55 research outputs found
Road Tracking from High resolution IRS And IKONOS Images Using Unscented Kalman Filtering
A typical way to update map is to compare recent satellite images with existing map data, detect new roads and add them as cartographic entities to the road layer. At present image processing and pattern recognition are not robust enough to automate the image interpretation system feasible. For this reason we have to develop an image interpretation system that rely on human guidance. More importantly road maps require final checking by a human due to the legal implementations of error. Our proposed technique is applied to IRS and IKONOS images using Unscented Kalman Filter(UKF) . UKF is used for tracing the median axis of the single road segment. The Extended Kalman Filter (EKF) is probably the most widely used estimation algorithm for road tracking. However, more than 35 years of experience in the estimation community has shown that is difficult to implement and is difficult to tune. To overcome this limitation,UKF is introduced in road tracking which is more accurate, easier to implement, and uses the same order of calculations as linearization. The principles and algorithm of EKF and UKF were also discussed. The core of our system is based on profile matching.UKF traces the roadbeyond obstacles and tries to find the continuation of the road finding all road branches initializing at the road junction.The completeness and correctness of road tracking from the IRS and IKONOS images were also compared
Platelet Alloantibody Specificities in Multiply Transfused Patients.
Transfusion plays an important role in the management of patients with hematological
malignancies and disorders. Patients during the induction chemotherapy may need multiple
transfusion of platelets and red cells and may develop refractoriness; platelet count increment
deteriorate even after adequate dose of platelets are transfused. Although several studies
reported non-immunological factors like fever, Splenomegaly, septicemia and severe bleeding
are responsible for refractoriness in some patients, no specific reasons can be found. This raises
the suspicion of platelet antibodies for the cause of refractoriness. Till now in many studies, the
presence of HLA and platelet specific antibodies were found to be between 10%-60%in the
patients who were treated with multiple transfusions.
Our results concluded that multiple random donor blood and platelet transfusion are able
to induce antibodies against HLA class 1 antigens and epitopes on GP iib/iiia. There was no
relationship between the number of units transfused and the antibodies formation. Women with
single pregnancy history were identified as high responder group for alloimmunization. Our
results show AML are frequently immunized than ALL patients.
Keeping in view the alloimmunization, leukoreduced irradiated single donor platelets
and blood components should be transfused for the treatment of hematological and oncological
patients. Till now, non-leukoreduced components are used in most of the centers in India due to
cost of leukoreduction. Testing for the presence of platelet antibodies and transfusion of
compatible platelets shall be important mode of management and prevention of platelet
refractoriness in India
Cellular immune response to Mycobacterium tuberculosis-speciWc antigen culture Wltrate protein-10 in south India
The Mycobacterium tuberculosis (M. tuberculosis)-
speciWc culture Wltrate protein-10 (CFP-10) is highly
recognized by M. tuberculosis infected subjects. In the
present study, the proliferative response and IFN-� secretion
was found for C-terminal peptides of the protein
(Cfp651–70, Cfp761–80, Cfp871–90, and Cfp981–100). The alleles
HLA DRB1 *04 and HLA DRB1 *10 recognized the
C-terminal peptides Cfp7, Cfp8, and Cfp9 in HHC. Cfp6
was predominantly recognized by the alleles HLA DRB1
*03 and HLA DRB1 *15 by PTB. The minimal nonameric
epitopes from the C-terminal region were CFP-1056–64 and
CFP-1076–84. These two peptides deserve attention for
inclusion in a vaccine against tuberculosis in this region
Immune response to Mycobacterium tuberculosis specific antigen ESAT-6 among south Indians
The 6-kDa early secreted antigenic target (ESAT-6) is a T-cell antigen recognized by individuals infected
with Mycobacterium tuberculosis. The aim of the study was to identify ‘‘protective epitopes’’ of ESAT-6
protein in the south Indian population. Proliferative and Interferon gamma (IFN-g) responses to ESAT-6
peptides were studied by flow cytometry and Enzyme linked immunosorbent assay (ELISA). Healthy
household contacts (HHC) recognized Esp1 (10/17) and Esp6 (9/17) peptides. Among pulmonary tuberculosis
patients (PTB), Esp1 (3/11) and Esp6 (5/11) were recognized. Maximal response (7/10) was found
for Esp1 and Esp8 in treated patients (TR). Median values for the responding subjects gave the following
results: Esp1 (76 pg/ml), Esp6 (64 pg/ml), induced IFN-g production in HHC; PTB gave low IFN-g
