Genetic Algorithm Optimization Model for Determining the Probability of Failure on Demand of the Safety Instrumented System

A more accurate determination for the Probability of Failure on Demand (PFD) of the Safety Instrumented System (SIS) contributes to more SIS realiability, thereby ensuring more safety and lower cost. IEC 61508 and ISA TR.84.02 provide the PFD detemination formulas. However, these formulas suffer from an uncertaity issue due to the inclusion of uncertainty sources, which, including high redundant systems architectures, cannot be assessed, have perfect proof test assumption, and are neglegted in partial stroke testing (PST) of impact on the system PFD. On the other hand, determining the values of PFD variables to achieve the target risk reduction involves daunting efforts and consumes time. This paper proposes a new approach for system PFD determination and PFD variables optimization that contributes to reduce the uncertainty problem. A higher redundant system can be assessed by generalizing the PFD formula into KooN architecture without neglecting the diagnostic coverage factor (DC) and common cause failures (CCF). In order to simulate the proof test effectiveness, the Proof Test Coverage (PTC) factor has been incorporated into the formula. Additionally, the system PFD value has been improved by incorporating PST for the final control element into the formula. The new developed formula is modelled using the Genetic Algorithm (GA) artificial technique. The GA model saves time and effort to examine system PFD and estimate near optimal values for PFD variables. The proposed model has been applicated on SIS design for crude oil test separator using MATLAB. The comparison between the proposed model and PFD formulas provided by IEC 61508 and ISA TR.84.02 showed that the proposed GA model can assess any system structure and simulate industrial reality. Furthermore, the cost and associated implementation testing activities are reduced

Neural substrates and potential treatments for levodopa-induced dyskinesias in Parkinson's disease

Parkinson’s disease (PD) is primarily a motor disorder that involves the gradual loss of motor function. Symptoms are observed initially in the extremities, such as hands and arms, while advanced stages of the disease can effect blinking, swallowing, speaking, and breathing. PD is a neurodegenerative disease, with dopaminergic neuronal loss occurring in the substantia nigra pars compacta, thus disrupting basal ganglia functions. This leads to downstream effects on other neurotransmitter systems such as glutamate, γ-aminobutyric acid, and serotonin. To date, one of the main treatments for PD is levodopa. While it is generally very effective, prolonged treatments lead to levodopa-induced dyskinesia (LID). LID encompasses a family of symptoms ranging from uncontrolled repetitive movements to sustained muscle contractions. In many cases, the symptoms of LID can cause more grief than PD itself. The purpose of this review is to discuss the possible clinical features, cognitive correlates, neural substrates, as well as potential psychopharmacological and surgical (including nondopaminergic and deep brain stimulation) treatments of LID

The relationship between associative learning, transfer generalization, and homocysteine levels in mild cognitive impairment

Previous studies have shown that high total homocysteine levels are associated with Alzheimer's disease (AD) and mild cognitive impairment (MCI). In this study, we test the relationship between cognitive function and total homocysteine levels in healthy subjects (Global Dementia Rating, CDR = 0) and individuals with MCI (CDR = 0.5). We have used a cognitive task that tests learning and generalization of rules, processes that have been previously shown to rely on the integrity of the striatal and hippocampal regions, respectively. We found that total homocysteine levels are higher in MCI individuals than in healthy controls. Unlike what we expected, we found no difference between MCI subjects and healthy controls in learning and generalization. We conducted further analysis after diving MCI subjects in two groups, depending on their Global Deterioration Scale (GDS) scores: individuals with very mild cognitive decline (vMCD, GDS = 2) and mild cognitive decline (MCD, GDS = 3). There was no difference among the two MCI and healthy control groups in learning performance. However, we found that individuals with MCD make more generalization errors than healthy controls and individuals with vMCD. We found no difference in the number of generalization errors between healthy controls and MCI individuals with vMCD. In addition, interestingly, we found that total homocysteine levels correlate positively with generalization errors, but not with learning errors. Our results are in agreement with prior results showing a link between hippocampal function, generalization performance, and total homocysteine levels. Importantly, our study is perhaps among the first to test the relationship between learning (and generalization) of rules and homocysteine levels in healthy controls and individuals with MCI

