Using supertags as source language context in SMT

Recent research has shown that Phrase-Based Statistical Machine Translation (PB-SMT) systems can benefit from two enhancements: (i) using words and POS tags as context-informed features on the source side; and (ii) incorporating lexical syntactic descriptions in the form of supertags on the target side. In this work we present a novel PB-SMT model that combines these two aspects by using supertags as source language contextinformed features. These features enable us to exploit source similarity in addition to target similarity, as modelled by the language model. In our experiments two kinds of supertags are employed: those from Lexicalized Tree-Adjoining Grammar and Combinatory Categorial Grammar. We use a memory-based classification framework that enables the estimation of these features while avoiding problems of sparseness. Despite the differences between these two approaches, the supertaggers give similar improvements. We evaluate the performance of our approach on an English-to-Chinese translation task using a state-of-the-art phrase-based SMT system, and report an improvement of 7.88% BLEU score in translation quality when adding supertags as context-informed features

Productive efficiency of tea industry: A stochastic frontier approach

In an economy where recourses are scarce and opportunities for a new technology are lacking, studies will be able to show the possibility of raising productivity by improving the industry’s efficiency. This study attempts to measure the status of technical efficiency of tea-producing industry for panel data in Bangladesh using the stochastic frontier production function, incorporating technical inefficiency effect model. It was observed that Translog Production Function is more preferable than Cobb-Douglas Production Function. The study estimates that the average technical efficiency of tea producing industries in Bangladesh is 59%. Therefore, the results indicated that there is a great potential exists fortea industry to further increase the value added by 41% using the available input, technology and efficiency improvement, thereby reducing the cost of production. The study identifies that the mean efficiency of tea industries for value added vary among the regions and year-wise mean efficiency seems to be unstable during the study period and therefore, continued efforts to update technologies and equipment are required in pursuit of efficiency in tea industry

Causality in Non-Commutative Quantum Field Theories

We study causality in non-commutative quantum field theory with a space-space non-commutativity. We employ the S-operator approach of Bogoliubov-Shirkov(BS). We generalize the BS criterion of causality to the noncommutative theory. The criterion to test causality leads to a nonzero difference between T*-product and T-product as a condition of causality violation for a spacelike separation. We discuss two examples; one in a scalar theory and one in the Yukawa theory. In particular, in the context of a non-commutative Yukawa theory, with the interaction Lagrangian $\bar{\psi}(x)\star\psi(x)\star\phi(x)$, is observed to be causality violating even in case of space-space noncommutativity for which \theta^{0i}=0. \Comment: 18 pages, LaTeX; A few changes in sections 3.2,3.3 and

Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening.

OBJECTIVE: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity and mortality rates in CKD patients, particularly in less developed countries. Thus, early diagnosis aided by vital parameter analytics using affordable computer-aided diagnosis could not only reduce diagnosis costs but improve patient management and outcomes. METHODS: In this study, we developed machine learning models using selective key pathological categories to identify clinical test attributes that will aid in accurate early diagnosis of CKD. Such an approach will save time and costs for diagnostic screening. We have also evaluated the performance of several classifiers with k-fold cross-validation on optimized datasets derived using these selected clinical test attributes. RESULTS: Our results suggest that the optimized datasets with important attributes perform well in diagnosis of CKD using our proposed machine learning models. Furthermore, we evaluated clinical test attributes based on urine and blood tests along with clinical parameters that have low costs of acquisition. The predictive models with the optimized and pathologically categorized attributes set yielded high levels of CKD diagnosis accuracy with random forest (RF) classifier being the best performing. CONCLUSIONS: Our machine learning approach has yielded effective predictive analytics for CKD screening which can be developed as a resource to facilitate improved CKD screening for enhanced and timely treatment plans

A comparative study on different physicochemical properties of fresh and frozen lamb meat

