nils-herrmann/clean_scirepeval huggingface dataset:
Corporate Social Responsibility Report Narratives and Analyst Forecast Accuracy

Standalone corporate social responsibility (CSR) reports vary considerably in the content of information released due to their voluntary nature. In this study, we develop a disclosure score based on the tone, readability, length, and the numerical and horizon content of CSR report narratives, and examine the relationship between the CSR disclosure scores and analyst forecasts. We find that CSR reporters with high disclosure scores are associated with more accurate forecasts, whereas low score CSR reporters are not associated with more accurate forecasts than firms who do not issue CSR reports. The findings are robust to controlling for firm characteristics including CSR activity ratings and financial narratives. The findings are driven by experienced CSR reporters rather than first time CSR reporters. Together, our findings suggest that the content of CSR reports helps to improve analyst forecast accuracy, and this relationship is more pronounced for CSR reports with more substantial content.
Compuestos nitrogenados indicadores de estres en respuesta a las dosis toxicas y deficientes de Nitrogeno en frijol ejotero

Un amplio rango de estreses ambientales, tales como baja temperatura, sequia, alcalinidad, salinidad, deficiencia y toxicidad de nutrientes son potencialmente daninos para las plantas. El papel del nitrogeno como nutriente esencial y componente estructural de aminoacidos, proteinas, acidos nucleicos y otros constituyentes esenciales para el desarrollo ha sido ampliamente documentado en varias especies debido a la importancia en los procesos de crecimiento y produccion agricola. Sin embargo, en la actualidad, existe escasa literatura del efecto de la deficiencia y toxicidad de nitrogeno sobre los compuestos osmoreguladores como indicadores de estres en plantas. Por lo que el objetivo del presente trabajo fue estudiar los compuestos nitrogenados indicadores de estres (prolina, glicinabetaina y colina) en respuesta a las dosis toxicas y deficientes de N en frijol ejotero desarrollado en camara de cultivo bajo condiciones controladas y sistema hidroponico.  El nitrogeno fue aplicado a la solucion nutritiva en la forma de NH 4 NO 3 y en dosis crecientes: N1 =1.5 mM, N2 =3.0 mM, N3 =6.0 mM, N4 =12.0 mM, N5 =18.0 mM y N6 =24.0 mM de N. Los parametros analizados fueron la acumulacion de biomasa, la concentracion de prolina, glicinabetaina y colina en hojas, raices, semillas y vainas de frijol ejotero cv. Strike.  La aplicacion de dosis deficientes y toxicas de N afecto la produccion de biomasa en frijol, siendo las dosis toxicas las que afectaron mas este parametro. Por otro lado, resaltar que los osmoreguladores prolina, glicinabetaina y colina solamente se acumularon bajo condiciones de toxicidad de N (N6) sin embargo, en condiciones de estres provocado por la deficiencia de N (N1) no se produce la acumulacion de estos compuestos.  Los compuestos nitrogenados indicadores de estres solamente se acumulan bajo condiciones de toxicidad de N (N6) sin embargo en condiciones de estres provocadas por la deficiencia de N no se produce la acumulacion de estos compuestos por lo que se podrian definir como bioindicadores solamente del estres por toxicidad de N. Finalmente, la acumulacion de prolina, glicinabetaina y colina pudieran actuar como una fuente de N en la celula bajo condiciones de estres, donde la acumulacion de estos compuestos nitrogenados pudieran ser utilizados como una forma de almacenar N.
Ultrafast Optical Modulation of Second and Third Harmonic Generation from Cut Disk Based Metasurfaces

We design and fabricate a metasurface composed of gold cut disk resonators that exhibits a strong coherent nonlinear response. We experimentally demonstrate all optical modulation of both second and third harmonic signals on a subpicosecond time scale. Pump probe experiments and numerical models show that the observed effects are due to the ultrafast response of the electronic excitations in the metal under external illumination. These effects pave the way for the development of novel active nonlinear metasurfaces with controllable and switchable coherent nonlinear response.
Privacy Preserving Data Mining With Abridge Time Using Vertical Partition Decision Tree
Venue: WIR '16

