A comparative evaluation of low-cycle fatigue behavior of type 316LN base metal, 316 weld metal,and 316LN/316 weld joint

A comparative evaluation of the low-cycle fatigue (LCF) behavior of type 316LN base metal, 316 weld metal, and 316LN/316 weld joints was carried out at 773 and 873 K. Total strain-controlled LCF tests were conducted at a constant strain rate of 3 × 10⁻³ s⁻¹ with strain amplitudes in the range ±0.20 to ±1.0 pct. Weld pads with single V and double V configuration were prepared by the shielded metal-arc welding (SMAW) process using 316 electrodes for weld-metal and weld-joint specimens. Optical microscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) of the untested and tested samples were carried out to elucidate the deformation and the fracture behavior. The cyclic stress response of the base metal shows a very rapid hardening to a maximum stress followed by a saturated stress response. Weld metal undergoes a relatively short initial hardening followed by a gradual softening regime. Weld joints exhibit an initial hardening and a subsequent softening regime at all strain amplitudes, except at low strain amplitudes where a saturation regime is noticed. The initial hardening observed in base metal has been attributed to interaction between dislocations and solute atoms/complexes and cyclic saturation to saturation in the number density of slip bands. From TEM, the cyclic softening in weld metal was ascribed to the annihilation of dislocations during LCF. Type 316LN base metal exhibits better fatigue resistance than weld metal at 773 K, whereas the reverse holds true at 873 K. The weld joint shows the lowest life at both temperatures. The better fatigue resistance of weld metal is related to the brittle transformed delta ferrite structure and the high density of dislocations at the interface, which inhibits the growth rate of cracks by deflecting the crack path. The lower fatigue endurance of the weld joint was ascribed to the shortening of the crack initiation phase caused by surface intergranular crack initiation and to the poor crack propagation resistance of the coarse-grained region in the heat-affected zone.     

Predictive models for multibiometric systems

Recognizing a subject given a set of biometrics is a fundamental pattern recognition problem. This paper builds novel statistical models for multibiometric systems using geometric and multinomial distributions. These models are generic as they are only based on the similarity scores produced by a recognition system. They predict the bounds on the range of indices within which a test subject is likely to be present in a sorted set of similarity scores. These bounds are then used in the multibiometric recognition system to predict a smaller subset of subjects from the database as probable candidates for a given test subject. Experimental results show that the proposed models enhance the recognition rate beyond the underlying matching algorithms for multiple face views, fingerprints, palm prints, irises and their combinations.     

Structural variability and its relation to edaphic attributes of mangroves in the south‐west coast of India

We estimated the tree structural variables (density, frequency and basal area) of true mangroves and soil variables like particle size distribution, carbon, available nitrogen and phosphorus, sulphur, nutrient cations (K, Na, Ca, Mg) of Cochin mangroves and examined the relationship between vegetation and environment. The study sites were classified as seaward fringe, riverine and interior. Of the thirteen true mangrove species present, Avicennia officinalis, Sonneratia caseolaris and Excoecaria agallocha showed higher Importance Value Index. The mean stem density varied from 80 to 25,000 no./ha and basal area from 0.1 to 39.68 m²/ha. Seaward mangroves showed maximum stand basal area and biomass production while riverine exhibited maximum density. Maturity Index value of Cochin mangroves revealed a very low degree of structural maturity. Interior mangroves were characterized by silty soil with higher nutrient concentrations. Principal component analysis of soil data revealed that the major factors influencing mangrove vegetation were soil texture, nutrients, salinity and oxidation–reduction potential. The stem density and basal area of different species correlated highly with soil nutrients and texture (p < .001) while salinity showed negative correlations with vegetation characteristics. The data generated in the study would be fundamental in site‐specific management and conservation efforts of these degrading mangroves.     

锌再生利用及发展对策探讨

本文简述了我国锌工业生产、消费和再生锌工业发展的现状,指出了我国再生锌工业发展缓慢,技术装备水平低,企业生产规模小等问题。提出了建立规范化的管理制度,在政策上鼓励发展废锌材料的回收利用,加速我国废锌材料的回收利用程度。     

Subspace filtering approach based on orthogonal projection for better analysis of stressed speech under clean and noisy environments

This study explores a novel subspace projection-based approach for analysis of stressed speech. Studies have shown that stress influences the speech production system and it results in a large acoustic variation between the neutral and the stressed speech. This degrades the discrimination capability of an automatic speech recognition system trained on neutral speech when tested on stressed speech. An effort is made to reduce the acoustic mismatch by explicitly normalizing the stress-specific attributes. The stress-specific divergences are normalized by exploiting the subspace filtering technique. To accomplish this, an orthogonal projection based linear relationship between the speech and the stress information has been explored to filter an effective speech subspace, which consists of speech information. Speech subspace is constructed using K-means clustering followed by singular value decomposition method using neutral speech data. The speech and the stress information are separated by projecting the stressed speech orthogonally onto an effective speech subspace. Experimental results indicate that, the bases of an effective subspace comprises the first few eigenvectors corresponding to the highest eigenvalues. To further improve the system performance, both the neutral and the stressed speech are projected onto the lower dimensional subspace. The projections derived using the neutral speech employs heteroscedastic linear discriminant analysis in maximum likelihood linear transformations-based semi-tied adaptation framework. Consistent improvements are noted for the proposed technique in all the discussed cases.     

