Ab initio estimate of temperature dependence of electrical conductivity in a model amorphous material: hydrogenated amorphous silicon

We present an ab initio calculation of the DC conductivity of amorphous silicon and hydrogenated amorphous silicon. The Kubo-Greenwood formula is used to obtain the DC conductivity, by thermal averaging over extended dynamical simulation. Its application to disordered solids is discussed. The conductivity is computed for a wide range of temperatures and doping is explored in a naive way by shifting the Fermi level. We observed the Meyer-Neldel rule for the electrical conductivity with E_MNR = 0.06 eV and a temperature coefficient of resistance, TCR ~ -2.0% K^-1 for a-Si:H. In general, experimental trends are reproduced by these calculations, and this suggests the possible utility of the approach for modeling carrier transport in other disordered systems.Comment: 9 pages, 8 figures, submitted to PRB Comments: corrected typos, referee's comments include

Hybrid Vigor and Heritability Estimates in Tomato Crosses Involving Solanum lycopersicum × S. pimpinellifolium under Cool Tropical Monsoon Climate

High humidity is a major constraint to increased tomato fruit production in a cool tropical monsoon climate. However, the genetic variation observed in Solanum pimpinellifolium makes it a good gene donor for breeding tomato cultivars capable of thriving under high humidity. The objective of this study was to estimate heterosis, heritability for higher yield, and to assess the adaptability of the genotypes to humid conditions. Genotypes were raised from five morphologically divergent parents, viz., wild parent (W)–“LA2093,” “CLN2498D” (D), “CLN2417H” (H), “Tima” (T), and “UC Dan INDIA” (U). The F1s were generated by biparental mating design using “LA2093” as a common pollen donor that was selfed to produce F2s and backcrossed to both parents to obtain BC1s and BC2s. The trial was laid out in a randomized complete block design with three replicates. Data were collected on selected yield-influencing traits and analyzed. “D × W” and “U × W” hybrids showed significant positive better parent heterosis for fruit weight per plant (30.4% and 35.5%) and total fruit yield (48.6% and 26.9%), respectively. The additive variance was higher than dominance variance for all the traits, including total fruit yield in all hybrids viz., “H × W,” “D × W,” “T × W,” and “U × W.” High narrow sense heritability estimate of ≥60% was observed in “D × W” and “U × W” hybrids for the majority of the floral and fruit traits including total fruit yield. This makes the improvement of “D × W” and “U × W” hybrids by direct selection advantageous. Hence, the adoption of selection for the affected traits in subsequent tomato breeding programs would enhance fruit yield and adaptability to humid environments

Selfing revealed potential for higher yield performance than backcrossing among tomato segregating populations of Solanum lycopersicum × S. pimpinellifolium crosses under tropical humid climate

The objectives of this study were to assess and identify new source of phenotypic variability among F3 and BC1F2 tomato populations, and apply genotype by yield*trait (GYT) biplots for population and line selection based on multiple traits. Four diverse cultivated parents (‘CLN2498D’ [D] and ‘CLN2417H’ [H] from Ethiopia; ‘UC Dan INDIA’ [U] and ‘Tima’ [T] from Nigeria), and wild parent ‘LA2093’ [W] were used to generate 276 potential breeding lines. The lines were categorized into eight populations (‘pop_1_W/H1’, ‘pop_2_W/H2’, ‘pop_3_W/D1’, ‘pop_4_W/D2’, ‘pop_5_W/T1’, ‘pop_6_W/T2’, ‘pop_7_W/U1’, and ‘pop_8_W/U2’), and evaluated twice in the field using 19 × 15 alpha-lattice design with two replicates. Significant differences were observed among lines and populations for all yield enhancing traits. ‘Pop_1_W/H1’, ‘pop_4_W/D2’ and ‘pop_6_W/T2’ expressed the highest genetic divergence for plant height, number of leaves, total flower and fruit number, and fruit weight. GYT biplots revealed that all yield*trait interactions had a positive correlation with each other. F3 populations, ‘pop_5_W/T1’ and ‘pop_1_W/H1’ exhibited the best performance for majority of the yield*trait combinations. Hierarchical clustering on principal components (HCPC) revealed overlapping lines (70.58% of Cluster D lines) and (54.05% of Cluster U lines) from the two F3 populations. In BC1F2 population, 32.35% of the 34 original lines of Cluster D and 48.48% of Cluster T lines overlapped between Clusters D and T, while 18.18% of Cluster T lines and 8.82% of Cluster H lines were transgressive between Clusters T and H. Transgressive segregants ‘0210U1’, ‘0211U1’, and ‘0171T1’ of selfed population using multivariate analysis were believed to represent potential sources of novel genetic variation for future tomato breeding