Security and privacy is an important concern during the analysis of the sensitive and private datasets. Data mining is used for the analysis of these datasets by classification, clustering, association rules etc. During the analysis of these datasets privacy should be maintained. Privacy preservation is a technique of analyzing the dataset with privacy such that external user can t access the conclusion of the analysis. Here in this paper a new decision tree based algorithm is proposed for the privacy of the datasets. The idea is to first divide the datasets vertically into a number of parties where each of the party calculates the gain of each of the attribute and send to the central authority where the gain from all the parties are compared to find the attribute with highest gain. The proposed technique implemented here provides reqired data and also provides less computational time and error rate.
Analysis of Users' Opinions about Reasons for Divorce

One of the most important issues related to knowledge discovery is the field of comment mining. Opinion mining is a tool through which the opinions of people who comment about a specific issue can be evaluated in order to achieve some interesting results. This is a subset of data mining. Opinion mining can be improved using the data mining algorithms. One of the important parts of opinion mining is the sentiment analysis in social networks. Today, the social networks contain billions of users' comments about different issues. In previous researches in this area, various methods have been used for Persian comments analysis. In these studies, preprocessing is one of the most important parts. It arranges the data set for analysis in a standard form. The number of hashtags selected for analysis is limited. To detect the positive and negative comments, knowledge extraction or neural network techniques have been used. The current research presents a method of analysis which can analyze any hashtag for each group of users and has no limitations in this regard. Type of hashtag, the number of likes, type of user and type of positive and negative sentences can be analyzed by this method. The results of simulation and comparison of divorce data set show that the proposed method has an acceptable performance.
Analisis Kompetensi Guru Berbasis Uji Kompetensi Guru (UKG) Pada Guru Sekolah Menengah Kejuruan (SMK) Bidang Keahlian Administrasi Perkantoran di Surakarta Tahun Ajaran 2015/2016

ABSTRAK Farida Retno Wardhani. ANALISIS KOMPETENSI GURU BERBASIS UJI KOMPETENSI GURU (UKG) PADA GURU SEKOLAH MENENGAH KEJURUAN (SMK) BIDANG KEAHLIAN ADMINISTRASI PERKANTORAN DI SURAKARTA TAHUN AJARAN 2015 2016. Skripsi, Surakarta: Fakultas Keguruan dan Ilmu Pendidikan Universitas Sebelas Maret Surakarta, September 2016. Penelitian ini bertujuan untuk mengetahui: (1) Gambaran kompetensi guru, khususnya kompetensi pedagogik dan profesional guru SMK bidang keahlian Adminstrasi Perkantoran di Surakarta yang telah mengikuti UKG; (2) Hambatan hambatan yang dialami guru SMK bidang keahlian Administrasi Perkantoran di Surakarta dalam mengikuti UKG; dan (3) Jenis pendidikan dan pelatihan (diklat) yang dibutuhkan oleh guru SMK bidang keahlian Administrasi Perkantoran di Surakarta yang memperoleh hasil UKG dibawah standar untuk dapat meningkatkan profesionalitas guru. Penelitian ini menggunakan metode penelitian kualitatif dengan pendekatan studi kasus. Sumber data yang digunakan adalah sumber data primer berupa kata kata dari informan dan sumber data sekunder berupa dokumentasi dan arsip hasil UKG Tahun 2015. Teknik cuplikan informan penelitian yang digunakan adalah purposive sampling dan snowball sampling. Teknik pengumpulan data menggunakan observasi, wawancara, dan kuesioner. Teknik uji validitas data menggunakan triangulasi sumber dan triangulasi metode. Teknik analisis data yang digunakan adalah model analisis interaktif dari Miles dan Huberman. Berdasarkan hasil penelitian dapat disimpulkan (1) kompetensi pedagogik maupun kompetensi profesional guru SMK bidang keahlian Administrasi perkantoran di Surakarta sudah baik namun masih perlu ditingkatkan. Hal ini terlihat dari (a)kompetensi pedagogik maupun profesional sudah dilaksanakan sesuai indikator Permendiknas No.16 Tahun 2007 (b) rata rata nilai UKG pada kompetensi pedagogik sebesar 51,13 dan kompetensi profesional 58,32 (c) nilai rata rata kompetensi pedagogik melalui kuesioner sebesar 78,35 dan kompetensi profesional sebesar 72,73. (2) Hambatan yang dialami guru SMK bidang keahlian Administrasi Perkantoran dalam mengikuti UKG adalah materi yang diujikan pada kompetensi profesional terlalu luas, kurangnya penguasaan terhadap kompetensi pedagogik, kurangnya penguasaan terhadap komputer (3) Diklat yang dibutuhkan oleg guru SMK bidang keahlian Adminstrasi Perkantoran di Surakarta yang memperoleh hasil UKG di bawah standar untuk dapat meningkatkan profesionalitas guru diantaranya diklat pendalaman materi mata pelajaran produktif Administrasi Perkantoran, diklat tentang kompetensi pedagogik dan kompetensi profesional secara bertahap, dan diklat komputer. Kata kunci: kompetensi pedagogik, kompetensi profesional, uji kompetensi guru
A Natural Language Interface for Querying RDF and Graph Databases

