nils-herrmann/clean_scirepeval huggingface dataset:
LCOE Analysis of Tower Concentrating Solar Power Plants Using Different Molten Salts for Thermal Energy Storage in China
Venue: Energies
Year: 2019

In recent years, the Chinese government has vigorously promoted the development of concentrating solar power (CSP) technology. For the commercialization of CSP technology, economically competitive costs of electricity generation is one of the major obstacles. However, studies of electricity generation cost analysis for CSP systems in China, particularly for the tower systems, are quite limited. This paper conducts an economic analysis by applying a levelized cost of electricity (LCOE) model for 100 MW tower CSP plants in five locations in China with four different molten salts for thermal energy storage (TES) The results show that it is inappropriate to build a tower CSP plant nearby Shenzhen and Shanghai. The solar salt (NaNO3 KNO3, 60 40 wt. has lower LCOE than the other three new molten salts. In order to calculate the time when the grid parity would be reached, four scenarios for CSP development roadmap proposed by International Energy Agency (IEA) were considered in this study. It was found that the LCOE of tower CSP would reach the grid parity in the years of 2038 2041 in the case of no future penalties for the CO2 emissions. This study can provide support information for the Chinese government to formulate incentive policies for the CSP industry.
Artificial intelligence and multi agent based distributed ledger system for better privacy and security of electronic healthcare records
Venue: PeerJ Comput. Sci.
Year: 2020

Application of Artificial Intelligence (AI) and the use of agent based systems in the healthcare system have attracted various researchers to improve the efficiency and utility in the Electronic Health Records (EHR) Nowadays, one of the most important and creative developments is the integration of AI and Blockchain that is, Distributed Ledger Technology (DLT) to enable better and decentralized governance. Privacy and security is a critical piece in EHR implementation and/or adoption. Health records are updated every time a patient visits a doctor as they contain important information about the health and wellbeing of the patient and describes the history of care received during the past and to date. Therefore, such records are critical to research, hospitals, emergency rooms, healthcare laboratories, and even health insurance providers.  In this article, a platform employing the AI and the use of multi agent based systems along with the DLT technology for privacy preservation is proposed. The emphasis of security and privacy is highlighted during the process of collecting, managing and distributing EHR data.  This article aims to ensure privacy, integrity and security metrics of the electronic health records are met when such copies are not only immutable but also distributed. The findings of this work will help guide the development of further techniques using the combination of AI and multi agent based systems backed by DLT technology for secure and effective handling EHR data. This proposed architecture uses various AI based intelligent based agents and blockchain for providing privacy and security in EHR. Future enhancement in this work can be the addition of the biometric based systems for improved security.
Implementation of Haar Cascade Classifier for Vehicle Security System Based on Face Authentication Using Wireless Networks
Year: 2019

This research work presents a vehicle security system for safeguarding the vehicle from theft issues under the architectural design of capturing and comparing the vehicle user's face. Since the face of human beings are unique and has different biometric characteristics which are complex to make fraudulent activities. Authenticating the vehicle users with face recognition mechanism is highly secured than token based and knowledge based security mechanisms. This research ultimately models and classifies the vehicle users into authorized and unauthorized users. Initially, an experimental prototype for vehicle security system is developed, and the application of image processing algorithms is incorporated into the model. The system uses Haar feature based cascade classifier and AdaBoost method which is a machine learning algorithm used for detecting the authorized user's face effectively. The algorithm is trained initially with appropriate amount of positive and negative images, and the feature gets extracted. When the person tries to access the vehicle, the experimental system captures the image of the person and makes comparison with extracted features to identify the authorized user. Finally, the results obtained from the prototype system are satisfied and beneficial against the issue of vehicle theft.
Number sense or working memory? The effect of two computer based trainings on mathematical skills in elementary school
Venue: Advances in cognitive psychology
Year: 2014

Research on the improvement of elementary school mathematics has shown that computer based training of number sense (e.g. processing magnitudes or locating numbers on the number line) can lead to substantial achievement gains in arithmetic skills. Recent studies, however, have highlighted that training domain general cognitive abilities (e.g. working memory [WM] may also improve mathematical achievement. This study addressed the question of whether a training of domain specific number sense skills or domain general WM abilities is more appropriate for improving mathematical abilities in elementary school. Fifty nine children (Mage 9 years, 32 girls and 27 boys) received either a computer based, adaptive training of number sense (n 20) WM skills (n 19) or served as a control group (n 20) The training duration was 20 min per day for 15 days. Before and after training, we measured mathematical ability using a curriculum based math test, as well as spatial WM. For both training groups, we observed substantial increases in the math posttest compared to the control group (d .54 for number sense skills training, d .57 for WM training, respectively) Whereas the number sense group showed significant gains in arithmetical skills, the WM training group exhibited marginally significant gains in word problem solving. However, no training group showed significant posttest gains on the spatial WM task. Results indicate that a short training of either domain specific or domain general skills may result in reliable short term training gains in math performance, although no stable training effects were found in the spatial WM task.
D 8 ULKELERINDE ISSIZLIK VE IKTISADI BUYUME ILISKISININ PANEL NEDENSELLIK ANALIZI
Year: 2020