This study described the comparison of different physicochemical parameters between fresh and frozen lamb meat. The pH measurement for fresh and frozen lamb meat did not show a significant difference. CIE L*a*b* (Commission Internationale de l'éclairage) color measurement technique was used and ∆E (distance between 2 colors) was found 5.32. On shrinkage measurement, there were significant differences (p<0.05) between the fresh and frozen meat. Frozen lamb sample showed 26.99% shrinkage compared to the fresh lamb which showed 18.09% shrinkage. The thawing loss did not show any significant difference. For texture analysis force and work were evaluated together for both fresh and frozen samples through Warner Bratzler texture analysis. The values did not show any significant difference. The absolute values of force and work were significantly different (p<0.05). Water binding capacity of the frozen and fresh sample were 56.57% and 59.27%, respectively. The moisture contents of fresh and frozen sample were 73.64% and 72.85%, respectively. Fat contents of fresh and frozen sample were 5.08% and 6.09% respectively. The study concludes that while comparing fresh and frozen lamb, only shrinkage and texture analysis showed significant difference whereas other physicochemical properties showed minor differences

Variability and traits association in maize (Zea mays L.) for yield and yield associated characters

Maize (Zea mays L.) is world’s third most important cereal crop that has a remarkable productive potential in Bangladesh. In Bangladesh, maize is the second most important cereal crop in terms of production. The selection for high yield with desirable traits depends on the genetic variability in the existing germplasm. Successful breeding programs need adequate genetic variation for selection and improvement based on necessity. The research was conducted in the experimental farm of the Department of Genetics and Plant Breeding, Bangladesh Agricultural University, Mymensingh during November 2015 to April 2016. The aim of this study was to evaluate the performance of 20 maize genotypes based on their yield and yield contributing characters to determine existing genetic variability. The extrapolated ANOVA for different yield contributing parameters showed a high degree of variation among the genotypes used. Correlation co-efficient analysis revealed that yield plant−1 (g) had positive and significant association with ear girth (cm), 1000-kernel weight (g), yield plot−1 (g), grain yield (tha−1) with dry weight. The genotypes differed significantly for most of the phenotypic traits. The phenotypic co-efficient of variation (PCV) was higher than genotypic co-efficient of variation (GCV) in all traits studied indicating that those traits were interacted with the environment. The traits under study expressed wide heritability estimates (26.81% to 99.95%). Among the characters, highest heritability was recorded for 1000-kernel weight (g). High heritability along with high genetic advance was noticed for 1000-kernel weight (g), yield plot−1 (g)and grain yield (tha−1). Considering different desirable traits P-12, Popcorn, V90-1, 988 were observed as superior genotypes. The data would be useful for proper identification and selection of appropriate parents in breeding programs to develop new maize varieties

Global constraint on the magnitude of anomalous chiral effects in heavy-ion collisions

When searching for anomalous chiral effects in heavy-ion collisions, one of the most crucial points is the relationship between the signal and the background. In this letter, we present a simulation in a modified blast wave model at LHC energy, which can simultaneously characterize the majority of measurable quantities, in particular, the chiral magnetic effect (CME) and the chiral magnetic wave (CMW) observables. Such a universal description, for the first time, naturally and quantitatively unifies the CME and the CMW studies and brings to light the connection with the local charge conservation (LCC) background. Moreover, a simple phenomenological approach is performed to introduce the signals, aiming at quantifying the maximum allowable strength of the signals within experimental precision. Such a constraint provides a novel perspective to understand the experimental data and sheds new light on the study of anomalous chiral effects as well as charge dependent correlations.Comment: 8 pages, 5 figure

The interaction of mammalian mitochondrial translational initiation factor 3 with ribosomes: evolution of terminal extensions in IF3mt

Mammalian mitochondrial initiation factor 3 (IF3mt) has a central region with homology to bacterial IF3. This homology region is preceded by an N-terminal extension and followed by a C-terminal extension. The role of these extensions on the binding of IF3mt to mitochondrial small ribosomal subunits (28S) was studied using derivatives in which the extensions had been deleted. The Kd for the binding of IF3mt to 28S subunits is ∼30 nM. Removal of either the N- or C-terminal extension has almost no effect on this value. IF3mt has very weak interactions with the large subunit of the mitochondrial ribosome (39S) (Kd = 1.5 μM). However, deletion of the extensions results in derivatives with significant affinity for 39S subunits (Kd = 0.12−0.25 μM). IF3mt does not bind 55S monosomes, while the deletion derivative binds slightly to these particles. IF3mt is very effective in dissociating 55S ribosomes. Removal of the N-terminal extension has little effect on this activity. However, removal of the C-terminal extension leads to a complex dissociation pattern due to the high affinity of this derivative for 39S subunits. These data suggest that the extensions have evolved to ensure the proper dissociation of IF3mt from the 28S subunits upon 39S subunit joining