The influence of decision-maker effort and case complexity on appealed rulings subject to multi-categorical selection

This study extends the standard econometric treatment of appellate court outcomes by 1) considering the role of decision-maker effort and case complexity, and 2) adopting a multi-categorical selection process of appealed cases. We find evidence of appellate courts being affected by both the effort made by first-stage decision makers and case complexity. This illustrates the value of widening the narrowly defined focus on heterogeneity in individual-specific preferences that characterises many applied studies on legal decision-making. Further, the majority of appealed cases represent non-random sub-samples and the multi-categorical selection process appears to offer advantages over the more commonly used dichotomous selection models.

Identifying strategies for mitigating the global warming impact of the EU-25 economy using a multi-objective input-output approach

Global warming mitigation has recently become a priority worldwide. A large body of literature dealing with energy related problems has focused on reducing greenhouse gases emissions at an engineering scale. In contrast, the minimization of climate change at a wider macroeconomic level has so far received much less attention. We investigate here the issue of how to mitigate global warming by performing changes in an economy. To this end, we make use of a systematic tool that combines three methods: linear programming, environmentally extended input output models, and life cycle assessment principles. The problem of identifying key economic sectors that contribute significantly to global warming is posed in mathematical terms as a bi criteria linear program that seeks to optimize simultaneously the total economic output and the total life cycle CO2 emissions. We have applied this approach to the European Union economy, finding that significant reductions in global warming potential can be attained by regulating specific economic sectors. Our tool is intended to aid policymakers in the design of more effective public policies for achieving the environmental and economic targets sought.

Efficient image mosaicing for multi-robot visual underwater mapping

Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

Dual inhibitors of beta-amyloid aggregation and acetylcholinesterase as multi-target anti-Alzheimer drug candidates

Notwithstanding the functional role that the aggregates of some amyloidogenic proteins can play in different organisms, protein aggregation plays a pivotal role in the pathogenesis of a large number of human diseases. One of such diseases is Alzheimer"s disease (AD), where the overproduction and aggregation of the β-amyloid peptide (Aβ) are regarded as early critical factors. Another protein that seems to occupy a prominent position within the complex pathological network of AD is the enzyme acetylcholinesterase (AChE), with classical and non-classical activities involved at the late (cholinergic deficit) and early (Aβ aggregation) phases of the disease. Dual inhibitors of Aβ aggregation and AChE are thus emerging as promising multi-target agents with potential to efficiently modify the natural course of AD. In the initial phases of the drug discovery process of such compounds, in vitro evaluation of the inhibition of Aβ aggregation is rather troublesome, as it is very sensitive to experimental assay conditions, and requires expensive synthetic Aβ peptides, which makes cost-prohibitive the screening of large compound libraries. Herein, we review recently developed multi-target anti-Alzheimer compounds that exhibit both Aβ aggregation and AChE inhibitory activities, and, in some cases also additional valuable activities such as BACE-1 inhibition or antioxidant properties. We also discuss the development of simplified in vivo methods for the rapid, simple, reliable, unexpensive, and high-throughput amenable screening of Aβ aggregation inhibitors that rely on the overexpression of Aβ42 alone or fused with reporter proteins in Escherichia coli.