nils-herrmann/clean_scirepeval huggingface dataset:
How managers can build trust in strategic alliances: a meta analysis on the central trust building mechanisms

Trust is an important driver of superior alliance performance. Alliance managers are influential in this regard because trust requires active involvement, commitment and the dedicated support of the key actors involved in the strategic alliance. Despite the importance of trust for explaining alliance performance, little effort has been made to systematically investigate the mechanisms that managers can use to purposefully create trust in strategic alliances. We use Parkhe's ( 1998b) theoretical framework to derive nine hypotheses that distinguish between process based, characteristic based and institutional based trust building mechanisms. Our meta analysis of 64 empirical studies shows that trust is strongly related to alliance performance. Process based mechanisms are more important for building trust than characteristic and institutional based mechanisms. The effects of prior ties and asset specificity are not as strong as expected and the impact of safeguards on trust is not well understood. Overall, theoretical trust research has outpaced empirical research by far and promising opportunities for future empirical research exist.
Importance and use of correlational research.
Venue: Nurse researcher

The importance of correlational research has been reported in the literature yet few research texts discuss design in any detail.  To discuss important issues and considerations in correlational research, and suggest ways to avert potential problems during the preparation and application of the design.  This article targets the gap identified in the literature regarding correlational research design. Specifically, it discusses the importance and purpose of correlational research, its application, analysis and interpretation with contextualisations to nursing and health research.  Findings from correlational research can be used to determine prevalence and relationships among variables, and to forecast events from current data and knowledge. In spite of its many uses, prudence is required when using the methodology and analysing data. To assist researchers in reducing mistakes, important issues are singled out for discussion and several options put forward for analysing data.  PRACTICE Correlational research is widely used and this paper should be particularly useful for novice nurse researchers. Furthermore, findings generated from correlational research can be used, for example, to inform decision making, and to improve or initiate health related activities or change.
Far infrared radiated energy proficient rapid one pot green hydrolysis of waste watermelon peel: optimization and heterogeneous kinetics of glucose synthesis

For the first time, a one pot green hydrolysis of waste watermelon (Citrullus lanatus) peel (WWP) was optimized for a maximum glucose yield employing a heterogeneous Amberlyst 15 catalyst. The effects of energy proficient far infrared radiation (FIRR) on intensification of pretreatment and subsequent solvent free hydrolysis reactions in the one pot system have been maximized. The optimal process variables for pretreatment and consequent hydrolysis were 20 min and 10 min batch times, 70 degC and 60 degC reactor temperatures, and 5 and 10 (w/w) water to WWP ratios, respectively. Optimal 2.5 (w/w) NH4OH loading and 2.5 wt% catalyst concentration for pretreatment and hydrolysis under FIRR resulted in a maximum glucose yield (89.87 mol% which was superior to that obtained (59.86 mol% using a conventional thermal source. In comparison with pseudo homogeneous and Langmuir Hinshelwood models, the Eley Rideal model described the hydrolysis kinetics more accurately. Significantly, a higher hydrolysis activation energy (92.02 kJ mol 1) in the conventional system compared to the FIRR mode (activation energy, 59.69 kJ mol 1) clearly demonstrated the superior energy efficiency of the FIRR system. The energy proficient fast hydrolysis process is expected to be sustainable and applicable to similar lignocellulosic biomasses.
PRICAI 2016: Trends in Artificial Intelligence
Venue: Lecture Notes in Computer Science

Much of the experience of videogame players remains hidden. This paper presents an empirical study that assesses the experience of 50 participants (i.e. 25 children and 25 adults) during brain games play. Results from the empir ical study show a number of significant correlations among diverse kinds of players' experiences (i.e. engagement, enjoyment, anxiety, usability, adaptability and noninvasiveness) It is further identified by the study that the similarities and differences exist among the experiences of children and adults. Consequently, the observations of presenting study provide an insight against the experience of players during brain games play, which was previously unknown. Besides, we exploit these insights to successfully narrow down the complexity of user feed back process for brain games playing activity.
Trends in Artificial Intelligence: PRICAI 2016 Workshops
Venue: Lecture Notes in Computer Science

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.
THE NEW RULES OF GREEN MARKETING A BOOK REVIEW

This paper's purpose is to provide a review of the book "The New Rules of Green Marketing. Strategies, Tools and Inspiration for Sustainable Branding" (2011) written by Jacquelyn A. Ottman. In this sense, the book is analyzed from a personal point of view, but exposed as objective as possible. In recent years, people's attitude changed from skepticism to positivism in what concerns green products and the trend is to include them into their lives as usual commodities. This book essentializes the new guidelines of green marketing. The most significant benefit of reading this book is that it embodies theoretical aspects with practical ones, such as concrete examples of companies involved in the green market. The book adresses multinationals, entreprises, agencies, trade associations, NGOs, government agencies involved in the green marketing environment, professors, researchers, students or any individual having an affinity for green marketing in general.
Effect of blanching treatments on antioxidant activity of frozen green capsicum (Capsicum annuum L. var bell pepper) using radical scavenging activity (DPPH) assay

Blanching treatments are needed to deactivate enzymes in frozen vegetables. Antioxidant activity using DPPH radical scavenging activity assay were evaluated in steaming, boiling water, and microwave blanching at different temperature, time and microwave power level on frozen green capsicum. Green capsicum was chosen for frozen treatment compared to other capsicum with different maturity index because of the firm texture. The objective of this study was to compare the antioxidant activity of frozen green capsicum between conventional and Oxi Count Kit(r) assay for DPPH radical scavenging activity. Results showed frozen green capsicum blanched using microwave at high level/90 seconds (sample J) contained higher level of DPPH in both conventional method and Oxi Count Kit(r) compared to other treatments. However, there were no significant differences between sample J and fresh sample (sample A) Overall, the sequences from highest to lowest in blanching treatments for both DPPH conventional method, and DPPH Oxi C.
Part of Speech Tagging Java Method Names
Venue: 2016 IEEE International Conference on Software Maintenance and Evolution (ICSME)

Numerous software engineering tools for evolution and comprehension, including code search, comment generation, and analyzing bug reports, make use of part of speech (POS) information. However, many POS taggers are developed for, and trained on, natural language. In this paper, we investigate the accuracy of 9 POS taggers on over 200 source code identifiers taken from method names in open source Java programs. The set of taggers includes traditional POS taggers for English as well as some tuned to source code identifiers. Our results indicate that taggers tailored for source code are significantly more effective.
When the Smoke Clears: Focusing Events, Issue Definition, Strategic Framing, and the Politics of Gun Control

This article explores the strategic nature of framing following a focusing event. We argue that focusing events serve as catalysts for bill introductions along three particular causal stories prevalent in gun control policy: restrictive, punitive, and lenient.  We employ a negative binomial regression model to investigate the effect firearm focusing events have on restrictive, lenient, and punitive bills introduced in both the House and the Senate.  Focusing events lead to an increase in restrictive, punitive, and lenient bills introduced in the House. In the Senate, however, focusing events lead to an increase in the number of punitive and lenient bills, while having no significant impact on the number of restrictive bills.  This represents an increase in attention to gun control policy regardless of the causal story.
Principal curvatures based rotation invariant algorithms for efficient texture classification
Venue: Neurocomputing

The histograms of oriented gradients (HOG) and co occurrence HOG (CoHOG) algorithms are simple and intuitive descriptors. However, the HOG and CoHOG algorithms based on gradient computation still have some shortcomings: they ignore meaningful textural properties and are unstable to noise. In this paper, two new efficient HOG and CoHOG methods are proposed. The proposed algorithms are based on the Gaussian derivative filters, and the feature vectors are obtained by means of principal curvatures. The feature vectors are rotation invariant by means of the rotation invariance characteristic of principal curvatures (i.e. eigenvalues) The experimental results on the CUReT, KTH TIPS, KTH TIPS2 a, UIUC, Brodatz album, Kylberg and Xu datasets confirm that the developed algorithms have higher classification rates than state of the art texture classification methods. The classification results also demonstrate that the developed algorithms are more stable to noise and rotation than the original HOG and CoHOG algorithms. Two continuous rotation invariant descriptors are proposed.The proposed descriptors are based on principal curvatures which are rotation invariant.The experimental results show the power of the methods particularly in extremely noisy conditions.Our approaches give high classification performance on seven texture databases.
Formulation challenges of organic poultry diets with readily available ingredients and limited synthetic methionine

