ASU Scholarship Showcase

The termites evolved eusociality and complex societies before the ants, but have been studied much less. The recent publication of the first two termite genomes provides a unique comparative opportunity, particularly because the sequenced termites represent opposite ends of the social complexity spectrum. Zootermopsis nevadensis has simple colonies with totipotent workers that can develop into all castes (dispersing reproductives, nest-inheriting replacement reproductives, and soldiers). In contrast, the fungus-growing termite Macrotermes natalensis belongs to the higher termites and has very large and complex societies with morphologically distinct castes that are life-time sterile. Here we compare key characteristics of genomic architecture, focusing on genes involved in communication, immune defenses, mating biology and symbiosis that were likely important in termite social evolution. We discuss these in relation to what is known about these genes in the ants and outline hypothesis for further testing.

The estimation of energy demand (by power plants) has traditionally relied on historical energy use data for the region(s) that a plant produces for. Regression analysis, artificial neural network and Bayesian theory are the most common approaches for analysing these data. Such data and techniques do not generate reliable results. Consequently, excess energy has to be generated to prevent blackout; causes for energy surge are not easily determined; and potential energy use reduction from energy efficiency solutions is usually not translated into actual energy use reduction. The paper highlights the weaknesses of traditional techniques, and lays out a framework to improve the prediction of energy demand by combining energy use models of equipment, physical systems and buildings, with the proposed data mining algorithms for reverse engineering. The research team first analyses data samples from large complex energy data, and then, presents a set of computationally efficient data mining algorithms for reverse engineering. In order to develop a structural system model for reverse engineering, two focus groups are developed that has direct relation with cause and effect variables. The research findings of this paper includes testing out different sets of reverse engineering algorithms, understand their output patterns and modify algorithms to elevate accuracy of the outputs.

Small and medium office buildings consume a significant parcel of the U.S. building stock energy consumption. Still, owners lack resources and experience to conduct detailed energy audits and retrofit analysis. We present an eight-steps framework for an energy retrofit assessment in small and medium office buildings. Through a bottom-up approach and a web-based retrofit toolkit tested on a case study in Arizona, this methodology was able to save about 50% of the total energy consumed by the case study building, depending on the adopted measures and invested capital. While the case study presented is a deep energy retrofit, the proposed framework is effective in guiding the decision-making process that precedes any energy retrofit, deep or light.

Commercial buildings’ consumption is driven by multiple factors that include occupancy, system and equipment efficiency, thermal heat transfer, equipment plug loads, maintenance and operational procedures, and outdoor and indoor temperatures. A modern building energy system can be viewed as a complex dynamical system that is interconnected and influenced by external and internal factors. Modern large scale sensor measures some physical signals to monitor real-time system behaviors. Such data has the potentials to detect anomalies, identify consumption patterns, and analyze peak loads. The paper proposes a novel method to detect hidden anomalies in commercial building energy consumption system. The framework is based on Hilbert-Huang transform and instantaneous frequency analysis. The objectives are to develop an automated data pre-processing system that can detect anomalies and provide solutions with real-time consumption database using Ensemble Empirical Mode Decomposition (EEMD) method. The finding of this paper will also include the comparisons of Empirical mode decomposition and Ensemble empirical mode decomposition of three important type of institutional buildings.

There are many data mining and machine learning techniques to manage large sets of complex energy supply and demand data for building, organization and city. As the amount of data continues to grow, new data analysis methods are needed to address the increasing complexity. Using data from the energy loss between the supply (energy production sources) and demand (buildings and cities consumption), this paper proposes a Semi-Supervised Energy Model (SSEM) to analyse different loss factors for a building cluster. This is done by deep machine learning by training machines to semi-supervise the learning, understanding and manage the process of energy losses. Semi-Supervised Energy Model (SSEM) aims at understanding the demand-supply characteristics of a building cluster and utilizes the confident unlabelled data (loss factors) using deep machine learning techniques. The research findings involves sample data from one of the university campuses and presents the output, which provides an estimate of losses that can be reduced. The paper also provides a list of loss factors that contributes to the total losses and suggests a threshold value for each loss factor, which is determined through real time experiments. The conclusion of this paper provides a proposed energy model that can provide accurate numbers on energy demand, which in turn helps the suppliers to adopt such a model to optimize their supply strategies.

