, progressive deepening for mining multiple-level knowledge, and meta-rule guided mining, the system provides a user-friendly, interactive data mining environment with good performance.
Cohomological consequences of the pattern map

Billey and Braden defined maps on flag manifolds that are the geometric counterpart of permutation patterns. A section of their pattern map is an embedding of the flag manifold of a Levi subgroup into the full flag manifold. We give two expressions for the induced map on cohomology. One is in terms of generators and the other is in terms of the Schubert basis. We show that the coefficients in the second expression are naturally Schubert structure constants and therefore positive. These formulas also hold for K-theory, and generalize known formulas in type A for cohomology and K-theory.
Billing Users and Pricing for TCP

This paper presents a system for billing users for their TCP traffic. This is achieved by postponing the establishment of connections while the user is contacted, verifying in a secure way that they are prepared to pay. By presenting the user with cost and price information, the system can be used for cost recovery and to encourage efficient use of network resources. The system requires no changes to existing protocols or applications and can be used to recover costs between cooperating sites. Statistics collected from a four-day trace of traffic between the University of California, Berkeley, and the rest of the Internet demonstrate that such a billing system is practical and introduces acceptable latency. An implementation based on the BayBridge prototype router is described. Our study also indicates that pricing schemes may be used to control network congestion either by rescheduling time-insensitive traffic to a less expensive time of the day, or by smoothing packet transfers to reduce traffic peaks. >
Meditation and the neuroscience of consciousness

The overall goal of this essay is to explore the initial findings of neuroscientific research on meditation; in doing so, the essay also suggests potential avenues of further inquiry. The essay consists of three sections that, while integral to the essay as a whole, may also be read independently. The first section, “Defining Meditation,” notes the need for a more precise understanding of meditation as a scientific explanandum. Arguing for the importance of distinguishing the particularities of various traditions, the section presents the theory of meditation from the paradigmatic perspective of Buddhism, and it discusses the difficulties encountered when working with such theories. The section includes an overview of three practices that have been the subject of research, and it ends with a strategy for developing a questionnaire to more precisely define a practice under examination. The second section, “the Intersection of Neuroscience and Meditation,” explores some scientific motivations for the neuroscientific examination of meditation in terms of its potential impact on the brain and body of long-term practitioners. After an overview of the mechanisms of mind-body interaction, this section addresses the use of first-person expertise, especially in relation to the potential for research on the neural counterpart of subjective experience. In general terms, the section thus
Control of Protein Activity and Cell Fate Specification via Light-Mediated Nuclear Translocation

Light-activatable proteins allow precise spatial and temporal control of biological processes in living cells and animals. Several approaches have been developed for controlling protein localization with light, including the conditional inhibition of a nuclear localization signal (NLS) with the Light Oxygen Voltage (AsLOV2) domain of phototropin 1 from Avena sativa. In the dark, the switch adopts a closed conformation that sterically blocks the NLS motif. Upon activation with blue light the C-terminus of the protein unfolds, freeing the NLS to direct the protein to the nucleus. A previous study showed that this approach can be used to control the localization and activity of proteins in mammalian tissue culture cells. Here, we extend this result by characterizing the binding properties of a LOV/NLS switch and demonstrating that it can be used to control gene transcription in yeast. Additionally, we show that the switch, referred to as LANS (light-activated nuclear shuttle), functions in the C. elegans embryo and allows for control of nuclear localization in individual cells. By inserting LANS into the C. elegans lin-1 locus using Cas9-triggered homologous recombination, we demonstrated control of cell fate via light-dependent manipulation of a native transcription factor. We conclude that LANS can be a valuable experimental method for spatial and temporal control of nuclear localization in vivo.
Extracting decision trees from trained neural networks

Neural Networks are successful in acquiring hidden knowledge in datasets. Their biggest weakness is that the knowledge they acquire is represented in a form not understandable to humans. Researchers tried to address this problem by extracting rules from trained Neural Networks. Most of the proposed rule extraction methods required specialized type of Neural Networks; some required binary inputs and some were computationally expensive. Craven proposed extracting MofN type Decision Trees from Neural Networks. We believe MofN type Decision Trees are only good for MofN type problems and trees created for regular high dimensional real world problems may be very complex. In this paper, we introduced a new method for extracting regular C4.5 like Decision Trees from trained Neural Networks. We showed that the new method (DecText) is effective in extracting high fidelity trees from trained networks. We also introduced a new discretization technique to make DecText be able to handle continuous features and a new pruning technique for finding simplest tree with the highest fidelity.
Research Paper No . 2005 / 46 Inequality , Corruption , and Competition in the Presence of Market Imperfections

We analyze the relation between inequality, corruption and competition in a developing economy context where markets are imperfect. We consider an economy where different types of households (efficient and inefficient) choose to undertake production activities. For production, households borrow capital from the credit market. They also incur non-input costs which they could avoid by bribing inspectors. Due to information asymmetry and wealth inequality, the credit market fails to screen out the inefficient types. In addition to the imperfect screening, the inefficient type’s entry is further facilitated by corruption. We analyze the market equilibrium and look at some of the implications. We show that a rise in inequality can lead to an increase in corruption along with greater competition.
IBTC Model: A Model for classification of Queries

Text classification is a way to categorize data in various classes, which shows some identical properties. Data can be easily utilized if once it is stored in well arranged manner. Classification task is used in text mining for mainly two reasons one for store data in well manner in categories and another is to retrieve data as per user requirement in few milliseconds i.e. searching. If data is store in proper place retrieving the data and its information can be retrieved in less time then unstructured data. In text classification if the target text which user wants to search is present in the form of sentence known as query, then it is difficult to search particular document [1]. This paper proposed IBTC model to provide efficiency to search when the target text in the form of query. The results and snapshots show validation and accuracy of proposed model.
Realization of High-Quality Structural Color by Metal-Dielectric-Metal Structure

