Call auction transparency and market liquidity: Evidence from China

This paper uses the natural experiment offered by the Shanghai Stock Exchange to investigate the impact of opening call auction transparency on market liquidity. We find that the dissemination of indicative trade information during the pre-open call auction session leads to an overall improvement in stock liquidity in the continuous trading session. Bid-ask spreads narrow in the first trading hour because adverse selection risk fell significantly and there is less price volatility in the continuous market. This effect is greater for actively traded securities than illiquid securities. Our findings are robust for different lengths of sample period, different lengths of trading hours after market open, and stocks that had (and had not) reformed the share split structure during our research period.

Sedation protocols to reduce duration of mechanical ventilation in the ICU: a Cochrane Systematic Review

AIMS: Assess the effects of protocol-directed sedation management on the duration of mechanical ventilation and other relevant patient outcomes in mechanically ventilated intensive care unit patients. BACKGROUND: Sedation is a core component of critical care. Sub-optimal sedation management incorporates both under- and over-sedation and has been linked to poorer patient outcomes. DESIGN: Cochrane systematic review of randomized controlled trials. DATA SOURCES: Cochrane Central Register of Controlled trials, MEDLINE, EMBASE, CINAHL, Database of Abstracts of Reviews of Effects, LILACS, Current Controlled Trials and US National Institutes of Health Clinical Research Studies (1990-November 2013) and reference lists of articles were used. REVIEW METHODS: Randomized controlled trials conducted in intensive care units comparing management with and without protocol-directed sedation were included. Two authors screened titles, abstracts and full-text reports. Potential risk of bias was assessed. Clinical, methodological and statistical heterogeneity were examined and the random-effects model used for meta-analysis where appropriate. Mean difference for duration of mechanical ventilation and risk ratio for mortality, with 95% confidence intervals, were calculated. RESULTS: Two eligible studies with 633 participants comparing protocol-directed sedation delivered by nurses vs. usual care were identified. There was no evidence of differences in duration of mechanical ventilation or hospital mortality. There was statistically significant heterogeneity between studies for duration of mechanical ventilation. CONCLUSIONS: There is insufficient evidence to evaluate the effectiveness of protocol-directed sedation as results from the two randomized controlled trials were conflicting.

A stochastic time-domain model for burst data aggregation in IEEE 802.15.4 wireless sensor networks

In many network applications, the nature of traffic is of burst type. Often, the transient response of network to such traffics is the result of a series of interdependant events whose occurrence prediction is not a trivial task. The previous efforts in IEEE 802.15.4 networks often followed top-down approaches to model those sequences of events, i.e., through making top-view models of the whole network, they tried to track the transient response of network to burst packet arrivals. The problem with such approaches was that they were unable to give station-level views of network response and were usually complex. In this paper, we propose a non-stationary analytical model for the IEEE 802.15.4 slotted CSMA/CA medium access control (MAC) protocol under burst traffic arrival assumption and without the optional acknowledgements. We develop a station-level stochastic time-domain method from which the network-level metrics are extracted. Our bottom-up approach makes finding station-level details such as delay, collision and failure distributions possible. Moreover, network-level metrics like the average packet loss or transmission success rate can be extracted from the model. Compared to the previous models, our model is proven to be of lower memory and computational complexity order and also supports contention window sizes of greater than one. We have carried out extensive and comparative simulations to show the high accuracy of our model.

Aggregation on the fly: Reducing traffic for big data in the cloud

As a leading framework for processing and analyzing big data, MapReduce is leveraged by many enterprises to parallelize their data processing on distributed computing systems. Unfortunately, the all-to-all data forwarding from map tasks to reduce tasks in the traditional MapReduce framework would generate a large amount of network traffic. The fact that the intermediate data generated by map tasks can be combined with significant traffic reduction in many applications motivates us to propose a data aggregation scheme for MapReduce jobs in cloud. Specifically, we design an aggregation architecture under the existing MapReduce framework with the objective of minimizing the data traffic during the shuffle phase, in which aggregators can reside anywhere in the cloud. Some experimental results also show that our proposal outperforms existing work by reducing the network traffic significantly.

