Multiwavelength Observations of Supersonic Plasma Blob Triggered by Reconnection Generated Velocity Pulse in AR10808

Using multi-wavelength observations of Solar and Heliospheric Observatory (SoHO)/Michelson Doppler Imager (MDI), Transition Region and Coronal Explorer (TRACE) 171 \AA, and H$\alpha$ from Culgoora Solar Observatory at Narrabri, Australia, we present a unique observational signature of a propagating supersonic plasma blob before an M6.2 class solar flare in AR10808 on 9th September 2005. The blob was observed between 05:27 UT to 05:32 UT with almost a constant shape for the first 2-3 minutes, and thereafter it quickly vanished in the corona. The observed lower bound speed of the blob is estimated as $\sim$215 km s$^{-1}$ in its dynamical phase. The evidence of the blob with almost similar shape and velocity concurrent in H$\alpha$ and TRACE 171 \AA\ supports its formation by multi-temperature plasma. The energy release by a recurrent 3-D reconnection process via the separator dome below the magnetic null point, between the emerging flux and pre-existing field lines in the lower solar atmosphere, is found to be the driver of a radial velocity pulse outwards that accelerates this plasma blob in the solar atmosphere. In support of identification of the possible driver of the observed eruption, we solve the two-dimensional ideal magnetohydrodynamic equations numerically to simulate the observed supersonic plasma blob. The numerical modelling closely match the observed velocity, evolution of multi-temperature plasma, and quick vanishing of the blob found in the observations. Under typical coronal conditions, such blobs may also carry an energy flux of 7.0$\times10^{6}$ ergs cm$^{-2}$ s$^{-1}$ to re-balance the coronal losses above active regions.Comment: Solar Physics; 22 Pages; 8 Figure

Multiwavelength Study on Solar and Interplanetary Origins of the Strongest Geomagnetic Storm of Solar Cycle 23

We study the solar sources of an intense geomagnetic storm of solar cycle 23 that occurred on 20 November 2003, based on ground- and space-based multiwavelength observations. The coronal mass ejections (CMEs) responsible for the above geomagnetic storm originated from the super-active region NOAA 10501. We investigate the H-alpha observations of the flare events made with a 15 cm solar tower telescope at ARIES, Nainital, India. The propagation characteristics of the CMEs have been derived from the three-dimensional images of the solar wind (i.e., density and speed) obtained from the interplanetary scintillation data, supplemented with other ground- and space-based measurements. The TRACE, SXI and H-alpha observations revealed two successive ejections (of speeds ~350 and ~100 km/s), originating from the same filament channel, which were associated with two high speed CMEs (~1223 and ~1660 km/s, respectively). These two ejections generated propagating fast shock waves (i.e., fast drifting type II radio bursts) in the corona. The interaction of these CMEs along the Sun-Earth line has led to the severity of the storm. According to our investigation, the interplanetary medium consisted of two merging magnetic clouds (MCs) that preserved their identity during their propagation. These magnetic clouds made the interplanetary magnetic field (IMF) southward for a long time, which reconnected with the geomagnetic field, resulting the super-storm (Dst_peak=-472 nT) on the Earth.Comment: 24 pages, 16 figures, Accepted for publication in Solar Physic

Dynamics of Coronal Bright Points as seen by Sun Watcher using Active Pixel System detector and Image Processing (SWAP), Atmospheric Imaging Assembly AIA), and Helioseismic and Magnetic Imager (HMI)

The \textit{Sun Watcher using Active Pixel system detector and Image Processing}(SWAP) on board the \textit{PRoject for OnBoard Autonomy\todash 2} (PROBA\todash 2) spacecraft provides images of the solar corona in EUV channel centered at 174 \AA. These data, together with \textit{Atmospheric Imaging Assembly} (AIA) and the \textit{Helioseismic and Magnetic Imager} (HMI) on board \textit{Solar Dynamics Observatory} (SDO), are used to study the dynamics of coronal bright points. The evolution of the magnetic polarities and associated changes in morphology are studied using magnetograms and multi-wavelength imaging. The morphology of the bright points seen in low-resolution SWAP images and high-resolution AIA images show different structures, whereas the intensity variations with time show similar trends in both SWAP 174 and AIA 171 channels. We observe that bright points are seen in EUV channels corresponding to a magnetic-flux of the order of $10^{18}$ Mx. We find that there exists a good correlation between total emission from the bright point in several UV\todash EUV channels and total unsigned photospheric magnetic flux above certain thresholds. The bright points also show periodic brightenings and we have attempted to find the oscillation periods in bright points and their connection to magnetic flux changes. The observed periods are generally long (10\todash 25 minutes) and there is an indication that the intensity oscillations may be generated by repeated magnetic reconnection