Background: Mutual policing is an important mechanism for reducing conflict in cooperative groups. In societies of ants, bees, and wasps, mutual policing of worker reproduction can evolve when workers are more closely related to the queen's sons than to the sons of workers or when the costs of worker reproduction lower the inclusive fitness of workers. During colony growth, relatedness within the colony remains the same, but the costs of worker reproduction may change. The costs of worker reproduction are predicted to be greatest in incipient colonies. If the costs associated with worker reproduction outweigh the individual direct benefits to workers, policing mechanisms as found in larger colonies may be absent in incipient colonies.

Results: We investigated policing behavior across colony growth in the ant 'Camponotus floridanus.' In large colonies of this species, worker reproduction is policed by the destruction of worker-laid eggs. We found workers from incipient colonies do not exhibit policing behavior, and instead tolerate all conspecific eggs. The change in policing behavior is consistent with changes in egg surface hydrocarbons, which provide the informational basis for policing; eggs laid by queens from incipient colonies lack the characteristic hydrocarbons on the surface of eggs laid by queens from large colonies, making them chemically indistinguishable from worker-laid eggs. We also tested the response to fertility information in the context of queen tolerance. Workers from incipient colonies attacked foreign queens from large colonies; whereas workers from large colonies tolerated such queens. Workers from both incipient and large colonies attacked foreign queens from incipient colonies.

Conclusions: Our results provide novel insights into the regulation of worker reproduction in social insects at both the proximate and ultimate levels. At the proximate level, our results show that mechanisms of social regulation, such as the response to fertility signals, change dramatically over a colony's life cycle. At the ultimate level, our results emphasize the importance of factors besides relatedness in predicting the level of conflict within a colony. Our results also suggest policing may not be an important regulatory force at every stage of colony development. Changes relating to the life cycle of the colony are sufficient to account for major differences in social regulation in an insect colony. Mechanisms of conflict mediation observed in one phase of a social group's development cannot be generalized to all stages.

The Quadrangles Av-11 and Av-12 on Vesta are located at the northern rim of the giant Rheasilvia south polar impact basin. The primary geologic units in Av-11 and Av-12 include material from the Rheasilvia impact basin formation, smooth material and different types of impact crater structures (such as bimodal craters, dark and bright crater ray material and dark ejecta material). Av-11 and Av-12 exhibit almost the full range of mass wasting features observed on Vesta, such as slump blocks, spur-and-gully morphologies and landslides within craters. Processes of collapse, slope instability and seismically triggered events force material to slump down crater walls or scarps and produce landslides or rotational slump blocks. The spur-and-gully morphology that is known to form on Mars is also observed on Vesta; however, on Vesta this morphology formed under dry conditions.

A variety of geologic landforms and features are observed within quadrangle Av-13 Tuccia in the southern hemisphere of Vesta. The quadrangle covers parts of the highland Vestalia Terra as well as the floors of the large Rheasilvia and Veneneia impact basins, which results in a substantial elevation difference of more than 40 km between the northern and the southern portions of the quadrangle. Measurements of crater size–frequency distributions within and surrounding the Rheasilvia basin indicate that gravity-driven mass wasting in the interior of the basin has been important, and that the basin has a more ancient formation age than would be expected from the crater density on the basin floor alone. Subsequent to its formation, Rheasilvia was superimposed by several mid-sized impact craters. The most prominent craters are Tuccia, Eusebia, Vibidia, Galeria, and Antonia, whose geology and formation ages are investigated in detail in this work. These impact structures provide a variety of morphologies indicating different sorts of subsequent impact-related or gravity-driven mass wasting processes. Understanding the geologic history of the relatively young craters in the Rheasilvia basin is important in order to understand the even more degraded craters in other regions of Vesta.

