Mechanism of titanium sponge formation in the kroll reduction reactor

The Kroll process of magnesium reduction of titanium tetrachloride is used the world over the production of titanium metal in the form of sponge. Although the process has been in practice for the last five decades, there is no clear understanding of the reaction mechanism and sponge formation. The present study involved reduction experiments in a 2000 kg titanium sponge-capacity prototype reactor to develop a better understanding of TiCl₄ reduction of magnesium with respect to the process parameters. Experiments were also conducted in two smaller experimental reactors to study the temperature evolution during the process as a function of the TiCl₄ feed rate. Based on the results of all these experiments, a model has been proposed for the mechanism of sponge formation in the Kroll process.     

Controller design and performance evaluation for deadlock avoidance in automated flexible manufacturing cells

In this paper, the design of a deadlock avoidance controller is described. The uncontrolled system is modeled using colored Petri nets. The system controller is based on a restrictive (not maximally permissive) deadlock avoidance policy to resolve deadlocks and control the real-time resource allocation decisions in the system. Performance evaluation of systems controlled by not maximally permissive algorithms is essential in determining the applicability and effectiveness of the control algorithms. The performance of the controlled system is compared with performance of optimal control policies to quantify the effects of the restrictiveness of the deadlock avoidance policy on system performance.     

Design space exploration for real-time embedded stream processors

We explore tradeoffs between organization and number of ALUs and clock frequency in a stream processor. The tool provides candidate low-power configurations and estimates of their real-time performance. The tool relates instruction-level, subword, and data parallelism to functional units' organization and utilization. The exploration methodology is applicable to all embedded-processor designs in signal and media processing.     

Multiple metastatic infections in a hemodialysis patient with untunneled internal jugular catheter

We present an end‐stage renal disease patient on dialysis with fever. The primary source was right internal jugular vein catheter which had metastatic infections in the body probably via an arteriovenous communication in a cavity in left lung. Patient had right psoas muscle abscess and a left kidney abscess. An ¹⁸F‐fluorodeoxyglucose‐positron emission spectroscopy scan was done to find out left kidney abscess. A search of literature did not reveal many patients of psoas abscess secondary to infection of hemodialysis access.     

Strategic effort allocation in online innovation tournaments

Online innovation tournaments, such as those hosted by crowdsourcing platforms (e.g., Kaggle), have been widely adopted by firms to evolve creative solutions to various problems. Solvers compete in these tournaments to earn rewards. In such competitive environments, it is imperative that solvers provide creative solutions with minimum effort. This article explores the factors that influence the solvers’ effort allocation decisions in a dynamic tournament setting. Specifically, comprehensive time variant data of teams that participated in crowdsourcing competitions on Kaggle were analyzed to gain insight into how solvers continually formulate strategies in light of performance feedback obtained through interim ranking. The results suggest that solvers strategically allocate their efforts throughout the contest to dynamically optimize their payoffs through balancing the probability of winning and the cost of expending effort. In particular, solvers tend to increase their efforts toward the end of tournaments or when they get closer to winning positions. Furthermore, our findings indicate that a last-minute surge in effort is more prevalent among high-skill solvers than in those with lower skill levels. In addition to providing insights that may help solvers develop strategies to improve their performance, the study has implications for the design of online crowdsourcing platforms, particularly in terms of incentivizing solvers to put forth their best effort.     

Optimizing microstructure for toughness: the model problem of peeling

We consider the problem of peeling an adhesive thin film from a substrate that has a non-uniform distribution of adhesive. When the length scale of the non-uniformity is small compared to the overall dimensions of the film being peeled, it is possible to describe the overall peeling behavior with an effective adhesive strength. In this paper, we seek to find the distributions of adhesive strength at the microscale that optimize various aspects of the effective adhesive strength at the macroscale. We do so using both analytic bounds and topology optimization. We formulate the problem of peeling as a free boundary problem, and the effective strength as a maximum principle over the trajectory. For topology optimization, we replace the maximum with an integral norm, and use an adjoint method for the sensitivity. The problem of peeling may be viewed as a model problem in fracture mechanics where the crack (peel) front is confined to a plane, and thus our analysis as a first step toward studying the more general problem of optimizing microstructure for toughness.     

Feature Selection for Recognition of Online Handwritten Bangla Characters

Feature selection through optimization techniques provides an interesting approach to minimize computational time with enhanced prediction capability, and     

Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis

To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.