nils-herrmann/clean_scirepeval huggingface dataset:
The Economics of Analyzing the TPP: Submission to the US International Trade Commission

The Trans Pacific Partnership (TPP) is a landmark agreement for the United States and the global trading system. In a paper included in the Peterson Institute's submission for these Hearings (Petri Plummer, 2016) we estimated that the TPP will increase US real incomes substantially and establish new, market oriented rules in a host of rapidly changing areas of international commerce. We use a comprehensive, state of the art computable general equilibrium (CGE) model to analyze the TPP. The model is based on the GTAP database, but also includes new theoretical features and information on tariffs, non tariff barriers, trade agreements and other variables. It covers trade among 29 countries and regions and is documented on asiapacifictrade.org. Over the last three decades the granular microeconomic structure of CGE models has made them the tool of choice for trade policy analysis. They enable researchers to study changes in specific trade barriers and to trace effects on output, productivity and wages across countries. CGE models have been extensively tested and refined, and are now ubiquitous in policy analysis in fields ranging from trade to agriculture, energy and the environment. Given the Commission's expertise in CGE modeling, we expect that such analysis will also play an important role in its assessment of the TPP. Yet many contributors to the public debate fail to appreciate why long run, microeconomic models are needed, how they work, and what their limitations are. Comments at these Hearings have echoed such misperceptions, arguing for vaguely defined new approaches. In the following, we offer evidence that established
Effect of Vernonia amygdalina Bitter Leaf Extract on Growth Performance Carcass Quality and Economics of Production of Broiler Chickens

Vernonia amygdalina (bitter leaf) is a shrub or small tree that grows throughout tropical Africa. It is a very important protective food and useful for the maintenance of health and treatment of various diseases. The purpose of this study is to determine the effect of Vernonia amygdalina (VA) extract on growth performance, carcass quality and economics of production of broiler chicks. Sixty 7day old Oba Marshall broiler chicks were used for 54 days water infusion feeding trial. Four water infusion levels 0ml, 25ml, 50ml and 75ml of VA per litre of (clean) drinking water designated as T1, T2, T3 and T4 were used. Birds were randomly assigned in a completely randomized design (CRD) experiment with each treatment replicated three times (5 birds per replicate) daily feed and water were offered ad libitum. Data were collected on feed intake, weekly body weight and economics of production. The result showed that there was no significant (p>0.05) difference in weekly feed intake of birds among the four treatments, T1, T2, T3 and T4. Significant (p<0.05) differences were observed in the final body weight, weekly weight gain and feed conversion ratio of birds among the treatments. The result for carcass quality showed significant differences (p<0.05) in slaughtered weight, carcass weight, carcass dressing International Journal of Agriculture and Earth Science Vol. 2 No.1 ISSN 2489 0081 2016 www.iiardpub.org IIARD International Institute of Academic Research and Development Page 59 percentage, drum stick, thigh, breast, giblets and back but no significant (p>0.05) difference was observed in wing, abdominal fat, head, intestine length and intestine weight. There was decreased mortality of broilers fed 50ml and 75ml of VA. Birds on T3 (50% had the best feed conversion ratio (2.49% and least cost benefit ratio. It can be concluded that the birds fed 50% (T3) and 75% (T4) infusion level gave better result, highest revenue and can be recommended to achieve better feed conversion ratio, weight gain and carcass quality.
Raman spectroscopy of rare earth orthoferrites R FeO 3 R =La, Sm, Eu, Gd, Tb, Dy)

We report a Raman scattering study of six rare earth orthoferrites $R{\mathrm{FeO}}_{3} with $R$ La, Sm, Eu, Gd, Tb, Dy. The use of extensive polarized Raman scattering of \mathrm{SmFeO}}_{3} and first principles calculations enable the assignment of the observed phonon modes to vibrational symmetries and atomic displacements. The assignment of the spectra and their comparison throughout the whole series allow correlating the phonon modes with the orthorhombic structural distortions of $R{\mathrm{FeO}}_{3} perovskites. In particular, the positions of two specific $A{}_{g} modes scale linearly with the two \mathrm{FeO}}_{6} octahedra tilt angles, allowing the distortion to be tracked throughout the series. At variance with literature, we find that the two octahedra tilt angles scale differently with the vibration frequencies of their respective $A{}_{g} modes. This behavior, as well as the general relations between the tilt angles, the frequencies of the associated modes, and the ionic radii are rationalized in a simple Landau model. The reported Raman spectra and associated phonon mode assignment provide reference data for structural investigations of the whole series of orthoferrites.
Bi 1 x Ca x FeO 3 d (0 x 1) ceramics: Crystal structure, phase and elemental composition, and chemical bonding from X ray diffraction, Raman scattering, Mossbauer, and X ray photoelectron spectra