Energy Efficiency Improvements in Smart Grid Components

This book is intended for academics and engineers who are working in universities, research institutes, utility and industry sectors wishing to enhance their idea and get new information about the energy efficiency developments in smart grid. The readers will gain special experience with deep information and new idea about the energy efficiency topics. This book includes lots of problems and solutions that can easily be understood and integrated into larger projects and researches. The book enables some studies about monitoring, management and measures related to smart grid components, Energy Efficiency Improvements in smart grid components and new intelligent Control strategies for Distributed energy resources, boosting PV systems, electrical vehicles, etc. It included optimization concepts for power system, promoting value propositions; protection in power system, etc. The book also has some recent developments in solar cell technologies, LEDs and non thermal plasma technology. As I enjoyed preparing this book I am sure that it will be very valuable for large sector of readers

Late Cenomanian ostracod faunas from the area south of Ain Sukhna, western side of the Gulf of Suez, Egypt

Ostracod faunas from an exposure of the Cenomanian Galala Formation in the area south of Ain Sukhna on the western side of the Gulf of Suez have yielded 11 species belonging to 10 genera. The recorded speciesare have been taxonomically described, discussed where required, and illustrated. The ostracod assemblage is characteristic for the late Cenomanian. It is composed of taxa of a typical marine shelf setting. The majority of the recorded species have a vastly extended geographic distribution in the areas along the southern shores of Tethys, indicating the absence of significant geographic barriers along this stretch during the late Cenomanian

Late Cenomanian ostracod faunas from the area south of Ain Sukhna, western side of the Gulf of Suez, Egypt

Ostracod faunas from an exposure of the Cenomanian Galala Formation in the area south of Ain Sukhna on the western side of the Gulf of Suez have yielded 11 species belonging to 10 genera. The recorded speciesare have been taxonomically described, discussed where required, and illustrated. The ostracod assemblage is characteristic for the late Cenomanian. It is composed of taxa of a typical marine shelf setting. The majority of the recorded species have a vastly extended geographic distribution in the areas along the southern shores of Tethys, indicating the absence of significant geographic barriers along this stretch during the late Cenomanian

Neural substrates and potential treatments for levodopa-induced dyskinesias in Parkinson's disease

Parkinson's disease (PD) is primarily a motor disorder that involves the gradual loss of motor function. Symptoms are observed initially in the extremities, such as hands and arms, while advanced stages of the disease can effect blinking, swallowing, speaking, and breathing. PD is a neurodegenerative disease, with dopaminergic neuronal loss occurring in the substantia nigra pars compacta, thus disrupting basal ganglia functions. This leads to downstream effects on other neurotransmitter systems such as glutamate, gamma-aminobutyric acid, and serotonin. To date, one of the main treatments for PD is levodopa. While it is generally very effective, prolonged treatments lead to levodopa-induced dyskinesia (LID). LID encompasses a family of symptoms ranging from uncontrolled repetitive movements to sustained muscle contractions. In many cases, the symptoms of LID can cause more grief than PD itself. The purpose of this review is to discuss the possible clinical features, cognitive correlates, neural substrates, as well as potential psychopharmacological and surgical (including nondopaminergic and deep brain stimulation) treatments of LID

Factors underlying probabilistic and deterministic stimulus-response learning performance in medicated and unmedicated patients with Parkinson's disease

Objective: Prior studies have not tested individual differences or effects of medication dosage on stimulus-response learning in patients with Parkinson's disease (PD). In the current study, we investigated the effects of motor variables (including tremor, akinesia, and disease duration) as well as dopaminergic medication dosage on learning in unmedicated PD patients, medicated PD patients, and healthy controls. Method: We tested all subjects on probabilistic and deterministic learning tasks, and also collected awareness measures data using postexperimental questionnaires. Importantly, we tested learning performance in tremor-dominant and akinesia-dominant PD patients, and further correlated learning performance with disease duration and medication dosage. Results: Results show that akinesia-dominant patients were more impaired than tremor-dominant patients at probabilistic rewardbut not punishment-based learning, which is in agreement with prior studies of the relationship between akinesia and basal ganglia dysfunction. We also found no difference between medicated and unmedicated PD patients in reward- or punishment-based deterministic learning, but medicated patients were better than unmedicated patients at reward-based probabilistic learning. Our results show that awareness measures explain differences among probabilistic and deterministic learning performance. Moreover, we found that disease duration and motor severity are inversely correlated, and medication dosage is positively correlated, with reward-based probabilistic learning. Conclusion: Our results suggest that stimulus-response learning performance in patients with PD depends on the type of learning (probabilistic vs. deterministic), medication status (on vs. off medication, dopaminergic medication dosage), disease duration as well as motor severity and subtype in PD patients (tremor- vs. akinesia-dominant)