Querying big data by using formal languages may result too complex for end users and traditional translation techniques from natural language to SQL, that use generic knowledge, are inadeguate in many real life scenarios. Therefore, many researchers and practitioners are working on the definition of algorithms and systems capable to translate natural language questions into formal query languages able to query big data. In this paper we present a modular system, named MANTRA QA, that enables to accurately translate natural language questions into different formal queries (e.g. SPARQL and Cypher Query) exploiting various knowledge bases. The system we present is based on MANTRA Language a formalism that enables to represent grammar based programs combined with logic predicates to identify concepts and their relations in specific knowledge domains. The MANTRA language makes use of open linked data, thesaurus, and domain ontologies.
Performance of Blended Fly Ash (FA) and Palm Oil Fuel Ash (POFA) Geopolymer Mortar in Acidic Peat Environment

This paper presents performance of blended geopolymer mortars prepared from fly ash (FA) and palm oil fuel ash (POFA) Both materials are used their Si and Al elements were activated by alkaline solution. The alkaline solution was prepared by mixing sodium silicate and sodium hydroxide. The optimum mix proportion of geopolymer mortar with FA:POFA mass ratio was 90:10. The ratio of sodium silicate solution to sodium hydroxide solution by mass was 2.5:1. The mass ratio of sand to blended ashes was 2.75:1. The mortar specimens were prepared using 5x5x5 cm cube and cured at room temperature (28oC) for 3 days before subsequently heat cured at 110oC for 24 hours. The specimens were immersed in distilled water and peat water with pH 4 5 for 120 days. The compressive strength change, porosity, and sorptivity tests were taken. In general, the results shows there was a decrease in strength, an increase in porosity and sorptivity of the blended geopolymer mortars. Fourier Transform Infra Red (FTIR) test revealed that interaction of geopolymers mortar with the acidic peat water can also cause replacement of the exchangeable cations (Na, K) in polymers by hidrogen or hydronium ions. Formation of some new zeolitic phases in blended FA POFA geopolymer mortar exposed to acidic peat water were observed.
Hand Vein Image Enhancement Based on Multi Scale Top Hat Transform

