TESLA: an extended study of an energy-saving agent that leverages schedule flexibility

This paper presents transformative energy-saving schedule-leveraging agent (TESLA), an agent for optimizing energy usage in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. This paper provides four key contributions: (i) online scheduling algorithms, which are at the heart of TESLA, to solve a stochastic mixed integer linear program for energy-efficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; (iii) an extensive analysis on energy savings achieved by TESLA; and (iv) surveys of real users which indicate that TESLA’s assumptions of user flexibility hold in practice. TESLA was evaluated on data gathered from over 110,000 meetings held at nine campus buildings during an 8-month period in 2011–2012 at the University of Southern California and Singapore Management University. These results and analysis show that, compared to the current systems, TESLA can substantially reduce overall energy consumption.     

Study of B72.3 combining sites by molecular modeling and site-directed mutagenesis

A B72.3 Fab/sTn² complex was modeled from the known structureof B72.3 Fab and the dimeric Tn-serine cluster (sTn²). In thecomplex model, the side chains of 15 heavy- and light-chaincomplementarity-determining region (CDR) residues and the mainchains of two light-chain CDR residues contact the sTn² epitope.Among 15 CDR residues which contact sTn² in the model, two heavy-chainresidues (Ser95 and Tyr97) and light-chain CDR residue (Tyr96)have been confirmed in a previous study. To test the accuracyof the computational model, further site-directed mutagenesiswas performed by alanine scanning on the remaining 12 residuesthat are predicted in the model to have side-chain interactionswith sTn². Of these 12 mutants, eight that are all from theheavy-chain (His32Ala, Ala33Leu, Tyr50Ala, Ser52Ala, Asn52Ala,Asp56Ala, Lys58Ala and Tyr96Ala) had significantly reduced sTn²affinities, and four consisting of three light-chain mutations(Asn32Ala, Trp92Ala and Thr94Ala) and one heavy-chain mutation(His35Ala) retained wild-type sTn² affinity. On the whole, thisevidence suggests that the complex model, although not perfect,is correct in many of its features. In a more general vein,these results lend credibility to the computational modelingapproach for the study of the molecular basis of antigen–antibodycomplexes.     

Tris(acetylacetonato)rhodium(III)‐Catalyzed α‐Alkylation of Ketones, β‐Alkylation of Secondary Alcohols and Alkylation of Amines with Primary Alcohols

The tris(acetylacetonato)rhodium(III) catalyst is shown to be a versatile catalyst in the presence of DABCO (1,4‐diazabicyclo[2.2.2]octane) as ligand for the α‐alkylation of ketones followed by transfer hydrogenation, for the one‐pot β‐alkylation of secondary alcohols with primary alcohols and for the alkylation of aromatic amines in the presence of an inorganic base in toluene.     

Computational Markets to Regulate Mobile-Agent Systems

Mobile-agent systems allow applications to distribute their resource consumption across the network. By prioritizing applications and publishing the cost of actions, it is possible for applications to achieve faster performance than in an environment where resources are evenly shared. We enforce the costs of actions through markets, where user applications bid for computation from host machines.We represent applications as collections of mobile agents and introduce a distributed mechanism for allocating general computational priority to mobile agents. We derive a bidding strategy for an agent that plans expenditures given a budget, and a series of tasks to complete. We also show that a unique Nash equilibrium exists between the agents under our allocation policy. We present simulation results to show that the use of our resource-allocation mechanism and expenditure-planning algorithm results in shorter mean job completion times compared to traditional mobile-agent resource allocation. We also observe that our resource-allocation policy adapts favorably to allocate overloaded resources to higher priority agents, and that agents are able to effectively plan expenditures, even when faced with network delay and job-size estimation error.     

Effect of Density and Processing Conditions on Oxide Transformations and Mechanical Properties in Cr–Mo-Alloyed PM steels

To improve the mechanical properties and performances of water-atomized powder metallurgy steels, it is necessary to enhance the density. Consolidating water-atomized steel powders via conventional pressing and sintering to a relative density level > 95 pct involves processing challenges. Consolidation of gas-atomized powders to full density by hot isostatic pressing (HIP) is an established process route but utilizing water-atomized powders in HIP involves challenges that result in the formation of prior particle boundaries due to higher oxygen content. In this study, the effect of density and processing conditions on the oxide transformations and mechanical properties from conventional press and sintering, and HIP are evaluated. Hence, water-atomized Cr–Mo-alloyed powder is used and consolidated into different density levels between 6.8 and 7.3 g cm⁻³ by conventional die pressing and sintering. Fully dense material produced through HIP is evaluated not only of mechanical properties but also for microstructural and fractographic analysis. An empirical model based on power law is fitted to the sintered material properties to estimate and predict the properties up to full density at different sintering conditions. A model describing the mechanism of oxide transformation during sintering and HIP is proposed. The challenges when it comes to the HIP of water-atomized powder are addressed and the requirements for successful HIP processing are discussed.

