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Rice is an important commodity in Nepalese agriculture occupying 1.46-million-hectare area, where 92% area falls under main (Barkhe) season and 7% under spring (Chaite) season. Among various constraints for spring rice seedling raising, cold stress during early seedling establishment is the major one. To address the problem, an on-station trial entitled “varietal performance of spring rice seedlings against cold stress in Western Terai of Nepal” was conducted from February to March, 2021 at Horticulture research farm of Paklihawa Campus, Rupandehi. Research was carried out in Completely Randomized Design with two growing environment (inside and outside polyhouse) as main factor and seven varieties as sub-factor, each replicated three times. Spring rice varieties includes five released varieties (Hardinath-1, Hardinath-3, Hardinath Hybrid-1, Hardinath Hybrid-3, Chaite-5) and two promising varieties (IR-1008 and PR 126). Data related to growth of seedling were collected at one week interval up to 5 weeks. Significant difference was observed within two environmental conditions on days to germination parameters, shoot length, root length, seedling dry weight and leaf area. The values for all the parameters were found maximum in seedlings inside the polyhouse as compared to that of outside polyhouse and in the variety Hardinath – 1. For early transplanting of spring rice, it was found better to choose Hardinath- 1 variety and raise seedlings under polyhouse nursery to escape cold stress.

Background: Each year, two million people worldwide suffer snakebite envenoming (SBE), resulting in up to 138,000 deaths. The World Health Organization has added SBE to the list of Neglected Tropical Diseases, calling for stronger epidemiological evidence in highly endemic countries such as Nepal. Methods: We conducted a cross-sectional survey in 249 randomly selected clusters across Nepal’s Terai region, including 13,879 geospatially selected households. We analysed snakebite incidence rates and outcomes in humans and domestic animals. Findings :Among 63,454 human participants, 166 suffered snakebites over the previous 12 months; 48·8% were envenomed and 7·8% died. This corresponded to annual incidence rates of 262 snakebites [95% CI 225–305] , 127 envenomings [102–158], and 20 [12–35] deaths per 100,000 individuals, extrapolating into 37,661 yearly victims [32,362–43,836] and 2,949 deaths [1,728–5,053] in the Terai. Victim median age was 30 years (IQR 20–45) and 60% were female. Children younger than 15 years (n=6; 46%) and females (n=10; 77%) were over-represented among the 13 deceased. Incidence was higher in Eastern, and mortality in Central regions. Of 184,999 animals, owners reported 144 snakebites, with annual incidence rates of 42-202 and mortality of 79-100 per 100,000 varying by animal type. Spatial and seasonal incidence were similar in humans and animals. Conclusion: This first One Health study on snakebite across Nepal’s Terai shows high incidence and mortality rates in humans and animals. These results call for strengthening of preventive measures and better access to life-saving treatments. Funding: Swiss National Science Foundation project 315130_176271 (SNAKE-BYTE) Declaration of Interest: None to declare. Ethical Approval: The study was approved by the Nepal Health Research Council (NHRC Reg. 585/2018), and Commission Cantonale d’Ethique de la Recherche Scientifique in Geneva, Switzerland (CCER/SwissEthics Registry No. 2018-01331).

This study fits 22 theoretical distribution functions, four of them originally derived, onto 772 cryptocurrency daily returns with goodness-of-fit evaluated using Cramer-von Mises, Anderson-Darling, Kuiper, Kolmogorov-Smirnov, and Chi-squared tests, as well as a harmonic mean p-value synthetic criterion. Most cryptocurrency return distributions can be sufficiently approximated with a Johnson SU function or an asymmetric power function. Johnson SU, asymmetric Student, and asymmetric Laplace distributions have better fit for larger cryptocurrencies, while error, generalised Cauchy, and Hampel (a Gaussian-Cauchy mixture) distributions are more characteristic of smaller cryptocurrencies, with larger coins demonstrating better overall fit. Less than 8% of sample coins and less than 4% of the top quartile by size do not fit into any of the investigated distributions, three largest “misbehaving” cryptocurrencies being Litecoin, Dogecoin, and Decred. Bitcoin and Ethereum are best modelled with error and asymmetric power law distributions, respectively, with asymmetric power law distributions stable through time. More than 30% of sample cryptocurrencies, and 26% from the top quartile, have infinite theoretical variance, severely limiting the diversification potential with such cryptoassets. Three most prominent infinite-variance coins are Bitcoin SV, Tezos, and ZCash. This study has substantial implications for risk management, portfolio management, and cryptocurrency derivative pricing.