LLukas22/scidocs huggingface dataset:
Treating Affair Couples: Clinical Considerations and Initial Findings

Infidelity can have devastating effects on couples' relationships. Not only are couples typically confused and uncertain about how to proceed, but couple therapists also report that treating infidelity is one of their greatest clinical challenges. In the current article, we present a conceptual model of response to infidelity with a corresponding infidelity-specific, couple-based intervention. This intervention incorporates interventions from cognitive-behavioral, insight-oriented, trauma-based, and forgiveness approaches to working with couples. In addition to this intervention created specifically for treating infidelity, we discuss how existing, empirically supported couple therapies such as traditional behavioral couple therapy (TBCT) and integrative behavioral couple therapy (IBCT) approach the treatment of infidelity. Finally, we present preliminary findings from two small treatment studies that provide initial, encouraging findings for the utility of the infidelity-specific intervention as well as TBCT and IBCT for treating infidelity.
Variable rest masses in 5-dimensional gravitation confronted with experimental data

Cosmological solutions of Einstein equation for a 5-dimensional space time, in the case of a dust-filled universe, are presented. With these solutions we are able to test a hypothetical relation between the rest mass of a particle and the 5th dimension. Comparison with experiment strongly refutes the implied dependence of the rest mass on the cosmological time.
Mercury transformations in coal combustion flue gas

Project Description The EERC is performing fundamental research to understand mechanisms responsible for conversion of mercury to other chemical species within combustion and gasification flue gas. This research is imperative for development and validation of improved mercury emission measurement, monitoring, and control. Several tasks are devoted to understanding mercury transformations. Unburned carbon particles from two carbon-rich fly ashes derived from full-scale coal-fired utility boilers are being separated from inorganic ash fractions. The fly ash samples were selected based on a high propensity for effective capturing of mercury. Carbon concentrates are being characterized in detail to determine which physical and chemical properties may be important in capturing mercury. A portable bench-scale entrained-flow reactor (EFR) is being used to determine mercury oxidation and particulate formation rates as a function of coal type (at least two highly differing in rank and composition), flue gas residence time, and flue gas temperature. Sulfur species in unburned carbon from coal or tire rubber are being explored as possible reaction sites for oxidizing and stabilizing gaseous mercury. Chemical additives are being investigated in combination with tetrasulfide flue gas injection to determine the impact on mercury oxidation and capture. Finally, the effects of SO 2 , SO 3 , and HCl on mercury speciation in the presence of selective catalytic reduction catalyst material and a coal flue gas environment will be tested in a bench-scale system. Goal The overall goal of this project is to develop a fundamental understanding of Hg transformations in flue gas for the purpose of developing more effective mercury control strategies. Specific objectives to accomplish this goal include:
Perfectoid Spaces and their Applications

We survey the theory of perfectoid spaces and its applications. Mathematics Subject Classification (2010). Primary: 14G22, 11F80 Secondary: 14G20, 14C30, 14L05, 14G35, 11F03
Learning Human Pose Estimation Features with Convolutional Networks

This paper introduces a new architecture for human pose estimation using a multilayer convolutional network architecture and a modified learning technique that learns low-level features and a higher-level weak spatial model. Unconstrained human pose estimation is one of the hardest problems in computer vision, and our new architecture and learning schema shows improvement over the current stateof-the-art. The main contribution of this paper is showing, for the first time, that a specific variation of deep learning is able to meet the performance, and in many cases outperform, existing traditional architectures on this task. The paper also discusses several lessons learned while researching alternatives, most notably, that it is possible to learn strong low-level feature detectors on regions that might only cover a few pixels in the image. Higher-level spatial models improve somewhat the overall result, but to a much lesser extent than expected. Many researchers previously argued that the kinematic structure and top-down information are crucial for this domain, but with our purely bottom-up, and weak spatial model, we improve on other more complicated architectures that currently produce the best results. This echos what many other researchers, like those in the speech recognition, object recognition, and other domains have experienced [26]. Figure 1: The green cross is our new technique’s wrist locator, the red cross is the state-of-the-art CVPR13 MODEC detector [38] on the FLIC database.
Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet.

