Observations on a bumper catch of oil sardine by Rampan nets in Goa

During the past decade Sardinella longiceps hascontributed about 30 to 50% of the total fish catchalong the Goa coast. The annual oil sardine landingsin Goa during the year 2015 and 2016 was 16,212and 24951 tons (t) respectively. There are 20 landingcentres on the South Goa district and 14 landingcentres in the North Goa district. At Pale LandingCentre (150 22" 017’ N 0730 52" 552’ E) fishing 20shoreseine (Rampan) units are engaged in fishing

Globalization and Public Health: An Examination of Cross-Border Health Issues

The rapid interconnection facilitated by globalization intensifies the dissemination of infectious diseases, posing substantial obstacles for public health systems globally. This paper utilizes a comparative methodology to analyze the impact of globalization on the dynamics of health issues that transcend national borders. It does so by closely examining two distinct pandemics: COVID-19 and the Nipah virus. Utilizing epidemiological data, public health policies, and scholarly literature, we examine the transmission patterns, susceptibilities, and strategies for addressing both viruses. By contrasting the easily transmissible and airborne characteristics of COVID-19 with the localized outbreaks and zoonotic source of the Nipah virus, we expose the varied difficulties presented by distinct cross-border health hazards. The main discovery we made emphasizes the contradictory connection between globalization and the readiness of public health. Interconnectedness not only speeds up the spread of viruses, but also promotes international collaboration in areas such as research, surveillance, and sharing of resources. We contend that effectively addressing cross-border health threats necessitates a nuanced comprehension of the dual nature of globalization, highlighting the importance of strong national health systems in conjunction with intensified global cooperation. This paper seeks to offer valuable insights to policymakers and public health professionals by analyzing the divergent cases of COVID-19 and Nipah virus. It aims to assist them in effectively managing the intricate relationship between globalization and health concerns that transcend national borders. We promote a proactive strategy that utilizes the advantages of international collaboration while enhancing local capacity to guarantee efficient readiness and reaction to forthcoming pandemics

Anisotropic Superparamagnetism of Monodispersive Cobalt-Platinum Nanocrystals

Based on the high-temperature organometallic route (Sun et al. Science 287, 1989 (2000)), we have synthesized powders containing CoPt_3 single crystals with mean diameters of 3.3(2) nm and 6.0(2) nm and small log-normal widths sigma=0.15(1). In the entire temperature range from 5 K to 400 K, the zero-field cooled susceptibility chi(T) displays significant deviations from ideal superparamagnetism. Approaching the Curie temperature of 450(10) K, the deviations arise from the (mean-field) type reduction of the ferromagnetic moments, while below the blocking temperature T_b, chi(T) is suppressed by the presence of energy barriers, the distributions of which scale with the particle volumes obtained from transmission electron microscopy (TEM). This indication for volume anisotropy is supported by scaling analyses of the shape of the magnetic absorption chi''(T,omega) which reveal distribution functions for the barriers being also consistent with the volume distributions observed by TEM. Above 200 K, the magnetization isotherms M(H,T) display Langevin behavior providing 2.5(1) mu_B per CoPt_3 in agreement with reports on bulk and thin film CoPt_3. The non-Langevin shape of the magnetization curves at lower temperatures is for the first time interpreted as anisotropic superparamagnetism by taking into account an anisotropy energy of the nanoparticles E_A(T). Using the magnitude and temperature variation of E_A(T), the mean energy barriers and 'unphysical' small switching times of the particles obtained from the analyses of chi''(T,omega) are explained. Below T_b hysteresis loops appear and are quantitatively described by a blocking model, which also ignores particle interactions, but takes the size distributions from TEM and the conventional field dependence of E_A into account.Comment: 12 pages with 10 figures and 1 table. Version accepted for publication in Phys. Rev. B . Two-column layou

G × E interactions in QTL introgression lines of Spanish-type groundnut (Arachis hypogaea L.)

Multi-environment testing at five locations for rust and late leaf spot (LLS) resistance with 41 introgressed lines (ILs) bred using marker-assisted backcross breeding in the genetic background Spanish- type groundnut varieties identified significant genotype, and genotype 9 environment interactions (GEI) for LLS disease resistance and yield parameters. Significant GEI effects suggest the need to identify location specific breeding lines to achieve gains in pod yield and LLS resistance. The observed variable LLS disease reaction among the ILs in part suggests influence of background genotype on the level of resistance. A breeding scheme with early generation selection using molecular markers followed by phenotyping for LLS, and multi-location testing of fixed breeding lines was optimized to enhance selection intensity and accuracy in groundnut breeding. The ILs, ICGVs 14431, 14436 and 14438 with pooled LLS score at 90 DAS of 3.5–3.7 were superior to respective recurrent parent for pod yield, with early maturing similar to recurrent parents. The pod yield advantage in ILs is attributed by more number of pods, besides resistance to LLS that contributes to better filling

Molecular breeding tools improved drought tolerant groundnut variety for resistance to foliar fungal diseases

A largely rainfed crop in India, drought tolerance, particularly mid- and end-season tolerance, is a key trait in groundnut varieties. A combination of both empirical and trait-based approaches was used in breeding programs of ICAR and ICRISAT, resulting in release of few tolerant varieties that have superior pod yield under drought stress and/or have enhanced water-use-efficiency. There is a need to breed varieties with drought tolerance, disease resistance and quality traits that suit different production ecologies as well as meet the needs of the farmers, consumers and industries. ICRISAT has released an early-maturing (90-95 d) and drought- tolerant variety ICGV 91114 for the drought-prone Ananthapur district of Andhra Pradesh, India, where about 0.7 m ha area is under groundnut cultivation and has low (300 mm) and erratic (30-40 rainy days) rainfall. On-farm studies conducted with ICGV 91114 during 2008-10 showed 30% reduction in yield variability over the years. Following screening in hot-spots of both rust and LLS disease during 2014 rainy season, a total of 27 introgression lines derived from ICGV 91114 were selected and advanced for evaluation in multi-location trials at six locations in 2015 under rainfed conditions. Based on the pod yield under rainfed conditions and disease resistance, three superior introgression lines (ICGV 14410, ICGV 13189, ICGV 14421) were proposed for the first-ever NILs trial (near-isogenic lines trial) along with eight others conducted under All India Coordinated Research Project on Groundnut (AICRP-G) at national level

Not Available

Not AvailableDuring the past decade Sardinella longiceps hascontributed about 30 to 50% of the total fish catchalong the Goa coast. The annual oil sardine landingsin Goa during the year 2015 and 2016 was 16,212and 24951 tons (t) respectively. There are 20 landingcentres on the South Goa district and 14 landingcentres in the North Goa district. At Pale LandingCentre (150 22" 017’ N 0730 52" 552’ E) fishing 20shoreseine (Rampan) units are engaged in fishing.Not Availabl

DasPy 1.0 – the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized efficiently using the commonly used NetCDF file format. Online 1-D and 2-D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework