nils-herrmann/clean_scirepeval huggingface dataset:
Being seen by others as we see ourselves: the congruence between the ingroup and outgroup perceptions of health and social care students
Year: 2006

This paper examines inter group processes amongst neophyte health and social care students about to embark on an inter professional educational programme. Positive relationships between students of the different professions must be optimised to promote student learning of each other, a central objective of these courses. It has been proposed that to reduce conflict and promote harmonious inter group relations during this IPE activity, students from each professional group should feel their own group (the in group) to be distinctive from other professional groups (the out group) on some key characteristics (intergroup differentiation) Good relations are further promoted if the characteristics they see as distinctive to their identities are also recognised as distinctive by other professional groups (mutual inter group differentiation) The current paper considers the incidence of these two factors in neophyte health and social care students and identifies sources of potential inter group conflict. The findings of the study suggest that all groups of neophyte health and social care students perceived their in group as distinct from other professional groups with the exception of audiology students. The implications of this finding to the relationships between students participating in IPE are discussed. Further, in certain groups, there was evidence that students of these groups were seen by others as they saw themselves. This was particularly the case for doctors and social workers and implies these professions will suffer least from a threat to their group distinctiveness. However, there were instances where characteristics, seen as distinctive by the professional group itself, were not recognised by other groups. For example, physiotherapy students believe that being a team player, decision making and practical skills were all distinctive characteristics of their profession. However, these features were not recognised as distinctive by other professional groups. The implications of matches/mismatches in how students see themselves and how they may be viewed by others are discussed in terms of their impact on student learning experiences and relationships during inter professional education.
Machine Learning for Wireless Networks with Artificial Intelligence: A Tutorial on Neural Networks
Venue: ArXiv
Year: 2017

Next generation wireless networks must support ultra reliable, low latency communication and intelligently manage a massive number of Internet of Things (IoT) devices in real time, within a highly dynamic environment. This need for stringent communication quality of service (QoS) requirements as well as mobile edge and core intelligence can only be realized by integrating fundamental notions of artificial intelligence (AI) and machine learning across the wireless infrastructure and end user devices. In this context, this paper provides a comprehensive tutorial that introduces the main concepts of machine learning, in general, and artificial neural networks (ANNs) in particular, and their potential applications in wireless communications. For this purpose, we present a comprehensive overview on a number of key types of neural networks that include feed forward, recurrent, spiking, and deep neural networks. For each type of neural network, we present the basic architecture and training procedure, as well as the associated challenges and opportunities. Then, we provide an in depth overview on the variety of wireless communication problems that can be addressed using ANNs, ranging from communication using unmanned aerial vehicles to virtual reality and edge caching.For each individual application, we present the main motivation for using ANNs along with the associated challenges while also providing a detailed example for a use case scenario and outlining future works that can be addressed using ANNs. In a nutshell, this article constitutes one of the first holistic tutorials on the development of machine learning techniques tailored to the needs of future wireless networks.
Quantitative Phase and Intensity Microscopy Using Snapshot White Light Wavefront Sensing
Venue: Scientific Reports
Year: 2019

Phase imaging techniques are an invaluable tool in microscopy for quickly examining thin transparent specimens. Existing methods are limited to either simple and inexpensive methods that produce only qualitative phase information (e.g. phase contrast microscopy, DIC) or significantly more elaborate and expensive quantitative methods. Here we demonstrate a low cost, easy to implement microscopy setup for quantitative imaging of phase and bright field amplitude using collimated white light illumination.
The assessment of quality maturity levels in Nigerian university libraries
Year: 2017

Organizations constantly evaluate their activities to ensure that they are attaining their management goals. Maturity assessment enables organizations to examine their capabilities, support innovation and evaluate development. The aim of this paper is to evaluate the maturity statuses of a selection of Nigerian university libraries in a study to investigate their quality management (QM) approaches. The study provides recommendations for means to attain the required statuses in academic library development.  The study involved a multisite case study in which interviews were conducted with 15 university librarians (or their representatives) and ten focus groups were conducted with non management library staff. The resulting qualitative data were analyzed using an aspect of framework analysis charting, while a maturity model from the field of project management (Prince 2 Maturity Model, P2MM) was used to assess maturity in QM of the libraries.  The results of the maturity assessment indicate a basic knowledge of the concept of QM implementation among the libraries. The scores obtained on the P2MM capability scale placed the libraries studied mainly on Level 1 (awareness level) of the model.  This paper demonstrates that the culture of QM in academic libraries in Nigeria is at a low level with considerable potential for development. It is suggested that future adoption of quality maturity models to assess performance and organizational effectiveness would aid improvements for value added services.  This is the first study to attempt the assessment of quality maturity levels in Nigerian academic libraries for identification of the organization's positioning in QM and strategy.
Internal Combustion Engine (ICE) Fundamentals
Year: 2015

Engines are machines designed to provide mechanical energy to a wide variety of systems by converting the chemical energy of a fuel (devices that are capable of producing a mechanical output starting from different types of energy, such as electric or hydraulic energy, are usually called motors) Internal combustion engines (ICEs) exploit the conversion of the chemical energy contained in suitable fuels typically hydrocarbons (HCs) into mechanical energy, owing to a combustion process. The heat generated by oxidation reactions of elements such as carbon or hydrogen produces a temperature increase in the fluid that acts as the working fluid in the power plant. The enthalpy increase is then exploited to generate mechanical work in suitable machines, thanks to the fluid expansion. If the combustion takes place within the working fluid itself, the machine is then called ICE; on the contrary, if the working fluid receives the heat from the combustion products remaining separated from them by a solid surface (for instance, in a heat exchanger) the machine is referred to as external combustion engine. Typical examples of external combustion engines are steam turbine plants or Stirling engines, whereas the ICEs category includes gas turbines and reciprocating and rotary ICEs. External combustion engines operate according to a thermodynamic closed cycle, as the working fluid undergoes thermodynamic transformations in a closed loop without any Handbook of Clean Energy Systems, Edited by Jinyue Yan.  978 1 118 38858 7. need of being replaced. On the contrary, the fluid operating in an ICE undergoes chemical transformations that require its periodical replacement with fresh fluid, thus performing a thermodynamic open cycle. Even though gas turbine plants can also be designed to operate through a closed cycle, they are typically operating in open cycle: consequently, strictly speaking, they should be included in the ICEs category. Nevertheless, only reciprocating and rotary engines are commonly designated as ICEs and will therefore be discussed in this chapter
Characterizing the Integrality Gap of the Subtour LP for the Circulant Traveling Salesman Problem
Venue: SIAM J. Discret. Math.
Year: 2019

We consider the integrality gap of the subtour LP relaxation of the Traveling Salesman Problem restricted to circulant instances. De Klerk and Dobre conjectured that the value of the optimal solution to the subtour LP on these instances is equal to an entirely combinatorial lower bound from Van der Veen, Van Dal, and Sierksma. We prove this conjecture by giving an explicit optimal solution to the subtour LP. We then use it to show that the integrality gap of the subtour LP is 2 on circulant instances, making such instances one of the few non trivial classes of TSP instances for which the integrality gap of the subtour LP is exactly known. We also show that the degree constraints do not strengthen the subtour LP on circulant instances, mimicking the parsimonious property of metric, symmetric TSP instances shown in Goemans and Bertsimas in a distinctly non metric set of instances.
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Venue: The Lancet
Year: 2020

A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019 nCoV) We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients.  All patients with suspected 2019 nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory confirmed 2019 nCoV infection by real time RT PCR and next generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not.  By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory confirmed 2019 nCoV infection. Most of the infected patients were men (30 [73% of 41) less than half had underlying diseases (13 [32% including diabetes (eight [20% hypertension (six [15% and cardiovascular disease (six [15% Median age was 49*0 years (IQR 41*0 58*0) 27 (66% of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98% of 41 patients) cough (31 [76% and myalgia or fatigue (18 [44% less common symptoms were sputum production (11 [28% of 39) headache (three [8% of 38) haemoptysis (two [5% of 39) and diarrhoea (one [3% of 38) Dyspnoea developed in 22 (55% of 40 patients (median time from illness onset to dyspnoea 8*0 days [IQR 5*0 13*0] 26 (63% of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29% RNAaemia (six [15% acute cardiac injury (five [12% and secondary infection (four [10% 13 (32% patients were admitted to an ICU and six (15% died. Compared with non ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFa.  The 2019 nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
Associations between weight status and liking scores for sweet, salt and fat according to the gender in adults (The Nutrinet Sante study)
Venue: European Journal of Clinical Nutrition
Year: 2014

