437 research outputs found

    Reproductive strategies of the insidious fish ectoparasite, Neobenedenia sp. (Capsalidae: Monogenea)

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    Fish monogeneans are lethal parasites in aquaculture. We provide the first experimental evidence that a notorious fish monogenean, Neobenedenia sp., can produce viable eggs in isolation for three consecutive generations. We infected individual, isolated, farmed barramundi, Lates calcarifer (Bloch) with a single oncomiracidium (larva) of the hermaphroditic monogenean Neobenedenia sp. Isolated parasites reached sexual maturity at day 10 post-hatch (24°C, 35‰) and laid ~3,300 embryonated eggs over 17 days. Egg production rapidly increased following sexually maturity on day 10 (58±15 eggs) and peaked on day 15 (496±68 eggs) before gradually decreasing. Neobenedenia sp. exhibited egg laying and egg hatching rhythms. Parasites laid eggs continuously, but egg production increased in periods of darkness (64.3%), while the majority of oncomiracidia (81%) emerged from eggs in the first three hours of light. Eggs laid by isolated 'parent' parasites hatched and individual emerging oncomiracidia were used to infect more individual, isolated fish, with three consecutive, isolated, parasite generations (F1, F2 and F3) raised in the laboratory. Infection success and egg hatching success did not differ between generations. Our data show that one parasite, in the absence of a mate, presents a severe threat to captive fish populations

    Speculative parallelization of partially parallel loops

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    Current parallelizing compilers cannot identify a significant fraction of parallelizable loops because they have complex or statically insufficiently defined access patterns. In our previous work, we have speculatively executed a loop as a doall, and applied a fully parallel data dependence test to determine if it had any cross–processor depen- dences. If the test failed, then the loop was re–executed serially. While this method exploits doall parallelism well, it can cause slowdowns for loops with even one cross- processor flow dependence because we have to re-execute sequentially. Moreover, the existing, partial parallelism of loops is not exploited. We demonstrate a generalization of the speculative doall parallelization tech- nique, called the Recursive LRPD test, that can extract and exploit the maximum available parallelism of any loop and that limits potential slowdowns to the over- head of the run-time dependence test itself. In this thesis, we have presented the base algorithm and an analysis of the different heuristics for its practical applica- tion. To reduce the run-time overhead of the Recursive LRPD test, we have im- plemented on-demand checkpointing and commit, more efficient data dependence analysis and shadow structures, and feedback-guided load balancing. We obtained scalable speedups for loops from Track, Spice, and FMA3D that were not paralleliz- able by previous speculative parallelization methods

    Co-Morbidity of Pituitary Adenoma and Frontal Convexity Meningioma: A Case Report and Review of the Literature

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    Instruction: The current study reports a woman with pituitary adenoma and frontal convexity meningioma that was detected accidentially. To the best of our knowledge, this case is considered as a rare clinical scenario.Case presentation: A 37 years old woman suffering from amenorrhea and galactorrhea had her detail investigation showed hyperprolactinemia. The patient was diagnosed with a prolactinoma, and a frontal convexity meningioma was discovered on MRI. The prolactinoma controlled with Bromocriptine therapy, while the meningioma monitored through medical observation. After two months of pharmaceutical medication, her symptoms improved with the decrease in serum prolactin.Conclusion: Thanks to sophisticated MRI techniques, meningioma and prolactinoma were incidentally detected. It should be noted that co-morbidity of prolactinoma and meningioma is very rare. The mechanism of the association between these two familiar types of intracranial tumors has not yet been clarified, which indicates the need for further studies to offer possible targeted treatment for patients.Keyword: Meningiomas; Prolactinomas; Pituitary adenomas

    Light Absorption and Photoluminescence Quenching Properties of Bulk Heterojunction Materials Based on the Blend of Poly(n-vinylcarbazole)/poly(n-hexylthiophen)

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    The enhancement of light absorption and photoluminescence quenching properties of the bulk heterojunction systems which were fabricated using poly(N-vinylcarbazole) (PVK); poly(N-hexylthiophene)(P3HT) and fullerene derivative 1-(3-methoxycarbonyl) propyl-1-phenyl-[6,6] C61 (PCBM) were investigated. The optimized material showed a broad absorption in the region from ultra violet to near infra-red and the luminescence quenching higher than 90%. The obtained results provide further insight into photophysics of the heterojunction system and device performance improvement by using this system as an active layer

    Innovative Firm Performance Management Using a Recommendation System Based on Fuzzy Association Rules: The Case of Vietnam’s Apparel Small and Medium Enterprises

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    Purpose: This study aims to apply a classification algorithm based-on fuzzy association rules (FARs) to improve the effectiveness of firms' performance prediction problem. Particularly, this study investigates potential FARs exists between inputs and outputs of firms' performance management process. These extracted FARs could be used to help firm’s managers make better dicision to improve firm’s performance.   Theoretical framework: Private enterprise development has been identified as key to Vietnam's economy that was commonly depended on state enterprise. For that, understanding and improving firms' performance and productivity is one of the most important tasks, from both macro and micro perspectives. There have been many studies on Vietnam's firm performance, but mostly relying on econometric methods that limit the understanding with structural equations. This study, instead, attempts to utilize new achievements of Artificial Intelligence (AI) for this task. Among AI techniques, fuzzy association rule is able to address the relationship between input factors and firm performance indicators. For each company, the finding FARs can be used to predict its performance and then change the business plan or react to improve weekness of organization.   Design/Methodology/Approach: The proposal model is applied on data of small and medium-sized enterprises (SMEs) of the apparel industry in Vietnam in the period 2010-2015. The sample consist of a total of 23637 observation of  Vietnam firms in apparel and textile industry and contains 16 main criterias for those firms.   Finding: A recommendation system (RS) is constructed from disclosed FARs and is a key factor in a novel innovative firms' performance management process. The percentage of classified instances using the mining FARs is not quite high (about 82%), but it is not always the case. Vietnam’s apparel dataset includes rare classes of ROA, therefore applying only frequent FARs is not enough. This issue can be fixed by using both frequent and infrequent FARs.       Research, practical & social implications: The proposed model has a great opportunity to use not only in the small and medium-sized enterprises (SMEs) of the apparel industry but other industrial sectors. FARs support the well-understand of firm performance to firm’s manager and help them better to react. Besides, FARs could be used to create RSs that makes alerts about risk automatically.   Originality/Value: The fact, our current study is the first to inspect the ability of FARs on SMEs of the apparel industry in Vietnam. This study provides theoritical potential knowledge and empirical evidence in the application of FARs technology in innovative firm’s management

    An approach for linguistic multi-attribute decision making based on linguistic many-valued logic

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    There are various types of multi-attribute decision-making (MADM) problems in our daily lives and decision-making problems under uncertain environments with vague and imprecise information involved. Therefore, linguistic multi-attribute decision-making problems are an important type studied extensively. Besides, it is easier for decision-makers to use linguistic terms to evaluate/choose among alternatives in real life. Based on the theoretical foundation of the Hedge algebra and linguistic many-valued logic, this study aims to address multi-attribute decision-making problems by linguistic valued qualitative aggregation and reasoning method. In this paper, we construct a finite monotonous Hedge algebra for modeling the linguistic information related to MADM problems and use linguistic many-valued logic for deducing the outcome of decision making. Our method computes directly on linguistic terms without numerical approximation. This method takes advantage of linguistic information processing and shows the benefit of Hedge algebra
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