QCBA: Postoptimization of Quantitative Attributes in Classifiers based on Association Rules

The need to prediscretize numeric attributes before they can be used in association rule learning is a source of inefficiencies in the resulting classifier. This paper describes several new rule tuning steps aiming to recover information lost in the discretization of numeric (quantitative) attributes, and a new rule pruning strategy, which further reduces the size of the classification models. We demonstrate the effectiveness of the proposed methods on postoptimization of models generated by three state-of-the-art association rule classification algorithms: Classification based on Associations (Liu, 1998), Interpretable Decision Sets (Lakkaraju et al, 2016), and Scalable Bayesian Rule Lists (Yang, 2017). Benchmarks on 22 datasets from the UCI repository show that the postoptimized models are consistently smaller -- typically by about 50% -- and have better classification performance on most datasets

A review of associative classification mining

Associative classification mining is a promising approach in data mining that utilizes the association rule discovery techniques to construct classification systems, also known as associative classifiers. In the last few years, a number of associative classification algorithms have been proposed, i.e. CPAR, CMAR, MCAR, MMAC and others. These algorithms employ several different rule discovery, rule ranking, rule pruning, rule prediction and rule evaluation methods. This paper focuses on surveying and comparing the state-of-the-art associative classification techniques with regards to the above criteria. Finally, future directions in associative classification, such as incremental learning and mining low-quality data sets, are also highlighted in this paper

Modifications of Gait as Predictors of Natural Osteoarthritis Progression in STR/Ort Mice

OBJECTIVE: Osteoarthritis (OA) is a common chronic disease for which disease-modifying therapies are not currently available. Studies to seek new targets for slowing the progress of OA rely on mouse models, but these do not allow for longitudinal monitoring of disease development. This study was undertaken to determine whether gait can be used to measure disease severity in the STR/Ort mouse model of spontaneous OA and whether gait changes are related to OA joint pain. METHODS: Gait was monitored using a treadmill-based video system. Correlations between OA severity and gait at 3 treadmill speeds were assessed in STR/Ort mice. Gait and pain behaviors of STR/Ort mice and control CBA mice were analyzed longitudinally, with monthly assessments. RESULTS: The best speed to identify paw area changes associated with OA severity in STR/Ort mice was found to be 17 cm · seconds(−1). Paw area was modified with age in CBA and STR/Ort mice, but this began earlier in STR/Ort mice and correlated with the onset of OA at 20 weeks of age. In addition, task noncompliance appeared at 20 weeks. Surprisingly, STR/Ort mice did not show any signs of pain with OA development, even when treated with the opioid antagonist naloxone, but did exhibit normal pain behaviors in response to complete Freund's adjuvant–induced arthritis. CONCLUSION: The present results identify an animal model in which OA severity and OA pain can be studied in isolation from one another. The findings suggest that paw area and treadmill noncompliance may be useful tools to longitudinally monitor nonpainful OA development in STR/Ort mice. This will help in providing a noninvasive means of assessing new therapies to slow the progression of OA

Personality traits and beliefs about peers\u2019 on-road behaviors as predictors of adolescents\u2019 moped-riding profiles.

Several efforts aimed at discriminating between different degrees of on-road risky attitudes have been devoted to the identification of personality profiles among young drivers. However, the results are often inconsistent because of the limits of selfreport measures. To overcome these limits, we tried to identify different profiles based on our study participants\u2019 driving performances in a virtual environment and to look for psychological predictors of inclusion in one of three profiles. One-hundred and fourteen inexperienced adolescents were involved in this study, which included two experimental sessions. During the first, before riding along five virtual courses on a moped simulator, participants\u2019 sensation seeking, locus of control, aggressiveness and beliefs about their peers\u2019 on-road behaviors were measured by means of self-report tools. During the second session, the participants drove the simulator along six courses that were different from those faced in the first session. A cluster analysis was run on a wide number of indexes extracted from the participants\u2019 performances to detect different riding profiles. Three profiles emerged (Imprudent, Prudent and Insecure), with specific riding patterns. The profiles also differed in terms of riding safety, assessed by means of the scores automatically given by the simulator to the participants\u2019 performances. Reporting an external locus of control, underestimating peers\u2019 on-road risky behaviors and showing less concern for fate among the possible causes of crashes are predictors that increase the risk of being included in the Imprudent profile. Low levels of dangerous thrill seeking predict inclusion in the Prudent profile, whereas high rates of self-reported anger play a role in discriminating the Insecure riders from the other profiles. The study indicates that it is possible to identify riding profiles with different degrees of on-road safety among inexperienced adolescents by means of simulated road environments. Moreover, inclusion in these profiles is predicted by different patterns of personality variables and beliefs. Further research is needed to verify the validity of these conclusions in real road conditions

Incentive Contracts in Team Sports - Theory and Practice

A comparison of incentive clauses of players’ contracts in German soccer and clauses used in the NFL and NBA shows considerable differences. Against the background of principle-agent theory we have a closer look at these incentive systems. In contrast to other industries it is easy to observe the employees’ effort in team sports. Therefore, it would be desirable to set incentives for players based on their individual effort. We show that there are reasons why incentive clauses in professional German soccer, the NBA and the NFL are not directly based on effort. We argue that there are two main reasons: Firstly, efficient incentives are complementarily provided by subjective and objective performance measures. Secondly, cooperation amongst team members is essential in team sports.sports, labor contracts, agency theory, incentives,

