Do cyclic changes in women's face preferences target cues to long-term health?

A shift to prefer more masculine male faces when conception risk is high may be an adaptation for finding mates with good disease resistance. We investigated whether preferences for other facial cues to long-term health also increase when conception is likely. We examined preferences for the faces of men with good health histories and for facial averageness and symmetry, two putative indicators of health during development. Preferences were tested at two points in the menstrual cycle that differed maximally in conception risk. No cyclic changes in preferences were found. We consider implications for the sexual selection of variation in preferences across the menstrual cycle.

Improving telemarketing intelligence through significant proportion of target instances

In this paper we propose, develop, and test a new single-feature evaluator called Significant Proportion of Target Instances (SPTI) to handle the direct-marketing data with the class imbalance problem. The SPTI feature evaluator demonstrates its stability and outstanding performance through empirical experiments in which the real- orld customer data of an e-recruitment firm are used. This research demonstrates that the feature selection using SPTI successfully improves the classifier’s performance in terms of two practical performance metrics. Additionally, we show that it outperforms other well-known feature selection methods and state-of-the-art remedies to the class-imbalance problem. Practically, the findings, when used with the classification model, will help telemarketers to better understand their customers.

Skeletal muscle reactive oxygen species: a target of good cop/bad cop for exercise and disease

Metabolic stresses associated with disease, ageing, and exercise increase the levels of reactive oxygen species (ROS) in skeletal muscle. These ROS have been linked mechanistically to adaptations in skeletal muscle that can be favourable (i.e. in response to exercise) or detrimental (i.e. in response to disease). The magnitude, duration (acute versus chronic), and cellular origin of the ROS are important underlying factors in determining the metabolic perturbations associated with the ROS produced in skeletal muscle. In particular, insulin resistance has been linked to excess ROS production in skeletal muscle mitochondria. A chronic excess of mitochondrial ROS can impair normal insulin signalling pathways and glucose disposal in skeletal muscle. In contrast, ROS produced in skeletal muscle in response to exercise has been linked to beneficial metabolic adaptations including mitochondrial biogenesis and muscle hypertrophy. Moreover, unlike insulin resistance, exercise-induced ROS appears to be primarily of non-mitochondrial origin. The present review summarizes the diverse ROS-targeted metabolic outcomes associated with insulin resistance versus exercise in skeletal muscle, thus, presenting two contrasting perspectives of pathologically harmful versus physiologically beneficial ROS. Here, we discuss the key sites of ROS production during exercise and the effect of ROS in skeletal muscle of people with type 2 diabetes.

Last drinks: a study of rural emergency department data collection to identify and target community alcohol-related violence

The present study summarises the methodology and findings of a pilot project designed to measure the sources and locations of alcohol-related harm by implementing anonymised 'last drinks' questions in the ED of a rural community.

Target coverage in camera networks for manufacturing workplaces

In this paper, we investigate the camera network placement problem for target coverage in manufacturing workplaces. The problem is formulated to find the minimum number of cameras of different types and their best configurations to maximise the coverage of the monitored workplace such that the given set of target points of interest are each k-covered with a predefined minimum spatial resolution. Since the problem is NP-complete, and even NP-hard to approximate, a novel method based on Simulated Annealing is presented to solve the optimisation problem. A new neighbourhood generation function is proposed to handle the discrete nature of the problem. The visual coverage is modelled using realistic and coherent assumptions of camera intrinsic and extrinsic parameters making it suitable for many real world camera based applications. Task-specific quality of coverage measure is proposed to assist selecting the best among the set of camera network placements with equal coverage. A 3D CAD of the monitored space is used to examine physical occlusions of target points. The results show the accuracy, efficiency and scalability of the presented solution method; which can be applied effectively in the design of practical camera networks.

Homocysteine as a potential biomarker in bipolar disorders: a critical review and suggestions for improved studies

Introduction: Homocysteine levels have been associated with major depression, but associations with bipolar disorder remain less clear. Some data suggest homocysteine levels have potential as a biomarker of treatment response; however the literature is mixed.

Areas covered: Oxidized forms of homocysteine can be potentially neurotoxic leading to glutamate toxicity, apoptotic transformation and neurodegenerative processes. High homocysteine may be a risk biomarker for bipolar disorders, but the empirical base remains too weak for firm conclusions. This review discusses the current literature for homocysteine levels as a biomarker.

Expert opinion: It is premature to foreclose the utility of homocysteine levels as a biomarker for bipolar disorder due the methodological inadequacies in the existing literature. These methodological design issues include lack of control for the confounding variables of concurrent medication, phase of bipolar disorder, gender, age, nutritional status, thyroid, liver and renal function, smoking or lean body mass. Well-powered association studies with confounder control could help shed more light on the important clinical question of homocysteine's utility as a biomarker in bipolar disorder. Future experiments are needed to examine the outcome of interventions modulating homocysteine for treating bipolar disorder. Only prospective randomized control trials will provide definitive evidence of the utility of homocysteine as a biomarker or therapeutic target.

Does angling technique selectively target fishes based on their behavioural type?

Recently, there has been growing recognition that fish harvesting practices can have important impacts on the phenotypic distributions and diversity of natural populations through a phenomenon known as fisheries-induced evolution. Here we experimentally show that two common recreational angling techniques (active crank baits versus passive soft plastics) differentially target wild largemouth bass (Micropterus salmoides) and rock bass (Ambloplites rupestris) based on variation in their behavioural tendencies. Fish were first angled in the wild using both techniques and then brought back to the laboratory and tested for individual-level differences in common estimates of personality (refuge emergence, flight-initiation-distance, latency-to-recapture and with a net, and general activity) in an in-lake experimental arena. We found that different angling techniques appear to selectively target these species based on their boldness (as characterized by refuge emergence, a standard measure of boldness in fishes) but not other assays of personality. We also observed that body size was independently a significant predictor of personality in both species, though this varied between traits and species. Our results suggest a context-dependency for vulnerability to capture relative to behaviour in these fish species. Ascertaining the selective pressures angling practices exert on natural populations is an important area of fisheries research with significant implications for ecology, evolution, and resource management.

