Efficiency Improvement of a Plant Layout

Abstract: Facilities layout is a systematic and functional arrangement of different departments, machines, equipments and services in a manufacturing industry. It is essential to have a well developed plant layout for all the available resources in an optimum manner and get the maximum out of the capacity of the facilities. The efficiency of production depends on how well the various machines, services production facilities and employee's amenities are located in a plant. This research paper aims to study and improve the current plant layout and are analysed & designed by using string diagram. An Attempt is made to simulate the current and proposed factory layout by using ARENA software. Efficiency of the current & proposed plant layout are calculated

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Abstract ---This paper presents a new genetic algorithm (GA)-based approach for the simultaneous power quality improvement and optimal placement and sizing of fixed capacitor banks and distributed generation DGs in radial distribution networks in the presence of voltage and current harmonics. The objective function includes the cost of power losses, energy losses, capacitor banks . Constraints include voltage limit, voltage THD, number/ size of (capacitor and generator) and power quality limit Candidate buses for capacitor placement and distributed generation are selected using the sensitivities of constraints and the objective function with respect to reactive power injection at each bus The effect of harmonics on reactive power compensation of radial distribution systems is studied in this paper. The problem of optimal capacitor and distributed generation sizing and placement is solved for a non-uniform radial distribution system with lateral sub-feeders with linear and non-linear loads distributed along the feeder. The voltage at each bus along the feeder after capacitor and DGs installation is calculated for each harmonic order

Staring Spells: An Age-based Approach Toward Differential Diagnosis

Evaluations to rule out epileptic vs nonepileptic staring spells may entail unnecessary evaluations that can be costly and time consuming. Our study aims to identify common etiologies for staring spells across 3 different pediatric age groups and to propose an age-based clinical guidance to help determine which patients warrant further workup. Methods: This was a single-center retrospective chart analysis of 1496 patients aged 0.0-17.9 years presenting with confirmed staring spell diagnosis from January 2011 to January 2021. The patients were divided into 3 groups based on their age: 0.0-2.9, 3.0-12.9, and 13.0-17.9 years. Patient information collected included demographics, clinical presentation, comorbidities, and final diagnosis. Multilevel likelihood ratios and a receiver operating characteristic curve were determined using 8 of the 11 clinical variables. A total of 1142 patients who met the inclusion criteria were included for the final analysis. The most common final diagnosis was attention-deficit hyperactivity disorder (ADHD) (35%), followed by normal behavior (33%). Generalized and focal epilepsy were diagnosed in 8% and 4% of the patients, respectively. In the 0.0-2.9-year age group, normal behavior was the final diagnosis in 72% patients. In the 3.0-12.9-year and 13.0-17.9-year age groups, ADHD was the most frequent final diagnosis in 46% and 60%, respectively. Overall, ADHD and normal behaviors remain the most common final diagnoses. Multilevel likelihood ratios can be used to develop an age-based guidance to differentiate between epileptic and nonepileptic staring spell diagnoses

