Miracle-dz/UniFAR-FTUs huggingface dataset:
Cohort sampling in epidemiological studies

Cox regression is much used in epidemiology to assess the in uence of exposure variables and other covariates on mortality or morbidity. Estimation in Cox's model requires ascertainment of covariate values for all individuals in a cohort even when only a small fraction of these get diseased or die (\fail"). This may be very costly, or even logistically impossible. Cohort sampling techniques, where covariate information is collected for all failing individuals (\cases"), but only for a sample of the non-failing ones (\controls"), o er useful alternatives. Two common cohort sampling designs are nested case-control and case-cohort sampling. The purpose of this paper is to review, discuss and compare these two sampling designs with emphasis on recent developments and challenges for further research. We restrict our attention to situations which involve only a single disease.
The Effect of Foreign Demand on Residential Property Prices: Evidence from Australia

This study estimates the impact of foreign demand for Australian residential real estate on property prices. Using postcode‐level administrative data and fixed‐effects regression techniques we find a positive relationship between foreign investment approvals and price growth. Our analysis suggests that, on average, foreign investment contributed between $80 and $122 to quarterly price growth in Sydney and Melbourne between July 2010 and March 2015. This is a small proportion of the increase in property prices over the period.
Tongaraas: Tongs for Recognizing Littering Garbage with Active Acoustic Sensing

Littering has developed into a serious environmental problem. However, the actual situation of litter and the results of litter pickup activities are not organized as information. Therefore, the objective of this research is to grasp the distribution of the type and location of litter comprehensively. To achieve the objective of this research, we have proposed a method for recognizing litter using an acoustic sensor on a smartwatch worn on the wrist and a method for recognizing litter using a small camera mounted on tongs. However, in these studies, there were limitations in the range of litter type estimation, lack of recognition accuracy, and privacy issues. To solve the above problem, we propose a litter type recognition system, named Tongaraas, that combines active acoustic sensing with tongs. In the evaluation experiment, we built the litter type recognition model for six categories of litter. The evaluation results showed the models, which were trained with dataset collected by single person and three people, perform at F-value of 0.978 (SVM) and 0.849 (LightGBM), respectively. It suggests it is possible to estimate with common litter type recognition model, although there is a certain level of negative effects due to the individual difference.
Automatically Tagging the “AAA” Pattern in Unit Test Cases Using Machine Learning Models

The AAA pattern (i.e., Arrange-Act-Assert) is a common and natural layout to create a test case. Following this pattern in test cases may benefit comprehension, debugging, and maintenance. The AAA structure of real-life test cases, however, may not be clear due to their high complexity. Manually labeling AAA statements in test cases is tedious. Thus, we envision that an automated approach for labeling AAA statements in existing test cases could benefit new developers and projects that practice collective code ownership and test-driven development. This paper contributes an automatic approach based on machine learning models. The “secret sauce” of this approach is a set of three learning features that are based on the semantic, syntax, and context information in test cases, derived from the manual tagging process. Thus, our approach mimics how developers may manually tag the AAA pattern of a test case. We assess the precision, recall, and F-1 score of our approach based on 449 test cases, containing about 16,612 statements, across 4 Apache open source projects. To achieve the best performance in our approach, we explore the usage of six machine learning models; the contribution of the SMOTE data balancing technique; the comparison of the three learning features; and the comparison of five different methods for calculating the semantic feature. The results show our approach is able to identify Arrangement, Action, and Assertion statements with a precision upwards of 92%, and recall up to 74%. We also summarize some experience based on our experiments—regarding the choice of machine learning models, data balancing algorithm, and feature engineering methods—which could potentially provide some reference to related future research.
SymFusion: Hybrid Instrumentation for Concolic Execution

Concolic execution is a dynamic twist of symbolic execution designed with scalability in mind. Recent concolic executors heavily rely on program instrumentation to achieve such scalability. The instrumentation code can be added at compilation time (e.g., using an LLVM pass), or directly at execution time with the help of a dynamic binary translator. The former approach results in more efficient code but requires recompilation. Unfortunately, recompiling the entire code of a program is not always feasible or practical (e.g., in presence of third-party components). On the contrary, the latter approach does not require recompilation but incurs significantly higher execution time overhead. In this paper, we investigate a hybrid instrumentation approach for concolic execution, called SymFusion. In particular, this hybrid instrumentation approach allows the user to recompile the core components of an application, thus minimizing the analysis overhead on them, while still being able to dynamically instrument the rest of the application components at execution time. Our experimental evaluation shows that our design can achieve a nice balance between efficiency and efficacy on several real-world applications.
On Green Growth with Sustainable Capital

