nils-herrmann/clean_scirepeval huggingface dataset:
The Impact of a no deal Brexit on FIN UK Trade: Case study: the import and export of vehicles and paper products
Year: 2019

Author(s) Title Emmi Hillo The Impact of a no deal Brexit on FIN UK Trade, Case study: the import and export of vehicles and paper products Number of Pages Date 41 pages 0 appendices 30th of April 2019 Degree Bachelor of Business Administration Degree Programme International Business and Logistics Instructor(s) Rosli Kamarul Baharin, Senior Lecturer The impact of Brexit has been a topic of discussion ever since the referendum vote in the UK in 2016. What underlines the topic itself is the uncertainty of the true depth Brexit will impact the free movement of goods and other important areas in general, such as the free movement of persons, the possible impact on credit interest, in addition to the possible changes in the transportation sector. Nevertheless, Brexit will ultimately change how businesses are to continue trade across the UK EU border after a no deal scenario. Therefore, the research question intended to be answered is how a no deal Brexit will be impacting the current trade patterns between Finland and the UK, by focusing on the trade of vehicles imported to Finland and paper products exported to the UK. First, the current trade regulations must be established in order to determine what may change if the UK leaves without a divorce agreement. As the UK will automatically continue trade under WTO rules, these rules will be also established in order to make a comparative analysis on the possible outcomes. The research is conducted with qualitative research and the research method is a comparative in a case study. Sources, such as news articles, government websites and statistics websites, were used to gather information about the topic in order to determine the outcome of the research question. The analysis focuses on the most important aspects regarding trade between the UK and Finland. Moreover, the analysis indicated some major changes in vehicle trade due to tariff rises and additional documentation for Customs declarations. The paper product export is slightly less impacted by Brexit, which is beneficial for Finnish businesses, as the UK officials have issued no additional tariffs for their import on the UK border.
Dynamic programming based pico base station sleep mode control in heterogeneous networks
Venue: Int. J. Commun. Syst.
Year: 2017

In this paper, a sleeping mode control for low power wireless node, that is, pico base station (PBS) in heterogeneous networks, is proposed to save energy cost with adaptation to the time varying traffic load. By formulating the sleep mode control problem into the framework of a standard 0/1 knapsack problem, then a dynamic programming scheme for solving the sleeping on/off mode for PBS in heterogeneous networks was investigated. The complexity of the proposed scheme is only in linear order instead of exponential complexity with conventional scheme. Furthermore, the proposed algorithm is verified in dynamic traffic environment, which consists of two kinds of hot spot area covered by PBSs. The simulation results show that the proposed scheme can effectively save the system energy consumption during the period of low traffic load.
Deep Convolutional Neural Networks With Ensemble Learning and Generative Adversarial Networks for Alzheimer's Disease Image Data Classification
Venue: Frontiers in Aging Neuroscience
Year: 2021

Recent advancements in deep learning (DL) have made possible new methodologies for analyzing massive datasets with intriguing implications in healthcare. Convolutional neural networks (CNN) which have proven to be successful supervised algorithms for classifying imaging data, are of particular interest in the neuroscience community for their utility in the classification of Alzheimer's disease (AD) AD is the leading cause of dementia in the aging population. There remains a critical unmet need for early detection of AD pathogenesis based on non invasive neuroimaging techniques, such as magnetic resonance imaging (MRI) and positron emission tomography (PET) In this comprehensive review, we explore potential interdisciplinary approaches for early detection and provide insight into recent advances on AD classification using 3D CNN architectures for multi modal PET/MRI data. We also consider the application of generative adversarial networks (GANs) to overcome pitfalls associated with limited data. Finally, we discuss increasing the robustness of CNNs by combining them with ensemble learning (EL)
The effects of nitrogen, phosphorus, and potassium levels on the yield and fiber quality of cotton cultivars
Year: 2019

The objective of this work was to evaluate the effects of nitrogen (N) phosphorus (P) and potassium (K) levels on the yield and fiber quality of cotton cultivars with different maturation cycles and chemical fertility gradients. The experimental design was a randomized block design with five replicates. The treatments consisted of a combination of 13 cotton cultivars (FM 910, FM 993, IMA 12427, IMA 1595, IMA 1600, IMA 2059, IMA 278, IMA 2968, IMA 3869, IMA 474, IMA 6035, IMA 690, and IMA 8276) at three levels of fertilization (50% 100% and 150% of the recommended dose of each nutrient) with nitrogen, phosphorus, and potassium. Cultivars IMA 2059, IMA 2968, and IMA 8276 had little or no response to increase fertility levels. However, they all produced more than 1000 kg ha 1 of lint. Cultivars IMA 1600, IMA 3869, IMA 474, IMA 6035, and IMA 690 presented higher yields at the 150% level when compared to the 50% level, but these same yields were achieved with just the 100% recommended dose. IMA 6035 was the most productive. It had a lint yield of 1500 kg ha 1. In general, the use of 100% or 150% of the recommended nitrogen (N) phosphorus (P) and potassium (K) dose increased fiber quality, though this did not apply to micronaire values. These values decreased with increased fertility in 70% of the analyzed cultivars. We concluded that the level of soil fertility affects cotton yield and fiber quality responses. We found that demanding cultivars may increase yield. However, increasing the dose of nutrients can increase the cost of production in less demanding cultivars.
AQUARIUM FISH SMART FARMING ON INTERNET OF THINGS IOT AND MOBILE APPLICATION TECHNOLOGY
Year: 2019

Caring for fish raised in mini aquarium fish farming is very important in keeping fish beautiful and reduce the mortality of fish. This paper aims to present a mobile application system with IoT and android application to control the aquarium water system. Android studio, Java, C, Arduino IDE, SQL and Firebase software ware used to develop in this study. Node esp28266 MCU V.2 board, Wemos D1 boards and module ultrasonic hardware were used to create the control system. This system has been tested with real home miniaquarium and performance data collection. Black Box testing is used to evaluate the performance of the system with users and experts. The result shows the mean and standard division by after users and experts explain on 4.21, 4.15 and 0.74, 0.72 respectively. Thus, this system can be used a main information tool for helpful users and prototype in others smart farmer.
Saliva use as a lubricant for anal sex is a risk factor for rectal gonorrhoea among men who have sex with men, a new public health message: a cross sectional survey
Venue: Sexually Transmitted Infections
Year: 2016

Apart from penile anal intercourse, other anal sexual practices (rimming, fingering and saliva use as a lubricant for anal sex) are common among men who have sex with men (MSM) The aim of this study is to evaluate whether these anal sexual practices are risk factors for rectal gonorrhoea in MSM.  A cross sectional survey was conducted among MSM attending Melbourne Sexual Health Centre between 31 July 2014 and 30 June 2015. Rectal gonorrhoea cases were identified by culture.  Among 1312 MSM, 4.3% (n=56) had rectal gonorrhoea. Other anal sexual practices were common among MSM: receptive rimming (70.5% receptive fingering or penis dipping (84.3% and using partner's saliva as a lubricant for anal sex (68.5% Saliva as a lubricant (adjusted OR 2.17; 95% CI 1.00 to 4.71) was significantly associated with rectal gonorrhoea after adjusting for potential confounding factors. Receptive rimming and fingering or penis dipping were not statistically associated with rectal gonorrhoea. The crude population attributable fraction of rectal gonorrhoea associated with use of partner's saliva as a lubricant for anal sex was 48.9% (7.9% to 71.7%  Saliva use as a lubricant for anal sex is a common sexual practice in MSM, and it may play an important role in gonorrhoea transmission. Almost half of rectal gonorrhoea cases may be eliminated if MSM stopped using partner's saliva for anal sex.
Kluster Bag of Word Menggunakan Weka
Year: 2015

Dalam bidang pengolahan bahasa alami dan sistem temu balik informasi, representasi sebuah data teks sangat penting untuk mendukung proses analisis data statistik di dalamnya. Data teks dengan bentuk tidak terstruktur dapat direpresentasikan secara sederhana menggunakan sekumpulan set kata yang disebut bag of word s dan belum memiliki label atau kelas tertentu. Data unsupervised atau objek objek yang belum memiliki label dapat dikelompokan menggunakan klustering berdasarkan kemiripan satu objek dengan objek lain. Artikel ini membahas perbandingan hasil pengelompokan unsupervised data menggunakan algoritma kluster yang tersedia pada tools Weka, yaitu SimpleKMeans, X Means, dan Farthest First SimpleKMeans dan XMeans digunakan untuk mengolah dataset dan mengelompokan berdasarkan jumlah kluster tetap yang digunakan, sedangkan Farthest First akan meletakan semua pusat kluster pada titik terjauh dari pusat kluster yang sudah ada untuk mengelompokan data. Dataset berasal dari UCI machine learning dengan menggunakan 3 koleksi data, yaitu Enron Email, NIPS Proceedings dan Daily Kos Blog entries Performa dataset diuji dengan berbagai masukan parameter yang berbeda meliputi jumlah kluster hingga evaluasi sum squared error (SSE) serta iterasi selama proses pengolahan data. Hasil penelitian diharapkan dapat dijadikan acuan untuk menentukan algoritma dan parameter yang sesuai untuk melakukan pengelompokan data yang tidak memiliki label.
tidyLPA: An R Package to Easily Carry Out Latent Profile Analysis (LPA) Using Open Source or Commercial Software
Venue: J. Open Source Softw.
Year: 2018

Researchers are often interested in identifying homogeneous subgroups within heterogeneous samples on the basis of a set of measures, such as profiles of individuals' motivation (i.e. their values, competence beliefs, and achievement goals) Latent Profile Analysis (LPA) is a statistical method for identifying such groups, or latent profiles, and is a special case of the general mixture model where all measured variables are continuous (Harring Hodis, 2016; Pastor, Barron, Miller, Davis, 2007) The tidyLPA package allows users to specify different models that determine whether and how different parameters (i.e. means, variances, and covariances) are estimated, and to specify and compare different solutions based on the number of profiles extracted.
AVATAR: Implementation of a Human Computer Interface Based on an Intelligent Virtual Agent
Venue: 2019 IEEE Colombian Conference on Communications and Computing (COLCOM)
Year: 2019

For several years the use of Information and Communication Technologies (ICT) has been questioned as a reason to diminish the social interaction between people. Although, it is not possible to remove ICT from our lives as we depend on them in many aspects, we can adapt them so that their use allows us to improve our social skills. This is the case of the Human Computer Interface (HCI) and, especially those that involve emotions in a communication with machines similar to human interaction between peers. In this article, the implementation of an HCI based on an intelligent virtual agent is presented, with the possibility of learning basic information about the interlocutor and maintaining a short interaction on topics of general interest. The implementation was made in open source software, generating not only a tool, but a development platform for other people to make contributions. The virtual agent was evaluated through short sessions with university students, who, according to a survey conducted, showed their acceptance of the interaction process.
A 40 m Range 90 frames/s CMOS Time of Flight Sensor Using SPAD and In Pixel Time Gated Pulse Counter
Venue: IEEE Solid State Circuits Letters
Year: 2020

This letter presents a CMOS indirect time of flight (i ToF) image sensor, which is based on a single photon avalanche diode (SPAD) and a compact in pixel time gated pulse counter. The proposed SPAD based i ToF sensor makes it possible to achieve a time gated photon counting method at the pixel level and to enlarge a depth range up to 40 m while maintaining the pixel demodulation frequency up to 25 MHz. A prototype sensor is implemented in a 110 nm CMOS process and has a pixel array of <inline formula> <tex math notation="LaTeX"$64\times64$ /tex math>/inline formula> with a pixel pitch of <inline formula> <tex math notation="LaTeX"$32~\mu \text{m} /tex math>/inline formula> With a 3 D frame rate of 90 frames/s, the sensor achieves high 3 D image quality with a nonlinearity error below 2.25% and a relative precision error of 0.51% at a maximum distance of 40 m.
Trends in Artificial Intelligence: PRICAI 2016 Workshops
Venue: Lecture Notes in Computer Science
Year: 2016

Extraction of relations and their semantic relations from a clinical text is significant to comprehend the actionable harmful and beneficial events between two clinical entities. Particularly to implement drug safety surveillance, two simplest but most important semantic relations are adverse drug reaction and therapeutic indication. In this paper, a method to identify such semantic relations is proposed. A large scale of nearly 1.6 million sentences over 50,998 discharge summary from Electronic Medical Records were preliminary explored. Our approach provided the three main contributions; (i) Electronic Medical Records characteristic exploration; (ii) OpenIE examination for clinical text mining; (iii) automatic semantic relation identification. In this paper, the two complementary information from public knowledge base were introduced as a comparative advantage over expert annotation. Then the set of relation patterns were qualified with 0.05 significant level. The experimental results show that our method can identify the common adverse drug reaction and therapeutic indication with the high lift value. Additionally, a novel adverse drug reaction and alternative drug for a specific symptom therapy are reported to support the comprehensive further drug safety surveillance. The paper clearly illustrates that our method is not only effortless from expert annotation, automatic pattern specific semantic relation extraction, but also effective for semantic relation identification.
Johann Heinrich Glaser (1629 1675) und die Fissura petrotympanica
Year: 2014

Heinrich Glaser wird 1629 als Sohn eines Graveurs in Basel geboren und studiert zunachst drei Jahre lang Philosophie, bevor er 1648 in Genf ein Medizinstudium aufnimmt, das ihn nach Heidelberg und Paris, wo er sich acht Jahre aufhalt, sowie schliesslich in seine Heimatstadt Basel fuhrt.
Academic Misconduct Among Portuguese Economics and Business Undergraduate Students A Comparative Analysis with Other Major Students
Year: 2014

The main purpose of this study is to understand the demographic, personal and situational determining factors leading to academic misconduct among undergraduate students by comparatively analyzing the differences among Economics and Business students and other major students. Two thousand four hundred ninety two undergraduate students from different Portuguese Public Universities answered a questionnaire regarding their propensity to commit academic fraud, 640 of whom were Economics and Business students. Results concluded that Economics and Business students can be distinguished from others regarding the likelihood of copying from the other Major students. Younger students admit more readily to the possibility of cheating than older students. Results indicate a greater probability of acceptance of dishonest practices outside the area of Economics and Management and a greater probability of condemnation of improper practices by students of Economics and Management. This indicates that students of Economics and Management are aware that their behavior is incorrect and unacceptable; peer pressure and the learning process itself constitute the main justifications provided by Economics and Business students for their fraudulent actions. Implications for this practice are discussed.
Convolutional neural network for transition modeling based on linear stability theory
Year: 2020

Transition prediction is an important aspect of aerodynamic design because of its impact on skin friction and potential coupling with flow separation characteristics. Traditionally, the modeling of transition has relied on correlation based empirical formulas based on integral quantities such as the shape factor of the boundary layer. However, in many applications of computational fluid dynamics, the shape factor is not straightforwardly available or not well defined. We propose using the complete velocity profile along with other quantities (e.g. frequency, Reynolds number) to predict the perturbation amplification factor. While this can be achieved with regression models based on a classical fully connected neural network, such a model can be computationally more demanding. We propose a novel convolutional neural network inspired by the underlying physics as described by the stability equations. Specifically, convolutional layers are first used to extract integral quantities from the velocity profiles, and then fully connected layers are used to map the extracted integral quantities, along with frequency and Reynolds number, to the output (amplification ratio) Numerical tests on classical boundary layers clearly demonstrate the merits of the proposed method. More importantly, we demonstrate that, for Tollmien Schlichting instabilities in two dimensional, low speed boundary layers, the proposed network encodes information in the boundary layer profiles into an integral quantity that is strongly correlated to a well known, physically defined parameter the shape factor.
New insights into the mechanisms of epithelial mesenchymal transition and implications for cancer
Venue: Nature Reviews Molecular Cell Biology
Year: 2018

Epithelial mesenchymal transition (EMT) is a cellular programme that is known to be crucial for embryogenesis, wound healing and malignant progression. During EMT, cell cell and cell extracellular matrix interactions are remodelled, which leads to the detachment of epithelial cells from each other and the underlying basement membrane, and a new transcriptional programme is activated to promote the mesenchymal fate. In the context of neoplasias, EMT confers on cancer cells increased tumour initiating and metastatic potential and a greater resistance to elimination by several therapeutic regimens. In this Review, we discuss recent findings on the mechanisms and roles of EMT in normal and neoplastic tissues, and the cell intrinsic signals that sustain expression of this programme. We also highlight how EMT gives rise to a variety of intermediate cell states between the epithelial and the mesenchymal state, which could function as cancer stem cells. In addition, we describe the contributions of the tumour microenvironment in inducing EMT and the effects of EMT on the immunobiology of carcinomas.Epithelial mesenchymal transition (EMT) is crucial for embryogenesis, wound healing and cancer development, and confers greater resistance to cancer therapies. This Review discusses the mechanisms of EMT and its roles in normal and neoplastic tissues, the contribution of cell intrinsic signals and the microenvironment to inducing EMT, and its effects on the immunobiology of carcinomas.
Local and more local: Impact of size and organization type of settlement units on candidacy
Year: 2017

Following current debates on the study of the quality of local government, this article focuses on the effects of settlement unit size and organizational type on candidacy in local elections within the Czech Republic. Municipal size and institutional design are traditionally seen as important factors influencing political participation at the local level. However, citizens in differently defined settlement units included in a municipality are disadvantaged differently by these factors and thus, de motivated to participate in politics. The unit of analysis within the article is a settlement unit within a municipality. The article uses Poisson regression to estimate the effect of the absolute and relative size of the settlement unit and different organizational types of settlement unit on the relative number of candidates in the unit. The analysis is based on data from 6,124 Czech municipalities over three sets of elections. The results of the analysis show that increasing absolute size and decreasing relative size of settlement unit have negative effects on the number of candidates in units. Also the institutionally disadvantaged units (defined by the location of the municipal office within the settlement unit) produce smaller number of candidates. The results show the importance of structural factors on the traditionally neglected type of political participation (candidacy) within this field. This allows the formulation of recommendations for local government reforms, not only in the Czech Republic, but also for amalgamated municipal systems.
Kinetics and mechanistic aspects of removal of heavy metal through gas liquid sulfide precipitation: A computational and experimental study.
Venue: Journal of hazardous materials
Year: 2020

The production of fine particles from extremely high supersaturation has challenged the application of sulfide precipitation in treating heavy metal wastewater due to the difficulty of solid liquid separation. To this end, a gas liquid sulfide precipitation reactor for the removal of Cu2+ was designed by controlling the mass transfer and supersaturation levels during sulfidation processes. Particularly, a computational fluid dynamics (CFD) model of the reactor, integrating sulfidation reaction kinetics with two phase flow hydrodynamics, was first built, followed by examining the effects of H2S(g) bubble diameter and flow rate. Based on the CFD simulation, the rate limiting step of the gas liquid sulfide precipitation reaction is the gas liquid mass transfer process. Either reducing H2S(g) bubble diameter or increasing H2S(g) flow rate can result in the control of reaction rate and supersaturation level in the system. In order to validate the CFD simulations, we measured Cu2+ concentrations during the sulfidation process with the batch experiments. The agreement between computational and experimental results indicated that our mechanistic model can provide a protocol for the design and optimization of the reaction system, allowing one to visualize the time dependent reaction process and evaluate the performance of a reactor.