Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Grape Syrup as a Replacement for Sugar on the Chemical and Sensory Properties of Sponge Cake

The present study aimed to investigate the possibility of replacing sugar with different concentrations of natural sweetener (grape syrup) in making low-calorie cakes. For this purpose, different types of cakes with 0%, 50%, 75% and 100% grape syrup were cooked. Then, the chemical and sensory properties of cakes such as moisture content and water activity, PH, protein, sugar and fat content as well as acid-insoluble ash, sensory evolution, and color were studied. Results indicated that an increase in the grape syrup content of samples leads to many changes in their chemical and sensory properties. The sample made of 100% grape syrup showed the maximum content of moisture, water activity and high pH value as well as the minimum level of sugar on the seventh day, and the protein content of the sample remained the same as that of the control sample. The results from the comparison of means for the color parameter in seventh day, indicated that the maximum and minimum level of L* (lightness) belonged to the control treatment and the 100% grape syrup treatment, respectively, in which the cake was darker on the seventh day, while the maximum and minimum level of a* (redness) belonged to the 50% grape syrup and control respectively, the maximum (25% grape syrup) and minimum levels of b* (yellowness) belonged to the treatment and control treatment, respectively. The cake with 100% grape syrup obtained the highest score of sensory evaluation in terms of the quality and color of shell as well as soft texture to the cake, taste and aroma. Article History Received: 18 May 2017 Accepted:11 June 2017
A Memory-Driven Computing Approach to High-Dimensional Similarity Search

Given a query image, how can one perform a fast search on a large repository of images and accurately retrieve images most similar to the query image? This is an example of a high-dimensional similarity search problem. High-dimensional similarity search is an important component of many analytic tasks in information retrieval, machine learning and computer vision. We demonstrate how big-memory multicore computing platforms can enable fast high-dimensional similarity search over large repositories of data, by building similarity search indexes based on Locality-Sensitive Hashing (LSH). These indexes are large and require fast random access, thus making a Memory-Driven Computing approach a natural fit for our solution. We developed our similarity search prototype on a cluster of 4 HPE Proliant DL980 servers. On a repository containing 80 million images, the prototype achieves a 12x speed-up over a highly-optimized linear scan, with an average response time of 110 ms and search accuracy of 95%, while consuming 3.7 TB for in-memory search indexes. External Posting Date: May 11, 2016 [Fulltext] Internal Posting Date: May 11, 2016 [Fulltext]  Copyright 2016 Hewlett Packard Enterprise Development LP
Mining Linguistic Clues From Social Network: Impact of CEO Personality on Business Performance

Researchers in strategic management and organizational theory have demonstrated that executives explain a non-trivial proportion of organizational performance variance. Upper echelons theory further informs us what and why top managers’ characteristics affect organizational performance. As the leader of executives, CEO often has a disproportionate, sometimes dominating, influence on his or her firm. However, limited research has studied the impact of CEOs’ comprehensive personality on business performance. We capture linguistic clues CEOs leaving on social network to recognize their personality by a text mining approach. Meanwhile, we adopt a broader conceptualization of the construct space of business performance and measure it by both financial and operational indicators. The impact of each aspect of CEOs’ personality on business performance is then estimated. Interesting results are found and conceivable explanations are proposed.
Cluster-surface and cluster-cluster interactions: Ab initio calculations and modeling of asymptotic van der Waals forces

We present fully ab initio calculations of van der Waals coefficients for two different situations: (i) the interaction between hydrogenated silicon clusters and (ii) the interactions between these nanostructures and a nonmetallic surface (a silicon or a silicon carbide surface). The methods used are very efficient and allow the calculation of systems containing hundreds of atoms. The results obtained are further analyzed and understood with the help of simple models. These models can be of interest for molecular-dynamics simulations of silicon nanostructures on surfaces, where they can give a very fast yet sufficiently accurate determination of the van der Waals interaction at large separations.
Taking Fuzzy-Rough Application to Mars ? Fuzzy-Rough Feature Selection for Mars Terrain Image Classiﬁcation

