Welfare benefits and the rate of unemployment: some evidence from the European Union in the last thirty years

Our objective in this paper is to re-examine the hypothesis that welfare benefits may be responsi-ble for the observed differences in cross- country unemployment rates and test its validity by using panel data from 19 countries over the 1970-2000 period. For this purpose, we set up a general equi-librium model encompassing the private and public sectors of the economy, where the government comes to the relief of the unemployed by increasing the welfare benefits per man. From this model, we extract an unemployment rate equation. The results that emerge from the empirical analysis sug-gest that social benefits per man may indeed adversely influence the rate of unemployment in EU-15. But the results change significantly when the EU member states are classified as high-, low- and average unemployment countries. In particular, we find that, whereas unemployment benefits exert perceptible positive influences in the high and average unemployment sub-groups, their influence in the low unemployment sub-group is nil. This finding, in conjunction with the evi-dence that the unemployment rate is invariant with respect to social benefits in USA and Canada, leads us to the conclusion that some EU countries may have to restructure their welfare systems, so as to reduce welfare benefits in favour of greater labour market flexibility and self-reliance on the part of workers.unemployment rate, welfare benefits, European Union

Agent-Based Distributed Learning Applied to Fraud Detection

Inductive learning and classification techniques have been applied in many problems in diverse areas. In this paper we describe an AI-based approach that combines inductive learning algorithms and meta-learning methods as a means to compute accurate classification models for detecting electronic fraud. Inductive learning algorithms are used to compute detectors of anomalous or errant behavior over inherently distributed data sets and meta-learning methods integrate their collective knowledge into higher level classification models or "meta-classifiers". By supporting the exchange of models or "classifier agents" among data sites, our approach facilitates the cooperation between financial organizations and provides unified and cross-institution protection mechanisms against fraudulent transactions. Through experiments performed on actual credit card transaction data supplied by two different financial institutions, we evaluate this approach and we demonstrate its utility

Timing of Anterior Cruciate Ligament (ACL) reconstruction

Background: Anterior Cruciate Ligament (ACL) ruptures are common but the ideal timing for ACL reconstruction following injury is unclear. Objectives: To determine if there is a relationship between timing from ACL rupture to surgery and clinical, functional and patient-reported outcomes. To explore the feasibility of collecting clinicians’ views on ACL reconstruction timing. Design and methods: A systematic review of five databases to identify studies investigating outcomes following different timing of reconstruction surgery and a pilot vignette study to identify variations in clinical decisions about timing of surgery in four different case scenarios. Results: Systematic review: Ten studies were identified, only one was a randomised controlled trial. There appeared to be no difference in outcomes between early ( 6months) ACL reconstruction. The two studies on functional and/or patient reported outcomes had conflicting findings, with the trial suggesting no difference between early or delayed reconstruction. The studies had limited evidence about the relationship between timing of surgery and patient characteristics. Pilot Vignette study: The pilot vignette study had a response rate of 45% but a high question completion rate. There was clinical variation in timing between surgeons and across patient groups, but none recommended delayed surgery (>6 months). Conclusions: Given the potential deleterious effects of meniscal and chondral injuries on knee function, delays of more than 6 months in patients deemed suitable for ACL surgery are not recommended, but there is some evidence that these delays are not common in practice. Further research on timing of ACL reconstruction should focus on shorter time-frames, functional and patient-reported outcomes, and the influence of patient characteristics, as available evidence is limited, inconsistent and of low quality. A vignette study seems feasible to provide insights on clinical decisions and guide current practice and future research

Cost-based Modeling for Fraud and Intrusion Detection: Results from the JAM Project

