Identification and optimization of ammonia reactors through hybrid simulation

A hybrid simulation technique for identification and steady state optimization of a tubular reactor used in ammonia synthesis is presented. The parameter identification program finds the catalyst activity factor and certain heat transfer coefficients that minimize the sum of squares of deviation from simulated and actual temperature measurements obtained from an operating plant. The optimization program finds the values of three flows to the reactor to maximize the ammonia yield using the estimated parameter values. Powell's direct method of optimization is used in both cases. The results obtained here are compared with the plant data.

Carnatic music analysis: Shadja, swara identification and rAga verification in AlApana using stochastic models

We analyze the AlApana of a Carnatic music piece without the prior knowledge of the singer or the rAga. AlApana is ameans to communicate to the audience, the flavor or the bhAva of the rAga through the permitted notes and its phrases. The input to our analysis is a recording of the vocal AlApana along with the accompanying instrument. The AdhAra shadja(base note) of the singer for that AlApana is estimated through a stochastic model of note frequencies. Based on the shadja, we identify the notes (swaras) used in the AlApana using a semi-continuous GMM. Using the probabilities of each note interval, we recognize swaras of the AlApana. For sampurNa rAgas, we can identify the possible rAga, based on the swaras. We have been able to achieve correct shadja identification, which is crucial to all further steps, in 88.8% of 55 AlApanas. Among them (48 AlApanas of 7 rAgas), we get 91.5% correct swara identification and 62.13% correct R (rAga) accuracy.

Laser damage threshold studies on urea L-malic acid: A nonlinear optical crystal

A detailed study of surface laser damage performed on a nonlinear optical crystal, urea L-malic acid, using 7 ns laser pulses at 10 Hz repetition rate from a Q-switched Nd:YAG laser at wavelengths of 532 and 1064 nm is reported. The single shot and multiple shot surface laser damage threshold values are determined to be 26.64±0.19 and 20.60±0.36 GW cm−2 at 1064 nm and 18.44±0.31 and 7.52±0.22 GW cm−2 at 532 nm laser radiation, respectively. The laser damage anisotropy is consistent with the Vickers mechanical hardness measurement performed along three crystallographic directions. The Knoop polar plot also reflects the damage morphology. Our investigation reveals a direct correlation between the laser damage profile and hardness anisotropy. Thermal breakdown of the crystal is identified as the possible mechanism of laser induced surface damage.

Classification of road damage due to earthquakes

Earthquakes cause massive road damage which in turn causes adverse effects on the society. Previous studies have quantified the damage caused to residential and commercial buildings; however, not many studies have been conducted to quantify road damage caused by earthquakes. In this study, an attempt has been made to propose a new scale to classify and quantify the road damage due to earthquakes based on the data collected from major earthquakes in the past. The proposed classification for road damage due to earthquake is called as road damage scale (RDS). Earthquake details such as magnitude, distance of road damage from the epicenter, focal depth, and photographs of damaged roads have been collected from various sources with reported modified Mercalli intensity (MMI). The widely used MMI scale is found to be inadequate to clearly define the road damage. The proposed RDS is applied to various reported road damage and reclassified as per RDS. The correlation between RDS and earthquake parameters of magnitude, epicenter distance, hypocenter distance, and combination of magnitude with epicenter and hypocenter distance has been studied using available data. It is observed that the proposed RDS correlates well with the available earthquake data when compared with the MMI scale. Among several correlations, correlation between RDS and combination of magnitude and epicenter distance is appropriate. Summary of these correlations, their limitations, and the applicability of the proposed scale to forecast road damages and to carry out vulnerability analysis in urban areas is presented in the paper.

Molecular Identification and Phylogeny of Bactrocera Species (Diptera: Tephritidae)

Fruit flies that belong to the genus Bactrocera (Diptera: Tephritidae) are major invasive pests of agricultural crops in Asia and Australia. Increased transboundary movement of agricultural produce has resulted in the chance introduction of many invasive species that include Bactrocera mainly as immature stages. Therefore quick and accurate species diagnosis is important at the port of entry, where morphological identification has a limited role, as it requires the presence of adult specimens and the availability of a specialist. Unfortunately when only immature stages are present, a lacunae in their taxonomy impedes accurate species diagnosis. At this juncture, molecular species diagnostics based on COX-I have become handy, because diagnosis is not limited by developmental stages. Yet another method of quick and accurate species diagnosis for Bactrocera spp. is based on the development of species-specific markers. This study evaluated the utility of COX-I for the quick and accurate species diagnosis of eggs, larvae, pupae and adults of B. zonata Saunders, B. tau Walker, and B. dorsalis Hendel. Furthermore the utility of species-specific markers in differentiating B. zonata (500bp) and B. tau (220bp) was shown. Phylogenetic relationships among five subgenera, viz., Austrodacus, Bactrocera, Daculus, Notodacus and Zeugodacus have been resolved employing the 5' region of COX-I (1490-2198); where COX-I sequences for B. dorsalis Hendel, B. tau Walker, B. correcta Bezzi and B. zonata Saunders from India were compared with other NCBI-GenBank accessions. Phylogenetic analysis employing Maximum Parsimony (MP) and Bayesian phylogenetic approach (BP) showed that the subgenus Bactrocera is monophyletic.

Genetic Algorithm for Damage Assessment

Genetic Algorithms (GAs) are recognized as an alternative class of computational model, which mimic natural evolution to solve problems in a wide domain including machine learning, music generation, genetic synthesis etc. In the present study Genetic Algorithm has been employed to obtain damage assessment of composite structural elements. It is considered that a state of damage can be modeled as reduction in stiffness. The task is to determine the magnitude and location of damage. In a composite plate that is discretized into a set of finite elements, if a jth element is damaged, the GA based technique will predict the reduction in Ex and Ey and the location j. The fact that the natural frequency decreases with decrease in stiffness is made use of in the method. The natural frequency of any two modes of the damaged plates for the assumed damage parameters is facilitated by the use of Eigen sensitivity analysis. The Eigen value sensitivities are the derivatives of the Eigen values with respect to certain design parameters. If ωiu is the natural frequency of the ith mode of the undamaged plate and ωid is that of the damaged plate, with δωi as the difference between the two, while δωk is a similar difference in the kth mode, R is defined as the ratio of the two. For a random selection of Ex,Ey and j, a ratio Ri is obtained. A proper combination of Ex,Ey and j which makes Ri−R=0 is obtained by Genetic Algorithm.

Language identification using parallel sub-word recognition

Parallel sub-word recognition (PSWR) is a new model that has been proposed for language identification (LID) which does not need elaborate phonetic labeling of the speech data in a foreign language. The new approach performs a front-end tokenization in terms of sub-word units which are designed by automatic segmentation, segment clustering and segment HMM modeling. We develop PSWR based LID in a framework similar to the parallel phone recognition (PPR) approach in the literature. This includes a front-end tokenizer and a back-end language model, for each language to be identified. Considering various combinations of the statistical evaluation scores, it is found that PSWR can perform as well as PPR, even with broad acoustic sub-word tokenization, thus making it an efficient alternative to the PPR system.

Distinct Roles of FANCO/RAD51C Protein in DNA Damage Signaling and Repair Implications for Fanconi Anemia and Breast Cancer Susceptibility

RAD51C, a RAD51 paralog, has been implicated in homologous recombination (HR), and germ line mutations in RAD51C are known to cause Fanconi anemia (FA)-like disorder and breast and ovarian cancers. The role of RAD51C in the FA pathway of DNA interstrand cross-link (ICL) repair and as a tumor suppressor is obscure. Here, we report that RAD51C deficiency leads to ICL sensitivity, chromatid-type errors, and G(2)/M accumulation, which are hallmarks of the FA phenotype. We find that RAD51C is dispensable for ICL unhooking and FANCD2 monoubiquitination but is essential for HR, confirming the downstream role of RAD51C in ICL repair. Furthermore, we demonstrate that RAD51C plays a vital role in the HR-mediated repair of DNA lesions associated with replication. Finally, we show that RAD51C participates in ICL and double strand break-induced DNA damage signaling and controls intra-S-phase checkpoint through CHK2 activation. Our analyses with pathological mutants of RAD51C that were identified in FA and breast and ovarian cancers reveal that RAD51C regulates HR and DNA damage signaling distinctly. Together, these results unravel the critical role of RAD51C in the FA pathway of ICL repair and as a tumor suppressor.

Robust Approach for Identification of Bad Data in State Estimation Using SLP Technique

This paper proposes a new approach for solving the state estimation problem. The approach is aimed at producing a robust estimator that rejects bad data, even if they are associated with leverage-point measurements. This is achieved by solving a sequence of Linear Programming (LP) problems. Optimization is carried via a new algorithm which is a combination of “upper bound optimization technique" and “an improved algorithm for discrete linear approximation". In this formulation of the LP problem, in addition to the constraints corresponding to the measurement set, constraints corresponding to bounds of state variables are also involved, which enables the LP problem more efficient in rejecting bad data, even if they are associated with leverage-point measurements. Results of the proposed estimator on IEEE 39-bus system and a 24-bus EHV equivalent system of the southern Indian grid are presented for illustrative purpose.

Higher topoisomerase 2 alpha gene transcript levels predict better prognosis in GBM patients receiving temozolomide chemotherapy: identification of temozolomide as a TOP2A inhibitor

The search for molecular markers which predict response to chemotherapy is an important aspect of current neuro-oncology research. MGMT promoter methylation is the only proved marker of glioblastoma. The purpose of this study was to assess the effect of topoisomerase expression on glioblastoma survival and study the mechanisms involved. The transcript levels of all isoforms of the topoisomerase family in all grades of diffuse astrocytoma were assessed. A prospective study of patients with glioblastoma treated by a uniform treatment procedure was performed with the objective of correlating outcome with gene expression. The ability of TOP2A enzyme to relax the super coiled plasmid DNA in the presence of temozolomide was evaluated to assess its effect on TOP2A. The temozolomide cyctotoxicity of TOP2A-silenced U251 cells was assessed. The transcript levels of TOP2A, TOP2B, and TOP3A are upregulated significantly in GBM in comparison with lower grades of astrocytoma and normal brain samples. mRNA levels of TOP2A correlated significantly with survival of the patients. Higher TOP2A transcript levels in GBM patients predicted better prognosis (P = 0.043; HR = 0.889). Interestingly, we noted that temozolomide inhibited TOP2A activity in in-vitro enzyme assays. We also noted that siRNA knock down of TOP2A rendered a glioma cell line resistant to temozolomide chemotherapy. We demonstrated for the first time that temozolomide is also a TOP2A inhibitor and established that TOP2A transcript levels determine the chemosensitivity of glioblastoma to temozolomide therapy. Very high levels of TOP2A are a good prognostic indicator in GBM patients receiving temozolomide chemotherapy.