To the Editor: How do Shai et al. (July 17 issue)1 explain why the subjects in their study regained weight between month 6 and month 24, despite a reported reduction of 300 to 600 calories per day? Contributing possibilities may include the notion that a food-frequency questionnaire cannot precisely determine energy or macronutrient intake but, rather, ascertains general dietary patterns. Certain populations may underreport intake2,3 and have a decreased metabolic rate. The authors did not measure body composition, which is critical for documenting weight-loss components. In addition, the titles of the diets that are described in the article are misleading. Labeling the “low-carbohydrate” diet as such is questionable, since 40 to 42% of calories were from carbohydrates from month 6 to month 24, and data regarding ketosis support this view. Participants in the low-fat and Mediterranean-diet groups consumed between 30% and 33% of calories from fat and did not increase fiber consumption, highlighting the importance of diet quality. Furthermore, the authors should have provided baseline values and P values for within-group changes from baseline (see Table 2 of the article). Contrary to the authors’ assertion, it is not surprising that the effects on many biomarkers were minimal, since the dietary changes were minimal. The absence of biologically significant weight loss (2 to 4% after 2 years) highlights the fact that energy restriction and weight loss in themselves may minimally affect metabolic outcomes and that lifestyle changes must incorporate physical activity to optimize the reduction in the risk of chronic disease.4,5 Christian K. Roberts, Ph.D. R. James Barnard, Ph.D. Daniel M. Croymans, B.S.
Combination of Convolutional and Recurrent Neural Network for Sentiment Analysis of Short Texts

Sentiment analysis of short texts is challenging because of the limited contextual information they usually contain. In recent years, deep learning models such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) have been applied to text sentiment analysis with comparatively remarkable results. In this paper, we describe a jointed CNN and RNN architecture, taking advantage of the coarse-grained local features generated by CNN and long-distance dependencies learned via RNN for sentiment analysis of short texts. Experimental results show an obvious improvement upon the state-of-the-art on three benchmark corpora, MR, SST1 and SST2, with 82.28%, 51.50% and 89.95% accuracy, respectively. 1
Using machine learning techniques for sentiment analysis

The Natural language processing is the discipline that studies how to make the machines read and interpret the language that the people use, the natural language. But in the machines world, the words not exist and they are represented by sequences of numbers that the machine represents with a character when displaying them on screen. The Sentiment Analysis is the name of the problem that with a sentence or text the machine gets capable to analyze and predict with the maximum precision possible the sentiment that will be obtained by a person when reads it or the contextual opinion related to something. This document wants to show what we can obtain using the most used machine learning tools. Keywords– Sentiment Analysis, Data Mining, Machine Learning, Natural Language, Support Vector Machines, Decision Trees, Recurrent Neural Networks, Naive Bayes
Coupled exposure to ingredients of cosmetic products: II. Preservatives.

BACKGROUND
The use of cosmetics exposes consumers to mixtures of ingredients, many of which are potential allergens. Many cosmetics contain one or several preservatives, some being important contact allergens.


OBJECTIVE
To examine the pattern of co-exposure to preservatives in different categories of cosmetics.


METHODS
A survey of products marketed in Germany, conducted in 2006-2009 by the Chemical and Veterinary Investigation Office in Karlsruhe, identified 4680 products categorizable according to Annex I to the Cosmetics Directive with information on the presence of preservatives. The occurrence and co-occurrence of preservatives were analysed and presented in tabular and graphical format.


RESULTS
Thirty per cent of all products were not declared to contain any preservatives; for 8%, no INCI labelling was present. For the remainder, the number of preservatives used tended to be higher in leave-on than in rinse-off products. Most often, combinations of (up to all five) parabens were used (39% of all products). Combinations with phenoxyethanol were also frequent. Formaldehyde releasers were found in 8% of products overall.


CONCLUSIONS
The pattern of co-exposure to preservatives in important categories of cosmetic products illustrates the 'cocktail' of allergens that may facilitate sensitization, although, conversely, the combination of preservatives allows individual use levels to be kept lower, thereby possibly reducing sensitization risk.
A piezoelectric device for impact energy harvesting

This paper studies a piezoelectric impact energy harvesting device consisting of two piezoelectric beams and a seismic mass. The aim of this work is to find the influence of several mechanical design parameters on the output power of such a harvester so as to optimize its performance; the electrical design parameters were not studied. To account for the dynamics of the beams, a model including the mechanical and piezoelectric properties of the system is proposed. The impacts involved in the energy harvesting process are described through a Hertzian contact law that requires a time domain simulation to solve the nonlinear equations. A transient regime and a steady-state regime have been identified and the performance of the device is characterized by the steady-state mean electrical power and the transient electrical power. The time simulations have been used to study the influence of various mechanical design parameters (seismic mass, beam length, gap, gliding length, impact location) on the performance of the system. It has been shown that the impact location is an important parameter and may be optimized only through simulation. The models and the simulation technique used in this work are general and may be used to assess any other impact energy harvesting device.
Natural Law and Enlightenment in France and Scotland — A Comparative Perspective

