A method to weight three categories of adaptive thermal comfort

The adaptive thermal comfort theory considers people as active rather than passive recipients in response to ambient physical thermal stimuli, in contrast with conventional, heat-balance-based, thermal comfort theory. Occupants actively interact with the environments they occupy by means of utilizing adaptations in terms of physiological, behavioural and psychological dimensions to achieve ‘real world’ thermal comfort. This paper introduces a method of quantifying the physiological, behavioural and psychological portions of the adaptation process by using the analytic hierarchy process (AHP) based on the case studies conducted in the UK and China. Apart from three categories of adaptations which are viewed as criteria, six possible alternatives are considered: physiological indices/health status, the indoor environment, the outdoor environment, personal physical factors, environmental control and thermal expectation. With the AHP technique, all the above-mentioned criteria, factors and corresponding elements are arranged in a hierarchy tree and quantified by using a series of pair-wise judgements. A sensitivity analysis is carried out to improve the quality of these results. The proposed quantitative weighting method provides researchers with opportunities to better understand the adaptive mechanisms and reveal the significance of each category for the achievement of adaptive thermal comfort.

Field study on thermal comfort and adaptive strategies in residential buildings in China

This paper fully describes a nation-wide field study on building thermal environment and thermal comfort of occupant, which was carried out in summer 2005 and in winter 2006 respectively in China, illustrating the adaptive strategies adopted by occupants in domestic buildings in China. According to the climate division in China, the buildings in Beijing (BJ), Shanghai (SH), Wuhan (WH) and Chongqing (CQ), Guangzhou (GZ), Kunming (KM), were selected as targets which are corresponding to cold zone, hot summer and cold winter zone (SWC-SH, WH, CQ), hot summer and warm winter zone and temperate zone, respectively. The methodology used in the field study is the combination of subjective questionnaire regarding thermal sensation and adaptive approaches and physical environmental monitoring including indoor air temperature and relative humidity. A total of 1671 subjects participate in this investigation with more than 80% response rate in all surveyed cities. Both physiological and non-physiological factors (behavioural and psychological adaptations) have been analysed.

Results of a DSP based adaptive cancellation filter system for the chirp, pulsar and localiser sirens

Sirens’ used by police, fire and paramedic vehicles generate noise that propagates inside the vehicle cab that subsequently corrupts intelligibility of voice communications from the emergency vehicle to the control room. It is even common for the siren to be turned off to enable the control room to hear what is being said. Both fixed filter and adaptive filter systems have previously been developed to help cancel the transmission of the siren noise over the radio. Previous cancellation systems have only concentrated on the traditional 2-tone, wail and yelp sirens. This paper discusses an improvement to a previous adaptive filter system and presents the cancellation results to three new types of sirens; being chirp pulsar and localiser. A siren noise filter system has the capability to improve the response time for an emergency vehicle and thus help save lives. To date, this system has been tested using live recordings taken from a nonemergency situation with good results.

Adaptive recursive control of a soil testing load frame

Recursive Learning Control (RLC) has the potential to significantly reduce the tracking error in many repetitive trajectory applications. This paper presents an application of RLC to a soil testing load frame where non-adaptive techniques struggle with the highly nonlinear nature of soil. The main purpose of the controller is to apply a sinusoidal force reference trajectory on a soil sample with a high degree of accuracy and repeatability. The controller uses a feedforward control structure, recursive least squares adaptation algorithm and RLC to compensate for periodic errors. Tracking error is reduced and stability is maintained across various soil sample responses.

Are patterns of growth adaptive?

Models which define fitness in terms of per capita rate of increase of phenotypes are used to analyse patterns of individual growth. It is shown that sigmoid growth curves are an optimal strategy (i.e. maximize fitness) if (Assumption 1a) mortality decreases with body size; (2a) mortality is a convex function of specific growth rate, viewed from above; (3) there is a constraint on growth rate, which is attained in the first phase of growth. If the constraint is not attained then size should increase at a progressively reducing rate. These predictions are biologically plausible. Catch-up growth, for retarded individuals, is generally not an optimal strategy though in special cases (e.g. seasonal breeding) it might be. Growth may be advantageous after first breeding if birth rate is a convex function of G (the fraction of production devoted to growth) viewed from above (Assumption 5a), or if mortality rate is a convex function of G, viewed from above (Assumption 6c). If assumptions 5a and 6c are both false, growth should cease at the age of first reproduction. These predictions could be used to evaluate the incidence of indeterminate versus determinate growth in the animal kingdom though the data currently available do not allow quantitative tests. In animals with invariant adult size a method is given which allows one to calculate whether an increase in body size is favoured given that fecundity and developmental time are thereby increased.