We describe the results achieved using the JAM distributed data mining system for the real world problem of fraud detection in financial information systems. For this domain we provide clear evidence that state-of-the-art commercial fraud detection systems can be substantially improved in stopping losses due to fraud by combining multiple models of fraudulent transaction shared among banks. We demonstrate that the traditional statistical metrics used to train and evaluate the performance of learning systems (i.e. statistical accuracy or ROC analysis) are misleading and perhaps inappropriate for this application. Cost-based metrics are more relevant in certain domains, and defining such metrics poses significant and interesting research questions both in evaluating systems and alternative models, and in formalizing the problems to which one may wish to apply data mining technologies. This paper also demonstrates how the techniques developed for fraud detection can be generalized and applied to the important area of intrusion detection in networked information systems. We report the outcome of recent evaluations of our system applied to tcpdump network intrusion data specifically with respect to statistical accuracy. This work involved building additional components of JAM that we have come to call, MADAM ID (Mining Audit Data for Automated Models for Intrusion Detection). However, taking the next step to define cost-based models for intrusion detection poses interesting new research questions. We describe our initial ideas about how to evaluate intrusion detection systems using cost models learned during our work on fraud detection

Distributed Data Mining: The JAM system architecture

This paper describes the system architecture of JAM (Java Agents for Meta-learning), a distributed data mining system that scales up to large and physically separated data sets. An earlyversion of the JAM system was described in Stolfo-et-al-97-KDD-JAM. Since then, JAM has evolved both architecturally and functionally and here we present the final design and implementation details of this system architecture. JAM is an extensible agent-based distributed data mining system that supports the remote dispatch and exchange of agents among participating datasites and employs meta-learning techniques to combine the multiple models that are learned. One of JAM's target applications is fraud and intrusion detection in financial information systems. A brief description of this learning task and JAM's applicability and summary results are also discussed

The role of Platelet-Rich Plasma (PRP) intraarticular injections in restoring articular cartilage of osteoarthritic knees. A systematic review and meta-analysis

To assess the effect of PRP on knee articular cartilage content (thickness/volume) and examine the correlation between cartilage changes and clinical outcomes in patients with knee OA. A systematic literature search was performed using the Cochrane methodology in four online databases. Studies were included if they reported on cartilage content with cross-sectional imaging pre- and post-injection. A random-effects model meta-analysis was performed. Correlation with clinical outcomes was evaluated. 14 studies (n ​= ​1099 patients) from 1452 records met the inclusion criteria: seven RCTs (n ​= ​688), one prospective (n ​= ​50), one retrospective (n ​= ​68), and four case-series (n ​= ​224). The PRP preparation process and treatment protocol varied widely (follow-up 6-12 months). In meta-analysis, PRP treatment was not associated with a significant increase in cartilage thickness (4 studies, n ​= ​187, standardized mean difference: Hedges g: 0.079; 95%CI: 0.358 - 0.516; p ​= ​0.723). Meta-analysis of 3 RCTs (n ​= ​112) showed no significant difference in the change of overall knee cartilage content with PRP injections compared with no PRP (Hedges' g: 0.217; 95%CI: 0.177 - 0.611; P ​= ​0.281). The current literature does not support the PRP as chondrogenic in treatment of knee OA. However, there is substantial heterogeneity in the evaluated studies which limits the robustness of any conclusion. An adequately powered RCT, with a standardized PRP regime and standardized high-resolution MRI is needed to definitely define any effect of PRP on knee cartilage content and its relation to clinical outcomes. Until such high-quality evidence becomes available, we recommend that PRP is not administered with the intention of promoting chondrogenesis. [Abstract copyright: © 2022 The Authors.

Membrane sampler for interference-free flow injection NO determination in biological fluids with chemiluminescence detection

Abstract The development of a chemiluminescence (CL) method based on the perm-selective properties of a Nafion-cellulose acetate (CA) composite membrane for the monitoring of nitric oxide (NO) in biological fluids is described. Horseradish peroxidase (HRP) was used as NO trapping solution, forming the stable compound HRP-NO. The HRP was denatured and the trapped NO was released and detected by using the luminol-H 2 O 2 system. Using a mixed (size-exclusion and polar-based) transport control, the interference effects of various compounds were minimized. The method was used for NO monitoring in simulated samples, by using a blood specimen as sample matrix. The 3σ detection limit is 0.9 × 10 −6 mol and linear semi-log calibration plot in the range 1.8 × 10 −6 to 2.7 × 10 −3 mol NO was constructed. The applied methodology was further used to prolong the NO lifetime in order to increase the sensitivity of its determination. This was based on the increase of the response in the presence of certain reductive species, which act as NO preservatives in biological fluid samples