Evaluation of three field monitoring-density estimation protocols and their relevance to Komodo dragon conservation

Finding practical ways to robustly estimate abundance or density trends in threatened species is a key facet for effective conservation management. Further identifying less expensive monitoring methods that provide adequate data for robust population density estimates can facilitate increased investment into other conservation initiatives needed for species recovery. Here we evaluated and compared inference-and cost-effectiveness criteria for three field monitoring-density estimation protocols to improve conservation activities for the threatened Komodo dragon (Varanus komodoensis). We undertook line-transect counts, cage trapping and camera monitoring surveys for Komodo dragons at 11 sites within protected areas in Eastern Indonesia to collect data to estimate density using distance sampling methods or the Royle-Nichols abundance induced heterogeneity model. Distance sampling estimates were considered poor due to large confidence intervals, a high coefficient of variation and that false absences were obtained in 45 % of sites where other monitoring methods detected lizards present. The Royle-Nichols model using presence/absence data obtained from cage trapping and camera monitoring produced highly correlated density estimates, obtained similar measures of precision and recorded no false absences in data collation. However because costs associated with camera monitoring were considerably less than cage trapping methods, albeit marginally more expensive than distance sampling, better inference from this method is advocated for ongoing population monitoring of Komodo dragons. Further the cost-savings achieved by adopting this field monitoring method could facilitate increased expenditure on alternative management strategies that could help address current declines in two Komodo dragon populations.

Evaluating and predicting risk to a large reptile (Varanus varius) from feral cat baiting protocols

Control of introduced predators to mitigate biodiversity impacts is a pressing conservation challenge. Across Australia feral cats (Felis catus) are a major threat to terrestrial biodiversity. Currently feral cat control is hindered by the limited utility of existing predator baiting methods. Further proposed control methods include use of the novel poison para-aminopropiophenone (PAPP) which may present a hazard to some native animal populations. Here we used experimental and predictive approaches to evaluate feral cat bait take by a large native Australian predatory reptile the Lace monitor (Varanus varius). These lizards would be expected to readily detect, ingest and consume a lethal dose (depending on toxin) from surface-laid baits intended for feral cat control if a precautionary approach was not adopted when baiting. We modelled V. varius bait take using experimental and predictive biophysical modelling approaches to evaluate temporal effects of climate variables on V. varius activity and hence potential for bait removal. Finally we conducted a pre-PAPP baiting site occupancy assessment of V. varius within Wilson Promontory National Park (WPNP) to provide a basis for monitoring any longer term population effects of cat baiting. V. varius removed 7 % of deployed baits from 73 % of bait stations across another study area in Far Eastern Victoria. Daily bait removal was positively correlated with maximum temperature and solar radiation. Biophysical modelling for Far Eastern Victoria predicted that maximum temperatures <19.5 °C prevented V. varius activity and hence opportunity for bait removal. V. varius in WPNP was undetectable suggesting aerial baiting posed limited hazard to this species at this location. Depending how climate influences annual activity patterns and the specific poison, surface-laid baits could pose a significant mortality risk to V. varius. However, use of biophysical models to predict periods of V. varius inactivity may provide a novel means to reduce non-target bait take by this predator.

Biased experts and similarity based weights in preferences aggregation

In a group decision making setting, we consider the potential impact an expert can have on the overall ranking by providing a biased assessment of the alternatives that differs substantially from the majority opinion. In the framework of similarity based averaging functions, we show that some alternative approaches to weighting the experts' inputs during the aggregation process can minimize the influence the biased expert is able to exert.

A review of security protocols in mHealth Wireless Body Area Networks (WBAN)

The popularity of smartphones has led to an increasing demand for health apps. As a result, the healthcare industry is embracing mobile technology and the security of mHealth is essential in protecting patient’s user data and WBAN in a clinical setting. Breaches of security can potentially be life-threatening as someone with malicious intentions could misuse mHealth devices and user information. In this article, threats to security for mHealth networks are discussed in a layered approach addressing gaps in this emerging field of research. Suite B and Suite E, which are utilized in many security systems, including in mHealth applications, are also discussed. In this paper, the support for mHealth security will follow two approaches; protecting patient-centric systems and associated link technologies. Therefore this article is focused on the security provisioning of the communication path between the patient terminal (PT; e.g., sensors) and the monitoring devices (e.g., smartphone, data-collector).

Construction and aggregation of preference relations based on fuzzy partial orders

In group decision-making problems it is common to elicit preferences from human experts in the form of pairwise preference relations. When this is extended to a fuzzy setting, entries in the pairwise preference matrix are interpreted to denote strength of preference, however once logical properties such as consistency and transitivity are enforced, the resulting preference relation requires almost as much information as providing raw scores or a complete order over the alternatives. Here we instead interpret fuzzy degrees of preference to only apply where the preference over two alternatives is genuinely fuzzy and then suggest an aggregation procedure that minimizes a generalized Kemeny distance to the nearest complete or partial order. By focusing on the fuzzy partial order, the method is less affected by differences in the natural scale over which an expert expresses their preference, and can also limit the influence of extreme scores.