An integrated study of samples of Bi1 khCakhFeO3 d (BCFO) system for 0 x 1 (step 0.1) is performed using X ray diffraction (XRD) Raman scattering, Mossbauer spectroscopy, and X ray photoelectron spectroscopy (XPS) Measured elemental compositions of samples were found to deviate substantially from nominal ones. X ray structure analysis discovered a continuous series of solid solutions with perovskite structure (or its derivatives) on the interval of nominal Ca content 0 x 0.9. However, the analysis of the data from all the methods used, limits the region of single phase samples (in presence of insignificant amount of foreign ones) to nominal Ca content interval 0.1
Research of Structure Ordering in Ceramic Ferroelectromagnets Bi 1 x La x FeO 3 by Raman Spectroscopy

The ordering processes in structures of ceramic ferroelectromagnets Bi1 x La x FeO3 (x 0.075 0.20) is researched by Raman spectra It was discovered that Bi1 x La x FeO3 structure is close to the one of BiFeO3 However, bands in Raman spectra of Bi1 x La x FeO3 were much wider than bands of single crystal BiFeO3 which means that in ceramics solid solutions structure is more disordered than in single crystals. In Raman spectra of Bi1 x La x FeO3 in the area of oxygen octahedrons librations (50 90 cm 1) several groups of bands with frequencies 59 69, 72 77, 86 92 cm 1 were observed in dependence of solid solution compound. This result confirms XRD data that researched solid solutions are not single phase. At La (x 0.120) low frequency bands in Raman spectra narrowed which indicates ordering of structure units in cation sublattices. At increase of La concentration in Bi1 x La x FeO3 structure, unambiguous dependence of spectral bands parameters was not observed. Perhaps this could be explained by the fact that at increase of x value, character of La integration to the solid solution structure changes.
IoT technologies for embedded computing: A survey
Venue: 2016 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS)

Emergence of Internet of Things brings a whole new class of applications and higher efficiency for existing services. Application specific requirements, as well as connectivity and communication ability of devices have introduced new challenges for IoT applications. This paper provides an overview of IoT technologies required from an embedded design perspective and specific properties associated with IoT in embedded systems' landscape. We investigate essential technologies for development of IoT systems, existing trends, and its distinguishing properties. By discussing the key characteristics, main application domains, and major research issues in IoT, this paper provides a comprehensive IoT perspective for embedded system design.
Exploiting IoT technologies for enhancing Health Smart Homes through patient identification and emotion recognition
Venue: Comput. Commun.

Currently, there is an increasing number of patients that are treated in home, mainly in countries such as Japan, USA and Europe. As well as this, the number of elderly people has increased significantly in the last 15 years and these people are often treated in home and at times enter into a critical situation that may require help (e.g. when facing an accident, or becoming depressed) Advances in ubiquitous computing and the Internet of Things (IoT) have provided efficient and cheap equipments that include wireless communication and cameras, such as smartphones or embedded devices like Raspberry Pi. Embedded computing enables the deployment of Health Smart Homes (HSH) that can enhance in home medical treatment. The use of camera and image processing on IoT is still an application that has not been fully explored in the literature, especially in the context of HSH. Although use of images has been widely exploited to address issues such as safety and surveillance in the house, they have been little employed to assist patients and/or elderly people as part of the home care systems. In our view, these images can help nurses or caregivers to assist patients in need of timely help, and the implementation of this application can be extremely easy and cheap when aided by IoT technologies. This article discusses the use of patient images and emotional detection to assist patients and elderly people within an in home healthcare context. We also discuss the existing literature and show that most of the studies in this area do not make use of images for the purpose of monitoring patients. In addition, there are few studies that take into account the patient's emotional state, which is crucial for them to be able to recover from a disease. Finally, we outline our prototype which runs on multiple computing platforms and show results that demonstrate the feasibility of our approach.
Fears and concerns of Iranian diabetic women: A phenomenological study
Venue: Journal of health psychology