Extended Abstract The present study produced a metal-ceramic and air-ceramic complex thin film that has a nanohole structure of various sizes using anodization and metal sputtering in combination, and created a high-quality structural color by converting the complex thin film with a target effective refractive index into a multi-layer thin film. First, by applying the effective-medium theory, the nanohole structured thin film was assumed as a metal-ceramic or air-ceramic complex thin film with a new effective refractive index instead of the unique refractive index of the thin film. The effective refractive index was calculated using the Maxwell-Garnett equation [1] and the peak wavelength of the complex thin film’s reflective structural color spectrum was calculated based on the thin-film interference theory. A metal-dielectricmetal (MDM) structure was created by vapor-depositing a metal on the surface of a nanohole-structured complex thin film to improve the quality of low-quality reflective structural color and the improvement was verified through experiments. The complex thin film of a nanohole array structure was produced by altering the factors affecting the refractive index, such as the nanohole’s diameter and thickness as well as the distance between the nanoholes. The distance between the nanoholes was altered by changing the electrolyte and the magnitude of applied voltage used in the anodization process. The nanohole’s diameter was modified through the widening process using alumina etching. The distance between the nanoholes could be altered within the range between 30nm and 500nm depending on the conditions of electrolyte and applied voltage, while the nanohole’s diameter could be changed within the range between 10nm and 400nm. The thickness of a nanohole array was altered according to the growth rate by controlling the total size of applied electric charge using the real time current monitoring system. For the complex thin film simplified into a single medium, the peak wavelength of a reflective structural color spectrum was calculated based on the multi-layer interference theory. To compare the calculated value with the experimental value, this study measured the reflective structural color spectrum of the visible ray field using the halogen light source in the
A Study on an Integer Frequency Offset Estimation and Compensation for DOCSIS 3.1 Downstream

In this paper, we propose an integer frequency offset estimation and compensation method based on PLC preamble correlation in DOCSIS 3.1 Downstream system. The proposed method determines the PLC preamble subcarrier location recovered from PLC data and the one obtained from PLC preamble correlation. We showed the performance of PLC preamble detection in the received signal through the maximum value detection of PLC preamble correlation. Thus we can estimate and compensate for the integer frequency offset by computing the difference of PLC subcarrier locations.
Algorithms for ATPG under Leakage Constraints

Measuring the steady state leakage current (IDDQ) is a very successful testing paradigm detecting faults not discovered when considering standard fault models. Due to increasing vector dependencies and process variations IDDQ testing becomes more difficult. We propose ATPG algorithms to control test vector dependencies even before performing the IDDQ test. Experimental results show that leakage constraints can effectively be handled during test pattern generation without decreasing fault coverage.
ESVP-Cloud: Efficient social-aware video prefetching for adaptive multimedia streaming and video sharing in the clouds

While the demand of video streaming services (VSSs) over the mobile networks have been soaring, the capacity of wireless links cannot keep up with the traffic needs. The difference between traffic demand and the link capacity, together with time-varying link conditions, causes inadequate service quality of video streaming, such as long buffering delays and sporadic disruptions. In this paper, by leveraging the present cloud computing technology, ESVP-Cloud architecture (i.e. Efficient Social-aware Video Prefetching) for mobile video streaming is proposed. The cloud-assisted adaptive video streaming with efficient social video sharing (ESVS) and social-aware video prefetching (SAVP) are the two basic parts of the proposed system. The personalized private agent is constructed in the cloud by ESVS and SAVP for each active mobile user to provide video streaming services efficiently. The streaming flow is adaptively adjusted by using scalable video coding technique. Similarly, ESVS monitors the social activities between each mobile user; in order that their private agents can efficiently share the videos and also try to prefetch video data segments in advance. The ESVP-Cloud architecture is proposed to demonstrate its performance, which shows that cloud computing will improve the quality of multimedia streaming and effectively offers the adaptive streaming. Moreover, this will also perform video sharing and social-aware video prefetching which reduces the access delay of shared videos to match the user demands.
A family of FH sequences based on 3DES block cipher for FHMA communications

A novel family of frequency hopping sequences based on 3DES iterated block cipher is proposed for frequency-hopping multiple-access (FHMA) communications. The design offers a class of nonlinear FH codes with high security, large linear span and a uniform spread over the entire frequency bandwidth. Moreover, FH sequences among the family are independent from each other and they perform as well as random patterns in terms of multiple access interference in anti-jamming applications. With the performance of packet error and throughput for FHMA network being derived in theory, many numerical results of the 3DES sequences are presented, comparing with those of shift register sequences and chaotic FH sequences. Efficiently implemented in field-programmable–gate-arrays (FPGA), the generator prototype of the proposed sequence has been realized and incorporated into fast FH radio.
Variable Threshold Based Reversible Watermarking: Hiding Depth Maps

This paper presents a lossless data hiding approach based on integer wavelet transform and variable threshold for a novel application of watermarking. In this novel application, a depth map of an object obtained from sequence of 2D images is secretly embedded in one of the 2-D images for subsequent 3-D analysis after transmission. Additionally, for efficient generation of the depth map, we also propose a new focus measure based on discrete cosine transform (DCT) and principal component analysis. The proposed approach is able not only in extracting the depth map, but also recovers the cover image. Experimental results show the capability of the proposed approach of secretly transmitting and retrieving the depth information. The employment of this novel idea of hiding depth maps in corresponding 2-D cover images could be helpful in medical and military image processing, security based stickers, mobile advertizing, image vision, law enforcement, etc. Additionally, if the depth map is generated through a standard approach, it could also help in the authentication related applications of the cover image.