Miracle-dz/UniFAR-FTUs huggingface dataset:
Governance in the Blockchain Economy: A Framework and Research Agenda

Blockchain technology is often referred to as a groundbreaking innovation and the harbinger of a new economic era. Blockchains may be capable of engendering a new type of economic system: the blockchain economy. In the blockchain economy, agreed-upon transactions would be enforced autonomously, following rules defined by smart contracts. The blockchain economy would manifest itself in a new form of organizational design—decentralized autonomous organizations (DAO)—which are organizations with governance rules specified in the blockchain. We discuss the blockchain economy along dimensions defined in the IT governance literature: decision rights, accountability, and incentives. Our case study of a DAO illustrates that governance in the blockchain economy may depart radically from established notions of governance. Using the three governance dimensions, we propose a novel IT governance framework and a research agenda for governance in the blockchain economy. We challenge common assumptions in the blockchain discourse, and propose promising information systems research related to these assumptions.
Using Recurrent Neural Networks for P 300-based BCI

Efi Arazi School of Computer Science Computer science Master of Science (M.Sc.) Research Track in Computer Science Using Recurrent Neural Networks for P300-based BCI by Ori TAL P300-based spellers are one of the main methods for EEG-based brain computer interface, and the detection of the P300 target event with high accuracy is an important prerequisite. The rapid serial visual presentation (RSVP) protocol is of high interest because it can be used by patients who have lost control over their eyes. In this study we wish to explore the suitability of recurrent neural networks (RNNs) as a machine learning method for identifying the P300 signal in RSVP data. We systematically compare RNN with alternative methods such as linear discriminant analysis (LDA) and convolutional neural network (CNN). Our results indicate that RNN shows good results only with large amounts of data, and we show that a network combining CNN and RNN is significantly more resilient to temporal noise than other methods.
Benchmarking nuclear reaction models of the FLUKA Monte Carlo code for heavy ion collisions

In this report, I summarize the work conducted during my eight weeks as a summer student in the EN-STI-FLU department of CERN. The work focused on the benchmarking of FLUKA double differential cross sections of secondary fragments produced in fixed-target heavy ion collisions in the beam energy range between 10 MeV/nucleon and 1 GeV/nucleon. Specifically, the accuracy of FLUKA models for nucleus-nucleus interactions, namely the Boltzmann Master Equation (BME) and the Relativistic Quantum Molecular Dynamics (rQMD) models, were analyzed. Furthermore, we compared the FLUKA production version 2011.2x. 6 with the FLUKA development version 2018.2 and found that the latter is a considerable improvement to the former. Nevertheless, further improvements are required to better reproduce the experimental data. The major refinements needed are presented and discussed in this report.
STRATEGIES TO WIN CMAR AND DB PROPOSALS: Which Evaluation Criteria Best Differentiate between Competitors?

The procurement processes used in the alternative contracting methods of design-build (D-B) and construction manager at risk (CMAR) are heavily focused on best-value and qualifications-based selection. However, previous research had not examined the effectiveness of owners’ evaluation criteria in differentiating between competing bidders. The objective of this study was to document the selection outcomes of the bidders in D-B and CMAR projects and identify which evaluation criteria have the greatest differentiation in scores for competing bidders. The results were compared with previous research on the procurement of architectural and engineering consultants and design-bid-build (D-B-B) contractors. The study sample consisted of 362 bidders for 63 D-B and CMAR projects from the United States and Canada. The statistical analysis results show that scores on interviews and technical proposals have the greatest differentiation, while cost proposal scores have minimal differentiation. These findings provide practical guidance for owners and bidders regarding how to prioritize evaluation criteria and how to respond to them.
A Speech Intelligibility Estimation Method Based on Hidden Markov Model

This paper proposes a speech intelligibility estimation method based on hidden Markov model (HMM) that is widely used for speech recognition. The HMM-based method is a kind of non-intrusive speech quality measurement, which means it operates without a reference speech signal. The log-likelihood score of HMM is converted to a normalized intelligibility score. We estimate the speech intelligibility of standard digital speech coders. The experimental results show that the proposed HMM-based method gives improved performance than the conventional non-intrusive speech intelligibility evaluation tool. KeywordsSpeech intelligibility; hidden Markov model (HMM); digital speech coder; non-intrusive __________________________________________________*****_________________________________________________
Origin-Destination Matrix Estimation of Traffic Flow on Highway Network

Today’s road traffic control problems include solving a traffic situation with many congestions, increased traffic demand in peak hours, need for high mobility and fast response in case of an incident. Video sensor or camera combined with state of the art image processing algorithm is more and more becoming the approach to road traffic monitor. Advantage of obtained traffic video footage is that many high level traffic information can be extracted. High level traffic information includes incident detection, vehicle classification, origin-destination matrix estimation, etc. This reports deals with the possibility to track vehicles in a traffic network using license plate recognition. The final results include developed image processing system, vehicle detection and license plate recognition to create an application that fulfills all mentioned requirements. Extraction of traffic data using computer vision technology is nowadays related to creation of traffic statistics and to improvement of the traffic conditions for drivers. The first development direction has been carried out on two different videos and the data extracted were used to compile traffic statistics on a real world traffic highway and establish the principles of the automatic highway network origin destination estimation that will be developed in the future. This reports includes presentation of experimental results obtained from real world highway traffic video footage and conclude with a summary of the tasks done and future work proposals.
The role of predation in the diel vertical migration of zooplankton in two tropical freshwaters ecosystems

Aim: This study aimed to examine and compare the different patterns of diel vertical migration (DVM) in two tropical freshwater ecosystems: Carioca Lake (PERD, MG), dominated by piscivorous fishes and Nado reservoir (Belo Horizonte, MG), dominated by planktivorous/omnivorous fishes. Methods: The vertical distribution of the zooplankton was examined at noon and midnight, in April 2003 in both systems, using a Schindler-Patalas trap. Results: In Nado reservoir, the larvae of the invertebrate predator Chaoborus, remained in the hypolimnion during the day and ascended into the surface waters at night. The same migratory behavior was observed for the population of the copepod Thermocyclops inversus, the dominant zooplankter, as well as for the rotifers. In Carioca Lake, the Chaoborus larvae did not migrate, and individuals were found occupying the entire water column in daytime as well as at night. The population of the copepod T. minutus, a potential prey of Chaoborus larvae, and most rotifers also did not migrate in Carioca Lake. Conclusions: In Nado reservoir, where planktivorous and omnivorous fishes dominate, the zooplankton was forced to adopt the diurnal vertical migration (DVM), a phenomenon that propagated through the different trophic levels. In Carioca Lake, in the virtual absence of vertebrate predators of zooplankton, no migration in the planktonic community was observed.
Performance Evaluation of Intelligent Distribution Network Based on Big Data and Cloud Computing

Intelligent distribution network, located at the end of the smart grid, is integrating lots of inductor electronic smart components to realize intelligent decision based on big data and cloud computing technology. It is necessary to evaluate the performance of the big data and cloud computing in order to give better direction of the distribution network construction. This paper creates the big data and cloud computing performance evaluation index system, and proposed an evaluation method based on catastrophe theory and two-tuple linguistic. In the proposed method, linguistic assessments of experts are transformed into two-tuple linguistic firstly. And the catastrophe theory is expanded from real number to two-tuple linguistic based on its definition. Finally, a case study has been given, it has also confirmed the validity of the proposed method.
A new Bivariate Distribution with Log-Exponentiated Kumaraswamy Marginals

In this paper we introduce a new bivariate log-exponentiated Kumaraswamy (BlogEK) distribution. This new singular distribution has univariate log-EK distributions marginals. Some properties are studied; parameter estimation using maximum likelihood estimators (MLEs) of the unknown parameters cannot be obtained in explicit forms. A real data set and simulation study are used to obtain the parameters estimation, and confidence intervals to study the behavior of the parameters.
Smokeless Tobacco ( paan and gutkha ) Consumption and its Prevalence Contributing towards Oral Cancer