Traditional image contrast enhancement methods originally cannot improve the quality of vein images and may also import some unknown noise resulting in low recognition rate. To overcome the abovementioned disadvantages, the paper proposes an enhancement method based on the morphological filtering theory including three main procedures. Firstly, the algorithm extract the vein Region Of Interest (ROI) and then adopting the improved White Top Hat transform (WTH) and Black Top Hat transform (BTH) methods to get the features of vein in detail in both white and black pattern (vein information and background information) Secondly, to construct the filtering function with the self designed controlling operator, representing the gradient changes of the vein edges, which well reflects the importance of local detail in multi scale pattern; Finally, traditional nonlinear gray level transformation function is imported with modality to the parameters to realize the gray normalization. We perform rigorous experiments with the proposed method and other state of the art enhancement methods on the self built dorsal vein image databases, and the experimental results illustrate that the multiscale top hat theory based enhancement methods improve the contrast of hand vein images with restrictions on the possibility of enhancement on existing noise information.
A holistic approach for assessing impact of extreme weather on critical infrastructure

Urban infrastructures are essential to the health, safety, security and economic well being of citizens and organisations. Therefore, the managers of critical infrastructures (CI) and infrastructure systems in urban areas need to be constantly aware of and prepared for to any man made and natural disasters. In this paper, we propose a structured approach to assess extreme weather impacts on CI and discuss how resilience and risk tolerance of critical infrastructure can be enhanced. The approach is aimed at supporting CI owners' and managers' decision making on a strategic level. It follows a process flow from hazard and CI identification, vulnerability analysis, potential damage estimation, loss assessment to identification and assessment of measures. The approach incorporates many elements, phases and methods from hazard assessment, vulnerability assessment, risk assessment and cost benefit analysis (CBA) and combines and incorporates them into one aggregated structure, thus providing a holistic view to risk management and CI protection. The proposed approach is flexible in the sense that it encompasses not only a rigorous quantitative assessment, but also allows for a semi quantitative or qualitative assessment. In addition, the approach enhances transparency of decision making and contributes to more comprehensive use of available information. The paper is based on research carried out in the INTACT and HARMONISE projects, which are co funded by the European Union under the 7th Framework Programme.
Transformer Internal Insulation Fault Diagnosis Based on RBF Neural Network Evolved by Immune Particle Swarm Optimization

The reliability of the power transformer operation is directly related to the security of power system and the reliability of power supply. In order to improve the diagnosis accuracy of internal insulation fault in transformer, this paper proposes an algorithm of transformer internal insulation fault diagnosis which is based on RBF neural network evolved by immune particle swarm optimization by analyzing the internal insulation fault type of transformer and the content of dissolved gas in transformer oil composition. The paper focuses on the composition principle of transformer fault diagnosis based on RBF neural network. The method of determining the number of hidden layer of network center and the initial position based on artificial immune network algorithm is given. The method of network weight optimization based on particle swarm optimization algorithm is developed. And the simulation experiment is also given. The simulation results show that the proposed algorithm can effectively diagnose the transformer fault types and the diagnosis accuracy can reach above 90
Structure from Motion Revisited
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Incremental Structure from Motion is a prevalent strategy for 3D reconstruction from unordered image collections. While incremental reconstruction systems have tremendously advanced in all regards, robustness, accuracy, completeness, and scalability remain the key problems towards building a truly general purpose pipeline. We propose a new SfM technique that improves upon the state of the art to make a further step towards this ultimate goal. The full reconstruction pipeline is released to the public as an open source implementation.
Job search methods and immigrant earnings: A longitudinal analysis of the role of bridging social capital

This paper analyses how finding a new job affects the earnings of immigrants. I hypothesize that job changes are more successful for individuals who have access to bridging social capital. Using data from the German Socio economic Panel (1996 2011) fixed effects models show that finding a new job results in higher earnings only when immigrants have both native German friends and high levels of human capital. The effect is, however, not dependent on the search method: both formal (advertisement, employment agency) and informal search methods (referrals via friends) result in higher earnings. The presented evidence shows that bridging social capital can be activated and converted into a better position on the labour market. However, the effect of contact with natives is limited to those who are higher educated, or who have good German language proficiency, suggesting that only those individuals who are better off already profit from bridging social capital.
Smart cities, social capital, and citizens at play: a critique and a way forward