As taste preferences may be associated with obesity, the present study investigated whether obese subjects presented heightened liking for the sensations of sweet, salt and fat.Liking scores were determined by a questionnaire including 83 items on liking for sweet or fatty foods, and the preferred extent of seasoning with salt, sweet or fat. Data from 46 909 adults included in the French web based observational cohort of the Nutrinet Sante study were collected and weighted according to the national population census. Relationships between liking scores and body mass index (BMI) as categorical or linear explanatory variable were assessed separately by gender using covariance and linear regression analyses, adjusted for age, education level, living area, smoking and alcohol.Overall liking scores for salt and fat were linearly positively linked to BMI in men and women (P0.001) and were higher in obese than in normal weight individuals. The score difference between BMI categories was greater in women for fat liking only. For sweet liking, results differed between gender and compounding factors. Liking for added sugar and sweet foods was positively linked to BMI in women unlike in men; liking for natural sweetness was negatively linked to BMI in both genders.This study demonstrates that the relationship between liking and BMI differs according to the gender in its magnitude for fat and in its nature for sweet, unlike that for salt. Liking for sweet and fat may be linked to overconsumption of the corresponding foods, especially in women. This warrants further investigation.
KalKi: A Software Defined IoT Security Platform
Venue: 2020 IEEE 6th World Forum on Internet of Things (WF IoT)
Year: 2020

Commercial IoT devices are increasingly being integrated into software systems. However, given the also increasing number of IoT vulnerability reports, there is a pressing need to enable organizations to achieve such integration with high assurance, especially for systems with high security and safety requirements. We present KalKi, a software defined IoT security platform that moves security enforcement to the network to enable safe integration of IoT devices, even if the devices are not fully trusted or configurable. KalKi leverages software defined networking (SDN) concepts and constructs, combined with a rich policy model that specifies both cyber and kinetic attacks, to create a safe, highly dynamic and extensible IoT integration platform. Our experiments demonstrate high performance, scalability and resilience, even in the presence of a powerful attacker.
Estimating the Economic Value of National Parks with Count Data Models Using On Site, Secondary Data: The Case of the Great Sand Dunes National Park and Preserve
Venue: Environmental management
Year: 2009

We estimate an individual travel cost model for Great Sand Dunes National Park and Preserve (GSD) in Colorado using on site, secondary data. The purpose of the on site survey was to help the National Park Service better understand the visitors of GSD; it was not intended for a travel cost model. Variables such as travel cost and income were estimated based on respondents' Zip Codes. Following approaches found in the literature, a negative binomial model corrected for truncation and endogenous stratification fit the data the best. We estimate a recreational benefit of U.S. $89/visitor/year or U.S. $54/visitor/24 h recreational day (in 2002 U.S. Based on the approach presented here, there are other data sets for national parks, preserves, and battlefields where travel cost models could be estimated and used to support National Park Service management decisions.
Mining Structured Data
Venue: IEEE Computational Intelligence Magazine
Year: 2010

In many application domains, the amount of available data increased so much that humans need help from automatic computerized methods for extracting relevant information. Moreover, it is becoming more and more common to store data that possess inherently structural or relational characteristics. These types of data are best represented by graphs, which can very naturally represent entities, their attributes, and their relationships to other entities. In this article, we review the state of the art in graph mining, and we present advances in processing trees and graphs by two computational intelligence classes of methods, namely neural networks and kernel methods.
Large Scale Evolution Strategy Based on Search Direction Adaptation
Venue: IEEE Transactions on Cybernetics
Year: 2021

The covariance matrix adaptation evolution strategy (CMA ES) is a powerful evolutionary algorithm for single objective real valued optimization. However, the time and space complexity may preclude its use in high dimensional decision space. Recent studies suggest that putting sparse or low rank constraints on the structure of the covariance matrix can improve the efficiency of CMA ES in handling large scale problems. Following this idea, this paper proposes a search direction adaptation evolution strategy (SDA ES) which achieves linear time and space complexity. SDA ES models the covariance matrix with an identity matrix and multiple search directions, and uses a heuristic to update the search directions in a way similar to the principal component analysis. We also generalize the traditional 1/5th success rule to adapt the mutation strength which exhibits the derandomization property. Numerical comparisons with nine state of the art algorithms are carried out on 31 test problems. The experimental results have shown that SDA ES is invariant under search space rotational transformations, and is scalable with respect to the number of variables. It also achieves competitive performance on generic black box problems, demonstrating its effectiveness in keeping a good tradeoff between solution quality and computational efficiency.
Preliminary Evidence of a Missing Self Bias in Face Perception for Individuals with Dissociative Identity Disorder
Venue: Journal of trauma dissociation the official journal of the International Society for the Study of Dissociation
Year: 2019

