Miracle-dz/UniFAR-FTUs huggingface dataset:
2‐Bromo‐1‐chloro­phenyl‐3‐(4‐methoxy­phen­yl)prop‐2‐en‐1‐one

The geometrical parameters for the title compound, C16H12BrClO2, are normal. The observed bond lengths and angles imply that there is little electronic conjugation between the two benzene ring systems. An intra­molecular C—H⋯Br inter­action may help to establish the mol­ecular conformation. The crystal packing results in a centrosymmetric structure.
The SELECT study: A multicenter phase II trial of adjuvant erlotinib in resected epidermal growth factor receptor (EGFR) mutation-positive non-small cell lung cancer (NSCLC).

7010 Background: Cancers with activating EGFR mutations are exquisitely sensitive to EGFR tyrosine kinase inhibitors (TKIs) and retrospective data suggests adjuvant TKIs may improve outcomes in EGFR mutants. This prospective trial investigates the safety and efficacy of adjuvant erlotinib in EGFR mutation-positive NSCLC. Methods: Patients (pts) with surgically resected stage IA-IIIA NSCLC harboring activating EGFR mutations were treated with 150 mg/day of erlotinib for 2 years (y) after completion of any standard adjuvant chemotherapy and/or radiotherapy. The trial was designed to enroll 36 patients, and powered to demonstrate a primary endpoint of 2 y disease free survival (DFS) exceeding 85%, which would suggest improvement over the historically expected 70% 2 y DFS in early stage EGFR-mutant NSCLC (J Thorac Oncol 6:569). Results: Thirty-six pts were enrolled at five sites between 1/08 and 11/09; 53% stage I; 19% stage II; 28% stage IIIA. Toxicities were typical of erlotinib; no grade 4 or 5 events or p.
Bowes' and Church's Food Values of Portions Commonly Used

This reference text has been revised to ensure relevance to today's eating habits - 85% of the text is new or updated. It provides complete nutritional information on 8,500 foods in an easy-access tabular format. Comprehensive, "Bowes and Church's" discusses not only general foods but common brand name products, for extra utility in real-life nutritional analysis. Appendices list all foods containing a particular substance, such as caffeine or iron. New to this edition: food tables which cover monounsaturated fat content; 3,000 more foods; and listings of the sources for each food entry.
Maternal smoking and newborn sex, birth weight and breastfeeding: a population-based study

Abstract Objective: Today, it is acknowledged that smoking during pregnancy and/or the postnatal period has significant risks for a foetus and newborn child. This research examines the relationship between smoking only postnatally, both during pregnancy and postnatally, and the newborn sex, birth weight and breastfeeding. Methods: Total 664 women of randomly selected five primary healthcare centres between the dates 20 February 2010 and 20 July 2010 were included in the research. Statistical analyses were performed with SPSS for Windows 19.0 (Statistical Package for Social Sciences software package). Data were described as mean, standard deviation, percentages and Chi-square tests and backward stepwise logistic regression were analysed. Results: It was found that the percentage of smoking women with daughters is 2.5 times higher than women with sons. Women who smoke are 3.9 times more likely to start feeding their baby with supplementary infant foods at 4 months or earlier than those who do not smoke. Finally, the risk of a birth weight under 2500 g is 3.8 times higher for maternal smokers. Conclusions: This study suggests that women who expect a girl smoke more heavily than those who expect a boy. The birth weight of maternal smokers’ newborns is lower. Those women who smoke while breastfeeding start feeding their babies with supplementary infant foods at an earlier age.
Comparing Sequential Steps For Detection Of Circulating Tumor Cells: More Specific Or Just Less Sensitive?

Abstract Background: We compared two surface epithelialantigen (EpCAM)-based approaches for the detectionof breast cancer cells present in the circulation.Methods: Blood from 20 breast cancer patients wasdrawn into standard blood collection tubes (SBCT) andof 7 of these additionally into CellSave® tubes. Aftererythrocyte lysis of the samples from both systems,cells were stained with FITC-anti-EpCAM andpropidium iodide, quantified with an automatedmicroscope and intact cells counted.Results: EpCAM-positive events from 1ml of bloodranged between 2051 and 28875/ml and from SBCT(MAINTRAC® approach) as compared to between 97and 2343/ml from the CellSave® tubes, indicating amore than 10-fold reduction in EpCAM accessibility bythe preservative. Duplicate cell preparations showed ahigh correlation of R2=0.89 (MAINTRAC®) from SBCTvs. a moderate correlation of R2=0.81 from CellSave®tubes, but a good correlation (R2=0.91) between theevents detected from both systems.Between 1/2 and 1/5 of the positive events were viablecells in the MAINTRAC® approach with unequivocalmorphology, and a good (R2=0.89) correlation to totalevents; by contrast, 1/10 to less than 1/100 of theevents in the CellSave® tubes were perhaps cells withequivocal morphology no correlation to total eventsmost positive events being non-recognizable cells. Still30 to 100-fold more cells were recovered than with theCellTrack® Analyzer.Conclusions: The approach without fixative detectsconsiderably more EpCAM-positive events with goodcell morphology as compared to the CellSave®fixation where cell morphology is poor. Magnetic beadenrichment further reduces the number of retrievedcells.
Teacher Learning through National Board Candidacy: A Comparative Case Study

This study describes three teachers’ learning experiences during National Board candidacy and explores National Board for Professional Teaching Standards (NBPTS) influences on their learning as evidenced by changes in teaching practice. National Board candidacy positively influenced all three teachers. Common areas of learning were increased respect for student individuality and improved capacity for intentional teaching. NBPTS influences were reflection and analysis of teaching practice and professional reading/preparation for the written assessment. The study identifies National Board certification as one pathway to teacher leadership. The study’s findings are consistent with other studies of teacher learning experiences during National Board candidacy with one exception: The teachers in this study identified professional reading and preparation for the NBPTS written assessment as key learning influences. The National Board for Professional Teaching Standards (NBPTS) was established in 1987. Since then, over 160,000 teachers nationwide have attempted the certification process, and more than 82,000 have become National Board certified (NBPTS, 2009). Most teachers who seek the certification consider it the best professional development they have ever experienced (Kanter, Bergee, & Unrath, 2000; Rotberg, Futrell, & Holmes, 2000), yet few studies describe candidates’ learning experiences in detail. This study describes three teachers’ learning experiences during National Board candidacy and explores NBPTS influences on their learning as evidenced by changes in teaching practice.
Attitudes Toward Seeking Help Among College Students Enrolled in Helping Profession Courses: A Comparative Study Between Clinical Mental Health Counselors, Social Workers, and Psychologists

This study used the Inventory of Attitudes Toward Seeking Mental Health Services to measure and compare college students’ attitudes toward seeking mental health services from professional clinical mental health counselors, social workers, psychologists, and mental health providers with a neutral identity. The participants’ (n = 131) attitudes toward seeking mental health services did not vary statistically among any of these four groups, even when participants’ academic majors and past experience with mental health services were covaried.
Multi-Task, Multi-Channel, Multi-Input Learning for Mental Illness Detection using Social Media Text

We investigate the impact of using emotional patterns identified by the clinical practitioners and computational linguists to enhance the prediction capabilities of a mental illness detection (in our case depression and post-traumatic stress disorder) model built using a deep neural network architecture. Over the years, deep learning methods have been successfully used in natural language processing tasks, including a few in the domain of mental illness and suicide ideation detection. We illustrate the effectiveness of using multi-task learning with a multi-channel convolutional neural network as the shared representation and use additional inputs identified by researchers as indicatives in detecting mental disorders to enhance the model predictability. Given the limited amount of unstructured data available for training, we managed to obtain a task-specific AUC higher than 0.90. In comparison to methods such as multi-class classification, we identified multi-task learning with multi-channel convolution neural network and multiple-inputs to be effective in detecting mental disorders.
Towards a better understanding of ungulate diets: a methodological approach

Populations of European ungulates have grown substantially over recent decades, resulting in considerable environmental and socio-economic impacts. Availability and quality of natural and supplemental food sources are among the main factors driving their population dynamics. Detailed knowledge of feeding strategies of management-targeted species is therefore of primary importance for their successful management. Over time, methods to study the feeding strategies of animals have also evolved considerably but each has its advantages as well as limitations. This doctoral thesis uses a combination of traditional methods (i.e. stomach content analysis) and novel methods (i.e. stable isotope analysis, near infrared reflectance spectroscopy) to achieve a better understanding of feeding strategies of two important ungulate species (i.e. wild boar and red deer) in the Czech Republic, where their populations are on the rise and supplementary feeding is rampant. Next, this dissertation aims to introduce and to establish a basis for these novel methodological approaches for the study of free-ranging individuals. In this respect, it also addresses methodological issues related to their application in this field. The diet composition of wild boar was investigated by examining stomach contents in order to identify their dependence on food resources of human origin (i.e. agricultural crops and supplemental foods). Foods of human origin were the dominant diet type and constituted the bulk of wild boar’s diet throughout the year. A necessary prerequisite for application of stable isotope analysis is the trophic discrimination factor (i.e. systematic difference between the isotopic composition of the consumer tissues and that of the diet), which was experimentally determined for stable carbon and nitrogen isotopes, the two most commonly used in ecology, in hair tissue of wild boar and red deer. Furthermore, possible sources of variation (such as sex, age, body weight, and lactation) on isotopic discrimination were investigated. The results of the experiments provide a starting point for the successful use of stable isotope analysis in field studies on wild boar and red deer. Finally, application of near infrared reflectance spectroscopy was proven to be useful in measuring faecal indices of food quality for red deer. The results of this thesis will contribute towards efficient management of wild boar and red deer in the Czech Republic.
Convergence analysis of a two-step method for the nonlinear least squares problem with decomposition of operator

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Convergence analysis of a two-step method for the nonlinear least squares problem with decomposition of operator Stepan Shakhno, Roman Iakymchuk, Halyna Yarmola
HTTP SERVICE BASED NETWORK INTRUSION DETECTION SYSTEM IN CLOUD COMPUTING

Recently, the usages of Cloud Computing are increasing rapidly and gained tremendous success over the internet. Therefore, security is the major challenge in Cloud computing and one of the major issues is to protect the Cloud resources and the services against network intrusions. So Network Intrusion Detection System (NIDS) are installed in the Cloud networks to detect the intrusions in the system. In this paper we proposed an NIDS based on Naïve Bayes Classifier to be implemented in Cloud. The main aim of the NIDS is to improve the performance by preparing the training dataset which can detect the malicious connections that exploit the Cloud HTTP services. In the training phase, the Naïve Bayes Classifiers select the important Network traffic that can be used to detect the attacks. In the testing and execution phases the proposed NIDS using the Naïve Bayes Classifier classifies the services based on the selected features into normal or attacks. The proposed IDS carried out on NSLKDD’99 dataset and results in high detection with low false alarm as compared with other similar IDS.
Running head: RAPID TRIAL-AND-ERROR LEARNING SUPPORTS TOOL USE 1 Rapid trial-and-error learning with mental simulation supports flexible tool use

Many animals, and an increasing number of artificial agents, display sophisticated capabilities to perceive and manipulate objects. But human beings remain distinctive in their capacity for flexible, creative tool use – using objects in new ways to act on the world, achieve a goal, or solve a problem. To study this type of general physical problem solving, we introduce the Virtual Tools game. In this game, people solve a large range of challenging physical puzzles in just a handful of attempts. We propose that the flexibility of human physical problem solving rests on an ability to imagine the effects of hypothesized actions, while the efficiency of human search arises from rich action priors which are updated via observations of the world. We instantiate these components in the “Sample, Simulate, Update” (SSUP) model and show that it captures human performance across 30 levels of the Virtual Tools game. More broadly, this model provides a mechanism for explaining how people condense general physical knowledge into actionable, task-specific plans to achieve flexible and efficient physical problem-solving.
120815-Beyond Rationality-NBP FCM v6

While there exists an extensive literature seeking to directly test the rationality of inflation expectations, this paper has instead investigated whether consumers have rational perceptions of inflation in the first place. We argue that this is a necessary prerequisite to establish rationality, and its lack of consideration by much of the previous literature purporting to test rational expectations potentially casts doubts on its conclusions. Nevertheless, we find that the perceptions of inflation by consumers contain significant biases relative to official measures of inflation, and that their expectation forecasts fall short of what might be labelled rational even after controlling for the biases found. The biases are attributed to a number of factors that might shape consumers’ understanding of inflation. Beyond those factors, it is clear that consumers do not operate in a vacuum of information, and have regular access to the forecasts of economic experts through the news media. We therefore proceed to studying the relationship between consumer and professional expectations in Europe, following Carroll’s (2003) work with US data. On the whole, our results were unable to evidence a clear-cut picture of information being transmitted from experts to consumers for most countries, with however the salient exception of the UK, for which a very clear such mechanism was evidenced. We discuss possible reasons for the similarity between the UK and US in this respect, and relevant differences that might set them apart from the other European countries considered. The views expressed in this paper are solely my own and do not necessarily reflect those of Google. I would like to thank especially Professor John Muellbauer for his extraordinary support and numerous insightful discussions over the years. I am also extremely grateful for comments from Dr. Mark Williams, Professor Peter Sinclair, Dr. Chris Bowdler, Dr. James Forder and Professor David Vines. Any errors are my own.
A Translation-based Data Acquisition Scheme for Industrial Computed Tomography

Today, X-ray Computed Tomography (CT) is widely used as a tool for industrial nondestructive testing (NDT). There is a manifold of applications in the laboratory as well with inline testing for industrial production control [1, 2]. Although, various CT data acquisition methods have been developed to meet the different applications, all systems are based on a rotation of the object. Alternatively, this can be achieved by rotating the detector and the source of x-rays around the object, but mathematically both methods are equivalent.
CURVE AND SKELETON BASED SHAPE DEFORMATIONS IN PRODUCT DESIGN

In this report we present an intuitive curve and skeleton based approach for digital product modelling. Morphing–like deformations have been developed to allow for the evaluation of a larger set of alternative shapes compared to the set of shapes generated by the current modelling tools. The method helps designers to search in the product domain for alternative shapes in a straightforward way and eliminates the work–arounds. Through a slide–bar control, these alternative shapes are generated by the transformation of an initial shape into the target one by means of a suitable skeleton extraction transparent to the user and a user-defined profile curve for the target surface. The initial shape is abstracted by a skeleton and a distance function from the skeleton to the surface. For the target surface two categories have been considered, namely revolution–like and sweep–like surfaces. They are both defined through curves: an axis or a path and a profile. The user has to specify only the profile curve, as the axis or the path is represented by the skeletal curve extracted from the initial surface. The distribution of the morphing–like deformation is computed based on the skeletal curve, the distance function and the user-defined profile curve. The use of the skeleton guarantee the generated shapes belong to specific product domains and are therefore context–dependent.
DIPARTIMENTO DI MATEMATICA

The human brain is a really complex organization of connectivity whose principal elements are neurons, synapses and brain regions. Up to now this connectivity is not fully understood, and recent impulse in investigating its structure has been given by Graph Theory. However, some points remain unclear, mainly due to possible mismatching between the Mathematical and the Neuroscientific approach. It is known that neural connectivity is classified into three categories: structural (or anatomical) connectivity, functional connectivity and effective connectivity. The point is that these categories demand different kinds of graphs, except in the case of the resting state, and sometimes topological and metrical parameters are involved simultaneously, without a specific distinction of their roles. In this paper we propose a mathematical model for treating the functional connectivity, based on directed graphs with weighted edges. The function W (i, j, t), representing the weight of the edge connecting nodes i, j at time t, is obtained by splitting the model in two parts, where different parameters have been introduced step by step and rigorously motivated. In particular, there is a double role played by the notion of distance, which, according to the different parts of the model, assumes a discrete or an Euclidean meaning. Analogously, the time t appears both from a local and from a global perspective. The local aspect relates to a specific task submitted to an health volunteer (in view of possible future applications also to subjects affected by neurological diseases), while the global one concerns the different periods in the human life that characterize the main changes in the neural brain network. In the particular case of the resting state, we have shown that W reduces to the usually employed probabilistic growth laws for the edge formation. We tested the correctness of our model by means of synthetic data, where the selection of all involved parameters has been motivated according to what is known from the available literature. It turns out that simulated outputs fit well with the expected results, which encourages further analysis on real data, and possible future applications to neurological pathologies.
ENHANCEMENT OF PERFORMANCE OF OLSR WITH VARIOUS TCP VARIANTS

In current research under proactive protocol various traffic variant performances is to be checked. The objectives of research are like to identify the performance of TCP variant like TCP sack and TCP vegas. There performance is checked based on different parameters like Throughput, End to End delay, packet overhead and routing overhead. In current work two different networks under OLSR protocol with different TCP variants are being implemented. Under different TCP variants different types of scenario is being produced. After the analysis the TCP vegas has come out to be the better performing TCP variants.
Farmer practices that influence risk factors, prevalence and control strategies of rabbit coccidiosis in Central Kenya

Rabbit production is a fast growing industry in Kenya. Despite the growth, an assessment of farmer's knowledge, attitude, and practices that influence the occurrence of rabbit coccidiosis is not documented. This study was conducted in Central Kenya to assess farmers' practices that influence risk factors, prevalence, and control strategies of rabbit coccidiosis. Questionnaires were used to collect data from 97 rabbit farmers and 27 agro-veterinary outlets. Prevalence and intensity of coccidia infection were also determined. Results revealed that rabbit production is majorly carried out by smallholder (53.6%) farmers who on average keep less than 10 rabbits. The overall prevalence of coccidiosis in the two counties was 49% with infection intensity ranging from 100 to 12.0 x 104 oocysts per gram. Poor housing structures (10.5%), inefficient and irregular cleaning methods (74.2%) were the major risk factors for coccidiosis. The majority of farmers reported treating coccidiosis using Sulpha-chloropyrazine (22%) and Trimethoprim/Sulphamethoxazole combination (15%). Nonchemotherapeutic methods used in the management of coccidiosis included the ethnoveterinary use of Aloe vera and and liquid paraffin. The study recommends that strategic farmers' training on best practices in rabbit production and health should be carried out and that a controlled laboratory Create PDF in your applications with the Pdfcrowd HTML to PDF API PDFCROWD and field study be conducted to determine the efficacy of the commonly used treatment and control strategies for rabbit coccidiosis amongst the available methods.