FAULT DETECTION AND DIAGNOSIS METHODS FOR RESIDENTIAL AIR CONDITIONING SYSTEMS USING CLOUD-BASED DATA

Buildings account for nearly 40% of total energy consumption and nearly 75% of electrical energy consumption in the United States, and a significant portion of this energy consumption is due to the heating and cooling systems. Both commercial and residential heating, ventilation, and air conditioning (HVAC) systems are prone to faults that degrade performance and increase energy consumption. Furthermore, these systems are robust to faults in that they will operate with faults present for an extended period of time and will often continue to maintain a comfortable indoor environment. While considerable work has been devoted to developing fault detection and diagnosis (FDD) strategies for large and small commercial systems, relatively little has been done specifically for residential systems. This research presents novel FDD methods developed specifically for residential air conditioning systems. By using a novel set of virtual sensing methods, the proposed methodology eliminates the need for installing sensors on the outdoor unit. This is a significant advantage for residential ‘split’ air conditioning systems because installing sensors on both the indoor and outdoor units increases the complexity and cost of the data acquisition system. In addition to the proposed set of virtual sensors, this research provides solutions to two other problems that arise when implementing FDD methods on field-operating systems. (1) While most FDD methods use static models and rely on steady state analysis, field-operating systems often will not achieve steady state operation. This research provides a method for predicting the equilibrium operating point for many air conditioning parameters while the system is still in a transient response. This enables the equilibrium point to be determined before steady state operation has been achieved, and thus a static analysis may be performed without the system reaching steady state. (2) Existing change-point detection methods that could be used for detecting faults are impractical to implement on a large scale because they may require a priori knowledge, extensive tuning, or high computational loads. This research proposes a change-point detection algorithm for the purpose of fault detection which requires minimal assumptions, tuning, and computation. This change-point detection algorithm is suitable for deployment across many different systems simultaneously. In addition to the solutions outlined above for performing FDD using installed sensors, this research also proposes methods for performing fault detection and diagnose using only thermostat data. While a full strategy for thermostat data is not presented, crucial preprocessing methods that more complete methods will be built on are presented in detail. Nearly all of the data analyzed for each method described in this study uses event-based data uploaded in real-time to a cloud-based database and then queried and analyzed to perform FDD

The effectiveness of public health interventions to reduce the health impact of climate change:a systematic review of systematic reviews

Climate change is likely to be one of the most important threats to public health in the coming years. Yet despite the large number of papers considering the health impact of climate change, few have considered what public health interventions may be of most value in reducing the disease burden. We aimed to evaluate the effectiveness of public health interventions to reduce the disease burden of high priority climate sensitive diseases

Consistency and flexibility in solving spatial tasks: different horses show different cognitive styles

Individual animals vary in their behaviour and reactions to novel situations. These differences may extend to differences in cognition among individuals. We tested twenty-six horses for their ability to detour around symmetric and asymmetric obstacles. All of the animals were able to get around the barrier to reach a food target, but varied in their approach. Some horses moved slowly but were more accurate in choosing the shortest way. Other horses acted quickly, consistently detoured in the same direction, and did not reliably choose the shortest way. The remaining horses shifted from a faster, directionally consistent response with the symmetric barrier, to a slower but more accurate response with the asymmetric barrier. The asymmetric barrier induced a reduction in heart rate variability, suggesting that this is a more demanding task. The different approaches used to solve the asymmetric task may reflect distinct cognitive styles in horses, which vary among individuals, and could be linked to different personality traits. Understanding equine behaviour and cognition can inform horse welfare and management