Replication issues in syntax-based aspect extraction for opinion mining

Reproducing experiments is an important instrument to validate previous work and build upon existing approaches. It has been tackled numerous times in different areas of science. In this paper, we introduce an empirical replicability study of three well-known algorithms for syntactic centric aspect-based opinion mining. We show that reproducing results continues to be a difficult endeavor, mainly due to the lack of details regarding preprocessing and parameter setting, as well as due to the absence of available implementations that clarify these details. We consider these are important threats to validity of the research on the field, specifically when compared to other problems in NLP where public datasets and code availability are critical validity components. We conclude by encouraging code-based research, which we think has a key role in helping researchers to understand the meaning of the state-of-the-art better and to generate continuous advances.Comment: Accepted in the EACL 2017 SR

Ex-ante Policy Assessment of Agricultural, Environmental, and Rural Policies from an Institutional Perspective: The Procedure for Institutional Compatibility Assessment

Ex-ante impact assessment of agricultural, environmental, and rural policies has become an integral part of political decision making processes in the EU. While there is a large variety of agrienvironmental modelling tools available to analyse likely social, economic, and environmental impacts of these policies, scientifically well-founded ex-ante policy assessment tools capturing the institutional dimension are still missing. In this paper, we introduce a formalised procedure for modelling – ex-ante – institutional aspects for policy implementation: the ‘Procedure for Institutional Compatibility Assessment’ (PICA). PICA has been designed as an explorative, yet formalised methodology that enables policy makers to identify at an early stage potential institutional incompatibilities. After providing a brief overview of relevant approaches for policy assessment we elaborate on the four distinct steps of PICA and use a core element of the EU Nitrate Directive to illustrate its function.Methodology, Ex-ante Policy Assessment, Institutional Policy Assessment, Agricultural and Food Policy, Environmental Economics and Policy,

A Public Choice Approach to the Economic Analysis of Animal Healthcare Systems

Privatisation of animal healthcare systems in developing countries, particularly in sub-Saharan Africa, has had very limited success. Introduced with inadequate transition time and too few resources, many livestock owners either cannot afford or, just as likely, are unable to gain access to the services they need. Poor livestock owners in remote rural areas suffer the greatest disadvantage. This fact is undisputed but, since privatisation, the primary focus has been on analysing the performance of animal healthcare systems and few authors have studied the underlying economic theories that have driven privatisation policy nor examined in what ways these may have been detrimental. This working paper examines how the economic analysis of animal health services has evolved since the '90s. A comparison is made with economic theories underlying the provision of human healthcare services where the debate started much earlier (in the '60s). Special emphasis is put on how these perspectives have influenced privatisation policy and, in particular, based in general economic literature, how the way in which 'public goods' is defined affects their financing and provision. Following this perspective, the role that governments should expect to play in the animal healthcare sector post privatisation is also debated. A relatively new approach to the economic analysis of animal health services is therefore presented, one that has been propounded recently by a number of economists working in this field. This economic theory, based on the perspective of 'public choice' argues that the process of decision-making may be highly significant in influencing efficiency and effectiveness. Traditional 'outcome' analysis omits factors such as self-interested behaviour and political interference. These may have contributed to higher than expected 'transaction' costs and, therefore, to the failure in many instances of the privatisation process. Given that much greater attention than in the past should be paid to issues of governance, governments in future may expect to act not only as external agents with regulatory power but as part of the nation's animal healthcare system with responsibility for defining overall goals and harmonising and facilitating the market economy.Animal health services, privatisation process, market failure, taxonomy of goods, poor livestock keepers, developing countries, community animal health workers, Livestock Production/Industries,

Flow cytofluorimetric analysis of anti-LRP4 (LDL receptor-related protein 4) autoantibodies in Italian patients with Myasthenia gravis

Background: Myasthenia gravis (MG) is an autoimmune disease in which 90% of patients have autoanti-bodies against the muscle nicotinic acetylcholine receptor (AChR), while autoantibodies to muscle-specific tyrosine kinase (MuSK) have been detected in half (5%) of the remaining 10%. Recently, the low-density lipoprotein receptor-related protein 4(LRP4), identified as the agrin receptor, has been recognized as a third autoimmune target in a significant portion of the double sero-negative (dSN) myasthenic individuals, with variable frequency depending on different methods and origin countries of the tested population. There is also convincing experimental evidence that anti-LRP4 autoantibodies may cause MG. Methods: The aim of this study was to test the presence and diagnostic significance of anti-LRP4 autoantibodies in an Italian population of 101 myasthenic patients (55 dSN, 23 AChR positive and 23 MuSK positive), 45 healthy blood donors and 40 patients with other neurological diseases as controls. All sera were analyzed by a cell-based antigen assay employing LRP4-transfected HEK293T cells, along with a flow cytofluorimetric detection system. Results: We found a 14.5% (8/55) frequency of positivity in the dSN-MG group and a 13% frequency of co-occurrence (3/23) in both AChR and MuSK positive patients; moreover, we report a younger female prevalence with a mild form of disease in LRP4-positive dSN-MG individuals. Conclusion: Our data confirm LRP4 as a new autoimmune target, supporting the value of including anti-LRP4 antibodies in further studies on Myasthenia gravis

Tackling Unstable and Unpredictable Work Schedules

While paying bills and taking care of family members are high on the list of challenges that workers in lower-wage jobs experience when they are subject to erratic scheduling practices,the harm they face does not stop there. Workers experience adverse health effects, have difficulty finding and keeping childcare arrangements, face transportation obstacles, have trouble going back to school to advance their education, and experience considerable overall stress and strain on family life. Since their schedules fluctuate so much, they can't predict the size of their paychecks. Communities suffer, too, when workers can't afford to buy groceries or other goods from neighborhood businesses. Even the employers that adopt volatile scheduling practices that contribute to these problems may face negative repercussions, as they cope with the significant expenses associated with high rates of turnover and low morale. Moreover, consumers are increasingly wary of spending their money at businesses that treat their workers poorly. The ripple effects of unstable and unpredictable scheduling are felt in the lives of individuals, in communities, and throughout the economy