In this paper we present a time-stratigraphic scheme and geologic time scale for the protoplanet Vesta, based on global geologic mapping and other analyses of NASA Dawn spacecraft data, complemented by insights gained from laboratory studies of howardite–eucrite–diogenite (HED) meteorites and geophysical modeling. On the basis of prominent impact structures and their associated deposits, we propose a time scale for Vesta that consists of four geologic time periods: Pre-Veneneian, Veneneian, Rheasilvian, and Marcian. The Pre-Veneneian Period covers the time from the formation of Vesta up to the Veneneia impact event, from 4.6 Ga to >2.1 Ga (using the asteroid flux-derived chronology system) or from 4.6 Ga to 3.7 Ga (under the lunar-derived chronology system). The Veneneian Period covers the time span between the Veneneia and Rheasilvia impact events, from >2.1 to 1 Ga (asteroid flux-derived chronology) or from 3.7 to 3.5 Ga (lunar-derived chronology), respectively. The Rheasilvian Period covers the time span between the Rheasilvia and Marcia impact events, and the Marcian Period covers the time between the Marcia impact event until the present. The age of the Marcia impact is still uncertain, but our current best estimates from crater counts of the ejecta blanket suggest an age between ∼120 and 390 Ma, depending upon choice of chronology system used. Regardless, the Marcia impact represents the youngest major geologic event on Vesta. Our proposed four-period geologic time scale for Vesta is, to a first order, comparable to those developed for other airless terrestrial bodies.

We report on a preliminary global geologic map of Vesta, based on data from the Dawn spacecraft’s High-Altitude Mapping Orbit (HAMO) and informed by Low-Altitude Mapping Orbit (LAMO) data. This map is part of an iterative mapping effort; the geologic map has been refined with each improvement in resolution. Vesta has a heavily-cratered surface, with large craters evident in numerous locations. The south pole is dominated by an impact structure identified before Dawn’s arrival. Two large impact structures have been resolved: the younger, larger Rheasilvia structure, and the older, more degraded Veneneia structure. The surface is also characterized by a system of deep, globe-girdling equatorial troughs and ridges, as well as an older system of troughs and ridges to the north. Troughs and ridges are also evident cutting across, and spiraling arcuately from, the Rheasilvia central mound.

However, no volcanic features have been unequivocally identified. Vesta can be divided very broadly into three terrains: heavily-cratered terrain; ridge-and-trough terrain (equatorial and northern); and terrain associated with the Rheasilvia crater. Localized features include bright and dark material and ejecta (some defined specifically by color); lobate deposits; and mass-wasting materials. No obvious volcanic features are evident. Stratigraphy of Vesta’s geologic units suggests a history in which formation of a primary crust was followed by the formation of impact craters, including Veneneia and the associated Saturnalia Fossae unit. Formation of Rheasilvia followed, along with associated structural deformation that shaped the Divalia Fossae ridge-and-trough unit at the equator. Subsequent impacts and mass wasting events subdued impact craters, rims and portions of ridge-and-trough sets, and formed slumps and landslides, especially within crater floors and along crater rims and scarps. Subsequent to the formation of Rheasilvia, discontinuous low-albedo deposits formed or were emplaced; these lie stratigraphically above the equatorial ridges that likely were formed by Rheasilvia. The last features to be formed were craters with bright rays and other surface mantling deposits.

Executed progressively throughout data acquisition, the iterative mapping process provided the team with geologic proto-units in a timely manner. However, interpretation of the resulting map was hampered by the necessity to provide the team with a standard nomenclature and symbology early in the process. With regard to mapping and interpreting units, the mapping process was hindered by the lack of calibrated mineralogic information. Topography and shadow played an important role in discriminating features and terrains, especially in the early stages of data acquisition.