Comparative evaluation of strain controlled low cycle fatigue behaviour of solution annealed and prior cold worked 316L(N) stainless steel

The effect of 20% prior cold work on low cycle fatigue (LCF) behaviour of type 316L(N) stainless steel (SS) was studied at 873 K by conducting total axial strain controlled tests in air with strain amplitudes in the range ±0.25% to ±1.0%. The cyclic deformation behaviour of 20% prior cold worked (PCW) material was compared with the LCF response of solution annealed (SA) alloy tested under similar conditions. The cyclic stress response (CSR) of 316L(N) SS in the PCW condition was characterized by a short period of hardening followed by prolonged softening prior to failure, whereas SA material exhibited a significant hardening regime followed by stress saturation. Interrupted tests on PCW material were carried out at different stages of CSR in order to determine the underlying mechanisms as reflected in substructural changes. The fatigue life in the solution annealed condition was similar to that of the PCW material at higher strain amplitudes of testing (≥±0.5%) while at lower strain amplitudes, the PCW material exhibited longer life.     

Impurities block the alpha to omega martensitic transformation in titanium

Impurities control phase stability and phase transformations in natural and man-made materials, from shape-memory alloys to steel to planetary cores. Experiments and empirical databases are still central to tuning the impurity effects. What is missing is a broad theoretical underpinning. Consider, for example, the titanium martensitic transformations: diffusionless structural transformations proceeding near the speed of sound. Pure titanium transforms from ductile alpha to brittle omega at 9 GPa, creating serious technological problems for beta-stabilized titanium alloys. Impurities in the titanium alloys A-70 and Ti-6Al-4V (wt%) suppress the transformation up to at least 35 GPa, increasing their technological utility as lightweight materials in aerospace applications. These and other empirical discoveries in technological materials call for broad theoretical understanding. Impurities pose two theoretical challenges: the effect on the relative phase stability, and the energy barrier of the transformation. Ab initio methods calculate both changes due to impurities. We show that interstitial oxygen, nitrogen and carbon retard the transformation whereas substitutional aluminium and vanadium influence the transformation by changing the d-electron concentration. The resulting microscopic picture explains the suppression of the transformation in commercial A-70 and Ti-6Al-4V alloys. In general, the effect of impurities on relative energies and energy barriers is central to understanding structural phase transformations.     

Term extraction from sparse,ungrammatical domain-specific documents

Existing term extraction systems have predominantly targeted large and well-written document collections, which provide reliable statistical and linguistic evidence to support term extraction. In this article, we address the term extraction challenges posed by sparse, ungrammatical texts with domain-specific contents, such as customer complaint emails and engineers’ repair notes. To this aim, we present ExtTerm, a novel term extraction system. Specifically, as our core innovations, we accurately detect rare (low frequency) terms, overcoming the issue of data sparsity. These rare terms may denote critical events, but they are often missed by extant TE systems. ExtTerm also precisely detects multi-word terms of arbitrarily lengths, e.g. with more than 2 words. This is achieved by exploiting fundamental theoretical notions underlying term formation, and by developing a technique to compute the collocation strength between any number of words. Thus, we address the limitation of existing TE systems, which are primarily designed to identify terms with 2 words. Furthermore, we show that open-domain (general) resources, such as Wikipedia, can be exploited to support domain-specific term extraction. Thus, they can be used to compensate for the unavailability of domain-specific knowledge resources. Our experimental evaluations reveal that ExtTerm outperforms a state-of-the-art baseline in extracting terms from a domain-specific, sparse and ungrammatical real-life text collection.     

Sensitivity analysis of nonlinear fractional order control systems with state delay

In this paper, we consider a class of nonlinear fractional order control system with delay in state variable. Existence and uniqueness of solution are shown by using method of steps. The sensitivity of the state and control with respect to the parameters of the system is shown. Finally, analytical results are substantiated by numerical examples.     

Is my model any good: differentially private regression diagnostics

Linear and logistic regression are popular statistical techniques for analyzing multi-variate data. Typically, analysts do not simply posit a particular form of the regression model, estimate its parameters, and use the results for inference or prediction. Instead, they first use a variety of diagnostic techniques to assess how well the model fits the relationships in the data and how well it can be expected to predict outcomes for out-of-sample records, revising the model as necessary to improve fit and predictive power. In this article, we develop \(\epsilon \)-differentially private diagnostics tools for regression, beginning to fill a gap in privacy-preserving data analysis. Specifically, we create differentially private versions of residual plots for linear regression and of receiver operating characteristic (ROC) curves as well as binned residual plot for logistic regression. The residual plot and binned residual plot help determine whether or not the data satisfy the assumptions underlying the regression model, and the ROC curve is used to assess the predictive power of the logistic regression model. These diagnostics improve the usefulness of algorithms for computing differentially private regression output, which alone does not allow analysts to assess the quality of the posited model. Our empirical studies show that these algorithms can be effective tools for allowing users to evaluate the quality of their models.     

Megalithic and Continuing Peninsular High-Tin Binary Bronzes: Possible Roots in Harappan Binary Bronze Usage?

This paper attempts to trace the development of an unusual and skilled class of alloys, of binary high-tin bronze (i.e. alloys of only copper with a higher percentage of tin), which are found from surprisingly early contexts from Indian antiquity. In particular, the deliberate use was made of binary beta bronze with around 22–24 % tin, specifically exploiting the properties of higher hot-forgability of bronze of this composition due to the formation of the high temperature beta intermetallic compound phase of 22.9 % tin. Quenching resulted in the retention of the beta phase, yielding a musical alloy with golden lustre and improved tensile strength as compared to the as-cast state. Examples of hot forged and quenched high-tin beta bronzes studied by the author from the South Indian Iron Age and megalithic cultures from Tamil Nadu and Maharashtra and Gandharan Grave Culture of Taxila are summarised here ranking amongst the earliest and most finely wrought such finds. There are technological and morphological similarities to surviving high-tin bronze crafts practices documented by the author in Kerala since 1990. Since the 1990’s she has also documented the making of high-tin delta bronze mirrors at Aranmula with a composition closer to the pure delta phase of 32.6 % tin, which instead exploited the specular properties this alloy while managing its brittleness. Although it is difficult to speculate about origins, a long standing practice of using binary tin–bronzes (i.e. only copper–tin alloys) can be detected going back to Harappan bronzes which also seem to be predominantly binary bronzes with not much lead added to them. Though most of these seem to be low-tin bronze, the presence of a couple with higher tin of about 20 % is also notable in terms of the above discussion.     

Understanding e‐Government portal use in rural India: role of demographic and personality characteristics

Electronic government (e‐Government) is one of the most important ways to bridge the digital divide in developing countries. We develop a model of e‐Government portal use. We use various individual characteristics, namely demographics and personality, as predictors of e‐Government portal use. Specifically, our predictors were (1) gender, age, income and education; (2) the Big Five personality characteristics, i.e. extraversion, neuroticism, conscientiousness, agreeableness and openness to experience; and (3) personal innovativeness with information technology. We conducted a field study in a village in India. We collected data from over 300 heads of household. We found support for our model, with most variables being significant and explaining 40% of the variance in e‐Government portal use.