Issizlik oranini azaltmak ve yuksek bir buyume orani gerceklestirmek butun ekonomilerin en onemli amaclaridir. Bu calismada issizlik ve iktisadi buyumenin ne oldugu ve bu kavramlar arasindaki iliski aciklanmaya calisilmistir. D 8 ulkeleri icin issizlik ve iktisadi buyume arasindaki iliski 1998 2017 donemine ait yillik verilerle incelendigi bu calismada panel nedensellik analizi kullanilmistir. Analiz sonuclarina gore Endonezya'da %1 anlamlilikta ve Turkiye'de ise %5 anlamlilikta iktisadi buyumeden issizlik oranina dogru bir nedensellik iliskisinin oldugu tespit edilmistir. Issizlik oranindan iktisadi buyumeye dogru nedensellik iliskisine bakildigina ise D 8 ulkelerinin hicbirinde issizlik oraninin iktisadi buyumenin nedeni olmadigi sonucuna ulasilmistir.
Analysis of Variance and Covariance: How to Choose and Construct Models for the Life Sciences
Year: 2007

Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts. Pictorial representations of designs and tabulated descriptions help readers differentiate between models and evaluate designs Worked examples of the principal models and illustrative examples of applications are developed through this book, bringing the statistics to life Chapter on troubleshooting problems, addresses frequently asked questions on data collection, practicalities of analysing data and interpretation of results Contents: Preface; Introduction to analysis of variance; Introduction to model structures; 1. One factor designs; 2. Nested designs; 3. Fully replicated factorial designs; 4. Randomised block designs; 5. Split plot designs; 6. Repeated measures designs; 7. Unreplicated designs; Further topics; Choosing experimental designs; How to request models in a statistics package; Best practice in presentation of the design; Troubleshooting problems during analysis; Glossary; Bibliography; Index of all ANOVA models with up to three factors; Index; Categories of model.
Morphology and ultrastructure of the spermatozoa of Lonchoptera lutea Panzer, 1809 (Diptera: Lonchopteridae)
Venue: Arthropod structure development
Year: 2020

Lonchoptera lutea males produce giant spermatozoa that are more than 2000 mm long and 1.4 mm wide. Unlike the typical brachyceran spermatozoon, they have a highly asymmetrical cross section with only a single, albeit very large, mitochondrial derivative and a pair of massive accessory bodies, one of which extends throughout the entire length of the sperm tail. The accessory bodies consist of an electron dense matrix in which numerous peculiar electron lucid substructures are embedded. In the mated female, the giant spermatozoa are found inside two tubular spermathecae which are also extremely long, measuring 4000 mm or more.
Effect of lignin and plant growth promoting bacteria (Staphylococcus pasteuri) on microbe plant Co remediation: A PAHs DDTs Co contaminated agricultural greenhouse study.
Venue: Chemosphere
Year: 2020

Due to the ecological toxicity and environmental residues, how to remove the persistent organic pollutants (POPs) especially of polycyclic aromatic hydrocarbons (PAHs) and dichloro diphenyl trichloroethanes (DDTs) from agricultural soil has captured the attention of scholars for a long time. To develop an effective and low cost in situ co remediation technique, five independent but complementary treatments were used on an over standard PAHs DDTs co contaminated soil in an agricultural greenhouse. Experimental results identified that the combination of microbe (Bacillus methylotrophicus) plant (Brassica rapa) could remove rhamnolipid activated PAHs and DDTs effectively after enhanced by Staphylococcus pasteuri. Also, the Benzoapyrene and total DDTs residue in Brassica rapa was up to the standard of National (China) food safety. The lignin enhanced the removal of high rings PAHs and p p' DDE but reduced soil microbial biomass carbon and soil enzymes activity (polyphenol oxidase, invertase and acid phosphatase) Pearson correlation analysis showed that polyphenol oxidase activity was significantly related to the PAHs/DDTs dissipation rate. Our research suggested a new amendment that could remediate PAHs/DDTs co contaminated agricultural soil without interrupting crop production, and the polyphenol oxidase activity should be considered as a micro ecological indicator in this process.
RELATIONSHIP BETWEEN FAMILY SUPPORT AND MEDICATION ADHERENCE AMONG PATIENTS WITH SCHIZOPHRENIA
Year: 2017

