Plasma power can make better powders

It may be a truism to say that round powders pack better, but spheroidisation of powder particles is one of the successful commercial applications of induction plasma technology and can play a key role in substantial improvement of powder quality and fluidity…     

Pancreaticoduodenectomy for selected periampullary neuroendocrine tumors: fifty patients

BACKGROUND: Most resectable pancreatic or peripancreatic neuroendocrine tumors are treated by enucleation or distal pancreatectomy. A minority of tumors may require pancreaticoduodenectomy for complete tumor excision because of their large size, location, or lymph node involvement. METHODS: This study reviews the management of 50 patients treated by pancreaticoduodenectomy for periampullary neuroendocrine tumors between 1962 and 1996 at a single institution. RESULTS: There were 30 men and 20 women with a mean age of 52 +/- 2 years. Functional tumors were resected in 17 patients: insulinoma, seven tumors; gastrinoma, eight tumors; vipoma, one tumor; and glucagonoma, one tumor. Tumors were classified as malignant in 29 patients and benign in 21. The median intraoperative blood loss was 800 ml, and the median number of units of blood transfused was zero. The postoperative length of stay was 20 +/- 2 days. Postoperative morbidity included 11 patients (24%) with a pancreatic fistula and four patients (8%) with a biliary fistula. There was one in-hospital death (2%), in 1967. The actuarial survival rates at 2, 5, and 7 years are 81%, 73%, and 65%, respectively. Patients with benign tumors had a significantly improved 5-year survival rate (94%) compared with those with malignant tumors (61%; p = 0.03). CONCLUSIONS: Selected patients with periampullary neuroendocrine tumors can be managed successfully by pancreaticoduodenectomy, with low mortality and acceptable morbidity rates.     

Arylidene polymers. XVIII. Synthesis and thermal behavior of organometallic arylidene polyesters containing ferrocene derivatives in the main chain

A new interesting category of organometallic polyesters based on diarylidenecycloalkanones containing ferrocene derivatives in the polymer main chain has been prepared by interfacial polycondensation of 1,1′-dichlorocarbonyl ferrocene or 1,1′-dichlorocarbonyl-4,4′-diiodoferrocene with 2,5-bis(p-hydroxybenzylidene)cyclopentanone, 2,5-divanillylidenecyclopentanone, 2,6-bis(p-hydroxybenzylidene)cyclohexanone, 2,6-divanillylidenecyclohexanone, and 2,7-bis(p-hydroxybenzylidene) cycloheptanone. The resulting polyesters were characterized by elemental analyses, infrared spectroscopy, solubility, and viscometry measurements. The thermal behavior of the synthesized polymers was evaluated by thermal gravimetric analysis and correlated with their structures. The crystallinity of all polymers were examined by x-ray diffraction analysis. Moreover, the electrical conductivity of a selected example of polymer was investigated above the temperature range (300–500 K) and showed that it followed an Arrhenius-type equation with activation energy 2.09 eV. © 1993 John Wiley & Sons, Inc.     

Fuzzy clustering with learnable cluster-dependent kernels

We propose a new relational clustering approach, called Fuzzy clustering with Learnable Cluster-dependent Kernels (FLeCK), that learns the underlying cluster-dependent dissimilarity measure while seeking compact clusters. The learned dissimilarity is based on a Gaussian kernel function with cluster-dependent parameters. Each cluster’s parameter learned by FLeCK reflects the relative intra-cluster and inter-cluster characteristics. These parameters are learned by optimizing both the intra-cluster and the inter-cluster distances. This optimization is achieved iteratively by dynamically updating the partition and the local kernel. This makes the kernel learning task takes advantages of the available unlabeled data and reciprocally, the categorization task takes advantages of the learned local kernels. Another key advantage of FLeCK is that it is formulated to work on relational data. This makes it applicable to data where objects cannot be represented by vectors or when clusters of similar objects cannot be represented efficiently by a single prototype. Using synthetic and real data sets, we show that FLeCK learns meaningful parameters and outperforms several other algorithms. In particular, we show that when data include clusters with various inter- and intra-cluster distances, learning cluster-dependent parameters is crucial in obtaining a good partition.     