The Glutathione System: a new drug target in neuroimmune disorders

Glutathione (GSH) has a crucial role in cellular signaling and antioxidant defenses either by reacting directly with reactive oxygen or nitrogen species or by acting as an essential cofactor for GSH S-transferases and glutathione peroxidases. GSH acting in concert with its dependent enzymes, known as the glutathione system, is responsible for the detoxification of reactive oxygen and nitrogen species (ROS/RNS) and electrophiles produced by xenobiotics. Adequate levels of GSH are essential for the optimal functioning of the immune system in general and T cell activation and differentiation in particular. GSH is a ubiquitous regulator of the cell cycle per se. GSH also has crucial functions in the brain as an antioxidant, neuromodulator, neurotransmitter, and enabler of neuron survival. Depletion of GSH leads to exacerbation of damage by oxidative and nitrosative stress; hypernitrosylation; increased levels of proinflammatory mediators and inflammatory potential; dysfunctions of intracellular signaling networks, e.g., p53, nuclear factor-κB, and Janus kinases; decreased cell proliferation and DNA synthesis; inactivation of complex I of the electron transport chain; activation of cytochrome c and the apoptotic machinery; blockade of the methionine cycle; and compromised epigenetic regulation of gene expression. As such, GSH depletion has marked consequences for the homeostatic control of the immune system, oxidative and nitrosative stress (O&NS) pathways, regulation of energy production, and mitochondrial survival as well. GSH depletion and concomitant increase in O&NS and mitochondrial dysfunctions play a role in the pathophysiology of diverse neuroimmune disorders, including depression, myalgic encephalomyelitis/chronic fatigue syndrome and Parkinson’s disease, suggesting that depleted GSH is an integral part of these diseases. Therapeutical interventions that aim to increase GSH concentrations in vivo include N-acetyl cysteine; Nrf-2 activation via hyperbaric oxygen therapy; dimethyl fumarate; phytochemicals, including curcumin, resveratrol, and cinnamon; and folate supplementation.

Target coverage through distributed clustering in directional sensor networks

Maximum target coverage with minimum number of sensor nodes, known as an MCMS problem, is an important problem in directional sensor networks (DSNs). For guaranteed coverage and event reporting, the underlying mechanism must ensure that all targets are covered by the sensors and the resulting network is connected. Existing solutions allow individual sensor nodes to determine the sensing direction for maximum target coverage which produces sensing coverage redundancy and much overhead. Gathering nodes into clusters might provide a better solution to this problem. In this paper, we have designed distributed clustering and target coverage algorithms to address the problem in an energy-efficient way. To the best of our knowledge, this is the first work that exploits cluster heads to determine the active sensing nodes and their directions for solving target coverage problems in DSNs. Our extensive simulation study shows that our system outperforms a number of state-of-the-art approaches.

Labeled random finite sets and the bayes multi-target tracking filter

An analytic solution to the multi-target Bayes recursion known as the δ-Generalized Labeled Multi-Bernoulli ( δ-GLMB) filter has been recently proposed by Vo and Vo in [“Labeled Random Finite Sets and Multi-Object Conjugate Priors,” IEEE Trans. Signal Process., vol. 61, no. 13, pp. 3460-3475, 2014]. As a sequel to that paper, the present paper details efficient implementations of the δ-GLMB multi-target tracking filter. Each iteration of this filter involves an update operation and a prediction operation, both of which result in weighted sums of multi-target exponentials with intractably large number of terms. To truncate these sums, the ranked assignment and K-th shortest path algorithms are used in the update and prediction, respectively, to determine the most significant terms without exhaustively computing all of the terms. In addition, using tools derived from the same framework, such as probability hypothesis density filtering, we present inexpensive (relative to the δ-GLMB filter) look-ahead strategies to reduce the number of computations. Characterization of the L1-error in the multi-target density arising from the truncation is presented.

What happens after the central bank of Brazil increases the target interbank rate by 1%?

I start presenting an explicit solution to Taylorís (2001) model, in order to illustrate the link between the target interest rate and the overnight interest rate prevailing in the economy. Next, I use Vector Auto Regressions to shed some light on the evolution of key macroeconomic variables after the Central Bank of Brazil increases the target interest rate by 1%. Point estimates show a four-year accumulated output loss ranging from 0:04% (whole sample, 1980 : 1-2004 : 2; quarterly data) to 0:25% (Post-Real data only) with a Örst-year peak output response between 0:04% and 1:0%; respectively. Prices decline between 2% and 4% in a 4-year horizon. The accumulated output response is found to be between 3:5 and 6 times higher after the Real Plan than when the whole sample is considered. The 95% confidence bands obtained using bias-corrected bootstrap always include the null output response when the whole sample is used, but not when the data is restricted to the Post-Real period. Innovations to interest rates explain between 4:9% (whole sample) and 9:2% (post-Real sample) of the forecast error of GDP.

What if firms adjust their debt-equity ratios toward a target range?

We estimate optimal target-ranges of capital structure controlling for a series of firmspecific characteristics and accounting for the serial correlation that arises from the dynamic component of the leverage choice. Then, we empirically examine if firms adjust their leverages toward the estimated optimal ranges. Our analysis suggests that the observed behavior of firms is consistent with the notion of range-adjustment.