Assessment of climate change vulnerability of farm households in Pyapon District, a delta region in Myanmar

Sea level rise causes saltwater intrusion and flooding of agricultural land and ultimately threatens the livelihoods of farm households in the delta region of Myanmar. Empirical research on the effects of climate change on the delta's agriculture and an assessment of the vulnerability are becoming necessary. This study explores the vulnerability of farm households to sea level rise using two methods: the Livelihood Vulnerability Index (LVI), which is comprised of 37 indicators, and the Socioeconomic Vulnerability Index (SeVI), which contains 35 indicators. Interviews with 178 farmers were conducted in Bogale, Pyapon and Dedaye Townships in Pyapon District. In addition, 7 focus group discussions were performed, with at least 2 discussions in each Township. Both methods identify Bogale to be the most vulnerable Township, followed by Dedaye and Pyapon Townships. Following the LVI approach, Bogale Township has the highest sensitivity to climate effects and the highest exposure to natural hazards, but also a higher adaptive capacity than the other townships. In contrast using the SeVI approach, Bogale was found to have the highest sensitivity and exposure to natural hazards but the lowest adaptive capacity score. The study found that the climate change adaptation measures taken by the farmers are important to limit vulnerable to the adverse effects of climate change and thus promotion of the adaptive capacity of farmers is important for the delta region of Myanmar

Genetic heterogeneity of porcine enteric caliciviruses identified from diarrhoeic piglets

Enteric caliciviruses (noroviruses and sapoviruses) are responsible for the majority of non-bacterial gastroenteritis in humans of all age groups. Analysis of the polymerase and capsid genes has provided evidence for a huge genetic diversity, but the understanding of their ecology is limited. In this study, we investigated the presence of porcine enteric caliciviruses in the faeces of piglets with diarrhoea. A total of 209 samples from 118 herds were analyszd and calicivirus RNA was detected by RT-PCR in 68 sample (32.5%) and in 46 herds (38.9%), alone or in mixed infection with group A and C rotaviruses. Sequence and phylogenetic analysis of the calicivirus-positive samples characterized the majority as genogroup III (GGIII) sapoviruses. Unclassified caliciviruses, distantly related to the representatives of the other sapovirus genogroups, were identified in five herds, while one outbreak was associated with a porcine sapovirus related genetically to human GGII and GGIV sapovirus strains. By converse, norovirus strains were not detected. Altogether, these data suggest the epidemiological relevance of porcine enteric caliciviruses and suggest a role in the etiology of piglets diarrhoe

West Nile virus transmission. results from the integrated surveillance system in Italy, 2008 to 2015

IIn Italy a national Plan for the surveillance of imported and autochthonous human vector-borne diseases (chikungunya, dengue, Zika virus disease and West Nile virus (WNV) disease) that integrates human and veterinary (animals and vectors) surveillance, is issued and revised annually according with the observed epidemiological changes. Here we describe results of the WNV integrated veterinary and human surveillance systems in Italy from 2008 to 2015. A real time data exchange protocol is in place between the surveillance systems to rapidly identify occurrence of human and animal cases and to define and update the map of affected areas i.e. provinces during the vector activity period from June to October. WNV continues to cause severe illnesses in Italy during every transmission season, albeit cases are sporadic and the epidemiology varies by virus lineage and geographic area. The integration of surveillance activities and a multidisciplinary approach made it possible and have been fundamental in supporting implementation of and/or strengthening preventive measures aimed at reducing the risk of transmission of WNV trough blood, tissues and organ donation and to implementing further measures for vector control

Software development effort estimation using function points and simpler functional measures: a comparison