OBJECTIVES: Smokeless tobacco consumption leads to oral submucous fibrosis (OSMF) condition, which is a long-lasting devastating condition of oral cavity having the potential of malignancy across the world. In this review, we mainly focus on smokeless tobacco such as paan and gutkha consumption, and their role in the induction of OSMF and finally oral cancer. METHODS: The list of articles to be examined was established using citation discovery tools provided by PubMed, Scopus and Google Sscholar. RESULTS: The continuous chewing of paan and swallowing of gutkha triggers the progressive fibrosis of sub-mucosal mucous tissue. Usually, the condition arises initiated from multifactorial risks especially smokeless tobacco, such as betel quid, areca nuts, and slaked lime used in paan and gutkha, which progressively lead to OSMF. The incidence of oral cancer is high in women as compared to men across the Southern Asian countries. The human oral epithelium cells are affected due to slake lime present in the betel quid and/or with areca nut, which causes carcinogenic and genotoxic effects. CONCLUSIONS: It is concluded that these products such as 3(methyl nitrosamino) proprionitrile, nitrosamines, and nicotine initiates the production of reactive oxygen species (ROS) present in non-burn tobacco which eventually leads to fibroblast, DNA and RNA damage with carcinogenic effects in the mouth of tobacco consumers. The nitrosamine of tobacco bears metabolic activation by cytochrome P450s may lead to formation of Nnitrosonornicotine (NNK); a major carcinogen and micronuclei (MN); a landmark for genotoxicity, which further leads to DNA damage and finally oral cavity cancer.
Toward A database of intracranial electrophysiology during natural language presentation

ABSTRACT Intracranial electrophysiology (iEEG) studies using cognitive tasks contribute to the understanding of the neural basis of language. However, though iEEG is recorded continuously during clinical treatment, due to patient considerations task time is limited. To increase the usefulness of iEEG recordings for language study we provided patients with a tablet pre-loaded with media filled with natural language, wirelessly synchronised to clinical iEEG. This iEEG data collected and time-locked to natural language presentation is particularly applicable for studying the neural basis of combining words into larger contexts. We validate this approach with pilot analyses involving words heard during a movie, tagging syntactic properties and verb contextual probabilities. Event-related averages of high-frequency power (70–170 Hz) identified bilateral perisylvian electrodes with differential responses to syntactic class and a linear regression identified activity associated with contextual probabilities, demonstrating the usefulness of aligning media to iEEG. We imagine future multi-site collaborations building an “intracranial neurolinguistic corpus”.
MeteCloud: Meteorological Cloud Computing Platform for Mobile Weather Forecasts based on Energy-aware Scheduling

Nowadays, more and more large-scale data intensive applications such as meteorological big data executed in data centers require a huge amount of electrical energy and energy costs. Therefore, minimizing the energy consumption and reducing the environmental impact is our goal of Green Cloud Computing. In this paper, a new meteorological cloud computing platform (MeteCloud) for Mobile Weather Forecasts based on energy-aware scheduling for improving the energy efficiency is proposed. This approach is different from the existing researches, which wants to emphasize the importance of energy consumption in the study of constructing cloud computing platform for meteorological applications. And, a novel MeteCloud architecture and a hybrid scheduling algorithm are given to testify the availability of meteorological cloud computing platform. Finally, the experimental results demonstrate that MeteCloud has better performance and efficiency.
Clinical Significance of Ultrasonography Markers in Prenatal Diagnosis of Turner Syndrome in Fetuses-90 Cases Reports

Objective: To evaluate the clinical significance of ultrasonography markers in prenatal diagnosis of Turner syndrome in fetuses. Methods: Retrospectively 90 karyotypically documented fetuses with Turner syndrome reviewed from our database between August 2010 and April 2018 made up our study population. Women were aged between 19 to 40 years and weeks of gestation from 9 to 32 weeks. Ultrasound findings documented by skilled sonographer, performed in a systemic order from fetal head to toe, indicative of turner syndrome were noted, grouped and tabulated. Advanced maternal age women had routine fetal karyotyping while for younger women, it was indicated after abnormal ultrasonic findings. Amniocentesis or chorionic villus sampling were source for fetal chromosome extraction for karyotyping. Karyotyping (G-banding) was performed under standard protocol and karyotypes were described according to the International System for Human Cytogenetic Nomenclature. The karyotypes results were grouped as pure monosomy, 45X, and Mosaics In the evaluation of clinical significance of ultrasound markers, P values lower than 0.001 were considered as statistically significant. The calculations were performed using a statistical package program. Results: 61 fetuses were diagnosed in 35yr group as 6 (50%) 45X vs 6 (50%) mosaic. 32 fetuses were diagnosed as Turner syndrome in 20 weeks period as 10 (16%) 45X vs 21 (72%) mosaic. From ultrasound findings, 25 fetuses were diagnosed as intrauterine death, of which 24 (96%) 45X vs 1(4%) mosaic, (p<0.001) and 20 (80%) of them occurring in <12 weeks period (p<0.001). From 90 fetuses, 27 (30%) had cystic hygroma of which 27 (100%) 45X vs “0” (0%) mosaic, p<0.001. 21(23.3%) fetuses showed skin edema of which 21 (100%) 45X vs “0” (0%) mosaic, p<0.001. 11 fetuses showed cavity effusion of which 11 (100%) 45X vs “0” (0%) mosaic, p<0.001. Conclusion: The cluster of ultrasonography findings; intrauterine death, cystic hygroma, skin edema and cavity effusion showed a statistically significant impact (p<0.001) for the prenatal ultrasound diagnosis of Turner Syndrome. About 96% of 45X fetuses are spontaneously lost in early trimester. Of those surviving to second trimester, almost 100% will express one or more of the cluster of findings while the mosaic fetuses hardly express any, (p<0.001). The clinical significance is that 45X fetuses are diagnosed in early trimester while the mosaic fetuses later in 2nd-3rd trimester or even postnatal, (p<0.001). Clinically the cluster of ultrasonography findings are highly predictive of TS whenever present, (p<0.001) while absence does not rule out TS but their presence are dependent on karyotype of fetus (p<0.001). Conclusively, though karyotyping remains the gold standard for definitive diagnosis of Turner syndrome, we confirmed the clinical importance of these ultrasonography findings as fundamental markers for the prenatal ultrasound diagnosis of fetuses.
1 . 2 Dynamic Immersive Visualization Environment as a Powerful Pedagogical Tool

As the speed of technical and scientific innovation accelerates past the speed at which humans can learn, the need for innovative pedagogical environments and techniques, such as immersive visualization environments, becomes essential and apparent. The primary purpose of this research is to explore the effectiveness immersive visualization environments may provide in combination with rich resources available on the Internet. An immersive visualization environment was designed and developed, and then an experimental research model was considered and conducted accordingly. Collected data were subjected to appropriate statistical analysis. The results showed a statistically significant difference in pedagogical outcomes when using an immersive visualization environment compared with traditional educational techniques. Immersive visualization environment models and experiments showed significant improvement in the effectiveness and efficiency of pedagogical techniques, enhancing the learning and teaching of abstract and complex computing concepts.
Quality circles as a means for achieving worker satisfaction-or just a healthy managerial climate ? A South African sample

There is very little evidence that participative work programmes such as quality circles (QCs) improve the subjective experience of workers, either on the job, or in their lives generally. Part of the reason for such limited success is offered by literature suggesting that interventions such as QCs should reflect a general organizational philosophy of participation, rather than being the means to enforce organizational change. This study was undertaken in a large South African electrical utility, and consisted of 187 QC members and 63 non-QC members. Managerial climate was measured using a short form of Likert's organizational climate questionnaire, while worker satisfaction was measured using five different measures. Results revealed QC members scored higher on life satisfaction, self-esteem and purpose-in-life than non-QC members. Significant positive correlation was found between managerial climate and satisfaction indices. Regression analysis indicated that managerial climate variables accounted for the major share of the total variance in satisfaction indices, while participation in the QC programme accounted for relatively little: the implication is that QC participation may bring about increased worker satisfaction, but a critical prerequisite appears to be a suitably participative climate in the organization.
Application of Intrinsic Mode Function Based Features and Artificial Neural Network for the Classification of Normal and Epileptic EEG Signals

A seizure is defined as „a transient occurrence of signs and/or symptoms due to abnormal excessive neuronal activity in the brain‟. A subsequent advancement made in epilepsy and neuroscience research defines that the clinical diagnosis of a seizure is experimental and it depends on groups of certain signs and symptoms. This paper on electroencephalogram (EEG) signal analysis focuses on seizure signalsorting byeliminatingsomepossiblesimilar signals to seizures. Seizures have been classified in time and the borders of signals during a seizure, signals between seizures and after a seizure are separated. In this paper a feature extraction method based on EmpiricalMode Decomposition (EMD) is proposed. The sifting process decomposes the EEG signal into Intrinsic Mode Functions (IMFs) by the EMD algorithm and five statistical parameters are computed using these IMFs whichforms the input to a classifiers. Experimental results of two class classifiercarried out on the clinicaldataset show that an accurate classification rate of 96.3% is achieved in the discriminationbetween normal and ictal EEG, and an accuracy of 95% is reached in the classification ofinterictal and ictal EEG signals. The results are comparable or have done better thancurrentresearchpublished.
Credibility of American Academy of Pediatrics Guidelines 2011 in Evaluating Apparent First Simple Febrile Seizures

DOI: 10.21276/sjams.2018. 6.1. 6 Abstract: Fever with seizures is a common presentation in pediatric emergency department. In apparent first simple febrile seizures (FSFS) acute bacterial meningitis (ABM) should always be considered as a differential diagnosis. American academy of Pediatrics (AAP) guidelines of FSFS 1996 strongly recommended lumbar puncture (LP) in 3-12 months infants and advised to consider LP in children of 12 to 18 months age as signs and symptoms of meningitis are absent or subtle. In 2011 AAP changed the guidelines and LP was made an option in these children based on Hemophilus influenza type b (HIB) and Pneumococcal vaccine (PCV) status. Present study was intended to evaluate the credibility of AAP guidelines 2011 in developing / underdeveloped countries. 226 children of 3-18 months of age with apparent FSFS were evaluated by meningeal signs and LP findings. Among 3-12 months children 13 had meningitis but only 5 (38%)) presented with meningeal signs and 8 (62%) had no meningeal signs. In 12-18 months of age, meningitis was noticed in 11 children and 6 (55%) presented with meningeal signs and 5 (45%) had no meningeal signs. LP findings of 3-12 months children with meningitis (N-13) were suggestive of ABM in 10 (77%) and viral meningitis in 3 (23%) cases. Comparatively in 12-18 months children with meningitis (N-11) LP was suggestive of ABM in 8 (73%), viral meningitis in 2 (18%) and tuberculous meningitis in 1 (9%) of cases. Therefore, LP detected meningitis in remaining 62% infants in 3-12 months and 45% children in 1218 months age group who could not be picked up by meningeal signs. Overall immunization coverage of HIB/PCV in our study was 64 (28.3%) and 11 (4.9%). In developing/under developed countries implementation of AAP recommendations 2011 need to wait till immunization coverage of HIB / PCV reaches more than 90 percent.
Environmental ageing of polymer-based thin film transistors : influence of the semiconducting polymer chemical structure

At variance with a high stability of the inorganic materials for electronics under normal atmospheric conditions, organic materials are more sensitive, due to charge transfer doping by oxygen and water and degradation when exposed to the ultraviolet radiation. Here we show that the chemical structure of the conjugated polymer used as active semiconducting material of polymer field-effect transistors has a drastic effect on their stability. These results show that, by chemical manipulation, some of the above limitations, when envisaging the use of organic materials for electronics, can be reduced.