68 research outputs found

    Impact of Corporate Governance Practices on Firm Capital Structure and Profitability: A Study of Selected Hotels and Restaurant Companies in Sri Lanka.

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    Corporate governance issues have been a growing area of management research especially among large and listed firms. Good corporate governance practices are regarded as important in reducing risk for investors, attracting investment capital and improving the performance of companies. Companies need financial resources and better earnings to promote their objectives. Therefore, factorsmay affect the capital structure and profitability of companies should be considered carefully. The purpose of the present study is to investigate whether there is any relationship among some specific characters of corporate governance, capital structure and profitability of listedHotels &Restaurant companies in Colombo Stock Exchange (CSE). To do so, 18 companies were selected from those which were listed inCSE during the 2007-2012. The ‘Board Composition(BC)’, ‘Board Size (BS)’ and ‘CEOduality (CEOD)’ were considered as independent variables, whereas,’ Debt Ratio(DR)’,‘Debt-to-Equity Ratio(DER)’,‘Returns on Equity(ROE)’,and ‘Return on Assets(ROA)’ as dependent variable. The results indicate a positive relationship between ‘BS; BC; CEOD; ROE; ROA and DERwhereas negative relationship between BS; BID and DR.in addition CEOD have a positive relationship with DR.In addition, none of the variables have a significant relationship with capital structure and profitability. Key words: Corporate Governance; Capital Structure and Profitability

    On the nature of progress

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    15th International Conference, OPODIS 2011, Toulouse, France, December 13-16, 2011. ProceedingsWe identify a simple relationship that unifies seemingly unrelated progress conditions ranging from the deadlock-free and starvation-free properties common to lock-based systems, to non-blocking conditions such as obstruction-freedom, lock-freedom, and wait-freedom. Properties can be classified along two dimensions based on the demands they make on the operating system scheduler. A gap in the classification reveals a new non-blocking progress condition, weaker than obstruction-freedom, which we call clash-freedom. The classification provides an intuitively-appealing explanation why programmers continue to devise data structures that mix both blocking and non-blocking progress conditions. It also explains why the wait-free property is a natural basis for the consensus hierarchy: a theory of shared-memory computation requires an independent progress condition, not one that makes demands of the operating system scheduler

    Efficient Symmetry Reduction and the Use of State Symmetries for Symbolic Model Checking

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    One technique to reduce the state-space explosion problem in temporal logic model checking is symmetry reduction. The combination of symmetry reduction and symbolic model checking by using BDDs suffered a long time from the prohibitively large BDD for the orbit relation. Dynamic symmetry reduction calculates representatives of equivalence classes of states dynamically and thus avoids the construction of the orbit relation. In this paper, we present a new efficient model checking algorithm based on dynamic symmetry reduction. Our experiments show that the algorithm is very fast and allows the verification of larger systems. We additionally implemented the use of state symmetries for symbolic symmetry reduction. To our knowledge we are the first who investigated state symmetries in combination with BDD based symbolic model checking

    Disrupted nitric oxide signaling due to GUCY1A3 mutations increases risk for moyamoya disease, achalasia and hypertension

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    Moyamoya disease (MMD) is a progressive vasculopathy characterized by occlusion of the terminal portion of the internal carotid arteries and its branches, and the formation of compensatory moyamoya collateral vessels. Homozygous mutations in GUCY1A3 have been reported as a cause of MMD and achalasia. Probands (n = 96) from unrelated families underwent sequencing of GUCY1A3. Functional studies were performed to confirm the pathogenicity of identified GUCY1A3 variants. Two affected individuals from the unrelated families were found to have compound heterozygous mutations in GUCY1A3. MM041 was diagnosed with achalasia at 4 years of age, hypertension and MMD at 18 years of age. MM149 was diagnosed with MMD and hypertension at the age of 20 months. Both individuals carry one allele that is predicted to lead to haploinsufficiency and a second allele that is predicted to produce a mutated protein. Biochemical studies of one of these alleles, GUCY1A3 Cys517Tyr, showed that the mutant protein (a subunit of soluble guanylate cyclase) has a significantly blunted signaling response with exposure to nitric oxide (NO). GUCY1A3 missense and haploinsufficiency mutations disrupt NO signaling leading to MMD and hypertension, with or without achalasia

