nils-herrmann/clean_scirepeval huggingface dataset:
Exploring mobility equity in a society undergoing changes in travel behavior: A case study of Aachen, Germany

This study highlights the necessity of mobility equity analyses in transportation system of societies with an increasing number of non drivers. The demographic shift towards older people, declining car accessibility for the younger generation and public concerns about environmental issues are some reasons of change in trip behavior and mobility demand structure as well as increase in potential mobility disadvantage groups in Germany. This paper explores the horizontal and vertical mobility equity statuses of various districts and socio economic groups in the city of Aachen considering different trip modes. A set of statistical measures including the Gini index were utilized in a horizontal equity analysis, and the role of urban texture in mobility equity analysis is highlighted. Despite an overall fair distribution of mobility between the inhabitants of different districts, the vertical equity analysis shows a significant variation between different socio economic groups and different transportation modes. This study also suggests some strategies to improve mobility equity based on the results of the analyses.
Concurrent Canonical Correlation Analysis Modeling for Quality Relevant Monitoring

Canonical correlation analysis (CCA) is a well known data analysis technique that extracts multidimensional correlation structure between two groups of variables. Due to the advantages of CCA on quality prediction, CCA based modeling and monitoring are discussed in this paper. To overcome the shortcoming of CCA that focuses on correlation but ignores variance information, a new concurrent CCA (CCCA) modeling method is proposed to completely decompose the input and output spaces into five subspaces, to retain the CCA efficiency in predicting the output while exploiting the variance structure for process monitoring using subsequent principal component decomposition in the input and output spaces, respectively. The corresponding monitoring statistics and control limits are then developed in these subspaces. The Tennessee Eastman process is used to demonstrate the effectiveness of CCCA based monitoring methods.
The FMRIB Variational Bayes Tutorial: Variational Bayesian Inference for a Non Linear Forward Model

Bayesian methods have proved powerful in many applications, including MRI, for the inference of model, e.g. physiological, parameters from data. These methods are based on Bayes' theorem, which itself is deceptively simple. However, in practice the computations required are intractable even for simple cases. Hence methods for Bayesian inference are either significantly approximate, e.g. Laplace approximation, or achieve samples from the exact solution at significant computational expense, e.g. Markov Chain Monte Carlo methods. However, more recently the Variational Bayes (VB) method has been proposed (Attias 2000) that facilitates analytical calculations of the posterior distributions over a model. The method makes use of the mean field approximation, making a factorised approximation to the true posterior, although unlike the Laplace approximation does not need to restrict these factorised posteriors to a Gaussian form. Practical implementations of VB typically make use of factorised approximate posteriors and priors that belong to the conjugate exponential family, making the required integral tractable. The procedure takes an iterative approach resembling an Expectation Maximisation method and whose convergence is guaranteed. Since the method is approximate the computational expense is significantly less than MCMC approaches and is also less than a Laplace approximation since no Hessian need be evaluated. Attias (2000) provides the original derivation of the 'Variational Bayes Framework for Graphical Models' (although is not the first person to take such an approach) He introduces the concept of 'free form' selection of the posterior given the chosen model and priors, although this is ultimately limited by the need for the priors and factorised posteriors to belong to the conjugate exponential family (Beal 2003) A comprehensive example of the application of VB to a one dimensional Gaussian mixture model has been presented by Penny et al. (2000) Beal (2003) has provided a thorough description of variation Bayes and its relationship to MAP and MLE, as well as its application to a number of standard inference problems. He has shown that Expectation Maximisation algorithm is a special case of VB. Friston et al. (2007) additionally has considered the VB approach and variational free energy in the context of the Laplace approximation and ReML. In this context they use a fixed 3 multi variate Gaussian form for the approximate posterior, in contrast to the 'free form' approach. To ensure tractablility of the VB approach the models to which it can be applied are limited (Beal 2003) However, Woolrich Behrens (2006) have avoided this problem,
Integrated health service delivery networks and tuberculosis avoidable hospitalizations: is there a relation between them in Brazil?
Venue: BMC Health Services Research

