Post-WMAP Assessment of Infrared Cutoff in the Primordial Spectrum from Inflation

The recent Cosmic Microwave Background (CMB) measurements indicate that there is power deficiency of the CMB anisotropies at large scales compared with the $\Lambda$CDM model. We have investigated the possibility of explaining such effects by a class of primordial power spectra which have infrared cutoffs close to the horizon scale. The primordial power spectrum recovered by direct deconvolution of the observed CMB angular spectrum indicates that the data prefers a sharp infrared cutoff with a localized excess (bump) just above the cutoff. We have been motivated to assess plausible extensions of simplest inflationary scenarios which readily accommodate similar form of infrared cutoff. We carry out a complete Bayesian analysis of the parameter space using {\it Markov Chain Monte Carlo} technique with such a class of primordial power spectra. We show that primordial power spectrum that have features such as an infrared cutoff followed by a subsequent excess in power give better fit to the observed data compared to a nearly scale-invariant power law or power spectrum with just a monotonic infrared cutoff. However, there is substantial room for improvement in the match to data and calls for exploration of other mechanisms that may lead to infrared cutoff even closer to that recovered by direct deconvolution approach.Comment: Changes to match version accepted for publication in PR

Hexokinase, Malate Dehydrogenase, Fluorescent Esterase and Malic Enzyme Polymorphisms in the Cocoa Pod Borer, Conopomorpha cramerella (Snellen)

Cocoa pod borers collected in the field from Tawau, Sabah and from Sua Betong, Negeri Sembilan and rambutan fruit borers collected from Puchong and the campus of Universiti Pertanian Malaysia (UPM) in Serdang, Selangor, Malaysia were analysed by polyacrylamide gel electrophoresis. Hexokinase was found to be polymorphic in the UPM population, malate dehydrogenase in the Tawau, Sua Betong and UPM populations and fluorescent esterase and malic enzyme were polymorphic in all four populations

An Electrophoretic Study of Natural Populations of the Cocoa Pod Borer, Canopomorpha cramerella (Snellen) from Malaysia

Cocoa pod borers from Tawau, Sabah and Sua Betong, Negeri Sembilan and rambutan fruit borers from Serdang and Puchong, Selangor and Kuala Kangsar, Perak, Malaysia were subjected to electrophoretic analysis in an effort to find diagnostic electromorphs between these two bio types of Conopomorpha cramerella. Thirty enzymes and general proteins were successfully demonstrated on zymograms but none of them could serve as diagnostic markers between cocoa pod borers and rambutan fruit borers. The allelic frequencies for 8 polymorphic enzymes are presented

Systems thinking in designing automotive textiles

We present the complexities in terms of designing automotive exterior seating materials (seat coverings and interior linings) at Sage Automotive Interiors (UK), which is a division of a global international automotive textile supplier with headquarters in the US. Sustainability and innovation are emphasized in documents communicating the company’s vision. Using a case study approach, we consider the current design, development and manufacture process and examine it for the potential for feedback loops, identify potential leverage points to effect change and how the process could divert wastes from disposal. We will highlight where sustainable decisions can be incorporated and the difficulties in achieving true sustainability. We argue that a systems approach is needed from conception to final product to ensure economic recycling of textiles and fibres used in automotive seating. Without which, the reality is at best incineration for energy and/or landfill, thus losing important, finite resources forever from a diminishing resource pool of raw materials

Expression profiling of cervical cancers in I ndian women at different stages to identify gene signatures during progression of the disease