There are many factors influencing medication adherence among patients with schizophrenia. Medication adherence have an important role in the treatment, especially to preventing relapse patients with schizophrenia.  The aim of the present study was to examine the relationship between family support and medication adherence among patients with schizophrenia in Bandung, West Java, Indonesia.  A cross sectional study was conducted at the outpatient department of the West Java Province Mental Hospital in Bandung, West Java, Indonesia. Individuals were assessed using the Bahasa versions of Medication Adherence Rating Scale (MARS) and Multidimensional Scale of Perceived Social Support (MSPSS) instruments.  A total of 88 patients with schizophrenia were enrolled. The prevalence of medication adherence was 64.8% By using Chi square test, the results revealed that family support have no significantly associated with medication adherence  This finding could contribute to nursing knowledge to increase the understanding of medication adherence among patients with schizophrenia. The health care providers should promote regarding medication adherence to improve patients' health status.
Risk Assessment of Groundwater Depletion Induced Land Subsidence: A Case Study in Taiyuan Basin, China
Venue: Geotechnical and Geological Engineering
Year: 2019

Groundwater depletion induced land subsidence affects the safety of local communities. In this research, a data driven approach is applied to predict and assess the risk level of land subsidence in Taiyuan Basin, Shanxi Province, China based on Geographic Information Systems data and field investigation data. First, the relevance vector machine is introduced to model and classify the risky/non risky ground subsidence cases. Next, an ensemble classifier using multiple relevance vector machines and elastic net is proposed in this research. Multiple land subsidence locations in Taiyuan Basin have been investigated in this study. Five benchmarking machine learning classification algorithms including decision tree, random forest, multi layer perceptron, support vector machine and classical relevance vector machine have been compared in this study. Four evaluation metrics including accuracy, sensitivity, specificity and area under the receiver operating characteristic curve have been introduced to assess the classification performance of all the algorithms tested. Computational results demonstrated the outperformance of the proposed approach in classifying risky land subsidence cases compared with other benchmarking algorithms.
How Did Parents View the Impact of the Curriculum Based HealthLit4Kids Program Beyond the Classroom?
Venue: International journal of environmental research and public health
Year: 2020

The HealthLit4Kids program aims to build health literacy in a participatory and contextually relevant way. Whole of school and curriculum strategies aim to empower and build capacity to make informed health choices amongst students, teachers, parents, and their local community. The aim of this study was to evaluate the HealthLit4Kids program from the perspective of parents, using a Self Determination Theory framework. This is one component within a larger evaluation of the program. Parents at four Australian primary schools were interviewed post program. Qualitative data collected through parent interviews were analyzed thematically to identify themes, and coding checks were completed by experienced qualitative researchers. The three key themes identified were student engagement, behaviour change, and parent engagement. Findings also indicated that parents placed a high value on effective communication from schools and raised a range of health areas such as food and nutrition, physical activity, and mental health with the interviewer. Parent opinions of the HealthLit4Kids program were positive, with many reporting a perceived increase in their children's ability to understand, communicate and act on health related knowledge at home. The HealthLit4Kids program requires further research to determine its viability as an optimal pedagogical strategy for the health literacy development of primary school aged children.
Oxidation and Repeated Bending Properties of Sn Based Solder Joints After Highly Accelerated Stress Testing (HAST)
Venue: Electronic Materials Letters
Year: 2018

The repeated bending properties of Sn 0.7Cu, Sn 0.3Ag 0.7Cu (SAC0307) and Sn 3.0Ag 0.5Cu (SAC305) solders mounted on flexible substrates were studied using highly accelerated stress testing (HAST) followed by repeated bending testing. In the Sn 0.7Cu joints, the Cu6Sn5 intermetallic compound (IMC) coarsened as the HAST time increased. For the SAC0307 and SAC305 joints, the Ag3Sn and Cu6Sn5 IMCs coarsened mainly along the grain boundary as the HAST time increased. The Sn 0.7Cu solder had a high contact angle, compared to the SAC0307 and SAC305 solders; consequently, the SAC0307 and SAC305 solder joints displayed smoother fillet shapes than the Sn 0.7Cu solder joint. The repeated bending for the Sn 0.7Cu solder produced the crack initiated from the interface between the Cu lead wire and the solder, and that for the SAC solders indicated the cracks initiated at the surface, but away from the interface between the Cu lead wire and the solder. Furthermore, the oxide layer was thickest for Sn 0.7Cu and thinnest for SAC305, regardless of the HAST time. For the SAC solders, the crack initiation rate increased as the oxide layer thickened and roughened. Cu6Sn5 precipitated and grew along the grain and subgrain boundaries as the HAST time increased, embrittling the grain boundary at the crack propagation site.
Two New Species of the Simulium (Simulium) variegatum Species Group of Black Flies (Diptera: Simuliidae) From Thailand
Venue: Journal of Medical Entomology
Year: 2017

Two new species of black flies, Simulium (Simulium) srisukai and S. (S. kiewmaepanense, are described from specimens collected in Thailand. Both species are assigned to the Simulium variegatum species group of the subgenus Simulium (Simulium) Latreille. They are characterized by the darkened female femora and tibiae and six inflated pupal gill filaments, and the darkened female tibiae and six ordinary thread like pupal gill filaments, respectively. Taxonomic notes are given to separate these new species from 10 related species among the group. These new species represent the third and fourth species of the S. variegatum species group from Thailand.
Research on the construction method of kansei image prediction model based on cognition of EEG and ET
Year: 2020

In order to more accurately predict kansei image of user when they interact with a product, and help designer to design a product that meets user's emotional appeal from a user centric perspective, a method for constructing kansei image prediction model from a more objective perspective of eye brain physiological cognition was presented in this paper. Firstly, deconstructing product shape to obtain form design elements, and then recombining those elements in different ways to get experimental samples. Next, EEG and ET techniques were introduced to obtain bioelectric data of eye brain physiological cognition when subjects view the experimental samples, and a space containing user kansei needs was established. Finally, the kansei image value of the product, the form design elements, and eye brain physiological data were associated together to establish a kansei image prediction model. To verify the effectiveness of this model, smartphones were used as validation cases in this research. User's kansei prediction model for smartphones was established based on subjects' evaluation of 30 experimental samples, and the model's performance was evaluated by a comparison verification method. The research results showed that the kansei image prediction model based on eye brain physiological cognition can more accurately predict kansei image in the process of user interaction with product, thus helping the designer to find out the key product from that trigger kansei image, and design a product that was more in line with the user' kansei experience.
'Radicalisation' The Transformation of Modern Understanding of Terrorist Origins, Psychology and Motivation.
Year: 2016

Our understanding of how people become involved in terrorism and violent extremism has transformed since the turn of the century. That transformation occurred at the same time that 'radicalisation' took over as the dominant framework for considering questions around terrorist psychology, motivation and recruitment. Today, radicalisation is typically seen to refer to a complex and dynamic process which results in individuals coming to embrace a violent ideology in support of a political or religious cause. The concept of radicalisation has become an almost universal element in contemporary efforts to understand and combat terrorism. This chapter outlines the rise and development of theoretical models and research on radicalisation. It highlights some of the major research breakthroughs but also focuses on where very significant gaps remain in our understanding. The chapter cautions that we need to be careful in terms of how we think about the broader role of radicalisation. A subtle and dangerously unquestioned assumption has spread that 'radicalisation' as a phenomenon is the major root cause of terrorism. When different radicalisation models are used to design or justify a variety of counter terrorism policies and programmes, care is needed to look beyond the headline banner of radicalisation and pay attention to the factors identified within those models as key drivers.
Edge Detection Based on Improved Sobel Operator
Year: 2016

Sobel algorithm is an important method of image edge detection. Comparing the Sobel operator with several other edge detection operators used frequently and making a further study on the classical Sobel operator, the advantages of Sobel operator are its fast detection speed, meanwhile it has an effect on smoothing and suppressing noise. Also, Sobel operator has a good effect on edge detection. Although Sobel operator has advantages in many aspects, it exists some problems: the Sobel operator is a kind of edge detection in horizontal and vertical direction, so it neglects edge points in other directions. It can not achieve a true detection for the points on image edge. In this paper, the algorithm is based on the Sobel operator, an increase of 45 degrees and 135 degrees 2 direction template, while the main edge of the oblique, re assigned the weight of the operator template. At the same time, in order to achieve an effect of detection, binarization method is used to make an edge thinning for detected image. According to simulation experiments, they show this method is simple and feasible, and the detective result is more concrete and abundant than traditional Sobel edge detection. Some problems are improved, such as traditional Sobel edge is rough and detection is incomplete. Keywords sobel operator; binarization; edge detection; edge thinning