Timed Probabilistic Automaton : a bridge between Raven and Song Scope for automatic species recognition

Raven and Song Scope are two automated sound anal-ysis tools based on machine learning technique for en-vironmental monitoring. Many research works have been conducted upon them, however, no or rare explo-ration mentions about the performance and comparison between them. This paper investigates the comparisons from six aspects: theory, software interface, ease of use, detection targets, detection accuracy, and potential application. Through deep exploration one critical gap is identified that there is a lack of approach to detect both syllables and call structures, since Raven only aims to detect syllables while Song Scope targets call structures. Therefore, a Timed Probabilistic Automata (TPA) system is proposed which separates syllables first and clusters them into complex structures after.

Sex-based comparisons of myofibrillar protein synthesis after resistance exercise in the fed state

Sex-based comparisons of myofibrillar protein synthesis after resistance exercise in the fed state. J Appl Physiol 112: 1805-1813, 2012. First published March 1, 2012; doi:10.1152/japplphysiol.00170.2012.- We made sex-based comparisons of rates of myofibrillar protein synthesis (MPS) and anabolic signaling after a single bout of high-intensity resistance exercise. Eight men (20 ± 10 yr, BMI = 24.3 ± 2.4) and eight women (22 ± 1.8 yr, BMI = 23.0 ± 1.9) underwent primed constant infusions of L-[ring-13C6]phenylalanine on consecutive days with serial muscle biopsies. Biopsies were taken from the vastus lateralis at rest and 1, 3, 5, 24, 26, and 28 h after exercise. Twenty-five grams of whey protein was ingested immediately and 26 h after exercise. We also measured exercise-induced serum testosterone because it is purported to contribute to increases in myofibrillar protein synthesis (MPS) postexercise and its absence has been hypothesized to attenuate adaptative responses to resistance exercise in women. The exercise-induced area under the testosterone curve was 45-fold greater in men than women in the early (1 h) recovery period following exercise (P < 0.001). MPS was elevated similarly in men and women (2.3- and 2.7-fold, respectively) 1-5 h postexercise and after protein ingestion following 24 h recovery. Phosphorylation of mTORSer2448 was elevated to a greater extent in men than women acutely after exercise (P = 0.003), whereas increased phosphorylation of p70S6K1Thr389 was not different between sexes. Androgen receptor content was greater in men (main effect for sex, P = 0.049). Atrogin-1 mRNA abundance was decreased after 5 h recovery in both men and women (P < 0.001), and MuRF-1 expression was elevated in men after protein ingestion following 24 h recovery (P = 0.003). These results demonstrate minor sex-based differences in signaling responses and no difference in the MPS response to resistance exercise in the fed state. Interestingly, our data demonstrate that exerciseinduced increases in MPS are dissociated from postexercise testosteronemia and that stimulation of MPS occurs effectively with low systemic testosterone concentrations in women.

Formalising human recognition : a fundamental building block for security proofs

A fundamental part of many authentication protocols which authenticate a party to a human involves the human recognizing or otherwise processing a message received from the party. Examples include typical implementations of Verified by Visa in which a message, previously stored by the human at a bank, is sent by the bank to the human to authenticate the bank to the human; or the expectation that humans will recognize or verify an extended validation certificate in a HTTPS context. This paper presents general definitions and building blocks for the modelling and analysis of human recognition in authentication protocols, allowing the creation of proofs for protocols which include humans. We cover both generalized trawling and human-specific targeted attacks. As examples of the range of uses of our construction, we use the model presented in this paper to prove the security of a mutual authentication login protocol and a human-assisted device pairing protocol.

Misperceptions about child sex offenders

Sexual offending against children is a highly emotive issue. It is nonetheless important that public policy initiatives to prevent and/or respond to child sexual abuse are based on the available evidence about child sex offenders. This paper addresses five common misperceptions about the perpetrators of sexual offences against children. Specifically, the issues addressed include whether all child sex offenders are ‘paedophiles’, who sexually abuse children, whether most child sex offenders were victims of sexual abuse themselves, rates of recidivism among child sex offenders and the number of children sex offenders typically abuse before they are detected by police. The evidence outlined in this paper highlights that there are few black and white answers to these questions. Perpetrators of sexual crimes against children are not, contrary to widespread opinion, a homogenous group. Rather, there are a number of varied offending profiles that characterise child sex offenders. Gaining an understanding of the nuances of this offender population is critical if children are to be protected from sexual abuse.

