Scheduling on Unrelated Machines under Tree-Like Precedence Constraints

We present polylogarithmic approximations for the R|prec|C _max and R|prec|∑ _j w _j C _j problems, when the precedence constraints are “treelike”—i.e., when the undirected graph underlying the precedences is a forest. These are the first non-trivial generalizations of the job shop scheduling problem to scheduling with precedence constraints that are not just chains. These are also the first non-trivial results for the weighted completion time objective on unrelated machines with precedence constraints of any kind. We obtain improved bounds for the weighted completion time and flow time for the case of chains with restricted assignment—this generalizes the job shop problem to these objective functions. We use the same lower bound of “congestion + dilation”, as in other job shop scheduling approaches (e.g. Shmoys, Stein and Wein, SIAM J. Comput. 23, 617–632, 1994). The first step in our algorithm for the R|prec|C _max problem with treelike precedences involves using the algorithm of Lenstra, Shmoys and Tardos to obtain a processor assignment with the congestion + dilation value within a constant factor of the optimal. We then show how to generalize the random-delays technique of Leighton, Maggs and Rao to the case of trees. For the special case of chains, we show a dependent rounding technique which leads to a bicriteria approximation algorithm for minimizing the flow time, a notoriously hard objective function. A preliminary version of this paper appeared in the Proc. International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX), pages 146–157, 2005. V.S. Anil Kumar supported in part by NSF Award CNS-0626964. Part of this work was done while at the Los Alamos National Laboratory, and supported in part by the Department of Energy under Contract W-7405-ENG-36. M.V. Marathe supported in part by NSF Award CNS-0626964. Part of this work was done while at the Los Alamos National Laboratory, and supported in part by the Department of Energy under Contract W-7405-ENG-36. Part of this work by S. Parthasarathy was done while at the Department of Computer Science, University of Maryland, College Park, MD 20742, and in part while visiting the Los Alamos National Laboratory. Research supported in part by NSF Award CCR-0208005 and NSF ITR Award CNS-0426683. Research of A. Srinivasan supported in part by NSF Award CCR-0208005, NSF ITR Award CNS-0426683, and NSF Award CNS-0626636.     

Formation of corn fiber gum-milk protein conjugates and their molecular characterization

Corn fiber arabinoxylan is hemicellulose B isolated from the fibrous portions (pericarp, tip cap, and endosperm cell wall fractions) of corn kernels and is commonly referred to as corn fiber gum (CFG). Our previous studies showed that CFG isolated from corn bran (a byproduct of corn dry milling) contains very little protein and is an inferior emulsifier for oil-in-water emulsion systems as compared to corn fiber gum isolated from corn fiber derived from the corn wet-milling process. The protein deficient CFG isolated from corn bran was covalently conjugated with byproducts of cheese processing, β-lactoglobulin (β-LG) and whey protein isolate (WPI) using an economical food-grade Maillard-type heating reaction for the purpose of increasing their commercialization potential as a food emulsifier and soluble nutritional additive in beverages. The formation of the CFG-protein conjugates has been confirmed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). It has also been demonstrated that CFG-protein conjugates are capable of producing fine emulsions with better stability than either CFG or protein alone. The molecular characterization of CFG-protein conjugates was performed by high-performance size-exclusion chromatography (HPSEC) coupled to on-line multi-angle laser light scattering and viscometric detection. The analysis by HPSEC revealed that CFG-protein conjugates had higher weight-average molar mass (M_w, 340-359 kDa) and polydispersity (M_w/M_n, 1.74) than the corresponding unconjugated CFG (M_w, 290 kDa and M_w/M_n, 1.35). The z-average root-mean-square radius of gyration (R_gz) of CFG-protein conjugates was slightly higher (30.5-33.5 nm) in comparison to CFG (29.5 nm) but their weight-average-intrinsic viscosity (η) remained unchanged (about 1.32 dL g⁻¹). The Mark-Houwink exponent “a” of conjugates (0.40) was lower than the unconjugated CFG (0.53) indicating the formation of a more compact structure after conjugation with protein. These findings should benefit the beverage industry, which can use this information to produce a high quality emulsifier from the low-value byproducts of corn dry milling and cheese processing.     

Reinforced Stone Columns in Weak Deposits: Laboratory Model Study

This paper investigates the performance of stone columns in a weak deposit such as peat. It evaluates the effects of reinforcing stone columns by jacketing with a tubular wire mesh and bridging reinforcement with a metal rod and a concrete plug. A series of plate loading tests was conducted on isolated stone columns installed in a soil bed consisting of a peat layer sandwiched between two layers of sand. The load–displacement characteristics of footings supported by stone columns were investigated by applying load to a circular plate supported on: (a) untreated soil; (b) soil treated with stone columns; and (c) soil treated with stone columns reinforced with the above reinforcing techniques. The work has shown that the settlement characteristics of the soil can be improved by installing stone columns and that a significant enhancement in the load–settlement response is achieved when the columns are reinforced by the various methods.     