Temporal Orientation and its Relationships with Organizationally Valued Outcomes: Results from a 14 Country Investigation

In this investigation we were concerned with the cultural covariates of temporal orientation in 14 different national contexts. Data were collected from United States of America (US), Australia, Germany, Poland, Chile, Venezuela, Turkey, United Arab Emirates (UAE), India, Indonesia, Malaysia Japan, South Korea and China. Analyses show that collectivistic cultural orientation tends to be relatively important in the prediction of three facets of temporal orientation (i.e. emphasis on planning and scheduling; sense of time and attitude towards time)

Identification of risk factors for malaria control by focused interventions in Ranchi district, Jharkhand, India

Background & objectives: Ranchi, the capital of Jharkhand state is endemic for malaria, particularly the Bundu Primary Health Centre (PHC) is the worst affected. Therefore, a study was initiated during 2009 using remote sensing (RS) and geographical information system (GIS) to identify risk factors responsible for high endemicity in this PHC. Methods: Bundu and Angara in Ranchi district were identified as high and low malaria endemic PHCs based on epidemiological data of three years (2007–09). The habitation, streams, other water body, landform, PHC and village boundary thematic maps were prepared using IRS-P6/LISS III-IV imageries and macro level breeding sites were identified. Digital elevation model (DEM) of the PHCs was generated using Cartosat Stereo Pair images and from DEM, slope map was derived to calculate flat area. From slope, aspect map was derived to indicate direction of water flow. Length of perennial streams, area under rocky terrain and buffer zones of 250, 500 and 750 m were constructed around streams. High resolution remote sensing imageries were used to identify micro level breeding sites. Based on macro-micro breeding sites, six villages from each PHC were selected randomly having combination of different parameters representing all ecotypes. Entomological data were collected during 2010–11 in pre- and post-monsoon seasons following standard techniques and analyzed statistically. Differential analysis was attempted to comprehend socioeconomic and other determinants associated with malaria transmission. Results: The study identified eight risk factors responsible for higher malaria endemicity in Bundu in comparison to Angara PHC based on ecological, entomological, socioeconomic and other local parameters. Conclusion: Focused interventions in integrated vector management (IVM) mode are required to be carried out in the district for better management and control of disease

Multi-Wavelength Observations of a Flux Rope Failed in the Eruption and Associated M-Class Flare from NOAA AR 11045

We present the multi-wavelength observations of a flux rope that was trying to erupt from NOAA AR 11045 and the associated M-class solar flare on 12 February 2010 using space and ground based observations from TRACE, STEREO, SOHO/MDI, Hinode/XRT and BBSO. While the flux rope was rising from the active region, an M1.1/2F class flare was triggered nearby one of its footpoints. We suggest that the flare triggering was due to the reconnection of a rising flux rope with the surrounding low-lying magnetic loops. The flux rope reached a projected height of ~0.15 Rs with a speed of ~90 km/s while the soft X-ray flux enhanced gradually during its rise. The flux rope was suppressed by an overlying field and the filled plasma moved towards the negative polarity field to the west of its activation site. We find the first observational evidence of the initial suppression of a flux rope due to a remnant filament visible both at chromospheric and coronal temperatures that evolved couple of days before at the same location in the active region. SOHO/MDI magnetograms show the emergence of a bipole ~12 h prior to the flare initiation. The emerged negative polarity moved towards the flux rope activation site, and flare triggering near the photospheric polarity inversion line (PIL) took place. The motion of the negative polarity region towards PIL helped in the build-up of magnetic energy at the flare and flux rope activation site. This study provides a unique observational evidence of a rising flux rope that failed to erupt due to a remnant filament and overlying magnetic field, as well as associated triggering of an M-class flare.Comment: 20 pages, 11 figures, Sol. Phy

Multiwavelength studies of MHD waves in the solar chromosphere: An overview of recent results

The chromosphere is a thin layer of the solar atmosphere that bridges the relatively cool photosphere and the intensely heated transition region and corona. Compressible and incompressible waves propagating through the chromosphere can supply significant amounts of energy to the interface region and corona. In recent years an abundance of high-resolution observations from state-of-the-art facilities have provided new and exciting ways of disentangling the characteristics of oscillatory phenomena propagating through the dynamic chromosphere. Coupled with rapid advancements in magnetohydrodynamic wave theory, we are now in an ideal position to thoroughly investigate the role waves play in supplying energy to sustain chromospheric and coronal heating. Here, we review the recent progress made in characterising, categorising and interpreting oscillations manifesting in the solar chromosphere, with an impetus placed on their intrinsic energetics.Comment: 48 pages, 25 figures, accepted into Space Science Review

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