BackgroundThe early identification of the Breathing Symptoms within the scope of Primary Health Care is recommended, and is also one of the strategies of national sanitary authorities for reaching the elimination of tuberculosis. The purpose of this study is to consider which attributes and which territories have shown the most significant progress in Primary Health Care, in terms of coordination of Health Care Networks, and also check if those areas of Primary Health Care that are most critical regarding coordination, there were more or less cases of avoidable hospitalizations for tuberculosis.MethodsThis is an ecological study that uses primary and secondary data. For analysis, coropletic maps were developed through the ArcGIS software, version 10.2. There was also the calculation of gross annual and Bayesian rates for hospitalizations for tuberculosis, for each Primary Health Care territory.ResultsThere were satisfactory results for attributes such as Population (n 37; 80.4 Primary Health Care (n 43; 93.5 Support System (n 45; 97.8 the exceptions were Logistics System (n 32; 76.0 and Governance System, with fewer units in good condition (n 31; 67.3 There is no evidence of any connection between networks' coordination by Primary Health Care and tuberculosis avoidable admissions.ConclusionThe results show that progress has been made regarding the coordination of the Health Care Networks, and a positive trend has been shown, even though the levels are not excellent. It was found no relationship between the critical areas of Primary Health Care and tuberculosis avoidable hospitalizations, possibly because other variables necessary to comprehend the phenomena.
Metabolic variations in different citrus rootstock cultivars associated with different responses to Huanglongbing.
Venue: Plant physiology and biochemistry PPB

Huanglongbing (HLB) is one of the most destructive bacterial diseases of citrus. No resistant cultivars have been identified, although tolerance has been observed in the genus Poncirus and some of its hybrids with Citrus that are commonly used as rootstocks. In this study we exploited this tolerance by comparing five different tolerant hybrids with a cultivar that shows pronounced HLB sensitivity to discern potential contributing metabolic factors. Whole leaves of infected and non infected greenhouse grown seedlings were extracted and subjected to untargeted GC TOF MS based metabolomics. After BinBase data filtering, 342 (experiment 1) and 650 (experiment 2) unique metabolites were quantified, of which 122 and 195, respectively, were assigned by chemical structures. The number of metabolites found to be differently regulated in the infected state compared with the non infected state varied between the cultivars and was largest (166) in the susceptible cultivar Cleopatra mandarin (Citrus reticulata) and lowest (3) in the tolerant cultivars US 897 (C. reticulata 'Cleopatra' x Poncirus trifoliata) and US 942 (C. reticulata 'Sunki' x P. trifoliata) from experiment 2. Tolerance to HLB did not appear to be associated with accumulation of higher amounts of protective metabolites in response to infection. Many metabolites were found in higher concentrations in the tolerant cultivars compared with susceptible Cleopatra mandarin and may play important roles in conferring tolerance to HLB. Lower availability of specific sugars necessary for survival of the pathogen may also be a contributing factor in the decreased disease severity observed for these cultivars.
The Impact of Term Statistical Relationships on Rocchio s Model Parameters For Pseudo Relevance Feedback

Query Expansion using the Pseudo Relevance Feedback based on rocchio's model is a popular technique for reformulating the original user's query. This latter, assumes that most frequent terms in the returned documents are useful to ameliorate the original query and therefore to improve search results which is a challenge today with the proliferation of textual data on the web. In this study, we re examine this assumption and show that it does not hold in reality. Indeed, many expansion terms identified are unrelated to the query and reduce the performance of the retrieval system. In this paper, we present our method to revisit the rocchio's model parameters in order to take into account the relationships between terms which are defined by our proposed statistical method based on least square optimization. The evaluation process was performed on CLEF eHealth 2014 database which is composed of about one million medical and english documents and 50 professional and medical queries. Experimental results show that our proposed method is effective.
Using Image Modelling to Teach Newton's Laws with the Ollie Trick.

Image modelling is a video based teaching tool that is a combination of strobe images and video analysis. This tool can enable a qualitative and a quantitative approach to the teaching of physics, in a much more engaging and appealling way than the traditional expositive practice. In a specific scenario shown in this paper, the Ollie trick, we show how image modelling can contribute to the contextualisation of Newton's Laws, foster an effective learning and spell out the relation between forces and the different moments of skateboarding.
The Effect of Group Work on Misconceptions of 9th Grade Students about Newton's Laws

In this study, the effect of group work and traditional method on 9th grade students' misconceptions about Newton Laws was investigated. The study was conducted in three classes in an Anatolian Vocational High School in Ankara/Turkey in the second term of the 2014 2015 academic year. Two of these classes were chosen as the experimental group and one as the control group. The groups in the experimental group were formed on a voluntary basis with two students in each of them. These experimental groups were given activities which included methods such as concept maps, worksheets, concept cartoons, doing experiments, preparing a project homework and doing case studies. In the control group, the activities which were done in the experimental groups were converted into questions and solved by the students and the teacher. As the assessment tool, 'Force Motion Misconception Test' was used, whose validity and reliability studies had been performed by carrying out pilot studies. This test was administered to both the experimental groups and the control group as pre test before the teaching and post test after the teaching. The data obtained showed that there was no significant difference in post tests between the experimental and control group students in terms of misconceptions (p>,05) However, according to the averages, the students in the experimental groups were observed to have fewer misconceptions than those in the control group.
PREVALENCE OF PARASITIC CONTAMINATION OF RAW VEGETABLES IN AHAR IRAN

