Nuclear Scaffold Attachment Sites within ENCODE Regions Associate with Actively Transcribed Genes

The human genome must be packaged and organized in a functional manner for the regulation of DNA replication and transcription. The nuclear scaffold/matrix, consisting of structural and functional nuclear proteins, remains after extraction of nuclei and anchors loops of DNA. In the search for cis-elements functioning as chromatin domain boundaries, we identified 453 nuclear scaffold attachment sites purified by lithium-3,5-iodosalicylate extraction of HeLa nuclei across 30 Mb of the human genome studied by the ENCODE pilot project. The scaffold attachment sites mapped predominately near expressed genes and localized near transcription start sites and the ends of genes but not to boundary elements. In addition, these regions were enriched for RNA polymerase II and transcription factor binding sites and were located in early replicating regions of the genome. We believe these sites correspond to genome-interactions mediated by transcription factors and transcriptional machinery immobilized on a nuclear substructure

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Classification of rice crops based on submergence due to tropical cyclone using remotely sensed data : an Indian case study

Tropical cyclones are one of the most destructive natural disasters occurring frequently in coastal India. The socio economic impacts of these tropical cyclones are high as they result in enormous loss of life and property every year. In the present study, pre event visible-near IR images and post event Radarsat images were procured and used to identify completely submerged landcovers temporally. The methodology is developed considering a case study on the Kendrapara district of Orissa state, which was hit by a cyclone on 29-30(th) October 1999. The pre event IRS ID LISS III (resolution = 22m) image of Kendrapara district was procured geometrically corrected and classified into several landuse and landcover classes. For landuse/landcover classification, supervised classification technique was used. This georeferenced landuse/landcover map provided the baseline information for the district. Next step involved procurement of immediate temporal post-event SAR images of the cyclone-affected district. These images were geometrically corrected and cleaned for speckle noise. Deterministic approach was used to set up threshold for classifying pixel as completely submerged under water or non submerged for Radarsat SAR images i.e. Radarsat SAR images exactly delineated areas completely submerged under water due to cyclonic floods. This type of analysis will help policy makers in deten-nining the extent of submergence and damage. This methodology would be used as a rapid tool to assess damage. Further, this will help in expediting the release of relief funds as well as aid proper allocation of funds to the affected areas/people

Study of different image windowing on Turbidity regression model using remotely sensed data

The Thane creek region, near Mumbai city is being used as dumping site for treated and untreated effluents by government agencies and private industries for the last several decades. This coastal water is very important from environmental point of view since it supports a vast area of mangrove forest besides a wide variety of flora and fauna. Turbidity, an important marine physical pollution parameter, affects the growth of mangroves, causes loss of swamps and poses threat to aquatic life. The work presented discusses the effect of 'variations in sampling time' on Turbidity regression model using Remotely Sensed Data. Marine water samples were collected synchronous to pass of Landsat satellite and Turbidity (NTU) was measured (During the post monsoon season of 1996/97 window of sample collection was +/- 1 hour, which was reduced during the post monsoon season of 1997/98 to 15 minutes). The digital satellite images were corrected initially for geometric, sun angle and atmospheric errors. From the corrected remotely sensed data, DNs values were extracted. Multiple regression model was developed between water quality parameter, turbidity and extracted Digital Numbers (DNs) from corresponding sampling locations by varying image window sizes (Le. 1x1, 3x3 and 5x5 pixels). It was deduced that averaging 3X3 window corresponding to water sample collection locations followed by multiple regression with water quality parameter, turbidity, gave best results of regression coefficient

Identification of completely submerged areas due to tropical cyclone using satellite data : an Indian case study

Tropical cyclones are one of the most destructive natural disasters occurring frequently in coastal India. The socio economic impacts of these tropical cyclones are high as they result in enormous loss of life and property every year. In the present study, pre event visible-near IR images and post event Radarsat images were procured and used to identify completely submerged landcovers temporally. The methodology is developed considering a case study oil the Kendrapara district of Orissa state, which was hit by a cyclone on 29-30(th) October 1999. The pre event IRS 1D LISS III (resolution = 22m) image of Kendrapara district was procured geometrically corrected and classified into several landuse and landcover classes. For landuse/landcover classification, supervised classification technique was used. This georeferenced landuse/landcover map provided the baseline information for the district. Next step involved procurement of immediate temporal post-event SAR images of the cyclone-affected district. These images were geometrically corrected and cleaned for speckle noise. Deterministic approach was used to set tip threshold for classifying pixel as completely submerged under water or non submerged for Radarsat SAR images i.e. Radarsat SAR images exactly delineated areas completely submerged under water due to cyclonic floods. This type of analysis will help policy makers in determining the extent of submergence and damage. This methodology would be used as a rapid tool to assess damage. Further, this will help in expediting the release of relief funds as well as aid proper allocation of funds to the affected areas/people

Qualitative approaches to rapidly identify completely submerged rice due to tropical cyclone using satellite data