This paper presents a novel application of fuzzy-rough set-based feature selection (FRFS) for Mars terrain image classiﬁcation. The work allows the induction of low-dimensionality feature sets from sample descriptions of feature patterns of a much higher dimensionality. In particular, FRFS is applied in conjunction with multi-layer perceptron and K-nearest neighbor based classiﬁers. Supported with comparative studies, the paper demonstrates that FRFS helps to enhance the eﬀectiveness and eﬃciency of conventional classiﬁcation systems, by minimizing redundant and noisy features. This is of particular signiﬁcance for on-board image classiﬁcation in future Mars rover missions.
A Novel Linearization Method of Sin/Cos Sensor Signals Used for Angular Position Determination

In this paper a novel method for angular position determination using sensors with sin / cos output and without an excitation signal, is presented. The linearization of the sensor transfer characteristic and digitalization of the measurement results are performed simultaneously with a goal to increase the measurement resolution. This improvement is particularly important for low angular velocities, and can be used to increase the resolution of incremental Hall, magnetic and optical sensors. This method includes two phases of sin/cos signal linearization. In the first linearization phase the pseudo-linear signal is generated. The second linearization phase, executed by the two-stage piecewise linear ADC, is an additional linearization of the pseudo-linear signal. Based on the LabVIEW software simulations of the proposed method, the contribution of each processing phase to a final measurement error is examined. After the proposed method is applied within 2π [rad] range, the maximal nonlinearity is reduced from 0.3307 [rad] (18.9447°) to 3·10-4 [rad] (0.0172°).
Survey, Identification and Estimation of Damage in Major Diseases of Coconut

Coconut (Cocos nucifera Linn.) is an important plantation crop in India. It is cultivated for oil and raw materials used in the coir industry. The coconut palm globally cultivated in around 93 countries and in India, it is grown in 2.1 million ha (2015-16, 3rd estimates) with a production of 14,075 million nuts and an average productivity of 6,702 nuts/ha/year (CDB, 2016). Coconut farming and allied activities provide livelihood security to millions of people in India. The every part of a coconut tree has its own use or applications. It is generally called “Tree of Heaven”, „„Tree of Abundance”, “Tree of Life” and “kalpavriksha”. Western literature mentioned the Malayalam name “Tenga” for the coconut palm which related to Tamil „Tennai‟ and believed to have been introduced from Sri Lanka. The coconut is a benevolent crop and a perfect gift to mankind. It has during the span of history represented not only the source of food, beverage, oil seed, fibers, timber and health products but also associated with magic, mystery, medicine and omen in the life of people. The economic importance of this tree crop is evident from the fact that it is grown in more than 90 countries across the world in an area of International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 12 (2017) pp. 416-423 Journal homepage: http://www.ijcmas. com
New Weather Indices for China: Tool of Risk Control of International Supply Chain

China is at the core of the world’s supply chain because of its focus on production and consumption. However, as weather can significantly affect supply chain operations, China plans to introduce weather derivatives to secure the multinational supply chain. Using historical records over the decade, weather derivatives could be an important tool for hedging risk and meeting the needs of Chinese market. In this paper, new weather indices for China financial markets are experimentally created through simulated machine learning to assess the ability of the weather indices to reduce risk. Through a simulation test from 2008 to 2017, the indices were found to successfully match 98% of the risk with the situation across two dimensions: i). changing Chinese weather data; and ii). a connection with US weather indices.
Destinasyon Uzantılarının Turistlerin Duygusal Tepkileri ve Davranışsal Niyetleri ile İlişkisi1 (The Relationships between Destinationscapes, Emotional Response and Behavioral Intentions)

