Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of silymarin supplementation on some productive and hematological parameters in meat type male Japanese quails

A total of 90 14-day-old meat type male Japanese quails were included in the experiment and equally divided into 3 groups: control group (CG) without treatment, experimental group 1 (EG 0.5%), supplemented with silymarin 0.5% and experimental group 2 (EG 1%), supplemented with silymarin 1%. The aim of the current study was to establish the effect of supplementation with different doses of silymarin extract on the growth performance and some hematological parameters in male Japanese quails. Main growth performance (body weight, feed consumption and weight gain) were examined and FCR was calculated. Some hematological (WBC, RBC, HGB and HTC) and biochemical (triglycerides, AST and ALT) parameters were determined. The highest average body weight was observed in EG 0.5% group at 35-day-old age and the lowest in EG 1%, 239.61±2.96 g and 231.74±2.96 g respectively. The highest values of the weight gain were calculated in EG 0.5% group, 67.02±2.03 g during the first week of fattening and the lowest was observed in EG 1% group at the fifth week after hatching, 23.30±2.03 g respectively. The lowest values of FCR were observed during the first week of the trial, 2.42±0.08 kg/kg to 2.61±0.13 kg/kg in EG 1% and the control group respectively. The supplementation of 0.5% and 1% silymarin did not significantly change the studied hematological and biochemical parameters. A tendency of higher values of triglycerides and lower values of AST and ALT was observed in the groups, supplemented with silymarin compared to the controls. From the obtained results of the present study we can conclude that the silymarin supplementation at higher doses (0.5% and 1%) did not have effect on the main growth performance and some hematological and biochemical parameters of male Japanese quails.
Optimizing HPC Applications with Intel Cluster Tools: Hunting Petaflops

Optimizing HPC Applications with Intel Cluster Tools takes the reader on a tour of the fast-growing area of high performance computing and the optimization of hybrid programs. These programs typically combine distributed memory and shared memory programming models and use the Message Passing Interface (MPI) and OpenMP for multi-threading to achieve the ultimate goal of high performance at low power consumption on enterprise-class workstations and compute clusters. The book focuses on optimization for clusters consisting of the Intel Xeon processor, but the optimization methodologies also apply to the Intel Xeon Phi coprocessor and heterogeneous clusters mixing both architectures. Besides the tutorial and reference content, the authors address and refute many myths and misconceptions surrounding the topic. The text is augmented and enriched by descriptions of real-life situations.
The Work Values Inventory.

Values are an important part in the career decision-making process. It is important to select career options, which best fit your values. The list below will help you to identify those values that you think will be important to you in your work. Your work values may change as work situations change. It is important to evaluate your work values often. Read each value and decide if it is always important to you, sort of important or not important to you. Place an " X " in the appropriate box. The definition is there to help you think about the value. If your definition is different, use your own definition when rating the value.
New OFDM peak-to-average power reduction scheme

A main drawback of frequency division multiplexing (OFDM) system is the high peak-to-aver-age power ratio (PAPR). High PAPR leads to amplifier nonlinearity, inter-modulation and low inefficiency. As a simplest approach, traditional clipping method can reduce PAPR of OFDM signals, but it causes large unwanted out-of-band radiation. In this paper, a new clipping method is proposed, which can reduce PAPR without out-of-band radiation. It is based on the traditional clipping to generate the error signal. Zero out-of-band radiation is achieved by filtering the error signal. Although the proposed method produces more inband noise, by using noise cancel algorithm, the ideal unclipped signal′s BER performance can be achieved.
The Golden Notebook

Thank you for reading the golden notebook. Maybe you have knowledge that, people have search numerous times for their favorite readings like this the golden notebook, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some malicious virus inside their desktop computer. the golden notebook is available in our digital library an online access to it is set as public so you can get it instantly. Our book servers saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the the golden notebook is universally compatible with any devices to read.
Job Creation in Europe: A firm-level analysis

This note reports an innovative state-of-the-art empirical analysis of Job Creation in the European Union in the same vein as the classical studies in the United States. It is based on an exceptionally large sample of firm-level employment data in the period 2004-2015 obtained from Orbis, a databank published by Moody’s Bureau van Dijk. Consistently with our representiveness assessment, the final sample consists of firms registered in 20 out of the 28 EU Member States. The study follows the empirical literature and defines three indicators which may be equally plausible policy objectives. The job creation [destruction] is the total number of jobs created [destroyed] by growing [shrinking] firms and reflects the job turnover of a market and its capacity to enhance the labour market dynamism. The net job creation is the difference between job creation and job destruction and captures the employment growth. The net job creation rate is the employment growth rate and reflects the capacity of firms of being efficient in creating new jobs. The main findings are as follows: — The young-SME category is the largest contributor to net job creation (employment growth). Moreover, its contribution to job creation amounts to 40 percent which is far larger than its share in employment amounting to 15 percent. — The share of start-up firms in employment varies between 2 and 9 percent across countries with new Member States typically exhibiting larger shares. Even though to various degrees, nearly all Member States have experienced a decline of start-ups measured as the share of employment. — With nearly 60%, high-growth firms (HGF) exhibit the largest incidence on total job creation. Even though the young HGFs are more numerous, mature HGFs contribute to job creation to a larger extent. — Firms borrowing for the first time report net job creation rates of about 8 percent higher in the next three years, on average. Besides, the net job creation rates of firms with bank loans are less sensitive to economic cycles. The results yield a number of policy implications. In particular, they provide empirical support to policies aimed at encouraging young firms and entrepreneurship in Europe. They also show that job creation of SME may face obstacles in their “scaling-up” development phase. Last, the impact of external financing on net job creation rates may vary among Member States – especially through the business cycles. These results deserve further investigation. By providing a large-scale investigation of job creation in Europe and providing related policy tools, the report aims to contribute to the European Commission’s first priority, “to boost jobs, growth and investment. ”
SMS as a learning tool: an experimental study

The aim of this experimental study was to find out the potential of using mobile phones in teaching English as a foreign language, specifically the use of SMS as a support tool in the EFL class. The research questions formulated were: (1) Is using SMS messages via a mobile phone an effective tool in terms of motivation and engagement? (2) What type of mini-lessons do subjects think are better to be sent via SMS in terms of effectiveness, engagement, and usefulness for their learning purposes? (3) What is the appropriate timing for the activities to be sent? (4) Did students who participated in the project perform better than the control group? This experimental study lasted two academic years. As this was a preliminary study of the viability of the SMS methodology, it was conducted with a small group of students (n=13) from the English Degree at the University Rovira i Virgili (Tarragona, Spain). During the first year we designed various types of activities and sent them though a period of 15 weeks. The aim of this first part was to answer the research questions 1 to 3. The second year, a new set of exercises was created. This time, the aim was to gather data to be able to answer the fourth research question. Both qualitative data (from the first year) and quantitative data (from the second year) were analysed. We can conclude that the subjects have found this experience engaging. The subjects preferred receiving short, direct exercises which could be answered immediately. They preferred receiving the SMS in the afternoon or evening and the results show that this methodology enhances the retrieval of memorized English language rules. The results of this study were presented at the EuroCALL 2011 conference in Nottingham and are the result of a research project funded by the Institut de Ciencies de l'Educacio (Universitat Rovira i Virgili).
A fall detection algorithm based on pattern recognition and human posture analysis

Detecting fall is a particular important task in security monitoring and healthcare applications of sensor networks. However traditional approaches suffer from either a high false positive rate or high false negative rate, especially when the collected sensor data are unbalanced. Therefore, there is a lack of tradeoff between false alarms and misses for many traditional data mining methods to be applied. To solve this problem a novel fall detection algorithm based on pattern recognition and human posture analysis is presented in this paper. It firstly extracts thirty temporal features from the original data traces for different length adaptation of samples, and then exploits Hidden Markov Model (HMM) to filter the noisy character data and reduce the dimension of feature vectors. After that, it performs a closer classification with one-class Support Vector Machine (OCSVM) to filter the high false positive samples, and finally applies posture analysis to counteract the effects of high false negative samples until a satisfying accuracy is achieved. Simulation with real data demonstrates that the proposed algorithm outperforms other existing approaches.
Information Uncertainty and Implied Volatilities

In the U.S. stock and options markets from January 1996 to December 2013, we examine whether information uncertainty explains the discrepancy between historical and implied volatilities in Goyal and Saretto (2009). In addition, we clarified the impact of the uncertainty on the stock market as well as on the options market. In particular, we calculated the performance of our zero-investment option portfolio selling option straddle positions of stocks in the first decile with the lowest discrepancy between the two volatilities and purchasing option straddle positions in the last decile with the highest discrepancy. Moreover, we estimate the returns of these portfolios held by until to the earnings announcement days as well as the returns of the portfolios held by one month. In our results, changes in information uncertainty are in tandem with changes in implied volatility and reduce the predictability of implied volatility for the future realized volatility. Additionally, we show an insignificant change in volatility skew during the time of a significant change in volatility implied from ATM options. Conclusively, we provide novel evidence that the uncertainty of information concerning a firm’s fundamental underlying volatility proposed in Hirshleifer (2001) significantly affects implied volatility.
Optimal and Adaptive Online Learning

Online learning is one of the most important and well-established machine learning models. Generally speaking, the goal of online learning is to make a sequence of accurate predictions “on the fly,” given some information of the correct answers to previous prediction tasks. Online learning has been extensively studied in recent years, and has also become of great interest to practitioners due to its effectiveness in dealing with non-stationary data as well as its applicability to large-scale applications. While many useful ideas are well-established in the offline learning setting where a set of data is available beforehand, their counterparts in the online setting are not always straightforward and require more understanding. Moreover, existing online learning algorithms are not always directly applicable in practice. One important reason is that they usually rely on sophisticated tuning of parameters, a delicate approach that can yield sound theoretical guarantees, but that does not work well in practice. Another reason is that existing algorithms are usually guaranteed to work well in one particular situation or another, but not all. A single algorithm that can ensure worst-case robustness while still enjoying the ability to exploit easier data at the same time is relatively rare and certainly desirable in practice. Motivated by all the above issues, this thesis focuses on designing more practical, adaptive and ready-to-use online learning algorithms, including • novel online algorithms which combine expert advice in an optimal and parameter-free way and work simultaneously under different patterns of data as well as different evaluation criteria; • a novel and rigorous theory of online boosting which studies improving the accuracy of any existing online learning algorithm by training and combining several copies of it in a carefully designed manner;
Role of inhibition and hyperpolarization-activated membrane properties in a lick/gape central pattern generator.

The interplay between intrinsic and synaptic properties is an important determinant of the outputs of a central pattern generating network (CPG). The studies presented in this thesis are focused towards understanding the intrinsic and synaptic mechanisms underlying a brainstem central pattern generator, orchestrating tasteinduced ingestion and rejection responses. A combination of computational and mathematical modeling with whole cell electrophysiology are used for these studies. Using mathematical and computational methods, we show that the magnitude and kinetics of inhibitory synaptic currents can be critical for the strength and patterning of the motor outputs of taste-induced licks (ingestion) and gapes (rejection). Using whole cell electrophysiology, we explore the hyperpolarization-activated intrinsic properties of the potential CPG neurons in a brainstem slice preparation. We classify these neurons based on hyperpolarization-induced facilitation or suppression of spikes. Additionally, we show the existence of a hyperpolarization-induced inward cation current (Ih), a transient A-type potassium current (IA) among these neurons. We conclude that the hyperpolarization-induced changes in excitability do not arise by mere existence or absence of one type of ionic current. Rather, overlapping combinations of currents dynamically interact to lend specific groups of neurons more or less excitable as they recover from hyperpolarization/inhibition. We speculate that the intrinsic firing properties observed in these neurons may play a role during lick-gape
Does Online Course-Taking Increase High School Completion and Open Pathways to Postsecondary Education Opportunities?

Recent increases in high school graduation rates have been linked anecdotally to online course-taking for credit recovery. Online course-taking that supports high school completion could open opportunities for postsecondary education pursuits. Alternatively, poorer quality online instruction could diminish student learning and discourage persistence toward graduation and further education. Using quasi-experimental methods in an 8-year longitudinal study of high school online course-taking, we find positive associations between online course-taking, credits earned and high school graduation, and for those with limited online course-taking, small increases in college enrollment. However, we find significantly lower 4-year college enrollments and lower quality college enrollments for all online course-takers, leaving open the question of whether online course-taking will lead to long-term postsecondary education and labor market success.
Studying on Design of Small-chunk Learning Resources in Mobile Learning

With the rapid development of network technology and communication technology,mobile-learning is presenting a strong developing trend.It indeed provides learners with possibilities of anytime-anywhere learning.But learners suffer more interruptions from surrounding environment and their need on individual learning makes a higher demand on design of mobile learning resources,which is one of the key problems in mobile-learning design.This article reports our efforts in designing and developing "small-chunk" learning resources that are based on knowledge points and experimentally applied in mobile-learning.After learners finish one stage of mobile-learning by using these learning materials,we collect survey data from 940 participants on web.In addition,this research applied data-ming technology to execute a cluster analysis on large-scale data which produced a more valid result.By defining characteristics of various style learners and changing rule among them,research analyzes the feasibility and detailed design strategy of small-chunk self-contained learning sources in mobile-learning.
Probabilistic methods for pose-invariant recognition in computer vision

This thesis is concerned with two central themes in computer vision, the proper ties of oriented quadrature filters, and methods for implementing rotation invarianc e n an object matching and recognition system. Objects are modeled as combinations of local features, and human faces are used as the reference object class. The topics covered include optimal design of filter banks for feature detec tion and object recognition, modeling of pose effects in filter responses and th e construction of probability-based pose-invariant object matching and re cognition systems employing oriented filters. Gabor filters have been derived as information-theoretically optimal bandp ass filters, simultaneously maximizing the localization capability in space and spatialfrequency domains. Steerable oriented filters have been developed as a tool for reducing the amount of computation required in rotation invariant systems . In this work, the framework of steerable filters is applied to Gabor-type filter s and novel analytical derivations for the required steering equations fo r them are presented. Gabor filters and some related filters are experimentally shown to be approximately steerable with low steering error, given suitable filter shap e parameters. The effects of filter shape parameters in feature localization a nd object recognition are also studied using a complete feature matching system. A novel approach for modeling the pose variation of features due to depth rotations is introduced. Instead of manifold learning methods, the use synthe tic data makes it possible to apply simpler regression modeling methods. The use of synthetic data in learning the pose models for local features is a central contribution of the work. The object matching methods considered in the work are based on probabilistic reasoning. The required object likelihood functions are constructe d using feature similarity measures, and random sampling methods are applied for find ing the modes of high probability in the likelihood probability distribution functions. The Population Monte Carlo algorithm is shown to solve successfully pose estimation problems in which simple Metropolis and Gibbs sampling methods give unsatisfactory performance.
On global MDL-based Multichannel Image Restoration and Partitioning.

In this paper, we address the problem of multichannel image partitioning and restoration, which includes simultaneous denoising and segmentation processes. We consider a global approach for multichannel image partitioning using minimum description length (MDL). The studied model includes a piecewise constant image representation with uncorrelated Gaussian noise. We review existing singleand multichannel approaches and make an extension of the MDL-based grayscale image partitioning method for the multichannel case. We discuss the algorithm’s behavior with several minimization procedures and compare the presented method to state-of-the-art approaches such as Graph cuts, greedy region merging, anisotropic diffusion, and active contours in terms of convergence, speed, and accuracy, parallelizability and applicability of the proposed method.
The price of a view: estimating the impact of view on house prices

ABSTRACT Houses with desired aesthetic views have a price premium over similar houses without such views. This article raises the following questions in relation to view as a location-specific amenity: How can we calculate a reliable indicator for view using available information? Are dwellings with a view sold for a premium compared to otherwise similar properties? Using more than 5,000 house transactions in the Illawarra region in Australia, and applying hedonic price method, the study analyses the price effects of key aesthetic views. Due to unavailability of view as a housing characteristic within historical records, spatial analysis tools were used to estimate views for housing locations. The results confirm the significance of aesthetic views in explaining house prices. Beach view is the most important aesthetic view. An increase of 1% of beach view drives house prices up by nearly 2–3%. Significant positive contributions to prices are also evident from sea, conservation area and inland water views. In addition to the views, other location-specific attributes also influence house prices. Methods developed in this study to quantify the value of aesthetic views and location-specific characteristics associated with residential locations form an important contribution to urban planning and policy development.
A Quantitative Assessment and Comparison of Conceptual Learning in Online and Classroom-Instructed Anatomy and Physiology

i DEDICATION iv ACKNOWLEDGEMENTS v List of Illustrative Materials viii CHAPTER 1: INTRODUCTION 1 Statement of the Problem 1 Theoretical Framework 6 Purpose of the Study and Research Questions 10 Significance of the Study 12 Definition of Terms 15 Delimitations 17 Limitations 17 Ethical Considerations 20 CHAPTER 2: LITERATURE REVIEW 22 Overview 22 Comparison of Traditional and Online Science Courses 22 Online/Virtual Formats/Applications in Anatomy and Physiology 33 Advantages and Disadvantages of Online Science Courses 42 CHAPTER 3: METHODS AND PROCEDURES 55 Overview 55 Research Site 55 Course Descriptions 55 Sample and Measures 57 Recruitment of Participants 60 Procedure, Treatment, and Instrument 62 Data Analyses 65 Methodological Assumptions 68 CHAPTER 4: RESULTS AND DISCUSSION OF FINDINGS 69 Overview 69 Results 69 Discussion 73