It is well known that foodborne infections can be transmitted to humans via vegetable consumption. The study reported here aimed to determine the prevalence of parasitic contamination on raw vegetables sourced from market region of the Ahar sity of Iran. The vegetables examined in this work included lettuce, carrots, spinach, tomatoes, parsley, green pepper, leek and radish. For each vegetable type, 10 samples were collected and resulting in 80 samples used in subsequent analysis. These samples were analyzed by a concentration method and examined by light microscopy. Intestinal parasites were detected in 30% of the examined samples. The parasites included Ascaris lumbricoides eggs, Hymenolepis nana eggs, Giardia spp. cysts, Cryptosporidium spp. oocysts, Entamoeba coli spp. Entamoeba histolyca spp. The contamination of vegetables with infective ova emphasizes the need for adequate preventative measures that can assist in avoiding the transmission of diseases.
Diversity of parasitic contamination in raw vegetables commonly consumed in Shiraz, southwest of Iran

To evaluate the parasitic contamination of row vegetables at farms and retails, separately.  A total of 224 samples from 8 different kinds of vegetables were randomly collected from the retails and farms (retails: 80; farms: 144) in the same area and then were tested for helminth egg, Giardia spp. cysts and Cryptosporidium spp. oocysts by using sedimentation, floatation and common staining methods.  In total, 31.2% (25/80) and 36.8% (53/144) of retails and farms vegetables were contaminated with a variety of parasites, respectively. Parasites detected in retail and farm vegetables were Giardia cysts (3.7% and 4.8% Taenia spp. eggs (2.5% and 4.1% Trichostrongylus eggs (2.5% and 2.0% Ascaris eggs (2.5% and 2.0% Hymenolepis egg (1.2% and 0.0% Cryptosporidium spp. (1.2% and 1.3% and Trichuris eggs (0.0% and 1.3%  Based on our results, fresh vegetables can be a source of food borne parasitic disease in humans. Public educationand awareness, washing vegetables properly and improving of sanitary and irrigation conditions of these kinds of food should be necessary.
Application of TOPSIS and VIKOR improved versions in a multi criteria decision analysis to develop an optimized municipal solid waste management model.
Venue: Journal of environmental management

Selecting a suitable Multi Criteria Decision Making (MCDM) method is a crucial stage to establish a Solid Waste Management (SWM) system. Main objective of the current study is to demonstrate and evaluate a proposed method using Multiple Criteria Decision Making methods (MCDM) An improved version of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) applied to obtain the best municipal solid waste management method by comparing and ranking the scenarios. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Besides, Viekriterijumsko Kompromisno Rangiranje (VIKOR) compromise solution method applied for sensitivity analyses. The proposed method can assist urban decision makers in prioritizing and selecting an optimized Municipal Solid Waste (MSW) treatment system. Besides, a logical and systematic scientific method was proposed to guide an appropriate decision making. A modified TOPSIS methodology as a superior to existing methods for first time was applied for MSW problems. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Next, 11 scenarios of MSW treatment methods are defined and compared environmentally and economically based on the waste management conditions. Results show that integrating a sanitary landfill (18.1% RDF (3.1% composting (2% anaerobic digestion (40.4% and recycling (36.4% was an optimized model of integrated waste management. An applied decision making structure provides the opportunity for optimum decision making. Therefore, the mix of recycling and anaerobic digestion and a sanitary landfill with Electricity Production (EP) are the preferred options for MSW management.
Health Care Waste Treatment Technology Selection Using the Interval 2 Tuple Induced TOPSIS Method
Venue: International journal of environmental research and public health