responses for the peptides. TR responded to the peptides Esp1 (141 pg/ml), Esp8 (102 pg/ml). The
proliferation of CD4 cells was similar in both PTB and TR for all peptides; but HHC showed an increase for
Esp1 (p < 0.05) and Esp6 (p < 0.01). Esp1 (amino acids aa 1–20) and Esp6 (aa 51–70) were the immunogenic
peptides recognized by the alleles HLA DRB1*04 and HLA DRB1*10 among HHC. But the
association of the alleles with ESAT-6 peptide presentation needs to be confirmed in a large cohort of
subjects. We speculate that ESAT-6 can be used along with other immune-eliciting proteins for vaccine
design strategies in south Indian population
Human protein reference database—2006 update
Human Protein Reference Database (HPRD) () was developed to serve as a comprehensive collection of protein features, post-translational modifications (PTMs) and protein–protein interactions. Since the original report, this database has increased to >20 000 proteins entries and has become the largest database for literature-derived protein–protein interactions (>30 000) and PTMs (>8000) for human proteins. We have also introduced several new features in HPRD including: (i) protein isoforms, (ii) enhanced search options, (iii) linking of pathway annotations and (iv) integration of a novel browser, GenProt Viewer (), developed by us that allows integration of genomic and proteomic information. With the continued support and active participation by the biomedical community, we expect HPRD to become a unique source of curated information for the human proteome and spur biomedical discoveries based on integration of genomic, transcriptomic and proteomic data
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
Analysis of Various Road Pattern Recognition Methods for Satellite Images
Abstract--Recently road extraction from satellite imagery has emerged as one of the hot topics in the research field. It is particularly employed in the city planning, cartography and to revise already detected roads in Geographic Information Systems (GIS) environment.. Some of the several applications of road extraction are renewal of GIS database, reference for image registration, assistance for identification algorithms and fast mapping. Road extraction enables the road network to be truly presented in the object space when the image to ground systems transformation is carried out and it has been described as the method of detection and precise localization of roads in the image. Automatic road extraction attempts to simplify and speed up the road extraction process by focusing on automating all or few parts of this process. In photogrammetry and digital image processing fields, road extraction is considered as a challenging issue. In this paper detailed survey has been carried out on various road extraction techniques from satellite images and their performances were analyzed. Keywords-Particle filtering.kalman filtering, road extraction, Neural network and dense cloud points
Optimised DWT using cooperative particle swarm optimiser for hybrid domain based medical and natural image denoising
Using Response Surface Methodology in Synthesis of Ultra-fine Copper Nanoparticals by Electrolysis
Wdrożenie narzędzi „Lean Management” w przemyśle odzieżowym
Garment Manufacturing is one of the oldest in the world, compromising a high number of critical operations. The main issues in the garment industry are the lead time, production rate, very poor line balancing and fabric wastes. Productivity improvement is carried out by implementing the various lean tools in the industry, such as 5S, Value Stream Mapping (VSM) and line balancing in the sewing section. After the implementation of lean tools in the garment industry, the outcomes observed are a reduction in work-in-progress inventory, increases in the production process and increased line efficiency. Similarly the before and after implementation of 5S, which shows space utilisation in the sewing section, is increased. In this research, an implementation study was conducted in only one organisation. Hence the results extracted by the conduct of this implementation study are achievable and adaptable in similar organisations.Główne problemy w przemyśle odzieżowym to czas realizacji, tempo produkcji, bardzo niska równowaga linii i marnotrawstwo tkanin. Celem pracy było uzyskanie poprawy produktywności poprzez wdrożenie różnych narzędzi „Lean Management” w branży, takich jak 5S, Mapowanie Strumienia Wartości (VSM) i równoważenie linii w dziale szycia. Po wdrożeniu narzędzi „Lean Management” w przemyśle odzieżowym na podstawie uzyskanych rezultatów zaobserwowano zmniejszenie zapasów w toku prac, zwiększenie procesu produkcji i zwiększenie wydajności linii. Przedstawione w pracy wyniki dotyczą badania wdrożeniowego przeprowadzonego w jednej organizacji. W związku z tym wyniki uzyskane w ramach tego badania są możliwe do osiągnięcia i dostosowania w podobnych organizacjach
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