Process Variation Aware DRAM (Dynamic Random Access Memory) Design Using Block-Based Adaptive Body Biasing Algorithm

Large dense structures like DRAMs (Dynamic Random Access Memory) are particularly susceptible to process variation, which can lead to variable latencies in different memory arrays. However, very little work exists on variation studies in DRAMs. This is due to the fact that DRAMs were traditionally placed off-chip and their latency changes due to process variation did not impact the overall processor performance. However, emerging technology trends like three-dimensional integration, use of sophisticated memory controllers, and continued scaling of technology node, substantially reduce DRAM access latency. Hence, future technology nodes will see widespread adoption of embedded DRAMs. This makes process variation a critical upcoming challenge in DRAMs that must be addressed in current and forthcoming technology generations. In this paper, techniques for modeling the effect of random, as well as spatial variation, in large DRAM array structures are presented. Sensitivity-based gate level process variation models combined with statistical timing analysis are used to estimate the impact of process variation on the DRAM performance and leakage power. A simulated annealing-based Vth assignment algorithm using adaptive body biasing is proposed in this thesis to improve the yield of DRAM structures. By applying the algorithm on a 1GB DRAM array, an average of 14.66% improvement in the DRAM yield is obtained

Destination Branding Kabupaten Majalengka Oleh Dinas Pariwisata Dan Kebudayaan Kabupaten Majalengka

In dealing with tourism issues such as the development of destinations that are not yet optimal, management of the tourism industry that is not yet optimal, as well as tourism resources that have not been integrated, it is necessary to do destination branding in Majalengka Regency. In addition, Majalengka Regency still does not have strong branding that can attract many foreign tourists to visit Majalengka Regency. The purpose of this study was to determine the stages of destination branding carried out by the Department of Tourism and Culture of Majalengka Regency in the development of tourism in Majalengka Regency. The method used is a descriptive qualitative research method with a post-positivistic paradigm. Data collection techniques used were interviews, observation, literature study, and documentation study. The results of this study indicate that the Department of Tourism and Culture of Majalengka Regency carried out the stages of market investigation, analysis, and strategic recommendations by conducting research mapping market potential analysis through three sources, namely experts from academia as facilitators; potential attraction of natural tourist attractions that are already running and already have decent natural visitors, and scoring techniques. At the Brand identity development stage, Majalengka Regency does not yet have a tourism destination identity because it is still in the process. For the stage of brand launch and introduction using three ways, namely special events, media, and involving the community. At the stage of brand implementation by making programs and tourism activities that involve pentahelix. And for the stages of monitoring, evaluation, and review related to the development of tourism destinations and statistical data of tourists visiting Majalengka Regency. Keywords: Destination Branding; Development; Tourism; Traveler; Majalengka Regency  Abstrak Dalam menghadapi permasalahan kepariwisataan seperti pengembangan destinasi yang belum optimal, pengelolaan industri pariwisata yang belum optimal, serta SDM Pariwisata yang belum terintegrasi perlu dilakukan destination branding di Kabupaten Majalengka. Selain itu Kabupaten Majalengka pun masih belum memiliki branding kuat yang dapat menarik banyak minat wisatawan luar untuk berkunjung ke Kabupaten Majalengka. Tujuan penelitian ini adalah untuk mengetahui tahapan destination branding yang dilakukan oleh Dinas Pariwisata dan Kebudayaan Kabupaten Majalengka dalam pengembangan pariwisata di Kabupaten Majalengka. Metode yang digunakan adalah metode penelitian deskriptif kualitatif dengan paradigma post-positivistik. Teknik pengumpulan data yang digunakan adalah wawancara, observasi, studi pustaka, dan studi dokumentasi. Hasil penelitian ini menunjukkan bahwa Dinas Pariwisata dan Kebudayaan Kabupaten Majalengka melakukan tahapan market investigation, analysis, and strategic recommendations dengan melakukan riset pemetaan analisis potensi pasar melalui tiga sumber yaitu tenaga ahli dari akademisi sebagai fasilitator; potensi daya tarik objek wisata yang secara alami sudah berjalan dan sudah memiliki pengunjung alami yang lumayan, dan teknik skoring. Pada tahap Brand identity development, Kabupaten Majalengka belum memiliki identitas destinasi pariwisata dikarenakan masih dalam proses. Untuk tahapan brand launch and introduction menggunakan tiga cara yaitu special event, media, dan melibatkan komunitas. Pada tahapan brand implementation dengan membuat program serta kegiatan pariwisata yang melibatkan pentahelix. Dan untuk tahapan monitoring, evaluation, and review terkait dengan perkembangan destinasi pariwisata dan data statistik wisatawan yang berkunjung ke Kabupaten Majalengka. Kata Kunci: Destination  Branding; Pengembangan; Pariwisata; Wisatawan; Kabupaten Majalengk

