An economic investigation of the wind-hydrogen projects: A case study

Hydrogen as an energy carrier can play a significant role in reducing environmental emissions if it is produced from renewable energy resources. This research aims to assess hydrogen production from wind energy considering environmental, economic, and technical aspect for the East Azerbaijan province of Iran. The economic assessment is performed by calculation of payback period, levelized cost of hydrogen, and levelized cost of electricity. Since uncertainty in the power output of wind turbines may affect the payback period, all calculations are performed for four different turbine degradation rates. While it is common in the literature to choose the wind turbine based on a single criterion, this study implements Multi-Criteria Decision-Making (MCDM) techniques for this purpose. The results of Step-wise Weight Assessment Ratio Analysis illustrates that economic issue is the most important criterion for this research. The results of Weighted Aggregated Sum Product Assessment shows that Vestas V52 is the most suitable wind turbine for Ahar and Sarab cities, while Eovent EVA120 H-Darrieus is a better choice for other stations. The most suitable location for wind power generation is found to be Ahar, where it is estimated to annually generate 2914.8 kWh of electricity at the price of 0.045 $/kWh, and 47.2 tons of hydrogen at the price of 1.38 $/kg, which result in 583 tons of CO₂ emission reduction.     

A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

OWL‐based acquisition and editing of computer‐interpretable guidelines with the CompGuide editor

Computer‐Interpretable Guidelines (CIGs) are the dominant medium for the delivery of clinical decision support, given the evidence‐based nature of their source material. Therefore, these machine‐readable versions have the ability to improve practitioner performance and conformance to standards, with availability at the point and time of care. The formalisation of Clinical Practice Guideline knowledge in a machine‐readable format is a crucial task to make it suitable for the integration in Clinical Decision Support Systems. However, the current tools for this purpose reveal shortcomings with respect to their ease of use and the support offered during CIG acquisition and editing. In this work, we characterise the current landscape of CIG acquisition tools based on the properties of guideline visualisation, organisation, simplicity, automation, manipulation of knowledge elements, and guideline storage and dissemination. Additionally, we describe the CompGuide Editor, a tool for the acquisition of CIGs in the CompGuide model for Clinical Practice Guidelines that also allows the editing of previously encoded guidelines. The Editor guides the users throughout the process of guideline encoding and does not require proficiency in any programming language. The features of the CIG encoding process are revealed through a comparison with already established tools for CIG acquisition.     

A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

化妆品功效评价(Ⅵ)——化妆品人体功效评价的实验设计

概述了化妆品人体功效评价实验设计的概念、基本要素和基本原则,介绍了常用实验设计类型和实验设计要点,提供了人体功效评价实验方案设计的思路,有助于提高研究者制定实验设计方案的水平。     

Protection of power transformer using multi criteria decision-making

Power transformers are protected by different relays that operate independently. Malfunction of each relay has a major role in reducing the reliability of the protection system. In order to mitigate the main drawbacks of the power transformer relays, an overall protection scheme is presented in this paper. This scheme proposes a novel multi criterion algorithm using decision-making based on fuzzy logic. In this paper the outputs of restricted earth fault relay and a directional check unit, are combined with the output of the differential protection relay. Therefore, problems that are pertaining to independent operation of each relay have been mitigated and the relays cover protection blind spots of each other. The improved power transformer protection (IPTP) scheme enhances the sensitivity and reliability of the power transformer protection. Extensive simulations are used to measure the effectiveness and merit of the proposed IPTP relay. The above efforts result in a multi criteria approach for protection of power transformers.     

Sleep Disorders Reduce Health-Related Quality of Life in Multiple Sclerosis (Nottingham Health Profile Data in Patients with Multiple Sclerosis)

Quality of Life (QoL) is decreased in multiple sclerosis (MS), but studies about the impact of sleep disorders (SD) on health-related quality of Life (HRQoL) are lacking. From our original cohort, a cross-sectional polysomnographic (PSG) study in consecutive MS patients, we retrospectively analysed the previously unpublished data of the Nottingham Health Profile (NHP). Those MS patients suffering from sleep disorders (n = 49) showed significantly lower HRQoL compared to MS patients without sleep disorders (n = 17). Subsequently, we classified the patients into four subgroups: insomnia (n = 17), restless-legs syndrome, periodic limb movement disorder and SD due to leg pain (n = 24), obstructive sleep apnea (n = 8) and patients without sleep disorder (n = 17). OSA and insomnia patients showed significantly higher NHP values and decreased HRQoL not only for the sleep subscale but also for the “energy” and “emotional” area of the NHP. In addition, OSA patients also showed increased NHP values in the “physical abilities” area. Interestingly, we did not find a correlation between the objective PSG parameters and the subjective sleep items of the NHP. However, this study demonstrates that sleep disorders can reduce HRQoL in MS patients and should be considered as an important confounder in all studies investigating HRQoL in MS.     

Unresolved controversies concerning psychopathy: Implications for clinical and forensic decision making.

At some point in their careers, clinicians who work or consult in forensic and correctional settings will almost certainly encounter individuals who exhibit psychopathic personality features. Because of the widespread use of this disorder to inform legal and clinical decision making, psychologists should be exceedingly familiar with the relevant research literature on this topic before venturing into these settings. This article reviews the empirical bases of several clinically relevant claims and assertions regarding psychopathy and concludes that many areas of research are decidedly more equivocal in their findings than is commonly perceived. Although there is much to be gained by assessing psychopathy in various contexts, clinicians need to be cautious about drawing overzealous and empirically questionable conclusions about an important disorder that also has great potential for abuse. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Attentional Biases for Negative Interpersonal Stimuli in Clinical Depression.

An information-processing paradigm was used to examine attentional biases in clinically depressed participants, participants with generalized anxiety disorder (GAD), and nonpsychiatric control participants for faces expressing sadness, anger, and happiness. Faces were presented for 1,000 ms, at which point depressed participants had directed their attention selectively to depression-relevant (i.e., sad) faces. This attentional bias was specific to the emotion of sadness; the depressed participants did not exhibit attentional biases to the angry or happy faces. This bias was also specific to depression; at 1,000 ms, participants with GAD were not attending selectively to sad, happy, or anxiety-relevant (i.e., angry) faces. Implications of these findings for both the cognitive and the interpersonal functioning of depressed individuals are discussed and directions for future research are advanced. (PsycINFO Database Record (c) 2010 APA, all rights reserved)