Spatiotemporal climate and vegetation greenness changes and their nexus for Dhidhessa River Basin, Ethiopia

Background Understanding spatiotemporal climate and vegetation changes and their nexus is key for designing climate change adaptation strategies at a local scale. However, such a study is lacking in many basins of Ethiopia. The objectives of this study were (i) to analyze temperature, rainfall and vegetation greenness trends and (ii) determine the spatial relationship of climate variables and vegetation greenness, characterized using Normalized Difference in Vegetation Index (NDVI), for the Dhidhessa River Basin (DRB). Quality checked high spatial resolution satellite datasets were used for the study. Mann–Kendall test and Sen’s slope method were used for the trend analysis. The spatial relationship between climate change and NDVI was analyzed using geographically weighted regression (GWR) technique. Results According to the study, past and future climate trend analysis generally showed wetting and warming for the DRB where the degree of trends varies for the different time and spatial scales. A seasonal shift in rainfall was also observed for the basin. These findings informed that there will be a negative impact on rain-fed agriculture and water availability in the basin. Besides, NDVI trends analysis generally showed greening for most climatic zones for the annual and main rainy season timescales. However, no NDVI trends were observed in all timescales for cool sub-humid, tepid humid and warm humid climatic zones. The increasing NDVI trends could be attributed to agroforestry practices but do not necessarily indicate improved forest coverage for the basin. The change in NDVI was positively correlated to rainfall (r2 = 0.62) and negatively correlated to the minimum (r2 = 0.58) and maximum (r2 = 0.45) temperature. The study revealed a strong interaction between the climate variables and vegetation greenness for the basin that further influences the biophysical processes of the land surface like the hydrologic responses of a basin. Conclusion The study concluded that the trend in climate and vegetation greenness varies spatiotemporally for the DRB. Besides, the climate change and its strong relationship with vegetation greenness observed in this study will further affect the biophysical and environmental processes in the study area; mostly negatively on agricultural and water resource sectors. Thus, this study provides helpful information to device climate change adaptation strategies at a local scale

Prevalence, years lived with disability, and trends in anaemia burden by severity and cause, 1990-2021: findings from the Global Burden of Disease Study 2021

Background Anaemia is a major health problem worldwide. Global estimates of anaemia burden are crucial for developing appropriate interventions to meet current international targets for disease mitigation. We describe the prevalence, years lived with disability, and trends of anaemia and its underlying causes in 204 countries and territories. Methods We estimated population-level distributions of haemoglobin concentration by age and sex for each location from 1990 to 2021. We then calculated anaemia burden by severity and associated years lived with disability (YLDs). With data on prevalence of the causes of anaemia and associated cause-specific shifts in haemoglobin concentrations, we modelled the proportion of anaemia attributed to 37 underlying causes for all locations, years, and demographics in the Global Burden of Disease Study 2021. Findings In 2021, the global prevalence of anaemia across all ages was 24·3% (95% uncertainty interval [UI] 23·9–24·7), corresponding to 1·92 billion (1·89–1·95) prevalent cases, compared with a prevalence of 28·2% (27·8–28·5) and 1·50 billion (1·48–1·52) prevalent cases in 1990. Large variations were observed in anaemia burden by age, sex, and geography, with children younger than 5 years, women, and countries in sub-Saharan Africa and south Asia being particularly affected. Anaemia caused 52·0 million (35·1–75·1) YLDs in 2021, and the YLD rate due to anaemia declined with increasing Socio-demographic Index. The most common causes of anaemia YLDs in 2021 were dietary iron deficiency (cause-specific anaemia YLD rate per 100 000 population: 422·4 [95% UI 286·1–612·9]), haemoglobinopathies and haemolytic anaemias (89·0 [58·2–123·7]), and other neglected tropical diseases (36·3 [24·4–52·8]), collectively accounting for 84·7% (84·1–85·2) of anaemia YLDs. Interpretation Anaemia remains a substantial global health challenge, with persistent disparities according to age, sex, and geography. Estimates of cause-specific anaemia burden can be used to design locally relevant health interventions aimed at improving anaemia management and prevention. Funding Bill & Melinda Gates Foundation

The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. METHODS: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. FINDINGS: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). INTERPRETATION: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden