A 2022 τ\tau-Herculid meteor cluster from an airborne experiment: automated detection, characterization, and consequences for meteoroids

Context. The existence of meteor clusters has long since been a subject of speculation and so far only seven events have been reported, among which two involve less than five meteors, and three were seen during the Leonid storms. Aims. The 1995 outburst of Comet 73P/Schwassmann-Wachmann was predicted to result in a meteor shower in May 2022. We detected the shower, proved this to be the result of this outburst, and detected another meteor cluster during the same observation mission. Methods. The {\tau}-Herculids meteor shower outburst on 31 May 2022 was continuously monitored for 4 hours during an airborne campaign. The video data were analyzed using a recently developed computer-vision processing chain for meteor real-time detection. Results. We report and characterize the detection of a meteor cluster involving 38 fragments, detected at 06:48 UT for a total duration of 11.3 s. The derived cumulative size frequency distribution index is relatively shallow: s = 3.1. Our open-source computer-vision processing chain (named FMDT) detects 100% of the meteors that a human eye is able to detect in the video. Classical automated motion detection assuming a static camera was not suitable for the stabilized camera setup because of residual motion. Conclusions. From all reported meteor clusters, we crudely estimate their occurrence to be less than one per million observed meteors. Low heliocentric distance enhances the probability of such meteoroid self-disruption in the interplanetary space.Comment: 6 pqges, 5 figure

Database Optimization Using Genetic Algorithms for Distributed Databases

Databases can store a vast amount of information and particular sets of data are accessed via queries which are written in specific interface language such as structured query language (SQL). Database optimization is a process of maximizing the speed and efficiency with which kind of data is retrieved or simply it’s a mechanism that reduces database systems response time. Query optimization is one of the major functionality in database management systems (DBMS). The purpose of the query optimization is to determine the most efficient and effective way to execute a particular query by considering several query plans such as graphical plans, textual plans and etc. Execution of any particular datasets depends on the capability of the query optimization mechanism to acquire competent query processing approaches. Distributed database system is a collection several interrelated databases which are spread physically across different environments that communicate through a computer network. Inability to obtain an effective query strategy with an efficient accuracy and minimum response time or cost to execute the given query is one of the major key issues of the query optimization in distributed database systems. Further inefficient database compression methods, inefficient query processing, missing indexes, inexact statistics, and deadlocks are furthermore defects. In this paper, it describes the methodologies such as genetic algorithm strategy for distributed database systems so as to execute the query plan. Genetic algorithms are extensively using to solve constrained and unconstrained optimization problems. The genetic algorithms are using three main types of rules such as selection rules, crossover rules, and mutation rules

New Generation Cooperative and Cognitive Dual Satellite Systems: Performance Evaluation

Investigating innovative satellite architectures with enhanced system through- put is one of the most important challenges towards realizing the next generation of satellite communication systems. In this context, we study two advanced architectures, namely cooperative and cognitive satellite systems. These designs allow the spectral coexistence of two multibeam satellites over a common coverage area with the overlapping beam patterns. In the cooperative dual satellite system, we consider coordination between two coexisting transmitters in order to reduce the intersatellite interference. This is achieved by employing adequate user scheduling, based on the channel state information of each user. To this end, a semi-orthogonal interference aware scheduling algorithm is applied. Further, in the cognitive dual satellite system, we employ a cognitive beamhopping technique assuming that the secondary gateway is aware of the primary's beamhopping pattern. Moreover, we compare the performances of these schemes with those of the conventional multi- beam and overlapping dual satellite systems in terms of spectral efficiency, power efficiency and user fairness. Finally, we provide several insights on the performance of these schemes and provide interesting future works in these domains

Fludarabine, cytarabine, granulocyte colony-stimulating factor, and idarubicin with gemtuzumab ozogamicin improves event-free survival in younger patients with newly diagnosed aml and overall survival in patients with npm1 and flt3 mutations

Purpose To determine the optimal induction chemotherapy regimen for younger adults with newly diagnosed AML without known adverse risk cytogenetics. Patients and Methods One thousand thirty-three patients were randomly assigned to intensified (fludarabine, cytarabine, granulocyte colony-stimulating factor, and idarubicin [FLAG-Ida]) or standard (daunorubicin and Ara-C [DA]) induction chemotherapy, with one or two doses of gemtuzumab ozogamicin (GO). The primary end point was overall survival (OS). Results There was no difference in remission rate after two courses between FLAG-Ida + GO and DA + GO (complete remission [CR] + CR with incomplete hematologic recovery 93% v 91%) or in day 60 mortality (4.3% v 4.6%). There was no difference in OS (66% v 63%; P = .41); however, the risk of relapse was lower with FLAG-Ida + GO (24% v 41%; P < .001) and 3-year event-free survival was higher (57% v 45%; P < .001). In patients with an NPM1 mutation (30%), 3-year OS was significantly higher with FLAG-Ida + GO (82% v 64%; P = .005). NPM1 measurable residual disease (MRD) clearance was also greater, with 88% versus 77% becoming MRD-negative in peripheral blood after cycle 2 (P = .02). Three-year OS was also higher in patients with a FLT3 mutation (64% v 54%; P = .047). Fewer transplants were performed in patients receiving FLAG-Ida + GO (238 v 278; P = .02). There was no difference in outcome according to the number of GO doses, although NPM1 MRD clearance was higher with two doses in the DA arm. Patients with core binding factor AML treated with DA and one dose of GO had a 3-year OS of 96% with no survival benefit from FLAG-Ida + GO. Conclusion Overall, FLAG-Ida + GO significantly reduced relapse without improving OS. However, exploratory analyses show that patients with NPM1 and FLT3 mutations had substantial improvements in OS. By contrast, in patients with core binding factor AML, outcomes were excellent with DA + GO with no FLAG-Ida benefit

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Development of on package indicator sensor for real-time monitoring of meat quality

Aim: The aim was to develop an indicator sensor for real-time monitoring of meat quality and to compare the response of indicator sensor with meat quality parameters at ambient temperature. Materials and Methods: Indicator sensor was prepared using bromophenol blue (1% w/v) as indicator solution and filter paper as indicator carrier. Indicator sensor was fabricated by coating indicator solution onto carrier by centrifugation. To observe the response of indicator sensor buffalo meat was packed in polystyrene foam trays covered with PVC film and indicator sensor was attached to the inner side of packaging film. The pattern of color change in indicator sensor was monitored and compared with meat quality parameters viz. total volatile basic nitrogen, D-glucose, standard plate count and tyrosine value to correlate ability of indicator sensor for its suitability to predict the meat quality and storage life. Results: The indicator sensor changed its color from yellow to blue starting from margins during the storage period of 24 h at ambient temperature and this correlated well with changes in meat quality parameters. Conclusions: The indicator sensor can be used for real-time monitoring of meat quality as the color of indicator sensor changed from yellow to blue starting from margins when meat deteriorates with advancement of the storage period. Thus by observing the color of indicator sensor quality of meat and shelf life can be predicted

A study on purchasing pattern and awareness of medicines from medical pharmacy in Chennai city

Drug industry is a quickest developing industry in India. It is esteemed at above US 40 billion dollars. India trades enormous measure of medications to contrast regions of the planet. These days individuals are aware of what they purchase. Regardless of whether specialists recommend a medication, purchasers resort to web to get more data on the medication before they devour it. Shoppers have various insights on different sorts of medications. Understanding the buyer demeanor towards medications will assist the advertisers with figuring promoting procedures better. To study the awareness and purchasing pattern of medicine purchase form the medical shop in the study area, To analyses the awareness of medicine purchase in the study area and To evaluate the purchasing pattern of medicine in the study area. This study is test the responses got from the study survey (N=110).Using convenience sampling and primacy data collected for various customers thoughts and collected data analyzed by using Percentage methods, Chi-Square test, Friedman’s Non Parametric test, ANOVA and Independent Samples T Test.&nbsp