One of the predominant theories in political and social philosophy of the seventeenth and eighteenth centuries can arguably be identified in the modern natural law tradition, which was inaugurated and shaped by the influential writings of Hugo Grotius and then further developed by scholars like Samuel Pufendorf, Christian Thomasius or later by Christian Wolff. Pufendorf and Thomasius themselves fostered this picture of a linear and purposeful development from Grotius to their own writings.1 The Scottish philosophers, unlike those of any other country, were deeply influenced by this continental — mainly Dutch and German — brand of thought. In particular the Chair of Moral Philosophy at the university of Glasgow proved to play one of the key-roles in incorporating the natural law tradition. Obviously one cannot consider the natural law tradition as one homogenous block, nor can or should one consider the Scottish or French enlightenment in such a manner. The main concern of this chapter is a comparison, which will contribute to the endeavour to establish the cosmopolitan nature of European intellectual discourse in social and political theory during the eighteenth century. The case of Samuel Pufendorf will be considered as starting point, since his work played a central role in many of the contemporary debates of the early eighteenth century.2 Although most of the different discourses later used some aspects of Pufendorf s theory, it was frequently exploited with near contradictory aims and purposes.
JOB SATISFACTION AND ORGANIZATIONAL COMMITMENT : THE CASE OF SHKODRA MUNICIPALITY

The purpose of this investigation was to determine the levels of employees of public sector satisfaction with job dimensions and perceived organizational commitment in public sector in Shkoder, Albania. In addition, the study aimed at exploring to what extent these employees are committed to their job and satisfied with different dimensions to their job. A surveybased descriptive research design was used. The study was carried on public administrative sector, in Shkoder municipality. About 160 survey questionnaires were distributed in August, 2012 by employing diverse modes of communication such as email, in person and post. Multiple follow ups yielded 56 statistically usable questionnaires. Descriptive and inferential statistical techniques were used to give answer to the research questions. The findings of the study indicated that the satisfaction with work-itself, quality of supervision and pay satisfaction had significant positive influence on organizational commitment of municipality employees. They had high degree of organizational commitment and satisfaction with work-itself, supervision, salary, coworkers and opportunities for promotion. The focus of the study was employees working at public sector in Shkoder only. Job Descriptive Index (JDI) and Organizational Commitment questionnaire were used to measure job satisfaction and organizational commitment. The relevant literature shows that public sector employees’ commitment and job satisfaction is under-researched area particularly in the public sector institutions in Albania. So, the current investigation has contributed to improve the understanding on significant issue. Besides the study findings are discussed in perspective of practical implications in public administration sector.
Academic Socialization: Understanding Parental Influences on Children's School-Related Development in the Early Years

This review summarizes the research literature on the academic socialization of children within the family context. A conceptual model is introduced that describes the process of academic socialization, including parental experiences in school, parental school-related cognitions, and specific parenting behaviors. Parental attitudes and practices provide the foundation for children’s development of schemas about school performance and thus are critical determinants of children’s early school experiences. In addition, recent efforts to understand the role of transition practices aimed at facilitating children’s early adjustment in school are described. The present review extends the transition practices literature by providing a developmental perspective on parenting influences on children’s academic socialization, within an ecological systems perspective. The authors describe academic socialization as a process that occurs under the broad umbrella of socioeconomic and cultural contexts.
A randomised controlled trial of the use of aromatherapy and hand massage to reduce disruptive behaviour in people with dementia

BACKGROUND
Aromatherapy and hand massage therapies have been reported to have some benefit for people with dementia who display behavioural symptoms; however there are a number of limitations of reported studies. The aim is to investigate the effect of aromatherapy (3% lavender oil spray) with and without hand massage on disruptive behaviour in people with dementia living in long-term care.


METHODS
In a single blinded randomised controlled trial 67 people with a diagnosis of dementia and a history of disruptive behaviour, from three long-term care facilities were recruited and randomised using a random number table into three groups: (1) Combination (aromatherapy and hand massage) (n = 22), (2) Aromatherapy (n = 23), (3) Placebo control (water spray) (n = 22). The intervention was given twice daily for six weeks. Data on residents' behaviour (CMAI) and cognition (MMSE) were collected before, during and after the intervention.


RESULTS
Despite a downward trend in behaviours displayed not one of the interventions significantly reduced disruptive behaviour.


CONCLUSIONS
Further large-scale placebo controlled studies are required where antipsychotic medication is controlled and a comparison of the methods of application of aromatherapy are investigated.