This study explored the fears and concerns of 19 Iranian diabetic women using a phenomenological approach. Semistructured individual interviews were conducted; each interview was transcribed verbatim and analyzed simultaneously using Van Manen's method. Data analysis resulted in the emergence of two main themes: (1) "a vague and uncertain future" with sub themes of "fears of dependency," "loneliness," "disease complications," and "children's future" and (2) "changing lifestyles" with sub themes of "dietary restrictions" and "insulin injection." Psychological concerns are common in Iranian diabetic women. These concerns can contribute to poor disease self management. Thus, it is hoped that identifying these concerns can lead to better management of these issues and a better outcome in diabetic patients.
Reactive power compensation through active back to back converter in type 4 wind turbine
Venue: 2016 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)

In this paper, the mathematical model of type 4 wind turbine topology is developed to represent its dynamic behavior. The main objective of a type 4 wind turbine is to deliver active power to the system, but to perform this action; it must absorb reactive power from the power network, causing disturbances and stress in the rest of the power system. Through the dynamic control system used in the back to back converter, the reactive power compensation at the PCC is achieved, making possible the energy exchange between the type 4 wind turbine and the rest of the power network.
Reactive and real power compensation in distribution line using D STATCOM with energy storage
Venue: 2016 International Conference on Computation of Power, Energy Information and Commuincation (ICCPEIC)

In this paper, Distribution Static Synchronous Compensator (D STATCOM) using a control strategy based on instantaneous symmetrical component theory, has been utilized to provide reactive and real power compensation in the distribution line. Reactive power compensation is required in the distribution line to reduce the reactive power burden and to mitigate other undesirable effects being caused by the inductive type load, while real power compensation is also required to be provided to reduce the effect of voltage drop being caused due to the comparatively higher resistance of the distribution line. Generally, no compensation is provided in distribution line; even the conventional devices which are used for compensation suffer from many limitations. D STATCOM is a power electronics based shunt connected compensating device which proves to be very useful to provide reactive and real power compensation in the distribution line. In this paper, using D STATCOM, first reactive power compensation and then real power compensation is provided in the distribution line. To provide only reactive power compensation a capacitor is used, while to provide real power compensation a battery energy storage system is used. The simulation results prove that the D STATCOM with the proposed control strategy provides full reactive power compensation and also partial real power compensation in the distribution line for different values of loads.
Z Source Multilevel Inverters

There are two hotly researched Z source/quasi Z source (ZS/qZS) multilevel inverters: the ZS/qZS neutral point clamped (NPC) inverter and ZS/qZS cascaded multilevel inverter (CMI) The ZS/qZS concept, integrating with those traditional multilevel inverters, inherits the merits of both topologies with improved inverter reliability due to short circuit immunity. This chapter presents the configurations, operating principles, and modulation schemes of the two ZS/qZS multilevel inverters. Three level NPC inverters, having many inherent advantages, are commonly used as the preferred topology for medium voltage ac drives. The CMI is a promising candidate for the next generation of PV power converters because it has features such as separate PV sources, transformerless, low harmonics, small filters, and low switching frequency. The system level modeling and control of a qZS CMI based three phase grid tie PV power system were addressed, and simulation results were demonstrated, providing a competitive candidate for high power medium voltage power systems.
Organizing for Crisis Management: Building Governance Capacity and Legitimacy

What makes a well functioning governmental crisis management system, and how can this be studied using an organization theory based approach? A core argument is that such a system needs both governance capacity and governance legitimacy. Organizational arrangements as well as the legitimacy of government authorities will affect crisis management performance. A central argument is that both structural features and cultural context matter, as does the nature of the crisis. Is it a transboundary crisis? How unique is it, and how much uncertainty is associated with it? The arguments are substantiated with empirical examples and supported by a literature synthesis, focusing on public administration research. A main conclusion is that there is no optimal formula for harmonizing competing interests and tensions or for overcoming uncertainty and ambiguous government structures. Flexibility and adaptation are key assets, which are constrained by the political, administrative, and situational context. Furthermore, a future research agenda is indicated.
Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management.
Venue: Physics of life reviews

This paper proposes an essay concerning the understanding of human behaviours and crisis management of crowds in extreme situations, such as evacuation through complex venues. The first part focuses on the understanding of the main features of the crowd viewed as a living, hence complex system. The main concepts are subsequently addressed, in the second part, to a critical analysis of mathematical models suitable to capture them, as far as it is possible. Then, the third part focuses on the use, toward safety problems, of a model derived by the methods of the mathematical kinetic theory and theoretical tools of evolutionary game theory. It is shown how this model can depict critical situations and how these can be managed with the aim of minimizing the risk of catastrophic events.
Social media and crisis management: CERC, search strategies, and Twitter content
Venue: Comput. Hum. Behav.

