Flexible multibody approach in forward dynamic simulation of locomotive strains in human skeleton with flexible lower body bones

A method for bone strain estimation is examined in this article. The flexibility of a single bone in an otherwise rigid human skeleton model has been studied previously by various authors. However, in the previous studies, the effect of the flexibility of multiple bones on the musculoskeletal model behavior was ignored. This study describes a simulation method that can be used to estimate the bone strains at both tibias and femurs of a 65-year-old Caucasian male subject. The verification of the method is performed by the comparison of the results with other studies available in literature. The results of the study show good correlation with the results of previous empirical studies. A damping effect of the flexible bones on the model is also studied in this paper.     

Fixed points of the RSA encryption algorithm

In this paper the problem of the number of fixed points for an RSA algorithm is considered. This is an important question from the point of view of any cryptosystem. We have estimated the expected value of this number for randomly chosen RSA parameters. It turned out that it is O(ln²n), and the probability of finding such a point is O(ln²n/n). Thus, these values are really negligible, which had been intuitively expected.     

Makespan minimization of multi-slot just-in-time scheduling on single and parallel machines

The paper addresses the problem of multi-slot just-in-time scheduling. Unlike the existing literature on this subject, it studies a more general criterion—the minimization of the schedule makespan rather than the minimization of the number of slots used by schedule. It gives an O(nlog ² n)-time optimization algorithm for the single machine problem. For arbitrary number of m>1 identical parallel machines it presents an O(nlog n)-time optimization algorithm for the case when the processing time of each job does not exceed its due date. For the general case on m>1 machines, it proposes a polynomial time constant factor approximation algorithm.     

Is Evolution Algorithmic?

In Darwin’s Dangerous Idea, Daniel Dennett claims that evolution is algorithmic. On Dennett’s analysis, evolutionary processes are trivially algorithmic because he assumes that all natural processes are algorithmic. I will argue that there are more robust ways to understand algorithmic processes that make the claim that evolution is algorithmic empirical and not conceptual. While laws of nature can be seen as compression algorithms of information about the world, it does not follow logically that they are implemented as algorithms by physical processes. For that to be true, the processes have to be part of computational systems. The basic difference between mere simulation and real computing is having proper causal structure. I will show what kind of requirements this poses for natural evolutionary processes if they are to be computational.     

TSV constraints related to temperature excursion, pressure during molding, materials used and handling loads

The current paper focuses on several mechanical aspects of a waferlevel packaging approach using a direct face-to-face Chip-to-Wafer (C2W) bonding of a MEMS device on an ASIC substrate wafer. Requirements of minimized inherent stress from packaging and good decoupling from forces applied in manufacturing and application are discussed with particular attention to the presence of through-silicon vias (TSV) in the substrate wafer. The paper deals with FEM analysis of temperature excursion, pressure during molding, materials used and handling load influence on mechanical stress within the TSV system and on wafer level, which can be large enough to disintegrate the system.     

Time versus cost tradeoffs for deterministic rendezvous in networks

Two mobile agents, starting from different nodes of a network at possibly different times, have to meet at the same node. This problem is known as rendezvous. Agents move in synchronous rounds. Each agent has a distinct integer label from the set \(\{1,\ldots ,L\}\). Two main efficiency measures of rendezvous are its time (the number of rounds until the meeting) and its cost (the total number of edge traversals). We investigate tradeoffs between these two measures. A natural benchmark for both time and cost of rendezvous in a network is the number of edge traversals needed for visiting all nodes of the network, called the exploration time. Hence we express the time and cost of rendezvous as functions of an upper bound E on the time of exploration (where E and a corresponding exploration procedure are known to both agents) and of the size L of the label space. We present two natural rendezvous algorithms. Algorithm Cheap has cost O(E) (and, in fact, a version of this algorithm for the model where the agents start simultaneously has cost exactly E) and time O(EL). Algorithm Fast has both time and cost \(O(E\log L)\). Our main contributions are lower bounds showing that, perhaps surprisingly, these two algorithms capture the tradeoffs between time and cost of rendezvous almost tightly. We show that any deterministic rendezvous algorithm of cost asymptotically E (i.e., of cost \(E+o(E)\)) must have time \(\varOmega (EL)\). On the other hand, we show that any deterministic rendezvous algorithm with time complexity \(O(E\log L)\) must have cost \(\varOmega (E\log L)\).