Miracle-dz/UniFAR-FTUs huggingface dataset:
Finding Help: Exploring the Accounts of Persons With Disabilities in Western Zambia to Improve Their Situation

Background: Strategies proposed to improve the situation of persons with disabilities in the global South are not always developed in consideration of local contexts. Purpose: To explore and develop strategies to improve the situation of persons with disabilities in one context in the global South. Method: We recruited two groups of persons with disabilities in Western Zambia. Eighty-one disabilitygroup members participated in focus-group discussions and individual interviews, with a North American rehabilitation professional, in which they discussed life with a disability and what should be done to improve their situation. The transcribed audiorecordings of the focus-group discussions and interviews were analyzed thematically. Results: The accounts of ways to improve the situation of persons with disabilities in this context were framed around a single theme: help (“kutusa” in Silozi). When expressed by participants in this research, help refers to gifts or grants of material resources from those with the means to share but influenced by the presentation of need by potential recipients. Help occurs in a relationship of expected compassion. Conclusion: Help is very different from formal strategies that are currently being promoted to improve the situation of persons with disabilities in the global South.
Automatic Text Standardisation by Synonym Mapping

Creating a case-based reasoning system from textual sources is challenging because it requires that the text be interpreted in a meaningful wa y in order to create cases and interprete queries during problem-solving. H owever, this is only possible if a domain-specific conceptual model is available and if the different meanings that words can take, can be recognised in the text. T his paper presents an unsupervised methodology for text harmonisation in order t create a standard conceptual model of the domain, and for query interpretation . The main core of this technique is the disambiguation of each polysemous word in ord er to represent all synonyms of a particular word, with one common word. The algorithm for Word Sense Disambiguation relies on the syntactic structure of th e sentence in which the target word resides to obtain the context. It does not rely on large amounts of hand-crafted knowledge or statistical data from the c orpus, but makes use of two other knowledge sources, namely WordNet and G oogle. Preliminary results are promising when the algorithm is tested on documents in the SmartHouse domain.
Credit Market Frictions and the Linkage between Micro and Macro Uncertainty

This paper proposes a quantitative general equilibrium model with credit market frictions to explain the observed stylized facts of micro uncertainty (dispersion of realized firm-level outcomes) and macro uncertainty (volatility of aggregate economic variables). They are conceptually different but strongly comove and are countercyclical. In my model economy, an increase in the dispersion of idiosyncratic shocks leads to more firms in the left tail of the distribution to default, which reduces the aggregate net worth. Therefore, the economy becomes more leveraged and more sensitive to aggregate shocks when micro uncertainty is high, and the aggregate economy is more volatile.
The Effectiveness of Non-Persistent Social Status as an Incentive Mechanism

Content sharing platforms such as product review websites largely depend on users’ voluntary contributions. In order to motivate users to contribute more, many platforms established reputation-based incentive mechanisms. Though the academic community has devoted much effort to study the effectiveness of these mechanisms, most of the existing research has focused on everlasting reputations such as badges and points. It’s still largely underexplored how non-persistent social status actually influences user’s behavior ranging from contribution level, the opinion they express, to how they express. In this paper, we answer this question by examining data from Yelp Elite Squad where reviewers with good reviewing history are awarded into the elite group and most importantly re-evaluated each year. By applying propensity score matching and difference-in-difference methods, we find that in short term, reviewers significantly increase their contribution levels after acquiring the non-persistent social status, become more conservative with lower percentage of extreme ratings, and also increase the readability of their reviews. In long term, they continue to improve the quality of reviews while their numerical rating behaviors stabilize. Our research has significant implications and actionable insights for business models that rely on user contributions.
Determinants of Investment in Tangible and Intangible Fixed Assets

We investigate which firm characteristics are associated with investment in tangible and intangible fixed assets, paying special attention to the case of R&D, and which funding sources are used for each type of investment. Regarding firm characteristics, we find that younger and more profitable firms tend to invest more in all asset types. In the case of size, larger firms invest more in R&D and intangibles but less in tangible fixed assets. In addition, there is a concave relationship between leverage and investment. Regarding funding sources, we find that cash flow is the most important source of funding for intangibles and R&D, whereas financial debt is the most important funding source for tangible fixed assets. Stock issues are used to fund R&D and, especially, tangible fixed assets. Firms use cash holdings to smooth investment in R&D.
Montreal Cognitive Assessment Memory Index Score (MoCAMIS) as a Predictor of Conversion from Mild Cognitive Impairment to Alzheimers Disease

OBJECTIVES: To assess the usefulness of the Montreal Cognitive Assessment (MoCA) total score (MoCA-TS) and Memory Index Score (MoCA-MIS) in predicting conversion to Alzheimer’s disease (AD) in individuals with mild cognitive impairment (MCI). DESIGN: Retrospective chart review. SETTING: Community-based memory clinic. PARTICIPANTS: Individuals meeting Petersen’s MCI criteria (N = 165). MEASUREMENTS: Baseline MoCA scores at MCI diagnosis were collected from charts of eligible individuals with MCI, and MoCA-TS, MoCA-MIS, and a cognitive domain index score were calculated to assess their prognostic value in predicting conversion to AD. RESULTS: One hundred fourteen participants progressed to AD (MCI-AD), and 51 did not (nonconverters; MCINC); 90.5% of participants with MCI with a MoCA-TS less than 20/30 and a MoCA-MIS less than 7/15 at baseline converted to AD within the average follow-up period of 18 months, compared with 52.7% of participants with MCI above the cutoffs on both scores. Individuals with multiple-domain amnestic MCI had the highest AD conversion rates (73.9%). CONCLUSION: Identifying individuals with MCI at high risk of conversion to AD is important clinically and for selecting appropriate subjects for therapeutic trials. Individuals with MCI with a low MoCA-TS and a low newly devised memory index score (MoCA-MIS) are at greater risk of short-term conversion to AD. J Am Geriatr Soc 2014.
1 CEO Gender and Corporate Risk-Taking

We show that CEO gender helps explain corporate decision making. In particular, we document that firms run by female CEOs have lower leverage, less volatile earnings, and a higher chance of survival than firms run by male CEOs. The results are robust to various tests for endogeneity, including placebo tests, firm fixed effects specifications, additional controls for time-varying CEO characteristics, propensity score matching, a switching regression analysis with endogenous switching, and a treatment effects model. The documented gender-related differences in risk-taking are consistent with gender-related differences in risk-aversion, differences in altruism, and norms related to appropriate behavior for women in a given society. a Krannert School of Management, Purdue University, 403 W. State Street, West Lafayette, IN 47907, U.S.A. Tel: 765-496-1951. E-mail: mfaccio@purdue.edu. b Manchester Business School, University of Manchester, Crawford House, Booth Street East, Manchester, M13 9PL, U.K. Tel: +44-161-2750121. E-mail: maria.marchica@mbs.ac. uk. c Manchester Business School, University of Manchester, Crawford House, Booth Street East, Manchester, M13 9PL, U.K. Tel: +44-161-2750120. E-mail: roberto.mura@mbs.ac. uk. Acknowledgments: We thank Kevin Aretz, Kelley Bergsma, Paul Chaney, Dave Denis, Diane Denis, Art Durnev, Andrea Fracasso, Marc Goergen, Scott Hsu, Markku Kaustia, Seoyoung Kim, David Lesmond, Evgeny Lyandres, Roni Michaely, Bill O’Brien, Eric Powers, Stefano Puddu, Jeremy Stein, Anjan Thakor, Jin Xu, Deniz Yavuz, Scott Yonker, Feng Zhang, and seminar participants at the Arison School of Business (Interdisciplinary Center), Bristol University, Cardiff Business School, DePaul, Exeter Business School, INSEAD, Manchester Business School, Neuchatel University, Northwestern, Tulane, University of Florida, University of Southern California, University of Verona, Wayne State, the 2013 European Economic Association, and the 2012 & 2013 Financial Management Association Meetings for comments and Hossein Khatami for research assistance. We also thank Bobby Foster from Bureau van Dijk and Mark Greenwood for technical assistance. Mara Faccio wishes to dedicate this paper to the memory of her beloved “Diavoletto,” who recently passed away.
Disentangling the factors driving user satisfaction with travel review websites: content, social or hedonic gratifications