Bu çalışmada destinasyon uzantılarının belirlenmesi ve destinasyon uzantılarının turistlerin duygusal tepkileri ve davranışsal niyetleri ile nedensel ilişkilerinin belirlenmesi amaçlanmıştır. Destinasyon uzantılarının belirlenmesinde, çevre psikolojisi, evrimci psikoloji ve estetik, pazarlama ve turizm alanlarında geliştirilen teoriler ve modellerden yararlanılmıştır. Destinasyon uzantıları, turistlerin duygusal tepkileri ve davranışsal niyetleri, geliştirilen soru formu ile ortaya konulmuştur. Araştırmanın yürütüldüğü Bodrum’da tatillerini geçiren yerli ve yabancı turistlerden kişisel görüşme yoluyla elde edilen veriler analiz edilmiştir. Verilerin analizi sonucu, destinasyon uzantılarını oluşturan boyutlar belirlenmiş, destinasyon uzantılarının turistlerin duygusal tepkileri arasında doğrudan ilişkili olduğu belirlenmiştir. Ayrıca turistlerin duygusal tepkileri ve davranışsal niyetleri arasında doğrudan bir ilişki saptanmıştır.
Adoption of Recommended Varieties: A Farm level Analysis of Wheat Growers in Irrigated Punjab

This study uses farm level data to analyse the determinants of adoption of recommended wheat varieties in irrigated Punjab, Pakistan. A notable proportion of wheat acreage is sown to non-recommended wheat varieties in the province. These cultivars had either lost (overtime) or did not have resistance against yellow rust. Farm size, education, and size of wheat enterprise on the farm are the important determinants of adoption of recommended wheat varieties while tractor ownership and irrigation source play a positive but insignificant role in the adoption decisions. Age and tenure proved to be less of a constraint towards adoption of the recommended wheat varieties. The likelihood of the adoption of recommended wheat varieties varied among tehsils, with the highest probabilities of adoption in Melsi and Arifwala tehsils of cotton-wheat zones I and II respectively.
Diet and foraging areas of Southern Ocean seabirds and their prey inferred from stable isotopes: review and case study of Wilson's storm-petrel

Analysis of stable isotope ratios in animal tissues has emerged as a powerful tool for determining the trophic level and composition of prey and foraging location. We summarize here data on the stepwise trophic enrichment in δ 15 N and latitudinal gradient in δ 13 C in the Southern Ocean, and derive a regression equation to estimate latitudes from δ 13 C values. We analysed isotope ratios of feathers of the small, pelagic seabird Wilson's storm-petrel Oceanites oceanicus, in different breeding stages, in comparison to isotope ratios of 4 other seabird species breeding in close vicinity on King George Island, South Shetland Islands. δ 15 N analysis of feathers and albumen from Wilson's storm-petrels indicated a shift in diet from mainly crustaceans during egg formation to an increased proportion of fish during chick-feeding and moulting. δ 15 N values of Wilson's storm-petrels during the chick-rearing season were closer to the mainly piscivorous-carnivorous skuas than to krill-feed- ing penguins, confirming that fish is an important part of their diet. δ 13 C analysis of feathers identi- fied 4 distinct foraging areas: δ 13 C values in egg-white suggest that egg-forming females moved south to the sea ice edge. This coincides with the distribution of their main prey, Antarctic krill Euphausia superba, during this period. During the breeding season, Wilson's storm-petrels fed in the area around the colony, which is also used by penguins and skuas. δ 13 C of the feathers indicate that adults migrated to the Subtropical Front and beyond (north of 44°S) during the inter-breeding period. Feathers were also analysed from 10 Wilson's storm-petrels caught by mistnet and thought to be pre- breeders because they lacked foot markings; 8 of these had moulted in the same area as breeding birds, while 2 birds had moulted in an area further north (north of 30°S). Adelie penguins Pygoscelis adeliae and Gentoo penguins P. papua had significantly different δ 13 C, suggesting that the Adelie penguins foraged further south than the Gentoo penguins. The foraging areas of brown skuas Ster- corarius antarctica and south polar skuas S. maccormicki could not be separated by their isotope ratios.
Self-Congruity and the MOA Framework: An Integrated Approach to Understanding Social Cause Community Volunteer Participation

