The Rule of Law and Technocratisation

Contribution to a festschrfit for Martin Krygier; argues that the technocratisation of the rule of law has been a problem for the establishment of the global rule of law, but that taking a pluralist view of the norm & settng it in its proper historical context allows for a more postive view of the potenital for suport to local social actors to work in the domestic politics of of 'recipient' states to slowly build a thicker rule of la

The use of quality information by general practitioners: does it alter choices? A randomized clustered study

Background: Following the introduction of elements of managed competition in the Netherlands in 2006, General Practitioners (GPs) and patients were given the role to select treatment hospital using public quality information. In this study we investigate to what extent hospital preferences of GP's are affected by performance indicators on medical effectiveness and patient experiences. We selected three conditions: breast cancer, cataract surgery, and hip and knee replacement. Methods. After an inquiry 26 out of 226 GPs in the region signed up to participate in our study. After a 2:1 randomization, we analyzed the referral patterns in the region using three groups of GPs: GPs (n=17) who used the report cards and received personal clarification, GPs that signed up for the study but were assigned to the control group (n=9), and the GPs outside the study (n=200).We conducted a difference in differences analysis where the choice for a particular hospital was the dependent variable and time (2009 or 2010), the sum score of the CQI, the sum score of the PI's and dummy variables for the individual hospitals were used as independent variables. Results: The analysis of the conditions together and cataract surgery and hip and knee replacement separately, showed no significant relationships between the scores on the report cards and the referral patterns of the GPs. For breast cancer our analysis revealed that GPs in the intervention group refer 1.0% (p=0.01) more to hospitals that score one percent point better on the indicators for medical effectiveness. Conclusion: Our study provides empirical evidence that GP referral patterns were unaffected by the available quality information, except for the outcome indicators for breast cancer care that were presented. This finding was surprising since our study was designed to identify changes in hospital preference (1) amongst the most motivated GP's, (2) that received personal clarification of the performance indicators, and (3) selected indicators/conditions from a large set of indicators that they believed were most important. This finding may differ when quality information is based on outcome indicators with a clinically relevant difference, as shown by our indicators for breast cancer treatment. We believe that the current set of (largely process) hospital quality indicators do not serve the GP's information needs and consequently quality plays little role in the selection of hospitals for treatment. © 2013 Ikkersheim and Koolman; licensee BioMed Central Ltd

The Effects of Twitter Sentiment on Stock Price Returns

Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-know micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known "event study" from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the "event study" methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1-2%), but the dependence is statistically significant for several days after the events

Towards Intelligent Crowd Behavior Understanding through the STFD Descriptor Exploration

Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of input video signals. This integrated solution defines an image descriptor (named spatio-temporal feature descriptor - STFD) that reflects the global motion information of crowds over time. A CNN has then been adopted to classify dominant or large-scale crowd abnormal behaviors. The work reported has focused on: 1) detecting moving objects in online (or near real-time) manner through spatio-temporal segmentations of crowds that is defined by the similarity of group trajectory structures in temporal space and the foreground blocks based on Gaussian Mixture Model (GMM) in spatial space; 2) dividing multiple clustered groups based on the spectral clustering method by considering image pixels from spatio-temporal segmentation regions as dynamic particles; 3) generating the STFD descriptor instances by calculating the attributes (i.e., collectiveness, stability, conflict and crowd density) of particles in the corresponding groups; 4) inputting generated STFD descriptor instances into the devised convolutional neural network (CNN) to detect suspicious crowd behaviors. The test and evaluation of the devised models and techniques have selected the PETS database as the primary experimental data sets. Results against benchmarking models and systems have shown promising advancements of this novel approach in terms of accuracy and efficiency for detecting crowd anomalies

Towards Intelligent Crowd Behavior Understanding through the STFD Descriptor Exploration

Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of input video signals. This integrated solution defines an image descriptor (named spatio-temporal feature descriptor - STFD) that reflects the global motion information of crowds over time. A CNN has then been adopted to classify dominant or large-scale crowd abnormal behaviors. The work reported has focused on: 1) detecting moving objects in online (or near real-time) manner through spatio-temporal segmentations of crowds that is defined by the similarity of group trajectory structures in temporal space and the foreground blocks based on Gaussian Mixture Model (GMM) in spatial space; 2) dividing multiple clustered groups based on the spectral clustering method by considering image pixels from spatio-temporal segmentation regions as dynamic particles; 3) generating the STFD descriptor instances by calculating the attributes (i.e., collectiveness, stability, conflict and crowd density) of particles in the corresponding groups; 4) inputting generated STFD descriptor instances into the devised convolutional neural network (CNN) to detect suspicious crowd behaviors. The test and evaluation of the devised models and techniques have selected the PETS database as the primary experimental data sets. Results against benchmarking models and systems have shown promising advancements of this novel approach in terms of accuracy and efficiency for detecting crowd anomalies

