A Multi-Objective Optimization Approach for Multi-Head Beam-Type Placement Machines

This paper addresses a highly challenging scheduling problem in the field of printed circuit board (PCB) assembly systems using Surface Mounting Devices (SMD). After describing some challenging optimization sub-problems relating to the heads of multi-head surface mounting placement machines, we formulate an integrated multi-objective mathematical model considering of two main sub-problems simultaneously. The proposed model is a mixed integer nonlinear programming one which is very complex to be solved optimally. Therefore, it is first converted into a linearized model and then solved using an efficient multi-objective approach, i.e., the augmented epsilon constraint method. An illustrative example is also provided to show the usefulness and applicability of the proposed model and solution method.PCB assembly. Multi-head beam-type placement machine. Multi-objective mathematical programming. Augmented epsilon-constraint method

Tuning of antigen sensitivity by T cell receptor-dependent negative feedback controls T cell effector function inflammed tissues

Activated T cells must mediate effector responses sufficient to clear pathogens while avoiding excessive tissue damage. Here we have combined dynamic intravital microscopy with ex vivo assessments of T cell cytokine responses to generate a detailed spatiotemporal picture of CD4+ T cell effector regulation in the skin. In response to antigen, effector T cells arrested transiently on antigen presenting cells, briefly producing cytokine and then resuming migration. Antigen recognition led to PD-1 upregulation of the programmed death-1 (PD-1) glycoprotein by T cells and blocking its canonical ligand, programmed death-ligand 1 (PD-L1), lengthened the duration of migration arrest and cytokine production, showing that PD-1 interaction with PD-L1 is a major negative feedback regulator of antigen responsiveness. We speculate that the immune system employs a mechanism involving T cell recruitment, transient activation, and rapid desensitization, allowing the T cell response to rapidly adjust to changes in antigen presentation and minimize collateral injury to the host

How to Apply Service Operations Management Principles to Improve Student Engagement and Satisfaction

Students complain that technical courses like operations management are boring, dry or unenthralling. If we characterize classroom learning between a student and an instructor as a knowledge-intensive service encounter, then students are a kind of “customer” who must interact with the classroom system and play a key role in their own learning. Without engagement and a modicum of satisfaction, student learning plummets. But where to start and how? How might we apply our non-classroom subject matter expertise to the classroom? To overcome students’ negative opinions of the learning process in an operations management course, we applied tried and true principles from service operations management (SOM) to design a better service experience that is more engaging and interesting (without capitulating to the customer being right). Our study involves three phases across two different modalities. We identified and tested key components from SOM that might impact student learning (e.g., customer contact theory, the gap model of service quality, and the psychology of waiting) and linked these components to important suggestions for increasing engagement in the classroom. We then tested how applying the SOM framework improved student satisfaction as measured by assessment of learning and student evaluations. We discovered that applying service design principles to the learning process provides a systematic way to improve student engagement and satisfaction without sacrificing rigor

A framework for automatically checking anonymity with μ CRL

We present a powerful and flexible method for automatically checking anonymity in a possibilistic general-purpose process algebraic verification toolset. We propose new definitions of a choice anonymity degree and a player anonymity degree, to quantify the precision with which an intruder is able to single out the true originator of a given event or to associate the right event to a given protocol participant. We show how these measures of anonymity can be automatically calculated from a protocol specification in µCRL, by using a combination of dedicated tools and existing state-of-the-art µCRL tools. To illustrate the flexibility of our method we test the Dining Cryptographers problem and the FOO 92 voting protocol. Our definitions of anonymity provide an accurate picture of the different ways that anonymity can break down, due for instance to coallitions of inside intruders. Our calculations can be performed on a cluster of machines, allowing us to check protocols for large numbers of participants

Investigating the Effect of Mechanical Activation Parameters on Structural Changes and Leaching Rate of Molybdenite Concentrate

AbstractIn this research, mechanical activation (MA) was employed for leaching rate improvement of molybdenite concentrate in nitric acid media. These experiments were performed in two groups: with and without aluminum oxide (alumina). A full factorial design was used for each group of experiments. Leaching rate increment up to 5 times was observed only in 2hours activation procedure. XRD analysis demonstrated structural disordering in activated MoS2. TEM images showed that particle size has been reduced to nanoscale. The initial powder size was 80% between 2-44μm and dropped to about 10nm and 140nm in MA experiments with and without alumina, respectively. This size reduction would be the main reason of leaching rate enhancement which is more achievable in MA in presence of alumina. The results demonstrate that alumina has a motivating effect in activation procedure to achieve a nanostructure molybdenite. Analysis of variance revealed milling speed is the main parameter in MA without alumina, while, ball to powder ratio is the most important factor in MA procedure in presence of alumina on leaching rate

Herding model and 1/f noise

We provide evidence that for some values of the parameters a simple agent based model, describing herding behavior, yields signals with 1/f power spectral density. We derive a non-linear stochastic differential equation for the ratio of number of agents and show, that it has the form proposed earlier for modeling of 1/f^beta noise with different exponents beta. The non-linear terms in the transition probabilities, quantifying the herding behavior, are crucial to the appearance of 1/f noise. Thus, the herding dynamics can be seen as a microscopic explanation of the proposed non-linear stochastic differential equations generating signals with 1/f^beta spectrum. We also consider the possible feedback of macroscopic state on microscopic transition probabilities strengthening the non-linearity of equations and providing more opportunities in the modeling of processes exhibiting power-law statistics