Marketing efforts designed to increase participation in social causes have led to the creation of online and face-to-face communities. This study examines a not-for-profit organization and participation in a face-to-face and online community built around its social cause. The purpose of this study is to explore and test the relationships between participatory behaviors and self-congruity as moderated by motivation, opportunity, and ability as members of social cause communities. The authors present a framework which depicts the linkages between self-congruity and an individual’s motivation, ability, and opportunity to participate in the social cause community as a predictor of future participation behaviors.
Seabirds as samplers of the marine environment – a case study of northern gannets

Abstract. Understanding distribution patterns, activities, and foraging behaviours of seabirds requires interdisciplinary approaches. In this paper, we provide examples of the data and analytical procedures from a new study in the German Bight (North Sea) tracking northern gannets (Morus bassanus) at their breeding colony on the island of Heligoland. Individual adult northern gannets were equipped with different types of data loggers for several weeks, measuring geographic positions and other parameters mostly at 3–5 min intervals. Birds flew in all directions from the island to search for food, but most flights targeted areas to the (N)NW (north–northwest) of Heligoland. Foraging trips were remarkably variable in duration and distance; most trips lasted 1–15 h and extended from 3 to 80 km from the breeding colony on Heligoland. Dives of gannets were generally shallow, with more than half of the dives only reaching depths of 1–3 m. The maximum dive depth was 11.4 m. Gannets showed a clear diurnal rhythm in their diving activity, with dives being almost completely restricted to the daylight period. Most flight activity at sea occurred at an altitude between the sea surface and 40 m. Gannets mostly stayed away from the wind farms and passed around them much more frequently than flying through them. Detailed information on individual animals may provide important insights into processes that are not detectable at a community level.
Exploring the Relationship between R & D and Productivity : A Country-Level Study 1 March 2008

Research and development (R&D) has been considered a source of growth in productivity starting from Schultz (1953). Since then, significant research has studied this relationship at the firm, industry and country level. However, at the country level, most of the empirical studies assessing the R&D-productivity relationship often fail to consider the possible simultaneity of these variables. Do more productive countries invest more on R&D or does the higher level of R&D investment lead to higher levels of productivity? Do both relationships occur at the same time? Using a 65-country panel for the time period of 1960-2000, this study provides evidence that the relationship is mainly based on investment in R&D and not the reverse. In addition, we found that per capita R&D expenditure is strongly exogenous to productivity. These results suggest that, on average, those countries making the most effort in the R&D sector will be more productive in the future. Finally, we present evidence those points out a strong relationship between R&D and productivity in terms of both magnitude and significance.
Religious Beliefs: A Hidden Variable in the Performance of Science Teachers in the Classroom

This article focuses on some of the challenges of teaching science in a culture where science and religion sometimes appear to be or are set at odds with each other. Apparent conflicts between scholarly claims and religious claims are not limited to science, however — they occur in almost every subject. Many topics included in science education are acknowledged as controversial issues, for example, evolution, cloning, abortion and genetic engineering. These issues pose problems for science teachers, especially in a religiously based culture, because of the nature of the conflict between the implications of a scientific study of some of these issues and religion. Some other issues may not formally conflict with religion but teachers' views, or the way they interpret the religious view regarding these controversial issues, can create a false contradiction, which might influence their performance and, in turn, influence their students' learning. Therefore, there is a need to understand teachers' personal religious beliefs and practices around some of these, and the way their beliefs influence their performance in the classroom. This article describes a study conducted to address these needs. The study looks at the role and influence of religion on the science teacher's performance. The findings highlighted the powerful influence of teachers' religious beliefs in dealing with or gaining new knowledge (the epistemology and the ontology of science). Also, the findings found that teachers' religious beliefs are among the major constructs that drive teachers' ways of thinking and classroom practices about scientific issues related to religion.
A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting

As a type of clean and renewable energy, the superiority of wind power has increasingly captured the world’s attention. Reliable and precise wind speed prediction is vital for wind power generation systems. Thus, a more effective and precise prediction model is essentially needed in the field of wind speed forecasting. Most previous forecasting models could adapt to various wind speed series data; however, these models ignored the importance of the data preprocessing and model parameter optimization. In view of its importance, a novel hybrid ensemble learning paradigm is proposed. In this model, the original wind speed data is firstly divided into a finite set of signal components by ensemble empirical mode decomposition, and then each signal is predicted by several artificial intelligence models with optimized parameters by using the fruit fly optimization algorithm and the final prediction values were obtained by reconstructing the refined series. To estimate the forecasting ability of the proposed model, 15 min wind speed data for wind farms in the coastal areas of China was performed to forecast as a case study. The empirical results show that the proposed hybrid model is superior to some existing traditional forecasting models regarding forecast performance.
An Asynchronous, Personalized Learning Platform―Guided Learning Pathways (GLP)

The authors propose that personalized learning can be brought to traditional and non-traditional learners through a synchronous learning platform that recommends to individual learners the learning materials best suited for him or her. Such a platform would allow learners to advance towards individual learning goals at their own pace, with learning materials catered to each learner’s interests and motivations. This paper describes the authors’ vision and design for a modular, personalized learning platform called Guided Learning Pathways (GLP), and its characteristics and features. We provide detailed descriptions of and propose frameworks for critical modules like the Content Map, Learning Nuggets, and Recommendation Algorithms. A threaded user scenario is provided for each module to help the reader visualize different aspects of GLP. We discuss work done at MIT to support such a platform.
On the Interactions of Fused Pyrazole Derivative with Selected Amino Acids: DFT Calculations

Due to the increasing prevalence of neoplasms, there is a permanent need for new selective cytostatic compounds. Anticancer drugs can act in different ways, affecting protein expression and synthesis, including disruption of signaling pathways within cells. Continuing our previous research aiming at elucidating the mechanism of pyrazole’s anticancer activity, we carried out in silico studies on the interactions of fused pyrazole derivative with alanine, lysine, glutamic acid, and methionine. The objective of the study is to improve our understanding of the possible interactions of pyrazole derivatives with the above-mentioned amino acids. For this purpose, we apply the DFT formalism (optimization using the B3LYP, CAM-B3LYP, PBE0, and M06L functionals) and interaction energy calculations (counterpoise corrected method based on the basis set superposition error, BSSE) together with QTAIM approach and estimation of the 1H NMR chemical shifts of analyzed pyrazole derivative using different basis sets and DFT functionals in CPCM solvation model (and water used as a solvent).
A practitioner's guide to evaluation of software

Software quality evaluation comprises a number of steps. The first step is to identify the requirements of the evaluation. In the second step the available product information is identified and classified, and the evaluation is then specified in detail. Planning the evaluation according to that specification takes place in the third step. Conducting the evaluation and collecting the findings constitute the fourth step. Reporting is done is the final step. The article reports on a framework for this stepwise procedure. Attention is given to the problems arising during evaluation of characteristics defined in ISO/IEC 9126. The main aim of the guide is to give practical recommendations for specifying and executing an evaluation. <<ETX>>
Unsupervised Multi-view Nonlinear Graph Embedding

In this paper, we study the unsupervised multi-view graph embedding (UMGE) problem, which aims to learn graph embedding from multiple perspectives in an unsupervised manner. However, the vast majority of multi-view learning work focuses on non-graph data, and surprisingly there are limited work on UMGE. By systematically analyzing different existing methods for UMGE, we discover that cross-view and nonlinearity play a vital role in efﬁciently improving graph embedding quality. Motivated by this concept, we develop an unsupervised Multi-viEw nonlineaR Graph Embedding (MERGE) approach to model relational multi-view consistency. Experimental results on ﬁve benchmark datasets demonstrate that MERGE signiﬁcantly outperforms the state-of-the-art baselines in terms of accuracy in node classiﬁcation tasks without sacri-ﬁcing the computational efﬁciency.