Domestic violence and family law : recognition and appropriation

The battered women’s movement in the United States contributed to a sweeping change in the recognition of men’s violence against female intimate partners. Naming the problem and arguing in favour of its identification as a serious problem meriting a collective response were key aspects of this effort. Criminal and civil laws have been written and revised in an effort to answer calls to take such violence seriously. Scholars have devoted significant attention to the consequences of this reframing of violence, especially around the unintended outcomes of the incorporation of domestic violence into criminal justice regimes. Family law, however, has remained largely unexamined by criminologists. This paper calls for criminological attention to family law responses to domestic violence and provides directions for future research.

Jane McCredie - Making Girls and Boys : Inside the Science of Sex [Book Review]

Activists, Feminists, queer theorists, and those who live outside traditional gender narratives have long challenged the fixity of the sex and gender binaries. While the dominant Western paradigm posits sex and gender as natural and inherent, queer theory argues that sex and gender are socially constructed. This means that our ideas about sex and gender, and the concepts themselves, are shaped by particular social contexts. Questioning the nature of sex can be puzzling. After all, isn’t sex biology? Binary sex – male and female – was labelled as such by scientists based on existing binary categories and observations of hormones, genes, chromosomes, reproductive organs, genitals and other bodily elements. Binary sex is allocated at birth by genital appearance. Not everyone fits into these categories and this leads queer theorists, and others, to question the categories. Now, “some scientists are also starting to move away from the idea of biology as the fixed basis on which the social artefact of gender is built” (5). Making Girls and Boys: Inside the Science of Sex, by Jane McCredie, examines theories about gender roles and behaviours also considering those who don’t fit the arbitrary sex and gender binaries.

Robust recognition of human behaviour in challenging environments

Novel techniques have been developed for the automatic recognition of human behaviour in challenging environments using information from visual and infra-red camera feeds. The techniques have been applied to two interesting scenarios: Recognise drivers' speech using lip movements and recognising audience behaviour, while watching a movie, using facial features and body movements. Outcome of the research in these two areas will be useful in the improving the performance of voice recognition in automobiles for voice based control and for obtaining accurate movie interest ratings based on live audience response analysis.

Autonomous movement-driven place recognition calibration for generic multi-sensor robot platforms

In this paper we present a method for autonomously tuning the threshold between learning and recognizing a place in the world, based on both how the rodent brain is thought to process and calibrate multisensory data and the pivoting movement behaviour that rodents perform in doing so. The approach makes no assumptions about the number and type of sensors, the robot platform, or the environment, relying only on the ability of a robot to perform two revolutions on the spot. In addition, it self-assesses the quality of the tuning process in order to identify situations in which tuning may have failed. We demonstrate the autonomous movement-driven threshold tuning on a Pioneer 3DX robot in eight locations spread over an office environment and a building car park, and then evaluate the mapping capability of the system on journeys through these environments. The system is able to pick a place recognition threshold that enables successful environment mapping in six of the eight locations while also autonomously flagging the tuning failure in the remaining two locations. We discuss how the method, in combination with parallel work on autonomous weighting of individual sensors, moves the parameter dependent RatSLAM system significantly closer to sensor, platform and environment agnostic operation.

Sex and the virtual suburbs : the pornosphere and community standards

This chapter looks at the management and zoning of online sexual culture–the web sites which make up the pornosphere (McNair 2013). It explores the concept of ‘community standards’, which has been a central part of the management of sexually explicit materials in the offline world, and asks what it might mean to talk about ‘community standards’ on the Internet. And finally, it uses the concept of virtual-community standards to revisit the question of managing access to sexually explicit materials on the Internet.