We develop an endogenous growth model to address a long standing question whether sustainable green growth is feasible by re-allocating resource use between green (natural) and man-made (carbon intensive) capital. Although the model is general we relate it to the UK’s green growth policy objective. In our model, final output is produced with two reproducible inputs, green and man-made capital. The growth of man-made capital causes depreciation of green capital via carbon emissions and related externalities which the private sector does not internalize. A benevolent government uses carbon taxes to encourage firms to substitute man-made capital with green capital in so far the production technology allows. Doing so, the damage to natural capital by emissions can be partly reversed through a lower socially optimal long run growth. The trade-off between environmental quality and long-run growth can be overcome by a pollution abatement technology intervention. However, if the source of pollution is consumption, the optimal carbon tax is zero and there is no trade-off between environment policy and growth. A corrective consumption tax is then needed to finance a public investment programme for replenishing the green capital destroyed by consumption based emissions.
Boosting Spectrum-Based Fault Localization for Spreadsheets with Product Metrics in a Learning Approach

Faults in spreadsheets are not uncommon and they can have significant negative consequences in practice. Various approaches for fault localization were proposed in recent years, among them techniques that transferred ideas from spectrum-based fault localization (SFL) to the spreadsheet domain. Applying SFL to spreadsheets proved to be effective, but has certain limitations. Specifically, the constrained computational structures of spreadsheets may lead to large sets of cells that have the same assumed fault probability according to SFL and thus have to be inspected manually. In this work, we propose to combine SFL with a fault prediction method based on spreadsheet metrics in a machine learning (ML) approach. In particular, we train supervised ML models using two orthogonal types of features: (i) variables that are used to compute similarity coefficients in SFL and (ii) spreadsheet metrics that have shown to be good predictors for faulty formulas in previous work. Experiments with a widely-used corpus of faulty spreadsheets indicate that the combined model helps to significantly improve fault localization performance in terms of wasted effort and accuracy.
Oil Price Volatility and Stock Market Returns in an Emerging Economy: Evidence from Nigeria

The study examines the reaction of the Nigerian stock market to fluctuations in the mainstay of the Nigerian economy. Using time series data sourced from OPEC website and the Central Bank of Nigeria (CBN) Statistical Bulletin, we investigate the effect of oil price volatility on stock market returns in Nigeria during the period 1981 to 2017. Co-integration test established the long run relationship between variables, while, the Error Correction Model (ECM) and Pair-Wise Granger Causality test were used to ascertain the short run dynamics and the direction of causality between the variables of interest. The findings reveal among other things that Oil Price Volatility (OPV) has a non-significant positive effect on Stock Market Return (SMR) both in the short and long run period. Exchange Rate (EXR) and Interest rate (INT) were significant variables that influence stock market return in Nigeria during the period under review.
MORE IS LESS? THE CURVILINEAR EFFECTS OF POLITICAL TIES ON CORPORATE INNOVATION PERFORMANCE

Previous research has explored the impact of political ties on corporate innovation performance, yet with controversial results. This study proposes that political ties has a curvilinear impact on innovation performance, and the resulting curvilinear relationship is moderated by absorptive capacity and external environment. We conduct examination based on a survey among Chinese manufacturing firms, which demonstrates an inverted U-shape relationship between political ties and corporate innovation performance. This inverted U-shape relationship is moderated by the absorptive capacity, which means the positive effect of political ties on corporate innovation performance is strong when the absorptive capacity of a firm is high. Furthermore, political ties, absorptive capacity and external environment (i.e. dynamism, munificence, and complexity) have a three-way interactive effect on corporate innovation, which means firms with strong political ties exhibit the highest innovation performance when their absorptive capacity and external environmental condition (dynamism or munificence or complexity) stand at high level simultaneously. The research findings provide a comprehensive understanding for firms, especially for those with different characteristics and under different external environments, to exploit political ties to facilitate corporate innovation performance.
Observations on the Efficacy of Acupuncture at Point Shanzhong(CV17) plus Cupping on Back-Shu Points in Treating Migraine

