Artificial neural network for non-intrusive electrical energy monitoring system

This paper discusses non-intrusive electrical energy monitoring (NIEM) system in an effort to minimize electrical energy wastages. To realize the system, an energy meter is used to measure the electrical consumption by electrical appliances. The obtained data were analyzed using a method called multilayer perceptron (MLP) technique of artificial neural network (ANN). The event detection was implemented to identify the type of loads and the power consumption of the load which were identified as fan and lamp. The switching ON and OFF output events of the loads were inputted to MLP in order to test the capability of MLP in classifying the type of loads. The data were divided to 70% for training, 15% for testing, and 15% for validation. The output of the MLP is either ‘1’ for fan or ‘0’ for lamp. In conclusion, MLP with five hidden neurons results obtained the lowest average training time with 2.699 seconds, a small number of epochs with 62 iterations, a min square error of 7.3872×10-5, and a high regression coefficient of 0.99050

Palm oil mill effluent treatment using coconut shell - Based activated carbon: Adsorption equilibrium and isotherm

The current ponding system applied for palm oil mill effluent (POME) treatment often struggle to comply with the POME discharge limit, thus it has become a major environmental concern. Batch adsorption study was conducted for reducing the Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and Color of pre-treated POME using coconut shell-based activated carbon (CS-AC). The CS-AC showed BET surface area of 744.118 m2/g, with pore volume of 04359cm3/g. The adsorption uptake was studied at various contact time and POME initial concentration. The CS-AC exhibited good ability with average percentage removal of 70% for COD, TSS and Color. The adsorption uptake increased over time and attained equilibrium in 30 hours. The equilibrium data were analyzed using the Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherm models. Based on the coefficient regression and sum of squared errors, the Langmuir isotherm described the adsorption of COD satisfactorily, while best described the TSS and Color adsorption; giving the highest adsorption capacity of 10.215 mg/g, 1.435 mg/g, and 63.291 PtCo/g respectively. The CS-AC was shown to be a promising adsorbent for treating POME and was able to comply with the Environmental Quality Act (EQA) discharge limit. The outcome of treated effluent using CS-AC was shown to be cleaner than the industrial biologically treated effluent, achieved within shorter treatment tim

Screening for affective dysregulation in school-aged children: relationship with comprehensive measures of affective dysregulation and related mental disorders

Affective dysregulation (AD) is characterized by irritability, severe temper outbursts, anger, and unpredictable mood swings, and is typically classified as a transdiagnostic entity. A reliable and valid measure is needed to adequately identify children at risk of AD. This study sought to validate a parent-rated screening questionnaire, which is part of the comprehensive Diagnostic Tool for Affective Dysregulation in Children (DADYS-Screen), by analyzing relationships with comprehensive measures of AD and related mental disorders in a community sample of children with and without AD. The sample comprised 1114 children aged 8–12 years and their parents. We used clinical, parent, and child ratings for our analyses. Across all raters, the DADYS-Screen showed large correlations with comprehensive measures of AD. As expected, correlations were stronger for measures of externalizing symptoms than for measures of internalizing symptoms. Moreover, we found negative associations with emotion regulation strategies and health-related quality of life. In receiver operating characteristic (ROC) analyses, the DADYS-Screen adequately identified children with AD and provided an optimal cut-off. We conclude that the DADYS-Screen appears to be a reliable and valid measure to identify school-aged children at risk of AD

Rapid Colorimetric Detection of Pseudomonas aeruginosa in Clinical Isolates Using a Magnetic Nanoparticle Biosensor

A rapid, sensitive, and specific colorimetric biosensor based on the use of magnetic nanoparticles (MNPs) was designed for the detection of Pseudomonas aeruginosa in clinical samples. The biosensing platform was based on the measurement of P. aeruginosa proteolytic activity using a specific protease substrate. At the N-terminus, this substrate was covalently bound to MNPs and was linked to a gold sensor surface via cystine at the C-terminus of the substrates. The golden sensor appears black to naked eyes because of the coverage of the MNPs. However, upon proteolysis, the cleaved peptide-MNP moieties will be attracted by an external magnet, revealing the golden color of the sensor surface, which can be observed by the naked eye. In vitro, the biosensor was able to detect specifically and quantitatively the presence of P. aeruginosa with a detection limit of 102 cfu/mL in less than 1 min. The colorimetric biosensor was used to test its ability to detect in situ P. aeruginosa in clinical isolates from patients. This biochip is anticipated to be useful as a rapid point-of-care device for the diagnosis of P. aeruginosa-related infections

Impact of the COVID-19 pandemic on children with and without affective dysregulation and their families

Analyzing COVID-19-related stress in children with affective dysregulation (AD) seems especially interesting, as these children typically show heightened reactivity to potential stressors and an increased use of maladaptive emotion regulation strategies. Children in out-of-home care often show similar characteristics to those with AD. Since COVID-19 has led to interruptions in psychotherapy for children with mental health problems and to potentially reduced resources to implement treatment strategies in daily life in families or in out-of-home care, these children might show a particularly strong increase in stress levels. In this study, 512 families of children without AD and 269 families of children with AD reported on COVID-19-related stress. The sample comprised screened community, clinical, and out-of-home care samples. Sociodemographic factors, characteristics of child and caregiver before the pandemic, and perceived change in external conditions due to the pandemic were examined as potential risk or protective factors. Interestingly, only small differences emerged between families of children with and without AD or between subsamples: families of children with AD and families in out-of-home care were affected slightly more, but in few domains. Improvements and deteriorations in treatment-related effects balanced each other out. Overall, the most stable and strongest risk factor for COVID-19-related stress was perceived negative change in external conditions—particularly family conditions and leisure options. Additionally, caregiver characteristics emerged as risk factors across most models. Actions to support families during the pandemic should, therefore, facilitate external conditions and focus on caregiver characteristic to reduce familial COVID-19-related stress. Trial registration: German Clinical Trials Register (DRKS), ADOPT Online: DRKS00014963 registered 27 June 2018, ADOPT Treatment: DRKS00013317 registered 27 September 2018, ADOPT Institution: DRKS00014581 registered 04 July 2018