A branch and bound algorithm for extracting smallest minimal unsatisfiable subformulas

Explaining the causes of infeasibility of Boolean formulas has practical applications in numerous fields, such as artificial intelligence (repairing inconsistent knowledge bases), formal verification (abstraction refinement and unbounded model checking), and electronic design (diagnosing and correcting infeasibility). Minimal unsatisfiable subformulas (MUSes) provide useful insights into the causes of infeasibility. An unsatisfiable formula often has many MUSes. Based on the application domain, however, MUSes with specific properties might be of interest. In this paper, we tackle the problem of finding a smallest-cardinality MUS (SMUS) of a given formula. An SMUS provides a succinct explanation of infeasibility and is valuable for applications that are heavily affected by the size of the explanation. We present (1) a baseline algorithm for finding an SMUS, founded on earlier work for finding all MUSes, and (2) a new branch-and-bound algorithm called Digger that computes a strong lower bound on the size of an SMUS and splits the problem into more tractable subformulas in a recursive search tree. Using two benchmark suites, we experimentally compare Digger to the baseline algorithm and to an existing incomplete genetic algorithm approach. Digger is shown to be faster in nearly all cases. It is also able to solve far more instances within a given runtime limit than either of the other approaches.     

A dynamic video watermarking algorithm in fast motion areas in the wavelet domain

In this paper, we propose a video watermarking algorithm which embeds different parts of a single watermark into different shots of a video under the wavelet domain. Based on a Motion Activity Analysis, different regions of the original video are separated into perceptually distinct categories according to motion information and region complexity. Thus, the localizations of the watermark are adjusted adaptively in accordance with the human visual system and signal characteristics, which makes them perceptually invisible and less vulnerable to automated removal. In addition, contrary to traditional methods where the watermark remains at a fixed position on the screen, the watermark moves along with moving objects and thus motion artefacts can be avoid. The multi-frame based extraction strategy ensures that the watermark can be correctly recovered from a very short segment of video. Individual frames extracted from the video also contain watermark information. Experimental results show that the inserted watermark is not only less perceptible but also robust against common video processing attacks.     

Palladium nanoclusters-coated polyfuran as a novel sensor for catecholamine neurotransmitters and paracetamol

A promising electrochemical biosensor was developed by electrodeposition of palladium nanoclusters on polyfuran film modified platinum electrode. This biosensor electrode was used to determine some catecholamines, namely dopamine, epinephrine and norepinephrine, ascorbic acid and paracetamol. The method of formation of the polymer film and deposition of Pd particles plays a key role in the electroactivity of the resulting hybrid material. This sensor effectively resolved the overlapping anodic peaks of ascorbic acid (AA), dopamine (DA) and paracetamol (ACOP) into three well-defined voltammetric peaks in differential pulse voltammetry analysis. The detection limit of DA in the absence and presence of AA and ACOP are eventually the same which indicates that the oxidation processes of DA, AA and ACOP are independent and that the simultaneous measurements of the three analytes are possible without interference. The electrodeposition of Pd on polyfuran improved exceptionally the detection limit about four decades. Moreover, diffusion coefficient measurements confirmed the fast electron transfer kinetics of the electrochemical oxidation of the analyte molecules at the sensor/solution interface. It is very interesting to note that the electrocatalytic effect of PF/Pd composite has been increased to be sometimes 21 times that of the pristine PF which has been considered for a long time to be of low conductivity and attracted low attention as a result of the difficulty of its formation and poor conductivity.     

The Other Mathematical Bridge

This paper contextualises, describes and discusses a student project which takes a particular exploratory approach to using mathematical surface definition as a language and vehicle for co-rational design co-authorship for architecture and engineering. The project has two authors, one from an architectural and one from an engineering educational background. It investigates the metaphorical and operational role of mathematics in the design process and outcomes.     

Wavelet approximation-based affine invariant shape representation functions

In this paper, new wavelet-based affine invariant functions for shape representation are presented. Unlike the previous representation functions, only the approximation coefficients are used to obtain the proposed functions. One of the derived functions is computed by applying a single wavelet transform; the other function is calculated by applying two different wavelet transforms with two different wavelet families. One drawback of the previously derived detail-based invariant representation functions is that they are sensitive to noise at the finer scale levels, which limits the number of scale levels that can be used. The experimental results in this paper demonstrate that the proposed functions are more stable and less sensitive to noise than the detail-based functions.     

Projecting CLPR constraints

The presentation of constraints in a usable form is an essential aspect of Constraint Logic Programming (CLP) systems. It is needed both in the output of constraints, as well as in the production of an internal representation of constraints for meta-level manipulation. Typically, only a small subset \(\tilde x\) of the variables in constraints is of interest, and so an informal statement of the problem at hand is: given a conjunction \(c(\tilde x,\tilde y)\) of constraints, express the projection \(\exists \tilde y c(\tilde x,\tilde y)\) ofc onto \(\tilde x\) in the simplest form. In this paper, we consider the constraints of the CLP(R) system and describe the essential features of its projection module. One main part focuses on the well-known problem of projection inlinear arithmetic constraints. We start with a classical algorithm and augment it with a procedure for eliminating redundant constraints generated by the algorithm. A second part discusses projection of the other object-level constraints: equations over trees and nonlinear equations. The final part deals with producing a manipulable form of the constraints, which complicates the projection problem.