Effect of electrolyte pH on the structure andin vitro osteoblasts response to anodic titanium oxide

This study examines the surface morphology, microstructure, and chemical composition of titanium surfaces treated by anodic spark oxidation in phosphate buffer solution at pH 2, 7 and 12. The pH of the electrolyte was found to play a substantial role in the formation of different morphologies, chemical compositions, and pore dimensions with microporous structures. SEM revealed variation in the topologies of the anodized surface with electrolyte pH. Porous structures with uniform pores and high roughness were obtained in pH 12 solutions. However, intense anatase crystal was obtained at pH 7. The relationship between surface characteristics of titanium and initial interactions of titanium-osteoblasts was also in vestigated. Our findings demonstrated the cell viability and proliferation on the anodic oxides produced at pH 12 to be superior to those produced at pH 2 and 7 as well as on the control titanium surface. This study also provides evidence of enhanced osteoblast adhesion on anodized metal substrates under in vitro conditions.     

Polyol process for the synthesis of LiFePO4 rhombohedral particles

As a new approach, LiFePO₄ nanoparticles were directly synthesized from precursors iron(III) nitrate and lithium dihydrogen phosphate by a polyol process without post heat treatment in one step. The obtained powders were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and combined thermogravimetry and differential scanning calorimetry and mass spectroscopy TG/DSC/MS. The X-ray diffraction showed the orthorhombic crystal structure of LiFePO₄ without any impurity phases. The synthesized LiFePO₄ has rhombohedral morphology with high aspect ratio with a thickness of less than 100 nm. TG/DSC/MS revealed a weight loss of only 10.9 wt.% when heating up to 1000 °C. Electrodes prepared from the LiFePO₄ particles were electrochemically characterized by cycling at 0.1C current rate and temperatures in half cell measurements against lithium foil between 2 and 4.2 V in an EC/DMC electrolyte with 1 M LiPF₆ as conductive salt. A reversible specific capacity of 146 mAh/g was achieved by applying carbon coating on the rhombohedral particles.     

On the role of mass transport in high rate dissolution of iron and nickel in ECM electrolytes—I. Chloride solutions

High rate anodic dissolution of iron and nickel in 5 M NaCl was studied in a flow channel cell under controlled hydrodynamic conditions. Galvanostatic experiments were aimed at investigating the influence of current density and electrolyte flow rate on anode potential, current efficiency for metal dissolution and surface texture resulting from dissolution. Active dissolution at low current densities leads to surface etching and transpassive dissolution at high current densities leads to surface brightening. Transition from active to transpassive dissolution is mass transport controlled and is accompanied by a change in anode potential, surface microtexture and in case of iron by a change in the valence of metal dissolution.     