Failing to recognize one's mirror image can signal an abnormality in one's sense of self. In dissociative identity disorder (DID) individuals often report that their mirror image can feel unfamiliar or distorted. They also experience some of their own thoughts, emotions, and bodily sensations as if they are nonautobiographical and sometimes as if instead, they belong to someone else. To assess these experiences, we designed a novel backwards masking paradigm in which participants were covertly shown their own face, masked by a stranger's face. Participants rated feelings of familiarity associated with the strangers' faces. 21 control participants without trauma generated dissociation rated masks, which were covertly preceded by their own face, as more familiar compared to masks preceded by a stranger's face. In contrast, across two samples, 28 individuals with DID and similar clinical presentations (DSM IV Dissociative Disorder Not Otherwise Specified type 1) did not show increased familiarity ratings to their own masked face. However, their familiarity ratings interacted with self reported identity state integration. Individuals with higher levels of identity state integration had response patterns similar to control participants. These data provide empirical evidence of aberrant self referential processing in DID/DDNOS and suggest this is restored with identity state integration.
Regime changes in Bitcoin GARCH volatility dynamics
Venue: Finance Research Letters
Year: 2019

We test the presence of regime changes in the GARCH volatility dynamics of Bitcoin log returns using Markov switching GARCH (MSGARCH) models. We also compare MSGARCH to traditional single regime GARCH specifications in predicting one day ahead Value at Risk (VaR) The Bayesian approach is used to estimate the model parameters and to compute the VaR forecasts. We find strong evidence of regime changes in the GARCH process and show that MSGARCH models outperform single regime specifications when predicting the VaR.
PENGUJIAN UNSUR PENYALAHGUNAAN WEWENANG OLEH PENGADILAN TATA USAHA NEGARA DALAM KONTEKS PENANGANAN TINDAK PIDANA KORUPSI
Year: 2019

Penelitian ini bertujuan untuk mengkaji kewenangan Peradilan TUN menguji unsur penyalahgunaan wewenang yang diatur dalam UU No. 30 Tahun 2014 tentang Administrasi Pemerintahan yang menjadi alasan bagi Penulis melakukan penelitian ini karena konsekuensi kewenangan Peradilan TUN tersebut dapat menimbulkan implikasi hukum dalam proses penyidikan perkara korupsi penyalahgunaan wewenang dan kewenangan pengadilan korupsi dalam memeriksa dan mengadili perkara korupsi penyalahgunaan wewenang. Penelitian ini merupakan kajian hukum normatif, dengan menggunakan conceptual approach, statute approach, dan case approach. Hasil kajian menunjukkan terdapat inkonsistensi oleh Penuntut Umum dalam merumuskan dakwaan perkara korupsi penyalahgunaan wewenang dan korupsi melawan hukum serta adanya inkonsistensi oleh hakim dalam pertimbangan membuktikan unsur melawan hukum atau unsur dengan tujuan menyalahgunakan wewenang, unsur memperkaya atau menguntungkan diri sendiri atau orang lain atau suatu korporasi. Oleh karena itu rumusan Pasal 2 dan Pasal 3 UU PTPK merupakan rumusan delik yang terlalu luas yang menimbulkan ketidakpastian hukum karena dapat menjerat siapa saja sepanjang telah terjadi kerugian keuangan negara. Selain itu dari hasil kajian juga ditemukan konsep "penyalahgunaan wewenang" dalam UU Administrasi Pemerintahan sama dengan konsep "menyalahgunakan kewenangan" dalam UU Pemberantasan Tipikor. Karenanya, Peradilan Tipikor dan Peradilan TUN secara atributif sama sama memiliki kompetensi absolut untuk memeriksa dan memutus penyalahgunaan kewenangan dalam Tipikor. Implikasi hukum kebijakan legislasi yang memberikan kewenangan untuk memeriksa dan memutus penyalahgunaan kewenangan dalam Tipikor kepada dua lembaga peradilan, Pertama, berpotensi menimbulkan sengketa kewenangan mengadili antara kedua peradilan tersebut; Kedua, menimbulkan ketidakpastian mekanisme penanganan perkara korupsi penyalahgunaan kewenangan dalam Tipikor sehingga menghambat upaya pemberantasan Tipikor.