Miracle-dz/UniFAR-FTUs huggingface dataset:
1 0 Ju l 2 01 9 Visible Nonlinear Photonics

Yun Zhao, Xingchen ji, 2 Bok Young Kim, Prathamesh S. Donvalkar, 4 Jae K. Jang, Chaitanya Joshi, 4 Mengjie Yu, 3 Chaitali Joshi, 4 Renato R. Domeneguetti, Felippe A.S. Barbosa, Paulo Nussenzveig, Yoshitomo Okawachi, Michal Lipson, and Alexander L. Gaeta ∗ Department of Electrical Engineering, Columbia University, New York, NY 10027, USA School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853, USA Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY 10027, USA School of Applied and Engineering Physics, Cornell University, Ithaca, NY 14853, USA Instituto de Fisica, Universidade de So Paulo, P.O. Box 66318, So Paulo 05315-970, Brazil (Dated: July 11, 2019)
Constructing Portfolios Using Argumentation Based Decision Making and Performance Persistence of Mutual Funds

This paper proposes an argumentation based tool for the selection of mutual funds and then the composition of efficient portfolios based on the performance persistence of the mutual funds. Argumentation allows for combining different contexts and preferences in a way that can be optimized. It allows for defining a set of different investment policy scenarios and supports the investor/portfolio manager in composing efficient portfolios that meet his profile. Moreover, the proposed methodological approach and the obtained portfolios are validated through their comparison to the return of the Market Index and with portfolios obtained using a traditional performance index. This approach is applied on data of Greek domestic equity mutual funds over the period 2000-2011 with encouraging results.
Recontextualizing Observation: Ethnography, Pedagogy, and the Prospects for a Progressive Political Agenda.

Observation has been characterized as “the fundamental base of all research methods” in the social and behavioral sciences (Adler & Adler, 1994, p. 389) and as “the mainstay of the ethnographic enterprise” (Werner & Schoepfle, 1987, p. 257). Even studies that rely mainly on interviewing as a data collection technique employ observational methods to note body language and other gestural cues that lend meaning to the words of the persons being interviewed. Social scientists are
VARIABILITY IN THE GROWTH AND NODULATION OF SOYBEAN IN RESPONSE TO ELEVATION AND SOIL PROPERTIES IN THE HIMALAYAN REGION OF KASHMIR-PAKISTAN

This study was conducted to examine the variability of soybean nodulation and growth in relation to elevation and soil properties across the slopping uplands of the Himalayan region of Rawalakot Azad Jammu and Kashmir (AJK), Pakistan in order to find efficient native N2 fixing bacteria adapted to local soil and climatic characteristics. Soils from twenty two different sites with variable altitude were collected and analyzed for different physico-chemical characteristics including the quantitative estimation of rhizobium population through most probable number (MPN) technique. Soybean cultivar William-82 was grown in these soils under greenhouse condition for determining the nodulation potential (number and mass) and plant growth characteristics. Morphology of the nodules were observed through optical and transmission electron microscopy. Principal component analysis (PCA) and Biplot graph were used to jointly interpret the relationship between variables and soils (treatments). Soil altitude ranged from 855 m to 3000 m while organic matter content varied between 0.8% to 3.5% and pH from 6.0 to 8.1. The indigenous rhizobia population varied between 5.0 x10 to 8.0 x10 CFU g showing the existence of a substantial rhizobial population in these soils. The number of nodules per plant varied from 7 to 40 (CV 38%) suggesting site/location as an important factor contributing towards rhizobia population and impacting root nodulation. The electron microscopy of green plant nodules showed densely populated bacteria in these cells and nodule tissue cells were completely infected with bacteria. The growth characteristics of soybean i.e. shoot length, shoot fresh and dry weight, root length, root fresh and dry weight varied among the sites but in general a vigorous and healthy plant growth was observed reflecting N assimilation from native soils. Results showed a substantial variability between sites and this is likely to be due to inter/intra species diversity, as well as changes in microbial community composition/structure. The study suggests that soybean could be planted in this region without prior inoculation, and that native N2-fixing bacteria might be isolated from these soils and used as biofertilizers (or inoculants).
Meeting Thermal Safe Power in Fault-Tolerant Heterogeneous Embedded Systems