Combined Forward-Backward Asymmetry Measurements in Top-Antitop Quark Production at the Tevatron

The CDF and D0 experiments at the Fermilab Tevatron have measured the asymmetry between yields of forward- and backward-produced top and antitop quarks based on their rapidity difference and the asymmetry between their decay leptons. These measurements use the full data sets collected in proton-antiproton collisions at a center-of-mass energy of $\sqrt s =1.96$ TeV. We report the results of combinations of the inclusive asymmetries and their differential dependencies on relevant kinematic quantities. The combined inclusive asymmetry is $A_{\mathrm{FB}}^{t\bar{t}} = 0.128 \pm 0.025$. The combined inclusive and differential asymmetries are consistent with recent standard model predictions

SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion

Abstract: The B.1.617.2 (Delta) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in the state of Maharashtra in late 2020 and spread throughout India, outcompeting pre-existing lineages including B.1.617.1 (Kappa) and B.1.1.7 (Alpha)1. In vitro, B.1.617.2 is sixfold less sensitive to serum neutralizing antibodies from recovered individuals, and eightfold less sensitive to vaccine-elicited antibodies, compared with wild-type Wuhan-1 bearing D614G. Serum neutralizing titres against B.1.617.2 were lower in ChAdOx1 vaccinees than in BNT162b2 vaccinees. B.1.617.2 spike pseudotyped viruses exhibited compromised sensitivity to monoclonal antibodies to the receptor-binding domain and the amino-terminal domain. B.1.617.2 demonstrated higher replication efficiency than B.1.1.7 in both airway organoid and human airway epithelial systems, associated with B.1.617.2 spike being in a predominantly cleaved state compared with B.1.1.7 spike. The B.1.617.2 spike protein was able to mediate highly efficient syncytium formation that was less sensitive to inhibition by neutralizing antibody, compared with that of wild-type spike. We also observed that B.1.617.2 had higher replication and spike-mediated entry than B.1.617.1, potentially explaining the B.1.617.2 dominance. In an analysis of more than 130 SARS-CoV-2-infected health care workers across three centres in India during a period of mixed lineage circulation, we observed reduced ChAdOx1 vaccine effectiveness against B.1.617.2 relative to non-B.1.617.2, with the caveat of possible residual confounding. Compromised vaccine efficacy against the highly fit and immune-evasive B.1.617.2 Delta variant warrants continued infection control measures in the post-vaccination era

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

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

Using Adaptive Body Biasing for Robust Process Variation Aware DRAM Design

Large dense structures like DRAMs are particularly susceptible to process variation, which can lead to variable latencies in different memory arrays. However, very little work exists on variation studies in the DRAM as DRAMs were traditionally placed off-chip limiting their latency impact on the overall processor performance. However, emerging technology trends like three dimensional integration, sophisticated memory controllers substantially reduces DRAM access latency. This makes process variation a critical upcoming challenge in DRAMs that must be addressed in current and forthcoming technology generations. In this paper, we propose a unique adaptive body biasing algorithm for designing large DRAMs robust to process variation. WE propose a hierarchical and computationally efficient framework by combining cell level Hspice models with sensitivity based models for statistical timing analysis. We report an average of 14.66% improvement in the DRAM yield on 1GB DRAM array. To the best of our knowledge, ours is the first technique to model the impact of process variation on large scale DRAM arrays. Copyright © 2013 American Scientific Publishers