Objective To investigate the clinical efficacy of acupuncture at point Shanzhong(CV17) plus cupping on Back-Shu points in treating migraine. Methods Seventy migraine patients were randomly allocated to treatment and control groups, 35 cases each. The control group received conventional acupuncture and the treatment group, acupuncture at point Shanzhong(CV17) plus cupping on Back-Shu points in addition. The VAS score was counted in the two groups before and after treatment. The clinical therapeutic effects were compared between the two groups. Results The cure and marked efficacy rate and the total efficacy rate were 88.6% and 100.0%, respectively, in the treatment group and 62.9% and 94.3%, respectively, in the control group. There was a statistically significant difference in the cure and marked efficacy rate between the two groups(P0.05). There was a statistically significant pre-/post-treatment difference in the VAS score in the two groups(P0.05). There was a statistically significant post-treatment difference in the VAS score between the treatment and control groups(P0.01). The clinical symptom improvement rate was(78.3±10.6)% in the treatment group and(49.8±11.2)% in the control group; there was a statistically significant difference between the two groups(P0.01). Conclusion Acupuncture at point Shanzhong plus cupping on Back-Shu(CV17) points is an effective way to treat migraine.
Terrorism and Political Trust. A study of the relationship between terrorism and political trust in Europe in the time period 2002 to 2016, and a causal exploration of the relationship between the two phenomena

This thesis explores the relationship between terrorism and political trust. This is done in two ways, by two sub-studies, in order to get a more comprehensive understanding of the relationship between the two phenomena. The first sub-study uses longitudinal multilevel regression to explore the historical empirical relationship between terrorism and political trust, in Europe for the time period 2002-2016, focusing specifically on the parliaments, the legal systems, the police, and the politicians. The second sub-study consists of a survey experiment specifically designed to explore the causal relationship between terrorism and political trust. Concretely, building on trust theories and rooted within an institutional framework, the paper suggests a theoretical framework that has a potential for explaining the causal relationship between terrorism and political trust. A central mechanism in this theoretical framework is individuals’ perception of institutions’ capacity to deal with terrorism. It is this mechanism, capacity perception, that is explored in the survey experiment. The results from the regressions shows that within-country variation over time has affected the political trust in Europe. The effect has, however, been somewhat limited. The effect has also varied between institutions, where the police have received increased trust, while the parliaments and politicians have had their trust reduced, and the legal systems seem unaffected. The results from the survey experiment shows that capacity perception is a causal mechanism in the relationship between terrorism and political trust, but that its’ influence and role varies depending on the institution at hand.
The effects of site experience on job performance: a missing element in work experience

Abstract This study investigates the relationship of site experience (i.e. time employees work at a particular company site), a key aspect of work experience that has been overlooked, to job performance. In addition, it tests two moderators that are predicted to affect this relationship. We approximated job performance using commissions on sales earned by 3398 employees of a large Spanish bank. Data were collected in 2005 and 2012 and were structured as a panel to allow longitudinal analysis. Results indicate that the effects of site experience on job performance depict an inverted U. Job complexity and organizational experience moderate this relationship. The study concludes with empirical, theoretical and practical contributions, as well as directions for future research.
Social Media Big Data Analytics for Demand Forecasting: Development and Case Implementation of an Innovative Framework

Social media big data offers insights that can be used to make predictions of products' future demand and add value to the supply chain performance. The paper presents a framework for improvement of demand forecasting in a supply chain using social media data from Twitter and Facebook. The proposed framework uses sentiment, trend, and word analysis results from social media big data in an extended Bass emotion model along with predictive modelling on historical sales data to predict product demand. The forecasting framework is validated through a case study in a retail supply chain. It is concluded that the proposed framework for forecasting has a positive effect on improving accuracy of demand forecasting in a supply chain.
Identifying risk determinants of the financial sustainability of regional governments

ABSTRACT This paper identifies some of the important factors that influence the financial sustainability of regional governments. Data from all of Spain’s regional governments show that unemployment, immigrant population, dependent population, structure of revenues and expenditures, and the source of debt had impacts on financial sustainability. IMPACT This paper will help policy-makers and managers in regional and local governments to improve the management of risk and opportunities, as well as to prevent or resolve sustainability problems. The paper provides lessons, based on the Spanish experience, for politicians and practitioners to improve the management of regional governments’ financial sustainability. The authors stress the need to estimate the longer term financial effects of a migrant population and the unemployed; to analyse the long-term financial impact of subsidies from other levels of government; to monitor proportionality between awarding grants and making capital investments; and to look at ways of increasing a regional government’s contribution to its own revenue (for example through fees, taxes and rates).
On Financial Frictions and Firm Market Power