Due to the system-level power constraints, it is encountered that not all cores in a multicore chip can be simultaneously powered-on at the highest voltage/frequency levels. Also, in the future technology nodes, reliability issues due to the susceptibility of systems to transient faults should be considered in multicore platforms. Therefore, two major objectives in designing multicore embedded systems are low energy/power consumption and high reliability. This letter presents an energy management system that optimizes the energy consumption such that it satisfies reliability target and meets timing, thermal design power (TDP) and thermal safe power (TSP) constraints. Toward the TDP/TSP-constrained energy-reliability optimization, the proposed method schedules periodic real-time applications on different types of cores with voltage/frequency variations for heterogeneous multicore embedded systems. Experiments show that our proposed system provides up to 38.19% (in average by 29.66%) energy saving and up to 54.73% peak power reduction (in average by 24.55%) under different reliability targets and TDP/TSP constraints when compared to the state-of-the-art techniques.
Relationships of Kindergarten Children’s BMI amongst Parental Body Dissatisfaction and Dietary Restraint: A Case Study in Hong Kong

Objective: In this study, the aim was to explore the relationships of kindergarten children’s BMI amongst parental factors such as parental BMI, body dissatisfaction, parental dietary restraint, child weight concern and child weight-focused restrictive feeding. Method: 466 kindergarten students’ parents were participated in this study. A self-administrated questionnaire was distributed to parents. Independent t-test, one way ANOVA and Pearson’s correlation were performed to analyze the relationships amongst different factors contributing to children’s BMI. Results: 30% parents and 37% children were found either overweight or obese. The six pathways in the proposed model were all significantly correlated. It was found that parental BMI significantly correlated with body dissatisfaction [r (466)=0.282, p<0.001], which was then associated strongly with parental dietary restraint [r (466)=0.715, p<0.001] and weakly with child weight concern [r (466)=0.146, p=0.002]. The child weight-focused restrictive feeding practice was moderately correlated with both parental dietary restraint [r (466)=0.360, p<0.001] and child weight concern [r (466)=0.320, p<0.001], and then significantly correlated with child BMI [r (466)=0.121, p=0.009]. Conclusion: The results of this study confirmed the presence of upward trend of childhood obesity in Hong Kong. In addition, parental body dissatisfaction was found to be a significant factor to determine parental dietary restraint, which was associated with child weight-focused restrictive feeding and finally affected child BMI.
Essay : Agricultural Pest Detection and Classification

In agriculture research of automatic pest detection and disease detection is essential research topic as it may prove benefits in monitoring large fields of Cotton crops and thus automatically detect symptoms of disease as soon as they appear on Cotton plant. The studies of plant disease refer to the studies of visually observable patterns of a particular plant. Nowadays crops faces many diseases such as damage of the insect/pest is one of the major disease. A common practice for Cotton plant F O R S T U D E N T S : A L L T H E I N G R E D I E N T S O F A G O O D E S S AY
Open Research Online The environmental and ﬁnancial beneﬁts of recovering plastics from residual municipal waste before energy recovery

A life cycle assessment was carried out to investigate the environmental benefits of removing dense plastics from household waste before burning the waste in an energy from waste (EfW) facility. Such a process was found to improve the climate change impacts of the waste management system by 75% and the non-renewable resource depletion impacts by 18%. A preliminary financial assessment suggests that the value of the plastics recovered in this way would be less than the reduction in electricity income for the EfW leading to a loss of £2-5 million per year. However, if the plastics were separated by householders for a kerbside recycling scheme, the higher price commanded by the higher-quality reclaimed plastics and lower processing costs means that overall the operation would be financially viable giving a net present value of £768 000 at a 5% rate of return. In both cases, there is a further financial benefit to the EfW operator resulting from the additional gate fees for processing waste to replace the plastics removed. Further work is required to assess the costs and effectiveness of using both kerbside collections and mechanical recovery to reduce the plastics content and carbon intensity of EfW feeds.
INFLUENCE OF STOCKING DENSITY AND WATER PARAMETERS ON GROWTH OF JUVENILE BELUGA STURGEON ( HUSO HUSO , LINNAEUS , 1758 )