Cervical cancer is the second most common cancer among women worldwide, with developing countries accounting for >80% of the disease burden. Although in the West, active screening has been instrumental in reducing the incidence of cervical cancer, disease management is hampered due to lack of biomarkers for disease progression and defined therapeutic targets. Here we carried out gene expression profiling of 29 cervical cancer tissues from I ndian women, spanning International Federation of Gynaecology and Obstetrics ( FIGO ) stages of the disease from early lesion (IA and IIA) to progressive stages (IIB and IIIA–B), and identified distinct gene expression signatures. Overall, metabolic pathways, pathways in cancer and signaling pathways were found to be significantly upregulated, while focal adhesion, cytokine–cytokine receptor interaction and WNT signaling were downregulated. Additionally, we identified candidate biomarkers of disease progression such as SPP 1, proliferating cell nuclear antigen ( PCNA ), STK 17A, and DUSP 1 among others that were validated by quantitative real‐time polymerase chain reaction ( qRT ‐ PCR ) in the samples used for microarray studies as well in an independent set of 34 additional samples. Integrative analysis of our results with other cervical cancer profiling studies could facilitate the development of multiplex diagnostic markers of cervical cancer progression. Cervical cancer is the leading cause of cancer deaths among women in I ndia, yet it remains poorly characterized at molecular level. This study provides one of the largest molecular profiling efforts from this region involving cervical cancer tissues from well‐defined clinical stages to identify molecular signatures of disease progression, as well as identify novel biomarkers distinguishing early and advanced disease. We expect this study to serve as a template for larger studies, including those based on high‐throughput sequencing, to help develop robust biomarkers of disease progression and potentially identify actionable therapeutic targets.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/101800/1/cam4152.pd

Photometric Catalogue of Quasars and Other Point Sources in the Sloan Digital Sky Survey

We present a catalogue of about 6 million unresolved photometric detections in the Sloan Digital Sky Survey Seventh Data Release classifying them into stars, galaxies and quasars. We use a machine learning classifier trained on a subset of spectroscopically confirmed objects from 14th to 22nd magnitude in the SDSS {\it i}-band. Our catalogue consists of 2,430,625 quasars, 3,544,036 stars and 63,586 unresolved galaxies from 14th to 24th magnitude in the SDSS {\it i}-band. Our algorithm recovers 99.96% of spectroscopically confirmed quasars and 99.51% of stars to i $\sim$21.3 in the colour window that we study. The level of contamination due to data artefacts for objects beyond $i=21.3$ is highly uncertain and all mention of completeness and contamination in the paper are valid only for objects brighter than this magnitude. However, a comparison of the predicted number of quasars with the theoretical number counts shows reasonable agreement.Comment: 16 pages, Ref. No. MN-10-2382-MJ.R2, accepted for publication in MNRAS Main Journal, April 201

Phenomenological Lambda-Nuclear Interactions

Variational Monte Carlo calculations for ${_{\Lambda}^4}H$ (ground and excited states) and ${_{\Lambda}^5}He$ are performed to decipher information on ${\Lambda}$-nuclear interactions. Appropriate operatorial nuclear and ${\Lambda}$-nuclear correlations have been incorporated to minimize the expectation values of the energies. We use the Argonne $\upsilon_{18}$ two-body NN along with the Urbana IX three-body NNN interactions. The study demonstrates that a large part of the splitting energy in ${_{\Lambda}^4}H$ ($0^+-1^+$) is due to the three-body ${\Lambda}$ NN forces. $_{\Lambda}^{17}O$ hypernucleus is analyzed using the {\it s}-shell results. $\Lambda$ binding to nuclear matter is calculated within the variational framework using the Fermi-Hypernetted-Chain technique. There is a need to correctly incorporate the three-body ${\Lambda}$ NN correlations for $\Lambda$ binding to nuclear matter.Comment: 18 pages (TeX), 2 figure

State-of-the-art generalisation research in NLP: a taxonomy and review

The ability to generalise well is one of the primary desiderata of natural language processing (NLP). Yet, what `good generalisation' entails and how it should be evaluated is not well understood, nor are there any common standards to evaluate it. In this paper, we aim to lay the ground-work to improve both of these issues. We present a taxonomy for characterising and understanding generalisation research in NLP, we use that taxonomy to present a comprehensive map of published generalisation studies, and we make recommendations for which areas might deserve attention in the future. Our taxonomy is based on an extensive literature review of generalisation research, and contains five axes along which studies can differ: their main motivation, the type of generalisation they aim to solve, the type of data shift they consider, the source by which this data shift is obtained, and the locus of the shift within the modelling pipeline. We use our taxonomy to classify over 400 previous papers that test generalisation, for a total of more than 600 individual experiments. Considering the results of this review, we present an in-depth analysis of the current state of generalisation research in NLP, and make recommendations for the future. Along with this paper, we release a webpage where the results of our review can be dynamically explored, and which we intend to up-date as new NLP generalisation studies are published. With this work, we aim to make steps towards making state-of-the-art generalisation testing the new status quo in NLP.Comment: 35 pages of content + 53 pages of reference

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: the challenge ahead.

Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology