Integrated solar energy and absorption cooling model for HVAC (heating, ventilating, and air conditioning) applications in buildings

The demands in production and associate costs at power generation through non renewable resources are increasing at an alarming rate. Solar energy is one of the renewable resource that has the potential to minimize this increase. Utilization of solar energy have been concentrated mainly on heating application. The use of solar energy in cooling systems in building would benefit greatly achieving the goal of non-renewable energy minimization. The approaches of solar energy heating system research done by initiation such as University of Wisconsin at Madison and building heat flow model research conducted by Oklahoma State University can be used to develop and optimize solar cooling building system. The research uses two approaches to develop a Graphical User Interface (GUI) software for an integrated solar absorption cooling building model, which is capable of simulating and optimizing the absorption cooling system using solar energy as the main energy source to drive the cycle. The software was then put through a number of litmus test to verify its integrity. The litmus test was conducted on various building cooling system data sets of similar applications around the world. The output obtained from the software developed were identical with established experimental results from the data sets used. Software developed by other research are catered for advanced users. The software developed by this research is not only reliable in its code integrity but also through its integrated approach which is catered for new entry users. Hence, this dissertation aims to correctly model a complete building with the absorption cooling system in appropriate climate as a cost effective alternative to conventional vapor compression system.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

Generalizability and Applicability of Model-Based Business Process Compliance-Checking Approaches – A State-of-the-Art Analysis and Research Roadmap

With a steady increase of regulatory requirements for business processes, automation support of compliance management is a field garnering increasing attention in Information Systems research. Several approaches have been developed to support compliance checking of process models. One major challenge for such approaches is their ability to handle different modeling techniques and compliance rules in order to enable widespread adoption and application. Applying a structured literature search strategy, we reflect and discuss compliance-checking approaches in order to provide an insight into their generalizability and evaluation. The results imply that current approaches mainly focus on special modeling techniques and/or a restricted set of types of compliance rules. Most approaches abstain from real-world evaluation which raises the question of their practical applicability. Referring to the search results, we propose a roadmap for further research in model-based business process compliance checking.

Complex visual hallucinations and attentional performance in eye disease and dementia: a test of the Perception and Attention Deficit model

OBJECTIVE This study aimed to test the prediction from the Perception and Attention Deficit model of complex visual hallucinations (CVH) that impairments in visual attention and perception are key risk factors for complex hallucinations in eye disease and dementia. METHODS Two studies ran concurrently to investigate the relationship between CVH and impairments in perception (picture naming using the Graded Naming Test) and attention (Stroop task plus a novel Imagery task). The studies were in two populations-older patients with dementia (n = 28) and older people with eye disease (n = 50) with a shared control group (n = 37). The same methodology was used in both studies, and the North East Visual Hallucinations Inventory was used to identify CVH. RESULTS A reliable relationship was found for older patients with dementia between impaired perceptual and attentional performance and CVH. A reliable relationship was not found in the population of people with eye disease. CONCLUSIONS The results add to previous research that object perception and attentional deficits are associated with CVH in dementia, but that risk factors for CVH in eye disease are inconsistent, suggesting that dynamic rather than static impairments in attentional processes may be key in this population.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

Relative contributions of Enterococcus faecalis OG1RF sortase-encoding genes, srtA and bps (srtC), to biofilm formation and a murine model of urinary tract infection.