The main purpose of the present experiment consist in evaluation of growth performances of beluga sturgeon juveniles (obtained from the artificial reproduction of mature sturgeons with origins in the Danube-Pontic basin) reared in different stocking densities in a recirculating aquaculture system . The influence of stocking density and water quality on the growth of beluga fingerlings was studied during 30 days. The two experimental variants (V1 and V2) were formed by two rearing units each with a different fish density: 30 exemplars (initial average weight -34g) in first two aquaria (V1) and 10 exemplars (initial average weight -25g) in the following two aquaria (V2). The fish were fed a 55% protein feed to a feeding rate of 3 % body weight/day. During experiment water quality parameters (pH, O2, T, NH3-N, NO2-N, NO3-N) were recorded an a daily basis and, every 2 weeks, the fish were weight individually, and weight gain was recorded. Beluga growth performances were evaluated through analysis of various technological indicators: W (weight gain), FCR (food conversion ratio), SGR (specific growth rate), PER (protein efficiency ratio). The body profile was evaluated through allometric factor.
Twitter and Facebook Usage for Academic Motivation Among Post-Graduate Students in Lahore, Pakistan

The use of social networking sites is spreading globally. It is seen in present world that these social media tools are being used as academic media tools too. Students share their assignments-oriented information on Facebook pages. Students communicate among themselves regarding class schedules on Twitter by Tweets. The researcher also found out that the students involve their course instructors on these kinds of platforms too. After that the researcher decided to work on a question that are these tools academically motivating students or not? This research analyzed the link between academic motivation and post-graduate students via Twitter and Facebook in educational institutions that combines a social media forum for the students to share their educational involvement with each other for the enhancement of their knowledge, improvement in their academic assignments and receiving motivation for doing academic work. The study was conducted to add in the field of academic research. Mass Communication Management students were selected as respondents because they have much knowledge of communication tools either print, electronic or internet including social media tools, and they can more critically evaluate the benefits or flaws of communication advancements. The theoretical framework for this study was uses and gratifications theory. The approach was quantitative. The research showed that Twitter has slightly less role in academic motivation but Facebook has a very effective role in academic motivation in Lahore Pakistan.
THE RELATIONSHIP BETWEEN CLINICAL COMPETENCE AND OCCUPATIONAL STRESS IN IRANIAN CLINICAL NURSES

Purpose: Clinical competence is necessary to providing safe and effective patient care. Nursing is associated with high degree of stress. Despite the importance of quality care and nurse professional development, the relationship between the two has been neglected. The purpose of the study is to investigate the association between clinical competency and occupational stress Design: A cross-sectional descriptive correlation design was used. Methods: Iranian clinical nurses (N=230) were selected using stratified random sampling in seven university hospitals of Iran in 2015. Data was collected through Competency Inventory for Registered Nurse and occupational stress questionnaires. Data was analyzed with Spearman Correlation, Mann-Whitney-U and t-tests using SPSS /21 software. Findings: The mean score of clinical competence and occupational stress were (173.59 ± 26.72) and (72.46 ± 12.95) respectively, and assessed in high level. There was a significant positive correlation between clinical competence and occupational stress (r= 0.153, P= 0.020). Conclusions: It seems that when nurses' clinical competence is high, naturally the knowledge, practical skills and work experience as well as high, therefore their expectations and accountability will increase and this may increase stress. In addition, stress is an inseparable part of the nursing profession. Nurses experienced high stress in the workplace, and it may be possible, nurses despite having high clinical competence, have high occupational stress Clinical Relevance: Nurses stress may cause adverse professional and organizational complications. Nurse Managers and hospital administration need to collaborate on coping strategies and education to advocate for reduced work-related nurse stressors. data more In the results of a study the of in some including training and guidance and the quality other the of on the in with increasing in age and work experience, in the rate of NCC further discover the and that this unexpected result
Current and potential distributions of the most important diseases affecting Hass avocado in Antioquia Colombia