TRIAL REGISTRATION
ACTRN12612000917831.
A new algorithm for minutiae extraction and matching in fingerprint

........................................................................................................................ ii Acknowledgement........................................................................................................iii List of acronyms...........................................................................................................xi
Human Capital Risk and Economic Growth

This paper develops a tractable incomplete-markets model of economic growth in which households invest in risk-free physical capital and risky human capital. The paper shows that a reduction in uninsurable idiosyncratic labor income risk decreases physical capital investment, but increases human capital investment, growth, and welfare. A quantitative analysis based on a calibrated version of the model reveals that these effects are substantial and of the same order of magnitude as the effects of distortionary income taxation. The analysis further suggests that government-sponsored severance payments to displaced workers increase growth and welfare even if these payments have to be financed through distortionary income taxation.
Text binarization in color documents

This article presents a new method for the binarization of color document images. Initially, the colors of the document image are reduced to a small number using a new color reduction technique. Specifically, this technique estimates the dominant colors and then assigns the original image colors to them in order that the background and text components to become uniform. Each dominant color defines a color plane in which the connected components (CCs) are extracted. Next, in each color plane a CC filtering procedure is applied which is followed by a grouping procedure. At the end of this stage, blocks of CCs are constructed which are next redefined by obtaining the direction of connection (DOC) property for each CC. Using the DOC property, the blocks of CCs are classified as text or nontext. The identified text blocks are binarized properly using suitable binarization techniques, considering the rest of the pixels as background. The final result is a binary image which contains always black characters in white background independently of the original colors of each text block. The proposed document binarization approach can also be used for binarization of noisy color (or grayscale) document images. Several experiments that confirm the effectiveness of the proposed technique are presented. VC 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 262–274, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/
Keeping it in the family? The creative collaborations of Sophie and Dorothea Tieck

This essay explores the nature and extent of the collective aesthetic practices of the creative writer Sophie Tieck-Bernhardi-Knorring (1775-1833) and the literary translator Dorothea Tieck (1799-1841), primarily in relation to their collaborative ventures with the 'king of German Romanticism' Ludwig Tieck (1773-1853). The study addresses the politics of family and sibling creative partnerships, as well as the group dynamics of late eighteenth and early to mid-nineteenth century writers' circles and literary salons, inasmuch as they comprised individuals who shared and pooled ideas, values and visions and committed to similar poetic processes. Copyright © 2010 Thomson Reuters
Learning First-Order Horn Clauses from Web Text

Open Domain: There are nearly an unbounded number of classes, objects and relations Missing Data: Many useful facts are never explicitly stated No Negative Examples: Labeling positive and negative examples for all interesting relations is impractical Learning First-Order Horn Clauses from Web Text Stefan Schoenmackers Oren Etzioni Daniel S. Weld Jesse Davis Turing Center, University of Washington Katholieke Universiteit Leuven
Detecting Hate Speech on the World Wide Web

We present an approach to detecting hate speech in online text, where hate speech is defined as abusive speech targeting specific group characteristics, such as ethnic origin, religion, gender, or sexual orientation. While hate speech against any group may exhibit some common characteristics, we have observed that hatred against each different group is typically characterized by the use of a small set of high frequency stereotypical words; however, such words may be used in either a positive or a negative sense, making our task similar to that of words sense disambiguation. In this paper we describe our definition of hate speech, the collection and annotation of our hate speech corpus, and a mechanism for detecting some commonly used methods of evading common “dirty word” filters. We describe pilot classification experiments in which we classify anti-semitic speech reaching an accuracy 94%, precision of 68% and recall at 60%, for an F1 measure of .6375.
-Synuclein and Parkinson’s disease

Alpha-synuclein ( -syn) is a small soluble protein expressed primarily at presynaptic terminals in the central nervous system. Interest in -syn has increased dramatically after the discovery of a relationship between its dysfunction and several neurodegenerative diseases, including Parkinson’s disease (PD). The physiological functions of -syn remain to be fully defined, although recent data suggest a role in regulating membrane stability and neuronal plasticity. Various trigger factors, either environmental or genetic, can lead to a cascade of events involving misfolding or loss of normal function of -syn. In dopaminergic neurons, this may promote a vicious cycle in which elevation in cytoplasmic dopamine, oxidative stress, -syn dysfunction, and disruption of vesicle function lead to dopaminergic cell loss and PD. -Syn dysfunction appears to be a common feature of all forms of PD. The mechanism by which -syn induces neuronal cell toxicity may invoke multiple pathways, such as aggregation or interaction with other proteins and molecules, including synphilin-1, chaperone 14-3-3 protein, and dopamine itself. This complexity has hindered the development of models to study PD. The available animal models of PD, each present distinct advantages and limits. Findings to date suggest that -syn-based models represent a paradigm, which is closest to the human pathology.— Recchia, A., Debetto, P., Negro, A., Guidolin, D., Skaper, S. D., Giusti, P. -Synuclein and Parkinson’s disease. FASEB J. 18, 617–626 (2004)