Promoting resilient livelihoods through adaptive social protection: lessons from 124 programmes in South Asia

Adaptive Social Protection refers to efforts to integrate social protection (SP), disaster risk reduction (DRR) and climate change adaptation (CCA). The need to integrate these three domains is now increasingly recognized by practitioners and academics. Relying on 124 agricultural programmes implemented in 5 countries in Asia, this paper considers how these elements are being brought together, and explores the potential gains of these linkages. The analysis shows that full integration of SP, DRR and CCA interventions is still relatively limited but that when it occurs, integration helps to shift the time horizon beyond short-term interventions aimed at supporting peoples’ coping strategies and/or graduation objectives, toward longer-term interventions that can assist in promoting transformation towards climate and disaster resilient livelihood options.

Genotypic variation in photosynthetic and leaf traits in cocoa

The photosynthetic characteristics of eight contrasting cocoa genotypes were studied with the aim of examining genotypic variation in maximum (light-saturated) photosynthetic rates, light-response curve parameters and water use efficiency. Photosynthetic traits were derived from single leaf gas exchange measurements using a portable infra-red gas analyser. All measurements were conducted in a common greenhouse environment. Significant variation was observed in light-saturated photosynthesis ranging from 3.4 to 5.7 µmol CO2 m-2 s-1 for the clones IMC 47 and SCA 6, respectively. Furthermore, analyses of photosynthetic light response curves indicated genotypic differences in light saturation point and quantum efficiency (i.e. the efficiency of light use). Stomatal conductance was a significant factor underlying genotypic differences in assimilation. Genotypic variation was also observed in a number of leaf traits, including specific leaf area (the ratio of leaf area to leaf weight), chlorophyll concentration and nitrogen content. There was a positive correlation between leaf nitrogen per unit area and light-saturated photosynthesis. Water use efficiency, defined as the ratio of photosynthetic rate to transpiration rate, also varied significantly between clones (ranging from 3.1 mmol mol-1 H2O for the clone IMC 47 to 4.2 mmol mol-1 H2O for the clone ICS 1). Water use efficiency was a negative function of specific leaf area, suggesting that low specific leaf area might be a useful criterion for selection for increased water use efficiency. It is concluded that both variation in water use efficiency and the photosynthetic response to light have the potential to be exploited in breeding programmes.

EEG activation differences in the pre-motor cortex and supplementary motor area between normal individuals with high and low traits of autism

The human mirror neuron system (hMNS) is believed to provide a basic mechanism for social cognition. Event-related desynchronization (ERD) in alpha (8–12 Hz) and low beta band (12–20 Hz) over sensori-motor cortex has been suggested to index mirror neurons' activity. We tested whether autistic traits revealed by high and low scores on the Autistic Quotient (AQ) in the normal population are linked to variations in the electroencephalogram (EEG) over motor, pre-motor cortex and supplementary motor area (SMA) during action observation. Results revealed that in the low AQ group, the pre-motor cortex and SMA were more active during hand action than static hand observation whereas in the high AQ group the same areas were active both during static and hand action observation. In fact participants with high traits of autism showed greater low beta ERD while observing the static hand than those with low traits and this low beta ERD was not significantly different when they watched hand actions. Over primary motor cortex, the classical alpha and low beta ERD during hand actions relative to static hand observation was found across all participants. These findings suggest that the observation–execution matching system works differently according to the degree of autism traits in the normal population and that this is differentiated in terms of the EEG according to scalp site and bandwidth.

Reduced cortico-motor facilitation in a normal sample with high traits of autism

Recent research in social neuroscience proposes a link between mirror neuron system (MNS) and social cognition. The MNS has been proposed to be the neural mechanism underlying action recognition and intention understanding and more broadly social cognition. Pre-motor MNS has been suggested to modulate the motor cortex during action observation. This modulation results in an enhanced cortico-motor excitability reflected in increased motor evoked potentials (MEPs) at the muscle of interest during action observation. Anomalous MNS activity has been reported in the autistic population whose social skills are notably impaired. It is still an open question whether traits of autism in the normal population are linked to the MNS functioning. We measured TMS-induced MEPs in normal individuals with high and low traits of autism as measured by the autistic quotient (AQ), while observing videos of hand or mouth actions, static images of a hand or mouth or a blank screen. No differences were observed between the two while they observed a blank screen. However participants with low traits of autism showed significantly greater MEP amplitudes during observation of hand/mouth actions relative to static hand/mouth stimuli. In contrast, participants with high traits of autism did not show such a MEP amplitude difference between observation of actions and static stimuli. These results are discussed with reference to MNS functioning.