We build a static general-equilibrium model with monopolistically competitive firms that borrow funds from competitive banks in an economy subject to financial frictions. These frictions are due to non verifiability of both ex post firm returns and managerial effort. Market power has opposing effects. On one side, firms' pricing over marginal cost reduces output compared to perfect competition. On the other, by increasing firms' profitability, market power reduces the impact of financial frictions. The resulting tradeoff is ambiguous. We show that, other things equal, there exists an optimal positive level of market power that maximizes welfare. Such optimal degree of market power increases with moral hazard and decreases with the efficiency of firm liquidation following bankruptcy.
A Critical Legal Study of the Declaration of the Rights of Man and of the Citizen

This paper aims to examine and analyse from the perspective of Critical Legal Studies whether, and to what extent, the concept of law relates to the economic structure of society. Furthermore, the aim is to shed light on the potential problem of the perception and generation of legitimacy derived from economic interests. More precisely, this paper will investigate the relationship between the economic structure of the French society in 1789, the Declaration of the Rights of Man and the Citizen and the philosophy of the Enlightenment.
The Value of Sabbaticals to Revitalize and Retain Nurse Leaders in a Hospital Setting

6 Dedication and Acknowledgements.7 Background . 8 Statement of the Problem . 10 Purpose Statement . 10 The Context of Nursing Retention . 11 Nursing Shortage . 11 Nursing Burnout. 12 Nursing Turnover . 15 Nurse Leader Retention Strategies. 17 Sabbaticals . 19 History of Sabbaticals . 19 Benefits of Sabbaticals . 19 Leadership Sabbaticals. 21 Challenges of Sabbaticals . 22 Theoretical Frameworks . 23 Conservation of Resources Theory . 23 Quality Caring Model . 25
How Auctioneers Set Ex-Ante and Ex-Post Reserve Prices in English Auctions

We compare two commonly used procurement English auction formats - the ex-ante reserve price and the ex-post reserve price, with symmetric and independently distributed private costs. Both formats are indirect implementations of Myerson's optimal mechanism. Both formats yield the same ex post payoffs when auctioneers optimally choose reserve prices. However, the optimal reserve prices follow two counter-intuitive prescriptions: optimal ex-ante reserve prices do not vary with the number of bidders, and optimal ex-post reserve prices are invariant to the realized auction prices. Anticipated regret, Davis et al (2011), and subjective posterior probability judgement, Shachat and Tan (2015), are two different approaches to rationalize observed auctioneers' choices that violate the two counter-intuitive prescriptions respectively. We generalized the latter model to one of Subjective Conditional Probabilities (SCP) which predicts optimal ex-ante reserve prices decreasing in the number of bidders and also predicts optimal ex-post reserve prices increasing in the realized auction prices. In our first experiment, in which costs follow a uniform distribution, we find two possible explanations to the experimental results. First, the auctioneers use the SCP model for both formats. Second, they use format-specific models. In our second experiment with a left-skewed cost distribution, we finally find that the SCP provides a unified behavioral model of how auctioneer set reserve prices in the two formats.
Sustainable entrepreneurship, innovation, and business models: Integrative framework and propositions for future research

This article introduces the business models for sustainability innovation (BMfSI) framework to study how business models mediate between sustainability innovations and business cases for sustainability. The BMfSI framework integrates two major perspectives (implicitly) found in the sustainable business model literature. The first is the agency perspective. It takes into consideration that some form of agency is needed, that is, “someone” who takes decisions and acts. Sustainable entrepreneurs are discussed as those agents who align their new or existing business models with sustainability innovations in order to be successful in business and to create value with and for stakeholders. The second perspective is the systems perspective, which acknowledges that business models are always embedded within sociotechnical contexts through which, for example, public policies, private financing, or stakeholder interests influence whether and how business models can be developed. The agency and systems perspectives are integrated in the so‐called business model mediation space. This theoretical notion embraces the decisions and activities pursued by sustainable entrepreneurs as they align their business models with sustainability innovations on the one hand and the influence of environmental contingencies, barriers, and stakeholders from the sociotechnical context on the other hand. The paper concludes with propositions for future research derived from the BMfSI framework.