Travel review websites has become increasingly popular among travelers. But there is a lack of research on the motivations of travel review website use, and it is inconclusive whether customers use travel review websites because of different gratifications obtained in their travel review website use. Most research on travel review websites focuses on the utilitarian use of content on travel review website, such as eWOM, but less is known about whether other gratifications in using travel review websites might shape customers’ travel review website use, such as social and hedonic gratifications. In this article, we explore travel review website use among individuals from a Uses & Gratifications perspective. In addition to the content gratification obtained in using travel review website, such as eWOM information, two other categories of gratifications from travel review website use are also examined in this study: social gratification and hedonic gratification. The results indicate that content gratification (eWOM completeness) and hedonic gratification (enjoyment and curiosity fulfillment) in using travel review websites determine user satisfaction with a travel review website.
Chronic and Transient Poverty in Rural Ethiopia: A New Decomposition

I characterise a general class of intertemporal poverty measures with easily motivated properties, showing that they may be decomposed into a function that represents an ordering of trajectories of individual wellbeing over time and another function that establishes the social aggregation properties. I propose a new measure within this class that has trajectory ordering properties appropriate for the measurement of chronic poverty, showing that, although no such measure has been suggested in the existing literature, there is no fundamental inconsistency between continuity and sensitivity to persistence of poverty. Total poverty is decomposed into chronic and transient components using both the new measure and the method suggested by Jalan and Ravallion (2000). These measures are applied to household consumption data to determine the chronic and transient components of poverty in rural Ethiopia in the period 1994 to 2009.
Financial Crises and Failed Corporate Governance

The banking sector is special given the importance of credit to support economic growth, and enormous public costs periodically sustained to bailout extensive institutional failures. US banks fail in waves approximately every generation and are unable to cope with severe economic downturns and incur excessive risk in a predictable and preventable manner. Is good corporate governance focusing on efforts to refresh boards by age or term limits the cause of episodic failure? As institutions refresh boards, banks lose directors with experience related to prior periods of crisis. Consistent with the availability heuristic, recall and memory are important to judgment. If relatively few directors have personal experience of a prior financial disaster, they are unable to recommend more conservative strategies. While some deservedly will believe the proposal a reversal in good governance, banks should consider suspending term and/or mandatory age limits for a few directors. Each board will need to overcome common “blind spots” that young equals good. Ageism is well-known and documented.
Cooperation of bacteria and fungus on polycyclic aromatic hydrocarbons degradation

Polycyclic aromatic hydrocarbons are diverse family of hydrophobic organic pollutants. They can be removed from environment by bacterial degradation. One of the process which could limit biodegradation is transfer of hydrophobic contaminants in to aqueous phase were degrading microorganisms live. In this work we would like to evaluate possible role of fungi in increasing transport of hydrophobic pollutants such as polycyclic aromatic hydrocarbons in to the aqueous phase. Increased transport should result in increased degradation of contaminants in our case polycyclic aromatic hydrocarbons.
Coronary Artery Disease Diagnosis Using Optimized Adaptive Ensemble Machine Learning Algorithm