Health care waste (HCW) management is a major challenge for municipalities, particularly in the cities of developing nations. Selecting the best treatment technology for HCW can be regarded as a complex multi criteria decision making (MCDM) issue involving a number of alternatives and multiple evaluation criteria. In addition, decision makers tend to express their personal assessments via multi granularity linguistic term sets because of different backgrounds and knowledge, some of which may be imprecise, uncertain and incomplete. Therefore, the main objective of this study is to propose a new hybrid decision making approach combining interval 2 tuple induced distance operators with the technique for order preference by similarity to an ideal solution (TOPSIS) for tackling HCW treatment technology selection problems with linguistic information. The proposed interval 2 tuple induced TOPSIS (ITI TOPSIS) can not only model the uncertainty and diversity of the assessment information given by decision makers, but also reflect the complex attitudinal characters of decision makers and provide much more complete information for the selection of the optimum disposal alternative. Finally, an empirical example in Shanghai, China is provided to illustrate the proposed decision making method, and results show that the ITI TOPSIS proposed in this paper can solve the problem of HCW treatment technology selection effectively.
The fault tree analysis of infectious medical waste management

Providing an efficient and reliable system of medical waste management is one of the key environmental issues not only for health care institutions but for a wider range of organizations and communities. Medical waste produced in health care is a special kind of waste, which, if inadequately treated, can cause numerous possible health and safety hazards for people and the environment. In this paper the authors introduce an application for risk assessment of infectious medical waste management in the biggest health institution of South East Europe the Clinical Centre of Serbia. The fault tree analysis (FTA) method was used in the assessment regarding its three aspects functional, qualitative and quantitative. The qualitative analysis provided the structural function of the system and minimal cut sets, whilst the quantitative analysis based on experts' evaluations defined the probability of both basic and top events (spreading of infection with medical waste) Finally, according to Birbaim's, RAW (Risk achievement worth) RRW (Risk reduction worth) and Fussell Vesely's importance measures, the events have been ranked regarding their effect on the undesired event related to infectious medical waste management. In this paper, we have chosen the FTA approach because it enables the analysis of the individual risks (like the most of the risk assessment methods used in medical waste management FMEA, HACCP, PHA, CREA) but it also provides the analysis of risk relationships and interdependences. Based on the obtained results we identified the basic failures in the medical waste management systems whose prevention or mitigation have the biggest influence on the observed system improvement. Furthermore, the research presented in this paper has clearly pointed out that the FTA method and importance measures can be used in the risk assessment of the medical waste and should be taken into consideration in appropriate medical waste management systems.
Application Integrated Fuzzy TOPSIS based on LCA Results and the Nearest Weighted Approximation of FNs for Industrial Waste Management Aluminum Industry: Arak Iran

Aluminum dross as waste is always a problematic issue. The aim of this study is to apply a systematic method for the Aluminum waste management system selection problem in environment management.  In this study, a methodology extended fuzzy TOPSIS and based on LCA is applied by using the nearest weighted interval approximations. The functional unit includes aluminum dross and aluminum scrap, which are defined as 1000 kg. The model is confirmed in the case of aluminum waste management in the city of Arak. The scenarios are ranked based on their closeness coefficient to the ideal solution.  Five scenarios, in a step wise manner were surveyed. Based on study results and particularly the closeness coefficients, Scenario S4 was assigned as the most preferred choice with a weight of 0.723514. Also the Scenario S1with a value of 0.448137, Scenario S5 with a value of 0.354226, Scenario S2 with a value of 0.314215 and Scenario S3 with a value of 0.204909 were ranked from second to fifth respectively. The results of the present study illustrated that the procedure is simple in calculations and set priorities. It is very appropriate for solving MCDM problems.  From the application perspective, this research will provide a valuable insight for managers to attempt to improve the environmental, social and economic condition all together at the same time.
Science of Autonomy: Time Optimal Path Planning and Adaptive Sampling for Swarms of Ocean Vehicles

The science of autonomy is the systematic development of fundamental knowledge about autonomous decision making and task completing in the form of testable autonomous methods, models and systems. In ocean applications, it involves varied disciplines that are not often connected. However, marine autonomy applications are rapidly growing, both in numbers and in complexity. This new paradigm in ocean science and operations motivates the need to carry out interdisciplinary research in the science of autonomy. This chapter reviews some recent results and research directions in time optimal path planning and optimal adaptive sampling. The aim is to set a basis for a large number of vehicles forming heterogeneous and collaborative underwater swarms that are smart, i. e. knowledgeable about the predicted environment and their uncertainties, and about the predicted effects of autonomous sensing on future operations. The methodologies are generic and applicable to any swarm that moves and senses dynamic environmental fields. However, our focus is underwater path planning and adaptive sampling with a range of vehicles such as autonomous underwater vehicles (AUV s) gliders, ships or remote sensing platforms.