    High-throughput sequence alignment using Graphics Processing Units

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    <p>Abstract</p> <p>Background</p> <p>The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and <it>de novo </it>genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies.</p> <p>Results</p> <p>This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs) in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA) from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies.</p> <p>Conclusion</p> <p>MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU.</p

    Clinical history and management recommendations of the smooth muscle dysfunction syndrome due to ACTA2 arginine 179 alterations

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    Smooth muscle dysfunction syndrome (SMDS) due to heterozygous ACTA2 arginine 179 alterations is characterized by patent ductus arteriosus, vasculopathy (aneurysm and occlusive lesions), pulmonary arterial hypertension, and other complications in smooth muscle-dependent organs. We sought to define the clinical history of SMDS to develop recommendations for evaluation and management. Medical records of 33 patients with SMDS (median age 12 years) were abstracted and analyzed. All patients had congenital mydriasis and related pupillary abnormalities at birth and presented in infancy with a patent ductus arteriosus or aortopulmonary window. Patients had cerebrovascular disease characterized by small vessel disease (hyperintense periventricular white matter lesions; 95%), intracranial artery stenosis (77%), ischemic strokes (27%), and seizures (18%). Twelve (36%) patients had thoracic aortic aneurysm repair or dissection at median age of 14 years and aortic disease was fully penetrant by the age of 25 years. Three (9%) patients had axillary artery aneurysms complicated by thromboembolic episodes. Nine patients died between the ages of 0.5 and 32 years due to aortic, pulmonary, or stroke complications, or unknown causes. Based on these data, recommendations are provided for the surveillance and management of SMDS to help prevent early-onset life-threatening complications

    Active memory controller

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    Inability to hide main memory latency has been increasingly limiting the performance of modern processors. The problem is worse in large-scale shared memory systems, where remote memory latencies are hundreds, and soon thousands, of processor cycles. To mitigate this problem, we propose an intelligent memory and cache coherence controller (AMC) that can execute Active Memory Operations (AMOs). AMOs are select operations sent to and executed on the home memory controller of data. AMOs can eliminate a significant number of coherence messages, minimize intranode and internode memory traffic, and create opportunities for parallelism. Our implementation of AMOs is cache-coherent and requires no changes to the processor core or DRAM chips. In this paper, we present the microarchitecture design of AMC, and the programming model of AMOs. We compare AMOs\u27 performance to that of several other memory architectures on a variety of scientific and commercial benchmarks. Through simulation, we show that AMOs offer dramatic performance improvements for an important set of data-intensive operations, e.g., up to 50x faster barriers, 12x faster spinlocks, 8.5x-15x faster stream/array operations, and 3x faster database queries. We also present an analytical model that can predict the performance benefits of using AMOs with decent accuracy. The silicon cost required to support AMOs is less than 1% of the die area of a typical high performance processor, based on a standard cell implementation

    Algorithms for Scalable Synchronization on Shared-Memory Multiprocessors

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    Busy-wait techniques are heavily used for mutual exclusion and barrier synchronization in shared-memory parallel programs. Unfortunately, typical implementations of busy-waiting tend to produce large amounts of memory and interconnect contention, introducing performance bottlenecks that become markedly more pronounced as applications scale. We argue that this problem is not fundamental, and that one can in fact construct busy-wait synchronization algorithms that induce no memory or interconnect contention. The key to these algorithms is for every processor to spin on separate locally-accessible ag variables, and for some other processor to terminate the spin with a single remote write operation at an appropriate time. Flag variables may be locally-accessible as a result of coherent caching, or by virtue of allocation in the local portion of physically distributed shared memory. We present a new scalable algorithm for spin locks that generates O(1) remote references per lock acquisition, independent of the number of processors attempting to acquire the lock. Our algorithm provides reasonable latency in the absence of contention, requires only a constant amount of space per lock, and requires no hardware support other tha
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