The objective of the present study is to identify completely submerged rice areas due to tropical cyclones using remotely sensed data. The Kendrapara district of Orissa state hit by a tropical cyclone on 30(th) October 1999 is considered as study area and for this area, pre event (October 11, 1999) visible-near IR image and pre (October 11, 1999) and post event (November 2,4999 and November 4, 1999) Radarsat images were procured. The pre event IRS ID LISS III (resolution = 22m) image of Kendrapara district was geometrically corrected and classified into several landuse and landcover classes. Supervised classification technique was used for landuse/landcover classification. This landuse/landcover map is assumed to be accurate and is used as a base map in the present study. Pre and post event Radarsat-SAR images were also geometrically corrected. Further preprocessing included speckle noise removal, data calibration and incidence angle adjustment. Based on literature, a threshold of -16.5db (DN value =100) was chosen to classify each pixel in pre Radarsat-1 SAR image as water or non-water. The landuse/landcover map was used to identify the rice regions in the pre and post-event Radarsat images. Application of the threshold allows for the determination of the submerged rice areas. To determine the validity of a single threshold, water pixels in pre event Radarsat-1 SAR images were extracted corresponding to the base map. A histogram of these values suggests that a single value threshold approach may not be fully accurate. To overcome these limitations, two alternative approaches, namely image histogram and change in db were formulated. For both approaches, the rice pixels in pre and post event Radarsat-SAR images were extracted corresponding to base map rice pixels. In case of image approach, a histogram was plotted for the DN values of the pre and post Radarsat-1 SAR rice pixels. This allows the qualitative identification of the submerged rice areas. Using change in db approach, pixel-to-pixel change in db in pre and post event radarsat-1 SAR images in rice pixels was calculated. Analysis of these values allows for the identification of different effects of submergence on the rice area. This type of analysis will help policy makers in determining the extent of submergence and could serve as a tool for rapid assessment of damage and help expedite release of relief funds and aid proper allocation of funds to the affected areas/people

Accelerating Energy Efficiency Improvements in Room Air Conditioners in India: Potential, Costs-Benefits, and Policies

Rising incomes, increasing urbanization, and large cooling demand prompted by India’s hot, humid climate are driving increasing uptake of room air conditioners (ACs). Air conditioning already accounts for 40-60% of summer peak load in large Indian cities such as Delhi and is on track to contribute 140 gigawatts (GW) ( 30%) to peak demand in 2030. India’s standards and labeling policies improved the market average efficiency of room ACs by about 35% between 2006 and 2016 (3% per year) even as inflation-adjusted room AC prices continued to decline. In this report, we assess the technical feasibility and costs and benefits of accelerating the efficiency improvement in room ACs in India and discuss policy enhancements needed to achieve this goal.We also describe examples of rapid AC efficiency improvement from Japan and Korea. Driven by appropriate policies and programs, AC efficiency in these countries improved by more than 8% per year, resulting in near-doubling of energy efficiency over seven to ten years while inflation-adjusted AC prices declined. We also find that the most efficient room AC sold on the Indian market is almost twice as efficient as the average AC sold on the market in 2015-16. As a result, we conclude that the technology needed to accelerate room AC efficiency in India is available.If, starting in 2018, the market average room AC efficiency improves by 6% per year instead of the current 3% per year, about 39 GW of peak load (equivalent to about 80 power plants of 500 MW each), and more than 64 TWh per year of energy (equivalent to the current electricity consumption of the entire state of Gujarat) could be saved by 2030. The net present value (NPV) of the consumer benefit between 2018 and 2030 would range from rupees (Rs) 4,000 crore or US$600 million (if room AC prices increase as expected based on estimates of current cost of efficiency improvement) to Rs 173,000 crore or US$25 billion (if room AC prices do not increase with efficiency improvement, as has been the case historically). Although the rebound effect could reduce the financial benefit of efficiency improvements, it would not affect the overall consumer welfare benefit.This benefit is achievable by ratcheting up India’s one-star efficiency level (the de-facto minimum energy performance standard) for room ACs to the level of the current (2016) five-star rating by 2022 and to the level of current best available technology on the market by 2026. Bulk procurement, similar to that used in UJALA LED Program, and incentive programs would be crucial for accelerating the market transformation, especially pulling up the top of the market. Similar programs could be implemented for other types of ACs

Chlorophyll concentration studies in the Thane creek, Mumbai, India, through remote sensing: comparison of ground truth and OCNI (IRS-P4) data

The chemical analysis of the marine water samples was used along with IRS-P4 (OCM) data to prepare chlorophyll concentration maps for the Thane creek, Mumbai, India. The chlorophyll a +phaeopigment ([C+P]) retrieval was done using a bio-optical algorithm, which was applied to detect the concentration from Ocean Colour Monitor data. Marine water samples were collected on March 15, 2001, March 21, 2001, March 23, 2001 and March 25, 2001 synchronised with the IRS-P4 satellite overpass. Standard methods were used to chemically analyse the samples. The Chlorophyll distribution map from OCM data was prepared using Erdas Imagine 8.4 and SeaDas 4.0. The results show that the chlorophyll values range from 3.204mg/m(3) to 35.24mg/m(3). Discrepancies between the chlorophyll values derived using existing atmospheric model (developed by Space Application Centre, Ahmedabad, India), and those obtained from the analysis of the marine samples were removed by correlating them statistically and by applying a simple correction derived from this correlation. Lower chlorophyll values found near the mouths of the creek tributaries could be attributed to higher industrial waste discharges whereas comparatively higher values of chlorophyll seen further north in the Thane creek, are due to the nutrient disposals from domestic and food industrial sources

Multimodal Anti-spoofing in Biometric Recognition Systems

While multimodal biometric systems were commonly believed to be intrinsically more robust to spoof attacks than unimodal systems, recent results provided clear evidence that they can be evaded by spoofing a single biometric trait. This pointed out that also multimodal systems require specific anti-spoofing measures. In this chapter, we introduce the issue of multimodal anti-spoofing, and give an overview of state-of-the-art anti-spoofing measures. Such measures mainly consist of developing ad hoc score fusion rules that are based on assumptions about the match score distribution produced by fake biometric traits. We discuss the pros and cons of existing measures, and point out the current challenges in multimodal anti-spoofing