Output from VIP cells of the mammalian central clock regulates daily physiological rhythms

The suprachiasmatic nucleus (SCN) circadian clock is critical for optimising daily cycles in mammalian physiology and behaviour. The roles of the various SCN cell types in communicating timing information to downstream physiological systems remain incompletely understood, however. In particular, while vasoactive intestinal polypeptide (VIP) signalling is essential for SCN function and whole animal circadian rhythmicity, the specific contributions of VIP cell output to physiological control remains uncertain. Here we reveal a key role for SCN VIP cells in central clock output. Using multielectrode recording and optogenetic manipulations, we show that VIP neurons provide coordinated daily waves of GABAergic input to target cells across the paraventricular hypothalamus and ventral thalamus, supressing their activity during the mid to late day. Using chemogenetic manipulation, we further demonstrate specific roles for this circuitry in the daily control of heart rate and corticosterone secretion, collectively establishing SCN VIP cells as influential regulators of physiological timing

Are alcoholism treatments effective? The Project MATCH data

BACKGROUND: Project MATCH was the largest and most expensive alcoholism treatment trial ever conducted. The results were disappointing. There were essentially no patient-treatment matches, and three very different treatments produced nearly identical outcomes. These results were interpreted post hoc as evidence that all three treatments were quite effective. We re-analyzed the data in order to estimate effectiveness in relation to quantity of treatment. METHODS: This was a secondary analysis of data from a multisite clinical trial of alcohol dependent volunteers (N = 1726) who received outpatient psychosocial therapy. Analyses were confined to the primary outcome variables, percent days abstinent (PDA) and drinks per drinking day (DDD). Overall tests between treatment outcome and treatment quantity were conducted. Next, three specific groups were highlighted. One group consisted of those who dropped out immediately; the second were those who dropped out after receiving only one therapy session, and the third were those who attended 12 therapy sessions. RESULTS: Overall, a median of only 3% of the drinking outcome at follow-up could be attributed to treatment. However this effect appeared to be present at week one before most of the treatment had been delivered. The zero treatment dropout group showed great improvement, achieving a mean of 72 percent days abstinent at follow-up. Effect size estimates showed that two-thirds to three-fourths of the improvement in the full treatment group was duplicated in the zero treatment group. Outcomes for the one session treatment group were worse than for the zero treatment group, suggesting a patient self selection effect. Nearly all the improvement in all groups had occurred by week one. The full treatment group had improved in PDA by 62% at week one, and the additional 11 therapy sessions added only another 4% improvement. CONCLUSION: The results suggest that current psychosocial treatments for alcoholism are not particularly effective. Untreated alcoholics in clinical trials show significant improvement. Most of the improvement which is interpreted as treatment effect is not due to treatment. Part of the remainder appears to be due to selection effects

Increased risk of second malignancies after in situ breast carcinoma in a population-based registry

Among 1276 primary breast carcinoma in situ (BCIS) patients diagnosed in 1972–2002 in the Southern Netherlands, 11% developed a second cancer. Breast carcinoma in situ patients exhibited a two-fold increased risk of second cancer (standardised incidence ratios (SIR): 2.1, 95% confidence interval (CI): 1.7–2.5). The risk was highest for a second breast cancer (SIR: 3.4, 95% CI: 2.6–4.3; AER: 66 patients per 10 000 per year) followed by skin cancer (SIR: 1.7, 95% CI: 1.1–2.6; AER: 17 patients per 10 000 per year). The increased risk of second breast cancer was similar for the ipsilateral (SIR: 1.9, 95% CI: 1.3–2.7) and contralateral (SIR: 2.0, 95% CI: 1.4–2.8) breast. Risk of second cancer was independent of age at diagnosis, type of initial therapy, histologic type of BCIS and period of diagnosis. Standardised incidence ratios of second cancer after BCIS (SIR: 2.3, 95% CI: 1.8–2.8) resembled that after invasive breast cancer (SIR: 2.2, 95% CI: 2.1–2.4). Surveillance should be directed towards second (ipsi- and contra-lateral) breast cancer

Physics, Astrophysics and Cosmology with Gravitational Waves

Gravitational wave detectors are already operating at interesting sensitivity levels, and they have an upgrade path that should result in secure detections by 2014. We review the physics of gravitational waves, how they interact with detectors (bars and interferometers), and how these detectors operate. We study the most likely sources of gravitational waves and review the data analysis methods that are used to extract their signals from detector noise. Then we consider the consequences of gravitational wave detections and observations for physics, astrophysics, and cosmology.Comment: 137 pages, 16 figures, Published version <http://www.livingreviews.org/lrr-2009-2