Deletion mutants of the two sortase genes of Enterococcus faecalis OG1RF were constructed. srtC (renamed here bps for biofilm and pilus-associated sortase) was previously shown to be necessary for the production of Ebp pili and important for biofilm formation and endocarditis. Here, we report that a srtA deletion mutant showed a small (5%) yet significant (P = 0.037) reduction in biofilm relative to OG1RF, while a DeltasrtA Deltabps double mutant showed a much greater reduction (74% versus OG1RF and 44% versus the Deltabps mutant). In a murine urinary tract infection (UTI), the 50% infective doses of both the DeltasrtA Deltabps and Deltabps mutants were approximately 2 log10 greater than that of OG1RF or the DeltasrtA mutant. Similarly, approximately 2 log10 fewer bacteria were recovered from the kidneys after infection with the Deltabps mutant (P = 0.017) and the DeltasrtA Deltabps double mutant (P = 0.022) compared to wild-type strain OG1RF. In a competition UTI, the Deltabps mutant was slightly, but not significantly, less attenuated than the DeltasrtA Deltabps double mutant. Fluorescence-activated cell sorter analysis with Ebp-specific antibodies confirmed that a minority of OG1RF cells express Ebp pili on their surface in vitro and that Bps has a major role in Ebp pilus biogenesis but also indicated a function for SrtA in surface localization of the pilus subunit protein EbpA. In conclusion, deletion of bps had a major effect on virulence in murine UTIs, as well as biofilm; deletion of srtA from OG1RF had little effect on these phenotypes, but its deletion from a bps mutant had a pronounced effect on biofilm, suggesting that Bps and/or the proteins it anchors may compensate for the loss of some SrtA function(s).

Relative contributions of Enterococcus faecalis OG1RF sortase-encoding genes, srtA and bps (srtC), to biofilm formation and a murine model of urinary tract infection.

Deletion mutants of the two sortase genes of Enterococcus faecalis OG1RF were constructed. srtC (renamed here bps for biofilm and pilus-associated sortase) was previously shown to be necessary for the production of Ebp pili and important for biofilm formation and endocarditis. Here, we report that a srtA deletion mutant showed a small (5%) yet significant (P = 0.037) reduction in biofilm relative to OG1RF, while a DeltasrtA Deltabps double mutant showed a much greater reduction (74% versus OG1RF and 44% versus the Deltabps mutant). In a murine urinary tract infection (UTI), the 50% infective doses of both the DeltasrtA Deltabps and Deltabps mutants were approximately 2 log10 greater than that of OG1RF or the DeltasrtA mutant. Similarly, approximately 2 log10 fewer bacteria were recovered from the kidneys after infection with the Deltabps mutant (P = 0.017) and the DeltasrtA Deltabps double mutant (P = 0.022) compared to wild-type strain OG1RF. In a competition UTI, the Deltabps mutant was slightly, but not significantly, less attenuated than the DeltasrtA Deltabps double mutant. Fluorescence-activated cell sorter analysis with Ebp-specific antibodies confirmed that a minority of OG1RF cells express Ebp pili on their surface in vitro and that Bps has a major role in Ebp pilus biogenesis but also indicated a function for SrtA in surface localization of the pilus subunit protein EbpA. In conclusion, deletion of bps had a major effect on virulence in murine UTIs, as well as biofilm; deletion of srtA from OG1RF had little effect on these phenotypes, but its deletion from a bps mutant had a pronounced effect on biofilm, suggesting that Bps and/or the proteins it anchors may compensate for the loss of some SrtA function(s).

Sensitive Questions in Online Surveys: An Experimental Comparison of the RRT and the Crosswise Model

Self-administered online surveys provide a higher level of privacy protection to respondents than surveys administered by an interviewer. Yet, studies show that asking sensitive questions is problematic also in self-administered mode. Because respondents might not be willing to reveal the truth and provide answers that are subject to social desirability bias, the validity of prevalence estimates of sensitive behaviors gained via online surveys can be challenged. A wellknown method to combat these problems is the Randomized Response Technique (RRT). However, convincing evidence that the RRT provides more valid estimates than direct questioning in online mode is still lacking. Moreover, an alternative approach called the Crosswise Model (CM) has recently been suggested to overcome some of the deficiencies of the RRT. We therefore conducted an experimental study in which different implementations of the RRT and the CM have been tested and compared to direct questioning. Our study is a large-scale online survey on sensitive behaviors by students such as cheating in exams and paper plagiarism. The results of the study reveal poor per-formance of the RRT, while the CM yielded significantly higher estimates of sensitive behaviors than direct questioning. We conclude that the CM is a promising approach for asking sensitive questions in self-administered surveys.

Asking Sensitive Questions in Online Surveys: An Experimental Comparison of the Randomized Response Technique and the Crosswise Model

Self-administered online surveys provide a higher level of privacy protection to respondents than surveys administered by an interviewer. Yet, studies show that asking sensitive questions is problematic also in self-administered mode. Because respondents might not be willing to reveal the truth and provide answers that are subject to social desirability bias, the validity of prevalence estimates of sensitive behaviors gained via online surveys can be challenged. A well-known method to combat these problems is the Randomized Response Technique (RRT). However, convincing evidence that the RRT provides more valid estimates than direct questioning in online mode is still lacking. Moreover, an alternative approach called the Crosswise Model (CM) has recently been suggested to overcome some of the deficiencies of the RRT. In the context of an online survey on plagiarism and cheating on exams among students of two Swiss universities (N = 6,494), we tested different implementations of the RRT and the CM and compared them to direct questioning using a randomized experimental design. Results reveal a poor performance of the RRT, which failed to elicit higher prevalence estimates than direct questioning. Using the CM however, significantly higher prevalence estimates were obtained making it a promising new alternative to the conventional RRT.

Involvement of heparin-like glycosaminoglycans and expression of a novel heparan sulfate binding protein (p24) during human placentation and in a model for human implantation

Previous studies in our laboratory have indicated that heparan sulfate proteoglycans (HSPGs) play an important role in murine embryo implantation. To investigate the potential function of HSPGs in human implantation, two human cell lines (RL95 and JAR) were selected to model uterine epithelium and embryonal trophectoderm, respectively. A heterologous cell-cell adhesion assay showed that initial binding between JAR and RL95 cells is mediated by cell surface glycosaminoglycans (GAG) with heparin-like properties, i.e., heparan sulfate and dermatan sulfate. Furthermore, a single class of highly specific, protease-sensitive heparin/heparan sulfate binding sites exist on the surface of RL95 cells. Three heparin binding, tryptic peptide fragments were isolated from RL95 cell surfaces and their amino termini partially sequenced. Reverse transcription-polymerase chain reaction (RT-PCR) generated 1 to 4 PCR products per tryptic peptide. Northern blot analysis of RNA from RL95 cells using one of these RT-PCR products identified a 1.2 Kb mRNA species (p24). The amino acid sequence predicted from the cDNA sequence contains a putative heparin-binding domain. A synthetic peptide representing this putative heparin binding domain was used to generate a rabbit polyclonal antibody (anti-p24). Indirect immunofluorescence studies on RL95 and JAR cells as well as binding studies of anti-p24 to intact RL95 cells demonstrate that p24 is distributed on the cell surface. Western blots of RL95 membrane preparations identify a 24 kDa protein (p24) highly enriched in the 100,000 g pellet plasma membrane-enriched fraction. p24 eluted from membranes with 0.8 M NaCl, but not 0.6 M NaCl, suggesting that it is a peripheral membrane component. Solubilized p24 binds heparin by heparin affinity chromatography and $\sp{125}$I-heparin binding assays. Furthermore, indirect immunofluorescence studies indicate that cytotrophoblast of floating and attached villi of the human fetal-maternal interface are recognized by anti-p24. The study also indicates that the HSPG, perlecan, accumulates where chorionic villi are attached to uterine stroma and where p24-expressing cytotrophoblast penetrate the stroma. Collectively, these data indicate that p24 is a cell surface membrane-associated heparin/heparan sulfate binding protein found in cytotrophoblast, but not many other cell types of the fetal-maternal interface. Furthermore, p24 colocalizes with HSPGs in regions of cytotrophoblast invasion. These observations are consistent with a role for HSPGs and HSPG binding proteins in human trophoblast-uterine cell interactions. ^