Staring Spells in Children With Autism Spectrum Disorder: A Clinical Dilemma

Abstract To assess the role of clinical features in diagnosing seizures in children with autism spectrum disorder who present with staring spells. A 10-year retrospective chart analysis of autism spectrum disorder patients aged 3–14 years was performed at a tertiary care children’s hospital. Patient demographics, clinical presentation, and epileptic seizure versus non-epileptic spell diagnosis were assessed. Target episodes of staring spells were captured during a long-term electroencephalogram monitoring record. Multilevel likelihood ratios and a receiver operating characteristic curve were determined using 8 of the 11 clinical variables. Among the cohort of 140 patients with autism spectrum disorder, 16% were diagnosed with epileptic seizures with the most common seizure being atypical absence seizures (64%). Clinical semiology differed between those diagnosed with epileptic seizures versus those diagnosed with non-epileptic spells in the average duration of episodes (42 s vs 87 s), frequency of spells per week (6 vs 11.5 spells), increase in frequency of staring spells over time (100% vs 40%), and response to verbal stimulation (0% vs 100%), respectively. Multilevel likelihood ratios based on the receiver operating characteristic curves and clinical semiology features may be helpful in differentiating epileptic seizures from non-epileptic spells in children with autism spectrum disorder. Lay Abstract It is a common occurrence for children with autism spectrum disorder to be diagnosed with staring spells. Staring spells are defined as periods of time when children “space out” and are subcategorized as either “absence seizures” (brain activity resembling a seizure but with no physical seizure symptoms) or “non-epileptic spells” (inattentiveness or daydreaming). Due to the subtle characteristics of staring spells, they are usually diagnosed via long-term video electroencephalogram. The child is monitored for 3–5 days with an electroencephalogram which records brain waves. An electroencephalogram may be difficult to perform in children with autism spectrum disorder due to behavior, cognitive, or sensory concerns. Therefore, we wanted to investigate other clinical characteristics that may help us differentiate between epileptic seizures versus non-epileptic spells in children with autism spectrum disorder presenting with staring spells. We reviewed 140 charts retrospectively from the years of 2010–2021. We abstracted demographic and clinical information from the electronic medical record system and reviewed electroencephalogram videos to group the 140 children into epileptic seizure diagnosis group versus non-epileptic spell group. Of the 140 children in this study, 22 were diagnosed with epileptic seizures and the remaining were diagnosed with non-epileptic spells. We found that the two groups differed in certain clinical characteristics such as how long the staring spells lasted, how many staring spells the child had in 1 week, and whether they responded to verbal commands. We believe that clinical features may be helpful in differentiating epileptic seizures from non-epileptic spells in children with autism spectrum disorder

Staring Spells in Children With Autism Spectrum Disorder: A Clinical Dilemma

Abstract To assess the role of clinical features in diagnosing seizures in children with autism spectrum disorder who present with staring spells. A 10-year retrospective chart analysis of autism spectrum disorder patients aged 3–14 years was performed at a tertiary care children’s hospital. Patient demographics, clinical presentation, and epileptic seizure versus non-epileptic spell diagnosis were assessed. Target episodes of staring spells were captured during a long-term electroencephalogram monitoring record. Multilevel likelihood ratios and a receiver operating characteristic curve were determined using 8 of the 11 clinical variables. Among the cohort of 140 patients with autism spectrum disorder, 16% were diagnosed with epileptic seizures with the most common seizure being atypical absence seizures (64%). Clinical semiology differed between those diagnosed with epileptic seizures versus those diagnosed with non-epileptic spells in the average duration of episodes (42 s vs 87 s), frequency of spells per week (6 vs 11.5 spells), increase in frequency of staring spells over time (100% vs 40%), and response to verbal stimulation (0% vs 100%), respectively. Multilevel likelihood ratios based on the receiver operating characteristic curves and clinical semiology features may be helpful in differentiating epileptic seizures from non-epileptic spells in children with autism spectrum disorder. Lay Abstract It is a common occurrence for children with autism spectrum disorder to be diagnosed with staring spells. Staring spells are defined as periods of time when children “space out” and are subcategorized as either “absence seizures” (brain activity resembling a seizure but with no physical seizure symptoms) or “non-epileptic spells” (inattentiveness or daydreaming). Due to the subtle characteristics of staring spells, they are usually diagnosed via long-term video electroencephalogram. The child is monitored for 3–5 days with an electroencephalogram which records brain waves. An electroencephalogram may be difficult to perform in children with autism spectrum disorder due to behavior, cognitive, or sensory concerns. Therefore, we wanted to investigate other clinical characteristics that may help us differentiate between epileptic seizures versus non-epileptic spells in children with autism spectrum disorder presenting with staring spells. We reviewed 140 charts retrospectively from the years of 2010–2021. We abstracted demographic and clinical information from the electronic medical record system and reviewed electroencephalogram videos to group the 140 children into epileptic seizure diagnosis group versus non-epileptic spell group. Of the 140 children in this study, 22 were diagnosed with epileptic seizures and the remaining were diagnosed with non-epileptic spells. We found that the two groups differed in certain clinical characteristics such as how long the staring spells lasted, how many staring spells the child had in 1 week, and whether they responded to verbal commands. We believe that clinical features may be helpful in differentiating epileptic seizures from non-epileptic spells in children with autism spectrum disorder