Cardiovascular diseases (CVD) involving the heart and blood vessels are reported as the leading causes of mortality worldwide. Coronary Artery Disease (CAD) is a major group of CVD in which presence of atherosclerotic plaques in coronary arteries leads to myocardial infarction or sudden cardiac death. In the past decades, several research efforts have been made to better understand the etiology of CAD, which will enable effective CAD diagnosis and treatment strategies. In this study, we have proposed a novel Self Optimized and Adaptive Ensemble Machine Learning Algorithm for the diagnosis of CAD. In our proposed method, the system automatically selects the most appropriate machine learning models. Our main goal is to design an Optimized Adaptive Ensemble Machine Learning Algorithm that works in different CAD datasets with high accuracy even with raw dataset. One of the important aspects of the proposed method is that the solution works on real-time data without using any pre-processing techniques on the datasets. Throughout this research attempt, we obtained 88.38% accuracy using two publicly available CAD diagnosis datasets.
A deeper insight into the equilibrium of biological and ecological networks

The equilibrium of biological and ecological networks is often studied using eigenvector-eigenvalue analyses in order to reckon steady/unsteady properties and trajectories. Although at equilibrium inputs equal outputs for all the system variables, network flows continue to happen. Therefore, in this study I face three underestimated topics of network equilibrium: equilibrium flows, equilibrium sensitivity and equilibrium what-if properties. Using an applicative example, I show here that these three topics add important details to the knowledge of network behaviour at equilibrium.
The Structure and Evolution of Online Rating Biases in the Sharing Economy

A wave of sharing economy companies are profoundly changing the market landscape, disrupting traditional businesses alongside the social fabrics of exchange. A critical challenge to their growth, however, is that how to generate trust from online to offline transactions. Users in many online platforms rely on reputational systems such as ratings to infer quality and make decisions. However, ratings are biased by behavioral tendencies, such as homophily and power dependence. Our project examines the structure and evolution of rating biases by analyzing massive amount of platform data. Using big data techniques on leading sharing economy platforms, we identify the structure and evolution of biases, attempting to correct the tendencies in system design. We examine rating biases and their relationships to social distance among heterogeneous user populations. The coevolution of reputational systems and trust further implies long-term behavioral trends, which are critical to investigate for business growth.
Continued Development in Chrome-Free Anodic Oxide Finishes for Aluminum: Evaluation of Selected Mechanical Properties

The submitted manuscript has been created by the University of Chicago as Operator of Argonne National Laboratory (“Argonne”) under Contract No. W-31-109-ENG-38 with the U.S. Department of Energy. The U.S. Government retains for itself, and others acting on its behalf, a paid-up, nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government.
SAGE: Interactive State-aware Point-of-Interest Recommendation

Point-of-Interest (POI) recommendation is surfacing inmany locationbased services. User models are employed in these services to leverage historical check-ins and social links, and enable personalized and socialized POI recommendations. However these models often lack interactivity (incorporating user interactions) and stateawareness. This deficiency aggravates in cold start situations, where nearly no user information (historical check-ins and social graph) is available to generate effective recommendations. In this paper, we propose Sage, an interactive state-aware POI recommendation system which tackles the aforementioned challenges by exploiting look-alike groups mined in public POI datasets, such as Foursquare and Yelp. Sage reformulates the problem of POI recommendation as recommending explainable look-alike groups (and their POIs) which are in line with user’s intent. Sage frames the task of POI recommendation as an exploratory process where users interact with the system, and their interactions impact the way look-alike groups are picked out. Moreover, Sage defines and employsmindsetswhich capture the actual state of the user and enforce the semantics of POI interestingness. Our experiments show that Sage is an effective approach to capture interactivity and contextuality for recommending relevant look-alike groups and their POIs which are oriented towards the user’s mindset. ACM Reference Format: Behrooz Omidvar-Tehrani, Sruthi Viswanathan, Frederic Roulland, JeanMichel Renders. 2020. SAGE: Interactive State-aware Point-of-Interest Recommendation. In WSDM Workshop SUM’20: State-based User Modelling, February 7, 2020, Houston, Texas, TX, USA. ACM, New York, NY, USA, 6 pages. https://doi.org/10.1145/1122445.1122456
Humans in Charge of Trading Robots: The First Experiment

