MULTILATERAL GOVERNANCE OF FISHERIES: MANAGEMENT AND COOPERATION IN THE WESTERN AND CENTRAL PACIFIC TUNA FISHERIES

The tuna resources of the Western and Central Pacific are the world's largest and most valuable fisheries of their type and are of significant economic importance to the Pacific island countries through whose waters they migrate. Two major concerns exist with the current governance of this fishery. First, Pacific island countries receive only a small share of the resource rents from the tuna fisheries. Second, the current management structure of the fisheries will not ensure the long-term sustainability of the resources. This paper derives a model to show that the sustainability of the resource can be improved when a single policymaker acts as Stackelberg leader and sets a tax, or an equivalent quantity instrument, to maximize rents from the resource. A practical institutional mechanism is presented that mimics the model's rent maximization outcome and that offers substantial benefits to both Pacific island countries and distant water fishing nations.Resource /Energy Economics and Policy,

AN INTRIGUING CAUSE OF CHRONIC DIARRHEA – PROTEIN-LOSING ENTEROPATHY AS THE PRESENTING MANIFESTATION OF SYSTEMIC LUPUS ERYTHEMATOSUS

ABSTRACTSystemic lupus erythematosus (SLE) is a systemic autoimmune inflammatory disease.  It presents with myriad of clinical manifestations affecting every other organ system in human body. The gastrointestinal system is one of the commonest affected and it involves any part of the GI tract with incidences ranging from 1.3% to 27.5%. Gastrointestinal manifestations as a presenting feature of SLE is unusual. Chronic diarrhea due to protein losing enteropathy as the presenting manifestation of SLE is very rare and a diagnosis of SLE should be kept in mind when other systemic manifestations are absent. Hence, we report a 29-year-old female with chronic diarrhea as the main manifestation of SLE.Â

Nature Plus Plus Inspired Computing - The Superset of Nature Inspired Computing

The term Nature Plus Plus Inspired Computing is coined by us in this article The abbreviation for this new term is N IC Just like the C programming language is a superset of C programming language Nature Plus Plus Inspired Computing N IC field is a superset of the Nature Inspired Computing NIC field We defined and introduced Nature Plus Plus Inspired Computing Field in this work Several interesting opportunities in N IC Field are shown for Artificial Intelligence Field Scientists and Students We show a literature review of the N IC Field after showing the definition of Nature Inspired Computing NIC Field The primary purpose of publishing this innovative article is to show a new path to NIC Field Scientists so that they can come up with various innovative algorithms from scratch As the focus of this article is to introduce N IC to researchers across the globe we added N IC Field concepts to the Particle Swarm Optimization algorithm and created the Children Cycle Riding Algorithm CCR Algorithm Finally results obtained by CCR Algorithm are shown followed by Conclusion

An Artificial Human Optimization Algorithm titled Human Thinking Particle Swarm Optimization

Artificial Human Optimization is a latest field proposed in December 2016. Just like artificial Chromosomes are agents for Genetic Algorithms, similarly artificial Humans are agents for Artificial Human Optimization Algorithms. Particle Swarm Optimization is very popular algorithm for solving complex optimization problems in various domains. In this paper, Human Thinking Particle Swarm Optimization (HTPSO) is proposed by applying the concept of thinking of Humans into Particle Swarm Optimization. The proposed HTPSO algorithm is tested by applying it on various benchmark functions. Results obtained by HTPSO algorithm are compared with Particle Swarm Optimization algorithm.  &nbsp

Testing Multiple Strategy Human Optimization based Artificial Human Optimization Algorithms

Recently a new trend titled ‘Artificial Human Optimization’ has become popular in Evolutionary Computing Domain. More than 30 papers were published in this new field proposed in December 2016. ‘Hassan Satish Particle Swarm Optimization (HSPSO)’ and ‘Human Inspired Differential Evolution (HIDE)’ are the two latest Artificial Human Optimization algorithms proposed based on Multiple Strategy Human Optimization. In this paper we focus on Testing HSPSO and HIDE by applying these latest algorithms on Ackley, Bohachevsky, Booth, Three-Hump Camel and Beale benchmark functions. Results obtained for these Artificial Human Optimization Algorithms are compared with Differential Evolution and Particle Swarm Optimization

Artificial Satisfaction - The Brother of Artificial Intelligence

John McCarthy (September 4, 1927 2013; October 24, 2011) was an American computer scientist and cognitive scientist. The term 201C;Artificial Intelligence201D; was coined by him (Wikipedia, 2020). Satish Gajawada (March 12, 1988 2013; Present) is an Indian Independent Inventor and Scientist. He coined the term 201C;Artificial Satisfaction201D; in this article (Gajawada, S., and Hassan Mustafa, 2019a). A new field titled 201C;Artificial Satisfaction201D; is introduced in this article. 201C;Artificial Satisfaction201D; will be referred to as 201C;The Brother of Artificial Intelligence201D; after the publication of this article. A new algorithm titled 201C;Artificial Satisfaction Algorithm (ASA)201D; is designed and implemented in this work. For the sake of simplicity, Particle Swarm Optimization (PSO) Algorithm is modified with Artificial Satisfaction Concepts to create the 201C;Artificial Satisfaction Algorithm (ASA).201D; PSO and ASA algorithms are applied on five benchmark functions. A comparision is made between the results obtained. The focus of this paper is more on defining and introducing 201C;Artificial Satisfaction Field201D; to the rest of the world rather than on implementing complex algorithms from scratch