Digital transformations are not contained within the digital domain but are increasingly spilling over into the physical world. In this chapter, we analyse some of the transformations undergoing in cities today towards becoming smart cities. We offer a critique of smart cities and a way forward, divided into three parts: First, we explore the concept of Smart Citizens in terms of both localities, the move towards a hyperlocal network and also the citizen's role in the creation and use of data. We use the 'Smart London' plan drawn up by the Mayor of London, as a way to illustrate our discussion. Second, we turn to the civic innovations enabled by digital transformations and their potential impact on citizens and citizenship. Specifically, we are interested in the notion of social capital as an alternative form of in kind currency and its function as an indicator of value, in order to ask, can digital transformations give rise to 'civic capital, and how can such a concept help, for instance, a local government invite more representative residents and community champions to participate in community engagement for better urban planning. Third, we introduce a hybrid, location based game under development by design agency Preliminal Games in London, UK. This illustrative case critiques and highlights the current challenges to establishing a new economic model that bridges the digital physical divide. The game provides a vehicle for us to explore how established principles and strategies in game design such as immersive storytelling and goal setting, can be employed to encourage players to think of the interconnections of their hybrid digital physical environments in new ways.
The Effect of Time Stress on Store Loyalty: A Case of Food and Grocery Shopping in Thailand

In today's competitive environment, consumers face a hectic pace of life and are often time pressured when managing their occupation and family. This study investigates the effects of time pressure stress on store loyalty in the context of food and grocery shopping in Thailand. Additionally, this research introduces the concept of shopping motivations (i.e. utilitarian and hedonic motivation) to explain how and why time stressed shoppers may be loyal to particular retail stores. The philosophy of utilitarian oriented motivation asserts that time stressed consumers are more loyal toward a preferred store where they may shop with minimal exertion of time and energy. In addition, this study indicates that shoppers who experience time stress may be responding to hedonic motivations related to food and grocery shopping.
Effects of Spatial Crowding on Store Loyalty: Roles of Store Size

Spatial crowding and social crowding are mutually distinctive dimensions of perceived crowding. This study investigates the sole effects of spatial crowding on store loyalty and the roles of store size in spatial crowding store loyalty relationships. Two video clips which display different store size were recorded for the purpose of the study. An internet survey was conducted with 400 fashion brand consumers. A multiple group analysis was conducted using structural equation modeling. This study consists of three stages. The first stage tested the general effects of spatial crowding. Test results showed that, when social crowding was controlled, spatial crowding did not show negative impacts on pleasure, rather the relationship was positive. Pleasure showed positive impact on expectation and, subsequently, it led to store loyalty. Such results are opposed to a prevailing belief that retail store crowding results in negative retail outcomes. The second stage tested the role of store size. Density and social crowding were controlled as the same level in both small and large stores. In the large store, spatial crowding effected on pleasure positively, whereas, the effect was negative in the small store. The third stage revealed the mediating effect of perceived control, albeit partially. In the small store, the negative effects of spatial crowding on pleasure dropped in magnitude when perceived control was included as a mediator. Implications for practice and future research opportunities are discussed.
The Global Text Project: Spanish Translation Phase

The Global Text Project (GTP) was initiated in 2006 to provide free, high quality, open content textbooks to university students in developing economies. In 2011, the GTP refocused on marketing and distribution of its own and other open content textbooks, and in 2013 involved students and other volunteers in translating textbooks into Spanish. Translation and content localization is an ongoing issue in the Global delivery of information. The case follows a graduate student project leader managing a complex Spanish translation effort. The case encourages readers to reflect upon how the process of translation could be improved. Finally, it poses questions about how the translated textbooks could be promoted for use by professors in Spanish speaking countries, particularly those in Latin America. The issues in this case relate to volunteerism, information systems and technologies, project management, translation methodologies, and textbook adoption. Readers are encouraged to consider if machine translation, computer aided translation, or the application of computer game elements in distributed translation might increase productivity and provide high quality translated content.