Organic agriculture has increased greatly over the past several years as consumer demand for these products has risen. Organic meat production, including poultry, has grown especially quickly, resulting in increasingly stringent guidelines being put in place to ensure safe, uniform, and ideal products for these consumers. Feed formulation and manufacturing for organic poultry in the United States are strictly regulated by the United States Department of Agriculture National Organic Program. Currently, no synthetic amino acids are allowed to be used in organic poultry diets in the United States except for limited quantities of synthetic methionine since it is typically considered the first or second limiting amino acid in corn and soybean meal based poultry diets and it is a critical nutrient for maintaining bird growth and productive performance, especially regarding egg size in laying hens. The aim of the review herein is to discuss the impacts that current organic regulations on synthetic methionine have on diet formulation when using readily available ingredients. High levels of crude protein must be used to meet bird methionine requirements with this restriction in place, which both increases feed costs and can have negative impacts on bird health and on air quality and the surrounding environment due to increased ammonia emissions. Atypical feed formulation strategies have been explored to address this issue, including such methods as feeding alternative ingredients and providing forage materials. Another possibility would be to use an average lifetime maximum inclusion rate for synthetic methionine, which may allow for better flexibility to provide sufficient methionine throughout various phases of growth and production since the requirements of the bird change with age.
The Case for Small Data in Higher Education
Venue: Intelligent Environments

While colleges and universities seek to utilize big, complex and aggregated data to generate insights to support students, big data is limited in its use to design interventions due to limits it inherently has. Small data, or onedimensional teaching and learning analytics, provide quality feedback to teachers and students. In this paper, we will discuss how Abilene Christian University (ACU) a private university in the western region of the United States, uses alert system to serve at risk students, IDEA evaluations to gather feedback to improve teaching, and data from the use of a learning management system Canvas to identify ways to improve student learning by providing formative evaluation for faculty to improve their practices. Towards the end of the paper we will discuss what students can do to make informed choices about their learning.
Exploring Text Classification for Messy Data: An Industry Use Case for Domain Specific Analytics
Venue: EDBT

Industrial enterprise data present classication problems which are different from those problems typically discussed in the scientic community with larger amounts of classes and with domain specic, often unstructured data. We ad dress one such problem through an analytics environment which makes use of domain specic knowledge. Companies are beginning to use analytics on large amounts of text data which they have access to, but in day to day business, man ual effort is still the dominant method for processing un structured data. In the face of ever larger amounts of data, faster innovation cycles and higher product customization, human experts need to be supported in their work through data analytics. In cooperation with a large automotive man ufacturer, we have developed a use case in the area of quality management for supporting human labor through text ana lytics: When processing damaged car parts for quality im provement and warranty handling, quality experts have to read text reports and assign error codes to damaged parts. We design and implement a system to recommend likely er ror codes based on the automatic recognition of error men tions in textual quality reports. In our prototypical imple mentation, we test several methods forltering out accurate recommendations for error codes and develop further direc tions for applying this method to a competitive business intelligence use case.
[The early rehabilitation in children with Down. Paying special attention to shuffling and comorbidities of developmental disorder]
Venue: No to hattatsu Brain and development

There have been many reports on the effects of early rehabilitation in children with Down syndrome, which have demon strated that early intervention improves motor skill acquisition and prevents a shuffling gait in these children. With regard to the mental development and mental health of these children, they are known to be friendly and social but some experience difficulties with nursing. Recently there have been a few reports on comorbidities of developmental disorders in Down syndrome. In the present research we studied both the motor and mental developments in children with Down syndrome, paying special attention to the shuffling gait and the comorbidi ties of developmental disorder.  Clinical records of 121 children with Down syndrome (age, 1 11 years; mean age, 3.8 years) who visited the Yokohama rehabilitation center, were investigated.  Despite early intervention, we found that 14 patients (11.9% exhib ited a shuffling gait. Concerning the comorbidities of the psychiatric developmental disorder, 21 patients (17.4% had autism spectrum disorder (ASD) like characteristic. The children with a shuffling gait appeared slow with regard to motor developmental milestones. They also had ASD like characteristics.  Children with Down syndrome needed early rehabilitation not only for its motor skill effects but also for mental support. In spite of early intervention, those with a shuffling gait needed special care owing to the comorbidities such as ASD like characteristics. More research is needed to establish the prognosis of Down syndrome.
Paying Attention to Dead Bodies: The Future of Security Studies?