Adaptive evolution of four microcephaly genes and the evolution of brain size in anthropoid primates

The anatomical basis and adaptive function of the expansion in primate brain size have long been studied; however, we are only beginning to understand the genetic basis of these evolutionary changes. Genes linked to human primary microcephaly have received much attention as they have accelerated evolutionary rates along lineages leading to humans. However, these studies focus narrowly on apes, and the link between microcephaly gene evolution and brain evolution is disputed. We analyzed the molecular evolution of four genes associated with microcephaly (ASPM, CDK5RAP2, CENPJ, MCPH1) across 21 species representing all major clades of anthropoid primates. Contrary to prevailing assumptions, positive selection was not limited to or intensified along the lineage leading to humans. In fact we show that all four loci were subject to positive selection across the anthropoid primate phylogeny. We developed clearly defined hypotheses to explicitly test if selection on these loci was associated with the evolution of brain size. We found positive relationships between both CDK5RAP2 and ASPM and neonatal brain mass and somewhat weaker relationships between these genes and adult brain size. In contrast, there is no evidence linking CENPJ and MCPH1 to brain size evolution. The stronger association of ASPM and CDK5RAP2 evolution with neonatal brain size than with adult brain size is consistent with these loci having a direct effect on prenatal neuronal proliferation. These results suggest that primate brain size may have at least a partially conserved genetic basis. Our results contradict a previous study that linked adaptive evolution of ASPM to changes in relative cortex size; however, our analysis indicates that this conclusion is not robust. Our finding that the coding regions of two widely expressed loci has experienced pervasive positive selection in relation to a complex, quantitative developmental phenotype provides a notable counterexample to the commonly asserted hypothesis that cisregulatory regions play a dominant role in phenotypic evolution. Key words: ASPM, MCPH1, CDK5RAP2, CENPJ, brain, neurogenesis, primates.

Do variations in substitution rates and male mutation bias correlate with life-history traits? A study of 32 mammalian genomes

Life-history traits vary substantially across species, and have been demonstrated to affect substitution rates. We compute genomewide, branch-specific estimates of male mutation bias (the ratio of male-to-female mutation rates) across 32 mammalian genomes and study how these vary with life-history traits (generation time, metabolic rate, and sperm competition). We also investigate the influence of life-history traits on substitution rates at unconstrained sites across a wide phylogenetic range. We observe that increased generation time is the strongest predictor of variation in both substitution rates (for which it is a negative predictor) and male mutation bias (for which it is a positive predictor). Although less significant, we also observe that estimates of metabolic rate, reflecting replication-independent DNA damage and repair mechanisms, correlate negatively with autosomal substitution rates, and positively with male mutation bias. Finally, in contrast to expectations, we find no significant correlation between sperm competition and either autosomal substitution rates or male mutation bias. Our results support the important but frequently opposite effects of some, but not all, life history traits on substitution rates. KEY WORDS: Generation time, genome evolution, metabolic rate, sperm competition.

Abiotic drivers and plant traits explain landscape-scale patterns in soil microbial communities

The controls on aboveground community composition and diversity have been extensively studied, but our understanding of the drivers of belowground microbial communities is relatively lacking, despite their importance for ecosystem functioning. In this study, we fitted statistical models to explain landscape-scale variation in soil microbial community composition using data from 180 sites covering a broad range of grassland types, soil and climatic conditions in England. We found that variation in soil microbial communities was explained by abiotic factors like climate, pH and soil properties. Biotic factors, namely community- weighted means (CWM) of plant functional traits, also explained variation in soil microbial communities. In particular, more bacterial-dominated microbial communities were associated with exploitative plant traits versus fungal-dominated communities with resource-conservative traits, showing that plant functional traits and soil microbial communities are closely related at the landscape scale.

eRules: a modular adaptive classification rule learning algorithm for data streams

Advances in hardware and software in the past decade allow to capture, record and process fast data streams at a large scale. The research area of data stream mining has emerged as a consequence from these advances in order to cope with the real time analysis of potentially large and changing data streams. Examples of data streams include Google searches, credit card transactions, telemetric data and data of continuous chemical production processes. In some cases the data can be processed in batches by traditional data mining approaches. However, in some applications it is required to analyse the data in real time as soon as it is being captured. Such cases are for example if the data stream is infinite, fast changing, or simply too large in size to be stored. One of the most important data mining techniques on data streams is classification. This involves training the classifier on the data stream in real time and adapting it to concept drifts. Most data stream classifiers are based on decision trees. However, it is well known in the data mining community that there is no single optimal algorithm. An algorithm may work well on one or several datasets but badly on others. This paper introduces eRules, a new rule based adaptive classifier for data streams, based on an evolving set of Rules. eRules induces a set of rules that is constantly evaluated and adapted to changes in the data stream by adding new and removing old rules. It is different from the more popular decision tree based classifiers as it tends to leave data instances rather unclassified than forcing a classification that could be wrong. The ongoing development of eRules aims to improve its accuracy further through dynamic parameter setting which will also address the problem of changing feature domain values.

Adaptive noise cancellation with fast tunable RBF network

This paper describes a novel adaptive noise cancellation system with fast tunable radial basis function (RBF). The weight coefficients of the RBF network are adapted by the multi-innovation recursive least square (MRLS) algorithm. If the RBF network performs poorly despite of the weight adaptation, an insignificant node with little contribution to the overall performance is replaced with a new node without changing the model size. Otherwise, the RBF network structure remains unchanged and only the weight vector is adapted. The simulation results show that the proposed approach can well cancel the noise in both stationary and nonstationary ANC systems.