Hass avocado cultivation in Colombia has grown rapidly in area in recent years. It is being planted in marginal areas, which leads to low yields, and in many cases is related to diseases. Ecological niche modeling (ENM) can offer a view of the potential geographic and environmental distribution of diseases, and thus identify areas with suitable or unsuitable conditions for their development. The aim of the study was to assess current and potential distribution of the major diseases on Hass avocado in Colombia. Areas planted with Hass avocado in Antioquia, Colombia were sampled for diseases including the following pathogens: Phytophthora cinnamomi, Verticillium sp. , Lasiodiplodia theobromae, Phytophthora palmivora, Colletotrichum gloeosporioides sensu lato, Pestalotia sp. , and Capnodium sp. , and one disorder hypoxia-anoxia. These pathogens were selected based on their relevance (incidence-severity) and capacity to cause damage in different tissues of avocado plants. Severity and incidence of each disease were related to environmental information from vegetation indices and topographic variables using maximum entropy modeling approaches (MaxEnt). Models were calibrated only across areas sampled, and then transferred more broadly to areas currently planted, and to potential zones for planting. Combinations of best performance and low omission rates were the basis for model selection. Results show that Hass avocado has been planted in areas highly conducive for many pathogens, particularly for Phytophthora cinnamomi and hypoxia-anoxia disorder. Ecological niche modeling approaches offer an alternative toolset for planning and making assessments that can be incorporated into disease management plans.
ESTIMATING OF RAPD MARKER ASSOCIATED TO COLOR GENE IN Zinnia Elegans JACQ

Flower color contributes mainly to the market value of ornamental plants including Zinnia elegans Jacq. The coloration of flowers is determined by several genes. The previous study showed that Zinnia coloration is controlled by two independent genes, which are white color as dominant (chromogen) and its suppressor. The aim of this study is to investigate marker that associated with chromogen based on RAPD. DNA from each of 240 individuals in M2 population was extracted from leaf by CTAB method (Doyle and Doyle, 1990). Fifteen primers were used to amplify DNA fragments. The PCR program was consisted of preheating at 94 ̊C for 1 min, followed by 45 cycles of denaturation at 94 ̊C for 30 sec, annealing at 38 ̊C for 30 sec, and elongation at 72 ̊C for 1 min 30 sec. The last cycle was followed by a final extension cycle at 72 ̊C for 7 min. Six among fifteen primers were selected and produced 60 loci which is 100% was polymorphic. The binary data were analyzed using Fisher Exact Test and Kendall Tau correlation in the SAS program to get correlation between markers and those traits. The result showed OPB171400 and OPA181500 markers were associated with chromogen in Zinnia.
Sentiment analysis of feature ranking methods for classification accuracy

Text pre-processing and feature selection are important and critical steps in text mining. Text pre-processing of large volumes of datasets is a difficult task as unstructured raw data is converted into structured format. Traditional methods of processing and weighing took much time and were less accurate. To overcome this challenge, feature ranking techniques have been devised. A feature set from text preprocessing is fed as input for feature selection. Feature selection helps improve text classification accuracy. Of the three feature selection categories available, the filter category will be the focus. Five feature ranking methods namely: document frequency, standard deviation information gain, CHI-SQUARE, and weighted-log likelihood –ratio is analyzed.
NUMERICAL SIMULATION OF ACOUSTIC TIME