What does taking dead bodies seriously tell us about the state of global security studies? Dead bodies play different roles in conventional, human, and critical security studies and thus thinking about them opens conversations among these different approaches. This paper pushes further to argue that scholars should think about the global dead as an analytical category. It demonstrates that doing so will allow us to rethink the measurement of war casualties, and examine the assumptions embedded in quantitative casualty data, the ethnography of these numbers, and the politics of representing them. Establishing the dead as an analytical category also widens the lens of dead body management to examine how dead bodies are not only objects but also subjects of security. This should lead us to ask about the politics behind how they are secured and governed, as well as the political and legal structures in place to manage them. Corpses matter for how we define security and they matter a great deal for a wide variety of security behavior. Up until now, security scholars have treated them implicitly but we can understand much more about the politics of the dead if we make them an explicit category of study.
Mistress of everything: Queen Victoria in Indigenous worlds

Indigenous histories, settler colonies and Queen Victoria Maria Nugent and Sarah Carter Part I Monarch, metaphor, memory 1. 'We have seen the son of Heaven/We have seen the Son of Our Queen' African encounters with Prince Alfred on his royal tour, 1860 Hilary Sapire 2. 'We rejoice to honour the Queen, for she is a good woman, who cares for the Maori race' Loyalty and protest in Maori politics in nineteenth century New Zealand Michael Belgrave 3. 'The faithful children of the Great Mother are starving' Queen Victoria in contact zone dialogues in western Canada Sarah Carter 4. The politics of memory and the memory of politics: Australian Aboriginal interpretations of Queen Victoria, 1881 2011 Maria Nugent Part II Royal relations 5. 'My vast Empire all its many peoples' Queen Victoria's imperial family Barbara Caine 6. Maori encounters with 'Wikitoria' in 1863 and Albert VictorPomare, her Maori godchild Chanel Clarke 7. Southern African royalty and delegates visit Queen Victoria, 1882 95 Neil Parsons Part III Sovereign subjects? 8. Sovereignty performances, sovereignty testings: The Queen's currency and imperial pedagogies on Australia's south eastern settler frontiers Penelope Edmonds 9. Bracelets, blankets and badges of distinction: Aboriginal subjects and Queen Victoria's gifts in Canada and Australia Amanda Nettelbeck 10. Chiefly women: Queen Victoria, Meri Mangakahia, and the Maori parliament Miranda Johnson Select bibliography Index
Review of various Change Detection Techniques for Hyperspectral Images

Change detection is the process of automatically identifying and analyzing regions that have undergone spatial or spectral changes from multi temporal images. Remote sensing is the most suitable technology used for change detection in many application areas. Hyperspectral remote sensing images deal with a large number of wavelength bands as compared to single band or multispectral images. Thus ample of spectral information provided by hyperspectral images present promising change detection performance. The main objective of this paper is to study the comparative analysis of various change detection techniques for hyperspectral images. This paper presents a review of advantages and limitations of different change detection techniques.
Remote sensing of terrestrial non photosynthetic vegetation using hyperspectral, multispectral, SAR, and LiDAR data

Quantifying non photosynthetic vegetation (NPV) is important for ecosystem management and studies on climate change, ecology, and hydrology because it controls uptake of carbon, water, and nutrients together with frequency and intensity of natural fire, and serves as wildlife habitat. The ecological importance of NPV has driven considerable research on quantitatively estimating NPV in diverse ecosystems including croplands, forests, grasslands, savannah, and shrublands using remote sensing data. However, a comprehensive review is not available. This review highlights the theoretical bases and the critical elements of remote sensing for NPV estimation, and summarizes research on estimating fractional cover of NPV (NPV cover) and biomass using passive optical hyperspectral and multispectral remote sensing data, active synthetic aperture radar (SAR) and light detection and ranging (LiDAR) and integrated multi sensorial data. We also discuss advantages and disadvantages of optical, LiDAR, and SAR data and pinpoint future direction on NPV estimation using remote sensing data. Currently, most NPV research has been mainly focused on NPV cover, not NPV biomass, using passive optical data, while a few studies have used LiDAR data to quantify NPV biomass in forests and SAR data on NPV estimation in croplands and grasslands. In the future, more efforts should be made to estimate NPV biomass and to investigate the best use of hyperspectral, LiDAR, SAR data, and their integration. The upcoming new optical sensor on Sentinel 2 satellites, Radarsat 2 constellation and NovaSAR, technological innovation in hyperspectral, LiDAR, and SAR, and improvements on methodology for information extraction and combining multi sensorial data will provide more opportunities for NPV estimation.
Improvised asymptotic boundary conditions for quasi static magnetic field problems in ellipsoidal domains
Venue: 2016 IEEE Conference on Electromagnetic Field Computation (CEFC)

Improvised Asymptotic Boundary Conditions (IABC) in Ellipsoid coordinate have been derived. The IABC is one of the simplest techniques to emulate open boundary condition which can be improvised in virtually any finite element programs. The IABC was first proposed with the circular domain in 2D, and spherical in axisymmetric and 3D. This work extends the IABC formulation to ellipsoidal domains.