Parametric Probabilistic Routing in Sensor Networks

Motivated by realistic sensor network scenarios that have mis-in-formed nodes and variable network topologies, we propose an approach to routing that combines the best features of limited-flooding and information-sensitive path-finding protocols into a reliable, low-power method that can make delivery guarantees independent of parameter values or information noise levels. We introduce Parametric Probabilistic Sensor Network Routing Protocols, a family of light-weight and robust multi-path routing protocols for sensor networks in which an intermediate sensor decides to forward a message with a probability that depends on various parameters, such as the distance of the sensor to the destination, the distance of the source sensor to the destination, or the number of hops a packet has already traveled. We propose two protocol variants of this family and compare the new methods to other probabilistic and deterministic protocols, namely constant-probability gossiping, uncontrolled flooding, random wandering, shortest path routing (and a variation), and a load-spreading shortest-path protocol inspired by (Servetto and Barrenechea, 2002). We consider sensor networks where a sensor’s knowledge of the local or global information is uncertain (parametrically noised) due to sensor mobility, and investigate the trade-off between robustness of the protocol as measured by quality of service (in particular, successful delivery rate and delivery lag) and use of resources (total network load). Our results for networks with randomly placed nodes and realistic urban networks with varying density show that the multi-path protocols are less sensitive to misinformation, and suggest that in the presence of noisy data, a limited flooding strategy will actually perform better and use fewer resources than an attempted single-path routing strategy, with the Parametric Probabilistic Sensor Network Routing Protocols outperforming other protocols. Our results also suggest that protocols using network information perform better than protocols that do not, even in the presence of strong noise. Christopher L. Barrett is leader of the Basic and Applied Simulation Science Group of the Computing and Computational Sciences Division at Los Alamos National Laboratory. His Group is a simulation science and technology (S&T) invention organization of 30 scientists devoted to providing large-scale, high performance methods for systems analysis and simulation-based assisted reasoning. His Group engages in fundamental mathematical, algorithmic, and complex systems analysis research. Current applied research is focused on interdependent simulation and analysis tools for complex, socio-technical systems like transportation, communications, public health and other critical infrastructure areas. His scientific experience is in simulation, scientific computation, algorithm theory and development, system science and control, engineering science, bio-systems analysis, decision science, cognitive human factors, testing and training. His applied science and engineering achievements include, for example, development of large-scale, high performance simulation systems (e.g., Transportation Analysis Simulation System, TRANSIMS) and development of a distributed computing approach for detailed simulation-based study of mobile, packet switched digital communications systems (Self Organizing Stochastic Rebroadcast Relay, SORSRER). He has a M.S. and Ph.D. in Bio-information Systems from California Institute of Technology. He is a decorated Navy veteran having served in both the submarine service and as a pilot. He has been awarded three Distinguished Service Awards from Los Alamos National Laboratory, one from the Alliance for Transportation Research, one from the Royal Institute of Technology, Stockholm, and one from Artificial Life and Robotics, Oita University, Japan. Stephan J. Eidenbenz is a technical staff member in the Basic and Applied Simulation Science group (CCS-5) at Los Alamos National Laboratory (LANL). He received an M.Sc. in Computer Science from the Swiss Federal Institute of Technology (ETH) in Zurich in 1997 and a Ph.D. in Computer Science from ETH in 2000; he also obtained a Bachelor’s degree in business administration from GSBA in Zurich in 1999. Stephan has worked for McKinsey & Co. in Switzerland, where he received training in business administration and microeconomics. He has held a postdoctoral position at ETH and he has been a postdoctoral fellow at LANL. Stephan’s more than 30 publications cover a wide range of subjects such as approximability and inapproximability properties of visibility problems in polygons and terrains, error modeling in sequencing problems for computation biology, and designing communication protocols robust against selfish behavior. His current research interests include selfish networking, algorithmic game theory, network modeling and simulation, network design, and network optimization. Lukas Kroc is a student of M.Sc. program in Computer Science at Charles University in Prague. In 2003, he was a Graduate Research Assistant at the Basic and Applied Simulation Science group (CCS-5) at Los Alamos National Laboratory. His research interests include simulation, wireless networking and artificial intelligence. Madhav V. Marathe is a Team Leader for Mathematics and Computer Science in the Basic and Applied Simulation Science group, Computer and Computational Sciences (CCS-5) at the Los Alamos National Laboratory. He obtained his B.Tech in 1989 in Computer Science and Engg. from IIT Madras, India and his Ph.D. in 1994 in Computer Science, from University at Albany. His team focuses on developing mathematical and computational tools for design and analysis of large scale simulations of socio-technical and critical infrastructure systems. His research interests are in modeling and simulations of large socio-technical systems, design and analysis of algorithms, computational complexity theory, theory of parallel, distributed and mobile computing and communication systems. He has published over 100 research articles in peer reviewed journals and conferences. He is an adjunct faculty in the Computer Science Department at the University of New Mexico. James P. Smith is a technical staff member in the Basic and Applied Simulation Science Group of the Computing and Computational Sciences Division at Los Alamos National Laboratory. His principal interest is in high performance computing applied to modeling, simulation and analysis of socio-technical systems. His current research applies to national infrastructure, especially telecommunication/computing, public health, and transportation. He has scientific experience in high performance computing and parallel processing applied to large-scale microscopic simulations, including original software design and debugging of very large, evolving systems of inter-operable computational systems, and efficient analysis and synthesis of massive data produced by multi-scale complex environments. Before attending graduate school he worked for a short time in nuclear theory, and had several publications in experimental biophysics from the Pennsylvania Muscle Institute and Bockus Research Institute. During graduate school he took a one year hiatus to start a company to work in analytic finance, and then spent time doing theoretical space physics at LANL. His graduate work eventually included theoretical and experimental fusion research, but concentrated on computational space plasma physics. He has publications in biophysics, analytic finance, education, space plasma physics and computer science, and is a co-inventor on the TRANSIMS patent. He has a Ph.D. in Theoretical Plasma Physics from the University of Texas at Austin.This revised version was published online in August 2005 with a corrected cover date.