Background-Functional Size Measures are widely used for estimating the development effort of software. After the introduction of Function Points, a few "simplified"measures have been proposed, aiming to make measurement simpler and quicker, but also to make measures applicable when fully detailed software specifications are not yet available. It has been shown that, in general, software size measures expressed in Function Points do not support more accurate effort estimation with respect to simplified measures. Objective-Many practitioners believe that when considering "complex"projects, i.e., project that involve many complex transactions and data, traditional Function Points measures support more accurate estimates than simpler functional size measures that do not account for greater-Then-Average complexity. In this paper, we aim to produce evidence that confirms or disproves such belief. Method-Based on a dataset that contains both effort and size data, an empirical study is performed, to provide some evidence concerning the relations that link functional size (measured in different ways) and development effort. Results-Our analysis shows that there is no statistically significant evidence that Function Points are generally better at estimating more complex projects than simpler measures. Function Points appeared better in some specific conditions, but in those conditions they also performed worse than simpler measures when dealing with less complex projects. Conclusions-Traditional Function Points do not seem to effectively account for software complexity. To improve effort estimation, researchers should probably dedicate their effort to devise a way of measuring software complexity that can be used in effort models together with (traditional or simplified) functional size measures

Estimating functional size of software with confidence intervals

In many projects, software functional size is measured via the IFPUG (International Function Point Users Group) Function Point Analysis method. However, applying Function Point Analysis using the IFPUG process is possible only when functional user requirements are known completely and in detail. To solve this problem, several early estimation methods have been proposed and have become de facto standard processes. Among these, a prominent one is the ‘NESMA (Netherlands Software Metrics Association) estimated’ (also known as High-level Function Point Analysis) method. The NESMA estimated method simplifies the measurement by assigning fixed weights to Base Functional Components, instead of determining the weights via the detailed analysis of data and transactions. This makes the process faster and cheaper, and applicable when some details concerning data and transactions are not yet known. The accuracy of the mentioned method has been evaluated, also via large-scale empirical studies, showing that the yielded approximate measures are sufficiently accurate for practical usage. However, a limitation of the method is that it provides a specific size estimate, while other methods can provide confidence intervals, i.e., they indicate with a given confidence level that the size to be estimated is in a range. In this paper, we aim to enhance the NESMA estimated method with the possibility of computing a confidence interval. To this end, we carry out an empirical study, using data from real-life projects. The proposed approach appears effective. We expect that the possibility to estimate that the size of an application is in a range will help project managers deal with the risks connected with inevitable estimation errors

COVID-19 and Biomedical Experts: When Epistemic Authority is (Probably) Not Enough

This critical essay evaluates the potential integration of distinct kinds of expertise in policymaking, especially during situations of critical emergencies, such as the COVID-19 pandemic. This article relies on two case studies: (i) herd immunity (UK) and (ii) restricted access to ventilators for disabled people (USA). These case studies are discussed as examples of experts’ recommendations that have not been widely accepted, though they were made within the boundaries of expert epistemic authority. While the fundamental contribution of biomedical experts in devising public health policies during the COVID-19 pandemic is fully recognized, this paper intends to discuss potential issues and limitations that may arise when adopting a strict expert-based approach. By drawing attention to the interests of minorities (disenfranchized and underrepresented groups), the paper also claims a broader notion of “relevant expertise.” This critical essay thus calls for the necessity of wider inclusiveness and representativeness in the process underlying public health policymaking

The GOODSTEP project: General Object-Oriented Database for Software Engineering Processes

The goal of the GOODSTEP project is to enhance and improve the functionality of a fully object-oriented database management system to yield a platform suited for applications such as software development environments (SDEs). The baseline of the project is the O2 database management system (DBMS). The O2 DBMS already includes many of the features regulated by SDEs. The project has identified enhancements to O2 in order to make it a real software engineering DBMS. These enhancements are essentially upgrades of the existing O2 functionality, and hence require relatively easy extensions to the O2 system. They have been developed in the early stages of the project and are now exploited and validated by a number of software engineering tools built on top of the enhanced O2 DBMS. To ease tool construction, the GOODSTEP platform encompasses tool generation capabilities which allow for generation of integrated graphical and textual tools from high-level specifications. In addition, the GOODSTEP platform provides a software process toolset which enables modeling, analysis and enaction of software processes and is also built on top of the extended O2 database. The GOODSTEP platform is to be validated using two CASE studies carried out to develop an airline application and a business application