The current manuscript explores Twitter use and content in the precrisis stages of a major weather event in the northeast. A multi level content analysis of tweets collected in the lead up to landfall suggests that emergency management agencies largely underutilized the medium, and that actionable information was easier to find when searching along localized hashtags. The findings are discussed in terms of the Crisis and Emergency Risk Communication (CERC) model of crisis management and implications for emergency management agencies. We examined a large number of tweets in the days leading up to a major snowstorm.Twitter content dealt more with affective orientation than actionable information.Actionable information was easier to find using localized hashtags.Emergency management agencies were largely absent from the conversation.
Analysing Java identifier names

Identifier names are the principal means of recording and communicating ideas in source code and are a significant source of information for software developers and maintainers, and the tools that support their work. This research aims to increase understanding of identifier name content types words, abbreviations, etc. and phrasal structures noun phrases, verb phrases, etc. by improving techniques for the analysis of identifier names. The techniques and knowledge acquired can be applied to improve program comprehension tools that support internal code quality, concept location, traceability and model extraction. Previous detailed investigations of identifier names have focused on method names, and the content and structure of Java class and reference (field, parameter, and variable) names are less well understood. I developed improved algorithms to tokenise names, and trained part of speech tagger models on identifier names to support the analysis of class and reference names in a corpus of 60 open source Java projects. I confirm that developers structure the majority of names according to identifier naming conventions, and use phrasal structures reported in the literature. I also show that developers use a wider variety of content types and phrasal structures than previously understood. Unusually structured class names are largely project specific naming conventions, but could indicate design issues. Analysis of phrasal reference names showed that developers most often use the phrasal structures described in the literature and used to support the extraction of information from names, but also choose unexpected phrasal structures, and complex, multi phrasal, names. Using Nominal software I created to evaluate adherence to naming conventions I found developers tend to follow naming conventions, but that adherence to published conventions varies between projects because developers also establish new conventions for the use of typography, content types and phrasal structure to support their work: particularly to distinguish the roles of Java field names.
Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low Rank Tensors via Convex Optimization
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

This paper studies the Tensor Robust Principal Component (TRPCA) problem which extends the known Robust PCA  to the tensor case. Our model is based on a new tensor Singular Value Decomposition (t SVD)  and its induced tensor tubal rank and tensor nuclear norm. Consider that we have a 3 way tensor X e R<sup>n1xn2xn3</sup> such that X L<sub>0</sub> S<sub>0</sub> where L<sub>0</sub> has low tubal rank and <sub>S0 is</sub> sparse. Is that possible to recover both components? In this work, we prove that under certain suitable assumptions, we can recover both the low rank and the sparse components exactly by simply solving a convex program whose objective is a weighted combination of the tensor nuclear norm and the l1 norm, i.e. min L, E |L| l||e||1, s.t. X L e, where l 1/max(n<sub>1</sub> n<sub>2</sub>)n<sub>3</sub> Interestingly, TRPCA involves RPCA as a special case when n<sub>3</sub> 1 and thus it is a simple and elegant tensor extension of RPCA. Also numerical experiments verify our theory and the application for the image denoising demonstrates the effectiveness of our method.
First World Healthcare by Third World Provider:Position of Bangladesh

Despite being a third world country, Bangladesh has a huge prospect of providing modern, advanced healthcare in cheap rates. It has started that journey by building new health infrastructures, strengthening primary health care, increasing outputs of doctors, nurses and paramedics, developing a strong health information system and encouraging public private partnerships. With increasing GDP, health status of people has also been improved as evidenced by achieving targets of the health related indicators in Millennium Development Goals. In spite of having lower per capita health expenditure than neighboring countries, Bangladeshi people have achieved higher life expectancy at birth with progressively strengthened health system. This country is developing resources at a fast pace to attract the medical tourists challenging other Asian countries popular for medical tourism. Bangladesh needs to make curative sector stronger to earn massive sum of foreign currency and emerge as a country of medical tourism in near future.
Generating Videos with Scene Dynamics
Venue: NIPS

We capitalize on large amounts of unlabeled video in order to learn a model of scene dynamics for both video recognition tasks (e.g. action classification) and video generation tasks (e.g. future prediction) We propose a generative adversarial network for video with a spatio temporal convolutional architecture that untangles the scene's foreground from the background. Experiments suggest this model can generate tiny videos up to a second at full frame rate better than simple baselines, and we show its utility at predicting plausible futures of static images. Moreover, experiments and visualizations show the model internally learns useful features for recognizing actions with minimal supervision, suggesting scene dynamics are a promising signal for representation learning. We believe generative video models can impact many applications in video understanding and simulation.