We present results from an experiment where participants have access to automated trading algorithms, which they may deploy at will while still trading manually. Treatments differ in whether robots must not be halted, deployment is compulsory, or robots can be halted and replaced at will. We hypothesize that robot trading would reduce mispricing, and that the effect would be more pronounced as commitment degree increases. Yet, compared to manual trading only, we observe equally large and frequent mispricing and, in early trading, significantly higher bid-ask spreads and more frequent flash crashes/price surges. Participants earn more provided they combine robot and manual trading. Compared to evidence from archival data, we find significantly higher use of liquidity-taking robots. We attribute this to the inability, in the field, to identify the presence of liquidity takers when they happen not to trade.
Derivative Free Optimization by Using Genetic Algorithm Method

In this paper, derivative free optimization methods specifically Genetic Algorithm is discussed. The solution of bound-constrained optimization problems by using Genetic algorithm, the concept of the project is divided into five parts: The first part is the introduction part; under this statement of the problem and objective of the study are included. The second part is the preliminary which includes some lemma and theorems which are used in the body of the seminar paper. The part includes detail explanation of derivative free optimization methods specifically, Genetic Algorithm and Simulated Annealing and also supporting examples of them. The last part presents the summary of the study what was discussed in the main part of the paper. A Non linear Mathematical model is proposed and studied the combined effect of vertical Transmission (MTCT) and variable inflow of infective immigrants on the dynamics of HIV/AIDS: Vertical transmission means, Propagation of the disease from mother to children, ‘Variable in flow of infective immigrants’ includes both the aware and unaware infected immigrants. The equilibrium points of the model are found and the stability analysis of the model around. These equilibrium points are conducted. The stability analysis on the model shows that the disease free equilibrium point is locally asymptotically stable when the positive endemic equilibrium point is shown to be locally asymptotically stable Further it is shown that the basic reproduction number of the present model is greater than the one which is obtained from the model without vertical transmission. Through vertical transmission the disease flows from infected mother to children. That is, Vertical transmission contributes positively to the spread of the disease. Numerical simulation of the model is carried out to assess the effect of unaware HIV infective immigrants and vertical transmission (MTCT) in the spread of HIV/AIDS disease. The result showed that HIV infective immigrants and vertical transmission (MTCT) significantly affects the spread of the disease. Screening of the disease reduces the spread of HIV and also prevents mother to child transmission. It is well accepted that both vertical transmission and immigration contribute positively to the spread of the disease and these two parameters cannot be avoided in practice. Hence, the purpose of this study is to investigate the combined effect of vertical transmission, unaware and aware infected immigrants on the spread of HIV/AIDS and offers possible intervention strategies:
TEX forever!

This paper explores new ways of doing input to and output from TEX. These new ways bypass our current habits, and provide fresh opportunities. Usually, TEX is run as a batch program. But when run as a daemon, TEX can be part of an interactive program. Daemons often that run forever, or at least for a long time. Hence the title of this paper. Usually, parsing and transformation of the input data is done by TEX macros, with little outside help. Often, this results in input documents that only TEX can understand. Also, TEX macros can be hard to write. We demonstrate the replacement of TEX macros by an external program. This is done in real time. Usually, TEX’s principal output is a dvi representation of typeset pages, for processing by a printer driver. However, TEX’s log file or console can be used to allow TEX to output the boxes it holds internally. (Alternatively, an extension of TEX could write this data out in a binary form.) Shipping out boxes rather than dvi allows an external program to do the page makeup. Don Knuth’s original conception was that TEX would be “just a typesetting language”. In some sense he “put in many of TEX’s programming features only after kicking and screaming”. The developments described above reduce our dependence on TEX macros, and so bring our use of TEX closer to Knuth’s original conception. Doing this will greatly improve its usefulness. Long live TEX!