Lateralized behaviour as indicator of affective state in dairy cows

In humans, there is evidence that sensory processing of novel or threatening stimuli is right hemisphere dominated, especially in people experiencing negative affective states. There is also evidence for similar lateralization in a number of non-human animal species. Here we investigate whether this is also the case in domestic cattle that may experience long-term negative states due to commonly occurring conditions such as lameness. Health and welfare implications associated with pain in lame cows are a major concern in dairy farming. Behavioural tests combining animal behaviour and cognition could make a meaningful contribution to our understanding of disease-related changes in sensory processing in animals, and consequently enhance their welfare. We presented 216 lactating Holstein-Friesian cows with three different unfamiliar objects which were placed either bilaterally (e.g. two yellow party balloons, two black/white checkerboards) or hung centrally (a Kong™) within a familiar area. Cows were individually exposed to the objects on three consecutive days, and their viewing preference/eye use, exploration behaviour/nostril use, and stop position during approach was assessed. Mobility (lameness) was repeatedly scored during the testing period. Overall, a bias to view the right rather than the left object was found at initial presentation of the bilateral objects. More cows also explored the right object rather than the left object with their nose. There was a trend for cows appearing hesitant in approaching the objects by stopping at a distance to them, to then explore the left object rather than the right. In contrast, cows that approached the objects directly had a greater tendency to contact the right object. No significant preference in right or left eye/nostril use was found when cows explored the centrally-located object. We found no relationship between lameness and lateralized behaviour. Nevertheless, observed trends suggesting that lateralized behaviour in response to bilaterally located unfamiliar objects may reflect an immediate affective response are discussed. Further study is needed to understand the impact of long-term affective states on hemispheric dominance and lateralized behaviour

Using Grizzly Bears to Assess Harvest-Ecosystem Tradeoffs in Salmon Fisheries

Using grizzly bears as surrogates for “salmon ecosystem” function, the authors develop a generalizable ecosystem-based management framework that enables decision-makers to quantify ecosystem-harvest tradeoffs between wild and human recipients of natural resources like fish

Multiple Geographic Origins of Commensalism and Complex Dispersal History of Black Rats

The Black Rat (Rattus rattus) spread out of Asia to become one of the world's worst agricultural and urban pests, and a reservoir or vector of numerous zoonotic diseases, including the devastating plague. Despite the global scale and inestimable cost of their impacts on both human livelihoods and natural ecosystems, little is known of the global genetic diversity of Black Rats, the timing and directions of their historical dispersals, and the risks associated with contemporary movements. We surveyed mitochondrial DNA of Black Rats collected across their global range as a first step towards obtaining an historical genetic perspective on this socioeconomically important group of rodents. We found a strong phylogeographic pattern with well-differentiated lineages of Black Rats native to South Asia, the Himalayan region, southern Indochina, and northern Indochina to East Asia, and a diversification that probably commenced in the early Middle Pleistocene. We also identified two other currently recognised species of Rattus as potential derivatives of a paraphyletic R. rattus. Three of the four phylogenetic lineage units within R. rattus show clear genetic signatures of major population expansion in prehistoric times, and the distribution of particular haplogroups mirrors archaeologically and historically documented patterns of human dispersal and trade. Commensalism clearly arose multiple times in R. rattus and in widely separated geographic regions, and this may account for apparent regionalism in their associated pathogens. Our findings represent an important step towards deeper understanding the complex and influential relationship that has developed between Black Rats and humans, and invite a thorough re-examination of host-pathogen associations among Black Rats

Global Spatial Risk Assessment of Sharks Under the Footprint of Fisheries

Effective ocean management and conservation of highly migratory species depends on resolving overlap between animal movements and distributions and fishing effort. Yet, this information is lacking at a global scale. Here we show, using a big-data approach combining satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively) and were also associated with significant increases in fishing effort. We conclude that pelagic sharks have limited spatial refuge from current levels of high-seas fishing effort. Results demonstrate an urgent need for conservation and management measures at high-seas shark hotspots and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real time, dynamic management

Mutational spectrum in a worldwide study of 29,700 families with BRCA1 or BRCA2 mutations.

The prevalence and spectrum of germline mutations in BRCA1 and BRCA2 have been reported in single populations, with the majority of reports focused on White in Europe and North America. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) has assembled data on 18,435 families with BRCA1 mutations and 11,351 families with BRCA2 mutations ascertained from 69 centers in 49 countries on six continents. This study comprehensively describes the characteristics of the 1,650 unique BRCA1 and 1,731 unique BRCA2 deleterious (disease-associated) mutations identified in the CIMBA database. We observed substantial variation in mutation type and frequency by geographical region and race/ethnicity. In addition to known founder mutations, mutations of relatively high frequency were identified in specific racial/ethnic or geographic groups that may reflect founder mutations and which could be used in targeted (panel) first pass genotyping for specific populations. Knowledge of the population-specific mutational spectrum in BRCA1 and BRCA2 could inform efficient strategies for genetic testing and may justify a more broad-based oncogenetic testing in some populations

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype