Miracle-dz/UniFAR-FTUs huggingface dataset:
Some Robust and Classical Nonparametric Procedures of Estimations in Linear Regression Model

We examined some robust and nonparametric procedures for a simple linear regression model when the error terms are drawn from unit normal, lognormal, Student t-10df, Cauchy, and exponential power via Monte Carlo simulation technique. The results showed that the nonparametric Theil’s method demonstrates the strongest performance gains in many cases which imply they have negligible bias and the smallest Mean Square Error (MSE). The second best results are obtained from Least Trimmed Squares (LTS) Methods with relative reductions in MSE. Though Least Absolute Deviation (LAD) and weighted Theil’s regressions gave the poorest slope estimates with negative root mean square error (RMSE) values in most cases, it is noticed that LAD is always more efficient than LSE whenever the error component is Cauchy distributed. The LSE proved to be more efficient under normality assumption where as LTS and Theil’s estimators performed better under nonnormal data conditions. (
Case studies on RetroMAD1™, an orally administered recombinant chimeric protein to treat naturally infected Feline Leukemia Virus (FeLV) cats

Treatment options for Feline leukimia are presently very limited due to lack of efficacy and drug toxicity. A recombinant chimeric protein RetroMAD1 is described for the first time in the treatment of FeLV. The chimera has an A-B-C configuration comprising of multiple documented antiviral domains that can potentially overcome single point mutation driven resistance by multidomain action. Oral administration of RetroMAD1 was given daily at 0.4mg/kg/day divided equally into two feeds roughly 12 hours apart for one month to highly symptomatic FeLV cats in Brazil. RetroMAD1 treated cats were monitored for survival until day 433 and untreated cats were monitored until day 173. A significant different in survival rate of 73% (treated N=55) versus 33% (untreated N=21) existed. Gingivitis, F.U. R.D. and anaemia were shown to improve significantly as signs indicating improvement in quality of life. Some of the RetroMAD1 treated cats were given interferon treatment by their respective vets as supportive treatment (N=14) that gave a slightly improved survival outcome compared to those given only RetroMAD1 and other supportive medication. Being orally administered, this protein may be easily administered by cat owners. In addition, biochemistry and CBC data also indicated that RetroMAD1 is safe and well tolerated. A safe, efficacious oral delivery antiviral chimera will be very useful for veterinary treatment especially if it is also broad-spectrum in nature.
PII: S0028-3932(01)00025-2

To address the question of which brain regions subserve retrieval of emotionally-valenced memories, we used event-related fMRI to index neural activity during the incidental retrieval of emotional and non-emotional contextual information. At study, emotionally neutral words were presented in the context of sentences that were either negatively, neutrally or positively valenced. At test, fMRI data were obtained while participants discriminated between studied and unstudied words. Recognition of words presented in emotionally negative relative to emotionally neutral contexts was associated with enhanced activity in right dorsolateral prefrontal cortex, left amygdala and hippocampus, right lingual gyrus and posterior cingulate cortex. Recognition of words from positive relative to neutral contexts was associated with increased activity in bilateral prefrontal and orbitofrontal cortices, and left anterior temporal lobe. These findings suggest that neural activity mediating episodic retrieval of contextual information and its subsequent processing is modulated by emotion in at least two ways. First, there is enhancement of activity in networks supporting episodic retrieval of neutral information. Second, regions known to be activated when emotional information is encountered in the environment are also active when emotional information is retrieved from memory. © 2001 Elsevier Science Ltd. All rights reserved.
Crop Production Prediction System

In agriculture field where farmers and agriculture businesses have to make countless decisions every day and difficult complexities involves the various factors influencing them. An essential concern for agricultural planning intention is the accurate yield estimation for the many crops involved in the planning. DM techniques are approach for accomplishing practical and useful solutions for this problem. Agriculture has been an obvious aim for big data. Environmental situation, variability in soil, input levels, combinations and goods prices have made it all the more related for farmers to use information and get help to make serious farming decisions. The difficulty of yield prediction is a major problem that remains to be solved based on available data. DM techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. This paper presents a brief analysis of crop yield prediction using classification algorithm NB, SVM and KNN. These algorithms are used to classify the crop production, whether it will be low, average, high or very high.
Animal Biometrics: Individual Friesian Cattle Recovery and Visual Identification via an Autonomous UAV with Onboard Deep Inference. Paper presented at IEEE/RSJ International Conference on Intelligent Robots and Systems, Macau, China

This paper describes a computationally-enhanced M100 UAV platform with an onboard deep learning inference system for integrated computer vision and navigation. The system is able to autonomously find and visually identify by coat pattern individual Holstein Friesian cattle in freely moving herds. We propose an approach that utilises three deep convolutional neural network architectures running live onboard the aircraft: (1) a YOLOv2-based species detector, (2) a dual-stream deep network delivering exploratory agency, and (3) an InceptionV3-based biometric long-term recurrent convolutional network for individual animal identification. We evaluate the performance of each of the components offline, and also online via real-world field tests comprising 147 minutes of autonomous low altitude flight in a farm environment over a dispersed herd of 17 heifer dairy cows. We report errorfree identification performance on this online experiment. The presented proof-of-concept system is the first of its kind. It represents a practical step towards autonomous biometric identification of individual animals from the air in open pasture environments for tag-less AI support in farming and ecology.
Bug Triage with Data Reduction Techniques Using Instance Selection Algorithm

Bugs are one of the critical issues for any software firm. Most of the software firms pay near about 45 percent value to manage these bugs. An inevitable step of managing bugs is bug triage, which involves assigning new incoming bug to an expert person who can solve this bug. To handle these bugs manually is very time consuming process. To decrease the time in manual work, text classification techniques are applied to conduct automatic bug triage. This paper address the matter of reduction for bug triage, i.e., the way to reduced scale and improve the standard of bug information. We combine instance selection method with feature selection method to reduced information scale on the bug dimension and the word dimension. Then we propose a binary classification method to predict the order of instance selection and feature selection method based on the attributes of historical bug datasets. This method of information reduction will effectively reduce the scale of dataset and improve the accuracy of bug triage technique. Then the bugs are distributed to bug solving experts.
Schematic Coherence in Poetry

Schemata are the underlying connections that allow new experience and information to be aligned with previous knowledge. When one reads a text he usually uses all his levels of schemata. Schemata enable us to make sense of what is perceived and experienced in the world. In poetry, readers usually examine carefully and deeply what they are reading in comparison with other sorts of discourse. Coherence is achieved when a reader perceives connections among schemata. It is a connection between linguistic and textual features of the text, and reader's mental expectations as well as stored knowledge of the world. This paper discusses the role of schematic correlation in poetry, and the effect of different schematic background and difference among readers on schema change and interpretation of meaning.
A diagnostic of early massive supernovae

CS 22949–037 is one of the most metal-poor giants known ([Fe/H] ≈ −4.0), and it exhibits large overabundances of carbon and nitrogen (Norris et al.). Using VLT-UVES spectra of unprecedented quality, regarding resolution and S/N ratio, covering a wide wavelength range (from λ = 350 to 900 nm), we have determined abundances for 21 elements in this star over a wide range of atomic mass. The major new discovery is an exceptionally large oxygen enhancement, [O/Fe] = 1.97 ± 0.1, as measured from the [O I] line at 630.0 nm. We find an enhancement of [N/Fe] of 2.56 ± 0.2, and a milder one of [C/Fe] = 1.17 ± 0.1, similar to those already reported in the literature. This implies Z? = 0.01 Z . We also find carbon isotopic ratios 12C/13C= 4±2.0 and 13C/14N = 0.03+0.035 −0.015, close to the equilibrium value of the CN cycle. Lithium is not detected. Na is strongly enhanced ([Na/Fe] = +2.1± 0.2), while S and K are not detected. The silicon-burning elements Cr and Mn are underabundant, while Co and Zn are overabundant ([Zn/Fe] = +0.7). Zn is measured for the first time in such an extremely metal-poor star. The abundances of the neutron-capture elements Sr, Y, and Ba are strongly decreasing with the atomic number of the element: [Sr/Fe] ≈ +0.3, [Y/Fe] ≈ −0.1, and [Ba/Fe] ≈ −0.6. Among possible progenitors of CS 22949–037, we discuss the pairinstability supernovae. Such very massive objects indeed produce large amounts of oxygen, and have been found to be possible sources of primary nitrogen. However, the predicted odd/even effect is too large, and the predicted Zn abundance much too low. Other scenarios are also discussed. In particular, the yields of a recent model (Z35Z) from Heger and Woosley are shown to be in fair agreement with the observations. The only discrepant prediction is the very low abundance of nitrogen, possibly curable by taking into account other effects such as rotationally induced mixing. Alternatively, the absence of lithium in our star, and the values of the isotopic ratios 12C/13C and 13C/14N close to the equilibrium value of the CN cycle, suggest that the CNO abundances now observed might have been altered by nuclear processing in the star itself. A 30–40 M supernova, with fallback, seems the most likely progenitor for CS 22949–037.
Forced Accretion andyAssimilation Based on Self-Organizing Neural Network

The high level abstraction is developed layer after layer. This abstraction and generalization are important in language evolution and the study of mental processes. This chapter presents a self-organizing neural network based on cascading a series of layered perceptrons that resemble the development of the deep layers of the brain. This neural network is named ‘SOM perceptron’. It maps all received patterns in a single class into a point in the deep layer space and maps different classes into different points. These widely separated class points can facilitate the abstract categorization and analogy operated in the mental process. Categorizing similar objects into small categories and different objects into different small categories can simplify a problem and reduce the mental load. Those small categories that contain similar objects will be successively combined into large categories to further reduce the load. This categorization process is a kind of divide and conquer process. This work emulates such process in successive layers. This design also resembles the formation of the corlica sensory representation. It preserves the topological relations among classes. It constructs a layered feed-forward network. Each layer attempts to split different classes and concentrate the same class patterns. It is trained using the discrimination differences between classes and trained independently layer after layer in a bottom-up manner. The class labels are not used in the training process to relieve the loading complexity of weights. A bottom-up training method for the construction of the SOM perceptron Liou et al. (2000); Liou & Cheng (2008) is introduced in this chapter. This constructed SOM perceptron can be used as the mapping function to split different classes. It can be applied to split multiple classes. The construction ideas are discussed in this section. There are four issues concerning the method. The first issue is the reduction of the number of hidden representations. The second one discusses a design method for the weights, such that the accomplishment of the SOM perceptron is guaranteed. The third one is why we prefer a bottom-up construction for the MLP and why we do not apply the BP to training it. The fourth issue discusses the different functions of front layers and rear layers of MLP under the BP training. These four issues will be presented in four subsections in this section. The method and architecture of the SOM perceptron are described in the next section. Experiments are included in the third section. Several related works are discussed in the last section. We start with an introduction of the hidden representation. Let the set of all patterns be X = {xp, p = 1, . ,P}. Each pattern xp is a D-dimensional column vector. The label function, 35
Sustainable Development in Tourism Education A Comparative Study of Tourism Education in Upper Secondary Technical and Vocational Education and Training in Finland and Sweden

ii List of Figures . v List of Tables . v Abbreviations . vi Acknowledgements . vii Chapter 1: Introduction and the Frame of the Study . 8 1.1 Background . 8 1.2 Aims and Objectives . 9 1.3 Research Questions . 10 1.4 Outline of the Study . 10 1.5 Limitations of the Study . 10 1.6 Significance of the Study . 11 1.7 Previous Research . 13 Chapter 2: Key Concepts and Theoretical Framework . 15 2.1 Key Concepts . 15 2.1.1 Sustainable Development (SD) . 15 2.1.2 Education for Sustainable Development (ESD) . 18 2.1.3 Technical and Vocational Education and Training (TVET) . 19 2.1.4 TVET and Sustainable Development . 20 2.1.5 SD and Tourism Education . 22 2.2 Theoretical Framework . 24 2.2.1 Human Capital Theory . 24 2.2.2 Capability Approach . 25 Chapter 3: National Contexts of the Study . 28 3.1 Brief Overview of the SocioEconomic Background in Finland and Sweden . 28 3.2 Environment and Tourism in Finland and Sweden . 29 3.3 Upper Secondary TVET in Finland and Sweden . 30 Chapter 4: Methodology of the Research . 33 4.1 Research Design . 34
The Role of Work Motivation Towards Work Productivity

Work motivation is one of the factors that can affect work productivity of employees. This study aims to examine empirically the relationship between work motivation and work productivity. The subjects in this study are employees at the University of X Yogyakarta. The subject selection was randomized using a simple randomized sampling technique. Methods of collecting data using the work motivation scale and work productivity scale. Data analysis using product moment correlation techniques. Based on the results of hypothesis testing between work motivation and work productivity, the results of the correlation coefficient are = 0.411 with a significance of 0.008 (p <0.05) which means that there is a very significant positive relationship between work motivation and work productivity. Work motivation contributes 16.9% to work productivity, and the remaining 83.1% is influenced by other variables not examined in this study. Keywords— employee, work motivation, work productivity
A Descriptive Study to Assess the Knowledge and Attitude of Men Regarding Permanent Family Planning Methods in Selected Village Nagali Solan

Planning for healthy family is a happy family, to enjoy good health, to bring true happiness to one's family, to bring peace to all, one must first discipline and control one's own mind. if a human can control his mind one can find the way to enlightenment all wisdom and virtue will naturally come to him. Aim of the study is to assess knowledge and attitude regarding permanent family planning method among men. This study opts Descriptive Research design and is conducted at selected areas of Nagali, Oachghat, Distt. Solan. Total 40 adult’s male were selected by convenient Non-randomized sampling technique from Nagali, Solan H.P The main procedure of data collection was carried out during the month of August, 2018. The average time taken by each adults to answers the questions was 30 minutes. The gathered data was analyzed by using descriptive and inferential statistics. The major findings of the study revealed that knowledge of adult males regarding the permanent family planning method is 81.5% good knowledge and majority of respondents had overall 89% of positive attitude regarding permanent family planning method. Conclusion of this study showed that the subjects had good knowledge and positive attitude regarding permanent family planning method.
Optimal Data Deduplication in Cloud with Homomorphic Authenticated Tree

Cloud computing has become a new platform for personal computing. Cloud computing provides high performance computing resources and mass storage resources.Data Deduplication involves finding and removing duplication within data without compromising its integrity. A practical multi-user cloud storage system needs the secure client-side cross-user Deduplication technique, which allows a user to skip the uploading process and obtain the ownership of the files immediately, when other owners of the same files have uploaded them to the cloud server. To the best of our knowledge, none of the existing dynamic PoSs can support this technique. In this paper, we introduce the concept of deduplicatable dynamic proof of storage and propose an efficient construction called DeyPoS, to achieve dynamic PoS and secure cross-user Deduplication, simultaneously. Considering the challenges of structure diversity and private tag generation, we exploit a novel tool called Homomorphic Authenticated Tree (HAT). We prove the security of our construction, and the theoretical analysis and experimental results show that our construction is efficient in practice. Keywords— Structure Diversity, Cloud Storage, Deduplication, Dynamic Proof of Storage.
E-tracking technology in evaluating carotid artery elasticity function in passive smokers

Objective To explore the value of E-tracking technology(ET)in evaluating carotid artery elasticity function in passive smokers.Methods Fifty active smoking persons,44 passive smoking ones and 44 normal persons(the control group)were included.Quantitative analysis was made on hemodynamics of carotid artery by ET to evaluate the blood vessel elastic modulus,including pressure-strain elastic modulus(Eρ),stiffness parameters(β),arterial compliance(AC),internal systolic diameter(Ds)and internal diastolic diameter(Dd). Results β and Eρ were higher in passive and active smokers than those in normal(P0.05,P0.01),but there was no difference between passive smoke group and active smoke group(P0.05). AC was lower in passive and active smokers than that in normal persons(P0.01),and there was no statistical difference between passive smoke group and active smoke group(P0.05). There was no difference of Ds and Dd in three groups(P0.05). Conclusion As a convenient and non-invasive method,ET can be used to access the vessel endothelial dysfunction of passive and active smokers accurately.
Transient hot-carrier dynamics and intrinsic velocity saturation in monolayer 
MoS2

J. Nathawat,1,* K. K. H. Smithe,2 C. D. English,2 S. Yin,1 R. Dixit,1 M. Randle,1 N. Arabchigavkani,3 B. Barut,3 K. He,1 E. Pop,2,† and J. P. Bird1,3,‡ 1Department of Electrical Engineering, University at Buffalo, the State University of New York, Buffalo, New York 14260-1900, USA 2Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA 3Department of Physics, University at Buffalo, the State University of New York, Buffalo, New York 14260-1500, USA
STRATEGIC DESIGN INFORMATION SYSTEMS FOR INCREASING COMPETITIVENESS OF SMALL MEXICAN BUSINESS: VISION BASED ON THE THEORY OF THE FIRM AND RESOURCES

In Mexico, the use and implementation of strategies related to information systems have not been consistently addressed a claim that can be applied to small, medium and even large companies. However, these firms and multinational companies also have achieved competitive advantage by their heavy investment in business intelligence systems. This study aims to inform the SME business sector resources that can be used as a basis for the development and creation of strategies to increase their competitiveness. The high costs of implementing such systems can lessen with the use of existing information technologies. This paper will present the alternatives that small and medium producers can use to break into the culture of decision making based on information resources as well as inputs for the development of capacities for the development of strategies.
OTT_A_216362 10043..10055

Orgilmaa Regzedmaa * Ying Li* Yongwen Li * Hongbing Zhang Jin Wang Hao Gong Yin Yuan Weiting Li Hongyu Liu Jun Chen 1,2 1Department of Lung Cancer Surgery, Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Medical University General Hospital, Tianjin 300052, People’s Republic of China; 2Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin 300052, People’s Republic of China
An Overview of Helicobacter Pylori and Diagnostic Methods

Received: 22 July 2019; Accepted: 28 August 2019; Published: 30 August 2019 Abstract Helicobacter pylori are a gram negative, spiral, micro-aerophilic and slowgrowing organism with a length of 3 and a diameter of about half a micrometer. The bacterium also produces some enzymes, the most important of which are oxidase, catalase and urease. More than half of the world's people are infected with this bacterium.
Common Phase Error Mitigation and Data Detection in OFDM System

The performance of multi-carrier digital communication, OFDM, undergo with the presence of phase noise. This random process is the result of the fluctuations of phases of carrier signals generated at both transmitter and receiver. Phase noise creates common phase error (CPE) that makes the signal points rotate and causes inter-carrier interference (ICI) between the sub-carriers. In this paper, K-means algorithm based CPE reparation scheme is suggested to subside the phase noise influence in OFDM system to preserve the system bandwidth. In the proposed method, firstly the data vectors in the frequency domain is clustered and then average angle of each cluster is computed. The calculated angle is compared with idle angle and the difference is measured for each cluster. Then the difference angles are averaged which is known as CPE. The performance of the suggested method is validated by a number of simulations in MATLAB and results depict that the suggested algorithm perform much better than pilot based method.