Bearing Fault Diagnostics Using the Spectral Pattern Recognition

In the field of diagnostics of rolling element bearings, the development of sophisticated techniques, such as Spectral Kurtosis and 2nd Order Cyclostationarity, extended the capability of expert users to identify not only the presence, but also the location of the damage in the bearing. Most of the signal-analysis methods, as the ones previously mentioned, result in a spectrum-like diagram that presents line frequencies or peaks in the neighbourhood of some theoretical characteristic frequencies, in case of damage. These frequencies depend only on damage position, bearing geometry and rotational speed. The major improvement in this field would be the development of algorithms with high degree of automation. This paper aims at this important objective, by discussing for the first time how these peaks can draw away from the theoretical expected frequencies as a function of different working conditions, i.e. speed, torque and lubrication. After providing a brief description of the peak-patterns associated with each type of damage, this paper shows the typical magnitudes of the deviations from the theoretical expected frequencies. The last part of the study presents some remarks about increasing the reliability of the automatic algorithm. The research is based on experimental data obtained by using artificially damaged bearings installed in a gearbox.

No sex difference in body fat in response to supervised and measured exercise

It is often reported that females lose less body weight than males do in response to exercise. These differences are suggested to be a result of females exhibiting a stronger defense of body fat and a greater compensatory appetite response to exercise than males do. Purpose This study aimed to compare the effect of a 12-wk supervised exercise program on body weight, body composition, appetite, and energy intake in males and females. Methods A total of 107 overweight and obese adults (males = 35, premenopausal females = 72, BMI = 31.4 ± 4.2 kg·m−2, age = 40.9 ± 9.2 yr) completed a supervised 12-wk exercise program expending approximately 10.5 MJ·wk−1 at 70% HRmax. Body composition, energy intake, appetite ratings, RMR, and cardiovascular fitness were measured at weeks 0 and 12. Results The 12-wk exercise program led to significant reductions in body mass (males [M] = −3.03 ± 3.4 kg and females [F] = −2.28 ± 3.1 kg), fat mass (M = −3.14 ± 3.7 kg and F = −3.01 ± 3.0 kg), and percent body fat (M = −2.45% ± 3.3% and F = −2.45% ± 2.2%; all P < 0.0001), but there were no sex-based differences (P > 0.05). There were no significant changes in daily energy intake in males or females after the exercise intervention compared with baseline (M = 199.2 ± 2418.1 kJ and F = −131.6 ± 1912.0 kJ, P > 0.05). Fasting hunger levels significantly increased after the intervention compared with baseline values (M = 11.0 ± 21.1 min and F = 14.0 ± 22.9 mm, P < 0.0001), but there were no differences between males and females (P > 0.05). The exercise also improved satiety responses to an individualized fixed-energy breakfast (P < 0.0001). This was comparable in males and females. Conclusions Males and premenopausal females did not differ in their response to a 12-wk exercise intervention and achieved similar reductions in body fat. When exercise interventions are supervised and energy expenditure is controlled, there are no sex-based differences in the measured compensatory response to exercise.

Delirium knowledge and recognition : a randomized controlled trial of a web-based educational intervention for acute care nurses

Delirium is a significant problem for older hospitalized people and is associated with poor outcomes. It is poorly recognized and evidence suggests that a major reason is lack of education. Nurses, who are educated about delirium, can play a significant role in improving delirium recognition. This study evaluated the impact of a delirium specific educational website. A cluster randomized controlled trial, with a pretest/post-test time series design, was conducted to measure delirium knowledge (DK) and delirium recognition (DR) over three time-points. Statistically significant differences were found between the intervention and non-intervention group. The intervention groups' DK scores were higher and the change over time results were statistically significant [T3 and T1 (t=3.78 p=<0.001) and T2 and T1 baseline (t=5.83 p=<0.001)]. Statistically significant improvements were also seen for DR when comparing T2 and T1 results (t=2.56 p=0.011) between both groups but not for changes in DR scores between T3 and T1 (t=1.80 p=0.074). Participants rated the website highly on the visual, functional and content elements. This study supports the concept that web-based delirium learning is an effective and satisfying method of information delivery for registered nurses. Future research is required to investigate clinical outcomes as a result of this web-based education.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Towards bio-inspired place recognition over multiple spatial scales

This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.