     

An investigation on single machine total weighted tardiness scheduling problems

The urge to produce products in the production line at a faster rate with no compromise in quality has led to scheduling gaining greater importance in the modern day industries. Scheduling is concerned with the allocation of limited resources to tasks over time. The investigations on various scheduling problems have been of constant interest to researchers worldwide. This paper deals with an investigation on the total weighted tardiness of the single machine scheduling problems. The problems are solved by a heuristic procedure, namely backward forward heuristics. The different methods of formulating the problem instances are discussed. The benchmark problems and their best known values available in the OR library are used for the comparison to find out the influence of Relative Due Date (RDD) and Tardiness Factor (TF) used to generate the problem instances.     

In vitro expression and inhibition of procoagulant activity produced by bovine alveolar macrophages and peripheral blood cells

Local and systemic activation of coagulation is frequently associated with bacterial sepsis. The coagulopathy is due, at least in part, to expression of tissue factor (TF) by monocytes and macrophages. The purpose of this study was to evaluate the expression of procoagulant activity by bovine alveolar macrophages, leukocytes and platelets, and to determine the relative potency of three chemical inhibitors of TF expression (pentoxifylline, retinoic acid, and cyclosporin A). Bovine alveolar macrophages were stimulated with lipopolysaccharide (LPS) derived from Pasteurella haemolytica or recombinant bovine tumour nervous factor (TNF) and dose- and time-dependent effects on TF expression were studied. LPS and TNF induced TF expression in alveolar macrophages and LPS treatment of whole blood induced TF expression in mononuclear cells. Neutrophils and platelets also expressed procoagulant activity, but this activity was not inhibited by anti-bovine TF monoclonal antibody. Pentoxifylline (40 mumol/L), retinoic acid (0.01 mmol/L) and cyclosporin A (0.08 mumol/L) inhibited TF expression when added concurrently with LPS or TNF, but not when added 4 h after stimulation. TF mRNA was not detected in unstimulated alveolar macrophages by Northern blot analysis. In contrast, exposure to LPS or TNF for 6 h induced marked expression of TF mRNA, which was inhibited by treatment with pentoxifylline, retinoic acid and cyclosporin A. Expression of TNF by alveolar macrophages stimulated with LPS was also inhibited by these compounds. Our results indicate that procoagulant activity expressed by alveolar macrophages and monocytes is associated with expression of TF, whereas procoagulant activity expressed by neutrophils and platelets is not. The concentrations of pentoxifylline and retinoic acid necessary for inhibition of TF expression in vitro may not be achievable in vivo owing to their toxic effects. However, the in vitro concentration of cyclosporin A that inhibited TF expression did not exceed the plasma concentration observed in humans, and therefore may be useful for inhibition of TF expression in vivo.     

Privacy aware image template matching in clouds using ambient data

Cloud computing is ideal for image storage and processing because it provides enormously scalable storage and processing resources at low cost. One of the major drawbacks of cloud computing, however, is the lack of robust mechanisms for the users to control the privacy of the data they farm out to the clouds. In this paper, we develop an image encoding scheme that enhances the privacy of image data that is outsourced to the clouds for processing. Unlike previously proposed image encryption schemes, our encoding scheme allows different forms of pixel-level image processing to take place in the clouds while the actual image is not revealed to the cloud provider. Our encoding scheme uses a chaotic map to transform the image after it is masked with an arbitrarily chosen ambient image. We use template matching as a common image processing task to demonstrate the ability of our scheme to perform computations on privacy enhanced images. A simplified prototype of the image processing system was implemented and the experimental results are presented in this paper.     

A meta-heuristic approach to single machine scheduling problems

A new meta-heuristic evolutionary algorithm, named a memetic algorithm, for solving single machine total weighted tardiness scheduling problems is presented in this paper. Scheduling problems are proved to be NP-hard (Non-deterministic polynomial-time hard) types of problems and they are not easily or exactly solved for larger sizes. Therefore, application of the meta-heuristic technique to solve such NP hard problems is pursued by many researchers. The memetic algorithm is a marriage between population-based global searches with local improvement for each individual. The algorithm is tested with benchmark problems available in the OR (operations research) library. The results of the proposed algorithm are compared with the best available results and were found to be nearer to optimal. The memetic algorithm performs better than the heuristics like earliest due date and modified due date.