Policy-based Awareness Management (PAM): Case study of a wireless communication system at a hospital

The present paper evaluates the use of software agents to identify relevance of information, called awareness. This evaluation is based on existing policies and scenarios in the context of wireless communication of a hospital in Norway. The study is to address the lack of literature for experimental studies on a method to employ software agents for awareness identification. Research in computer supported cooperative work indicates the significant contributions of software agents to assist individuals. There are bodies of work that show awareness provides the means for software agents in which effective cooperation can take place. In addition, the role of the methods to identify awareness is emphasized in the literature of both computer supported cooperative work and software agents. This paper explains a step-wise process, called Policy-based Awareness Management, which allows agents to use policies as a source to identify awareness and thus change their behaviors accordingly. The contribution of this method is based on the concepts proposed by the logic of general awareness. The present study applies Directory Enabled Networks-next generation as the policy structure for the method. The paper evaluates the process via its application to identify the relevance of information in wireless communication scenarios in a hospital. The present study conducts observations, interviews and discussions on the wireless communication system of the hospital to identify the different scenarios happening in the system. The paper presents a set of simulations on these scenarios and concludes that the method is effective and cost-efficient.     

Adaptive target recognition

Target recognition is a multilevel process requiring a sequence of algorithms at low, intermediate and high levels. Generally, such systems are open loop with no feedback between levels and assuring their performance at the given probability of correct identification (PCI) and probability of false alarm (Pf) is a key challenge in computer vision and pattern recognition research. In this paper, a robust closed-loop system for recognition of SAR images based on reinforcement learning is presented. The parameters in model-based SAR target recognition are learned. The method meets performance specifications by using PCI and Pf as feedback for the learning system. It has been experimentally validated by learning the parameters of the recognition system for SAR imagery, successfully recognizing articulated targets, targets of different configuration and targets at different depression angles.     

Cholesterol is critical to the integrity of neuronal porosome/fusion pore

Secretion is one of the most fundamental cellular processes. Porosomes have been demonstrated as the universal secretory machinery in cells. Earlier studies determine the presence of a number of proteins in porosomes, among them the N- and P/Q-type calcium channels, actin, syntaxin-1, synaptotagmin-1, vimentin, the N-ethylmaleimide-sensitive factor (NSF), the chloride channel CLC-3, and the alpha subunit of the heterotrimeric GTP-binding protein G(o). Studies demonstrate that t-SNAREs localize at the base of porosomes, and directly interact with calcium channels. In the present study, we demonstrate that Syntaxin-1 co-localizes with cholesterol in solubilized synaptosomal membrane preparations. Depletion of cholesterol, results in the dissociation of both Syntaxin-1 and N-type calcium channel from neuronal porosomes. Thus, cholesterol participates as an integral component of the neuronal porosome complex, and is required for its stability.     

Maintaining awareness using policies; Enabling agents to identify relevance of information

The field of computer supported cooperative work aims at providing information technology models, methods, and tools that assist individuals to cooperate. The presented paper is based on three main observations from literature. First, one of the problems in utilizing information technology for cooperation is to identify the relevance of information, called awareness. Second, research in computer supported cooperative work proposes the use of agent technologies to aid individuals to maintain their awareness. Third, literature lacks the formalized methods on how software agents can identify awareness. This paper addresses the problem of awareness identification. The main contribution of this paper is to propose and evaluate a formalized structure, called Policy-based Awareness Management (PAM). PAM extends the logic of general awareness in order to identify relevance of information. PAM formalizes existing policies into Directory Enabled Networks-next generation structure and uses them as a source for awareness identification. The formalism is demonstrated by applying PAM to the space shuttle Columbia disaster occurred in 2003. The paper also argues that efficacy and cost-efficiency of the logic of general awareness will be increased by PAM. This is evaluated by simulation of hypothetical scenarios as well as a case study.     

Fingerprint indexing based on novel features of minutiae triplets

We are concerned with accurate and efficient indexing of fingerprint images. We present a model-based approach, which efficiently retrieves correct hypotheses using novel features of triangles formed by the triplets of minutiae as the basic representation unit. The triangle features that we use are its angles, handedness, type, direction, and maximum side. Geometric constraints based on other characteristics of minutiae are used to eliminate false correspondences. Experimental results on live-scan fingerprint images of varying quality and NIST special database 4 (NIST-4) show that our indexing approach efficiently narrows down the number of candidate hypotheses in the presence of translation, rotation, scale, shear, occlusion, and clutter. We also perform scientific experiments to compare the performance of our approach with another prominent indexing approach and show that the performance of our approach is better for both the live scan database and the ink based database NIST-4.