We study the time reversal phenomenon in a homogeneous and nondissipative medium containing sound-hard obstacles. We propose two mathematical models of time reversal mirrors in the frequency domain. The first one takes into account the interactions between the mirror and the obstacles. The second one provides an approximation of these interactions. We prove, in both cases, that the time reversal operator T is self-adjoint and compact. The DORT method (French acronym for decomposition of the time reversal operator) is explored numerically. In particular, we show that selective focusing, which is known to occur for small and distant enough scatterers, holds when the wavelength and the size of these scatterers are of the same order of magnitude (medium frequency situation). Moreover, we present the behavior of the eigenvalues of T according to the frequency, and we show their oscillations due to the interactions between the mirror and the obstacles and between the obstacles themselves.
An Effective Gated Recurrent Unit Network Model for Chinese Relation Extraction

Relation extraction becomes one important task in information extraction and it is becoming more and more used to discover relations from text. However, it is difficult to combine context information for relation extraction and some important information may appear many times in one sentence. In order to solve these problems, this paper presents Gated Recurrent Unit Networks with attention (CHGRU) model to catch important information in a sentence. In this model, we use the gated unit networks for embedding sentence semantics. Then, we build word-level attention to capture informative sentences with accurate relation patterns. On real-world datasets, our experimental results gains great improvements about relation extraction as compared with others.
Deep Sentiment Representation Through Char-level CNN and LSTM

Sentiment analysis is not the analysis of emotions, but it is the analysis of people’s opinions on a specific topic (e.g. product reviews and social media comments). In recent years, deep learning has gained more popularity for the use in sentiment analysis as different types of network architecture designs. They have significantly improved analysis accuracy over shallow machine learning methods. The deep neural network employs multiple layers for processing, and it has excellent capabilities for data modelling in order to solve challenges (e.g. polarity detection, cyber security, marketing and fraud detection). They are applied in large volumes of domainspecific data such as image recognition, sentiment analysis systems and internet search engines. Some of the more common techniques are Convolutional Neural Network (CNN) in which essential features can be extracted moreover, Long Short Term Memory network (LSTM) which maintains the sequential order of the data. In my thesis work, a novel deep learning method was developed using CNN and LSTM at the lowest atomic representation. This method overcomes the weakness of CNN’s sequential order and LSTM’s important features extraction of the text for sentiment analysis. This method is adaptable to any alphabetic languages and uses one hot encoding, benefits of the integration of capturing important features and ability to learn long term dependencies. Based on the new method, there are two different variations of the method namely CNN LSTM and VDCNN LSTM were developed in the thesis at different layer depth of ten and thirty. These proposed models have outperformed existing state-of-the-art methods for a single language. Furthermore, the model for multiple languages performed better than individual techniques.
Real-Time Analysis of Oil Price Risks Using Forecast Scenarios December 5 , 2011

Recently, there has been increased interest in real-time forecasts of the real price of crude oil. Standard oil price forecasts based on reduced-form regressions or based on oil futures prices do not allow consumers of forecasts to explore how much the forecast would change relative to the baseline forecast under alternative scenarios about future oil demand and oil supply conditions. Such scenario analysis is of central importance for end-users of oil price forecasts interested in evaluating the risks underlying these forecasts. We show how policy-relevant forecast scenarios can be constructed from recently proposed structural vector autoregressive models of the global oil market and how changes in the probability weights attached to these scenarios affect the upside and downside risks embodied in the baseline real-time oil price forecast. Such risk analysis helps forecast users understand what assumptions are driving the forecast. An application to real-time data for December 2010 illustrates the use of these tools in conjunction with reduced-form vector autoregressive forecasts of the real price of oil, the superior real-time forecast accuracy of which has recently been established. JEL Code: Q43, C53, E32
Information Interpretation of Heisenberg Uncertainty Relation

In this paper the following information interpretation of uncertainty relation is proposed: if one bit of information was extracted from the system as a result of the measurement process, then the measurement itself adds an additional uncertainty (chaos) into the system equaled to one bit. This formulation is developed by calculating of the Shannon information entropy for the classical N-slit interference experiment. This approach allows looking differently at several quantum phenomena. Particularly, the information interpretation is used for explanation of entangled photons diffraction picture compression.