Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine learning algorithms for document clustering and fraud detection

Machine Learning plays very important role in processing of large amounts of structured and unstructured data. A set of algorithms can be used to get meaningful insights into the data that are helpful in making effective business decisions. Document clustering is one of the popular machine learning technique used to group unstructured data (text documents) based on its content and further analyze the data to understand the patterns in it. The unstructured data gets transformed into semi-structured data and structured data in stages by using text mining and clustering (k-means) techniques. Classification is another machine learning technique that can be implemented for use cases like "fraud detection and cross-sell & up-sell opportunity identification" in banking, financial services and insurance industry. This paper focuses on the implementation of both document clustering algorithm and a set of classification algorithms (Decision Tree, Random Forest and Naïve Bayes), along with appropriate industry use cases. Also, the performance of three classification algorithms will be compared by calculation of "Confusion Matrix" which in turn helps us to calculate performance measures such as, "accuracy", "precision", and "recall".
Rover@Home: Computer Mediated Remote Interaction for Dogs

In this paper, we describe our combination of animal behavior and interface design to implement and test an artifact that allows dogs and humans to interact over the Internet. In particular, we generalize an established dog training technique known as “clicker training” such that the computer-mediated version and the legacy co-located version are reported by dog owners to be similar. In creating the Rover@Home interaction, we need to consider that dogs are not simply furry humans but have very different perceptual, motor, and cognitive abilities from humans. We introduce the notion of “asymmetric interfaces” to accommodate these differences. This work is significant because by systematically applying HCI design principles to non-humans, we include animals in the HCI community. This creates an opportunity for the evaluation of the generality of much HCI literature, as well as increasing the sources from which we can draw inspiration.
Intra-Abdominal Hypertension and Gastrointestinal Symptoms in Mechanically Ventilated Patients

Background. We aimed to describe the incidence of intra-abdominal hypertension (IAH) and gastrointestinal (GI) symptoms and related outcome in mechanically ventilated (MV) patients. Methods. Intra-abdominal pressure (IAP) and gastric residual volumes were measured at least twice daily. IAH was defined as a mean daily value of IAP ≥ 12 mmHg. Results. 398 patients were monitored for all together 2987 days. GI symptom(s) occurred in 80.2% patients. 152 (38.2%) patients developed IAH. Majority (93.4%) of patients with IAH had GI symptoms. The more severe IAH was associated with the higher number of concomitant GI symptoms (P < .001). 142 (35.7%) patients developed both IAH and at least one GI symptom at any time in ICU, and in 77 patients they occurred simultaneously on the same day. This subgroup had the highest ICU mortality (21.8%). In contrast, the small group of patients presenting only IAH, but not GI symptoms (10 patients), had no lethal outcome. Three patients (4.4%) died without showing either IAH or GI symptoms. Conclusions. GI symptoms and IAH often, but not always, occur together. The patients having IAH solely without developing GI symptoms have rather good outcome.
PARENTAL MEDIATION OF YOUNG CHILDREN ’ S INTERNET USE

Children are using the Internet at younger and younger ages. So far, however, we know little about how parents guide young children's online activities to prevent risks. Filling this void an Internet-survey established empirically which media guidance strategies 792 parents of children (2-12 years) in the Netherlands used. As was established in former television and game research factor analysis revealed that parents also applied ‘co-use’, ‘active mediation’, and ‘restrictive mediation’. In addition, parents also applied new strategies: ‘supervision’ i.e. keeping an eye on the child from a distance, and using safety software applications. Mediation types were mainly predicted by the child’s age and online behavior, such as gaming and social networking. Also, parents applied more mediation when they expected positive effects and particularly when they expected negative effects of the Internet, indicating that parents deliberately adjust their mediation to the child's needs and interests. Mediation was also predicted by the number of computers at home, and the parent’s gender, education and computer / Internet skills.
Breast Cancer Diagnosis Using a Microfluidic Multiplexed Immunohistochemistry Platform

Background Biomarkers play a key role in risk assessment, assessing treatment response, and detecting recurrence and the investigation of multiple biomarkers may also prove useful in accurate prediction and prognosis of cancers. Immunohistochemistry (IHC) has been a major diagnostic tool to identify therapeutic biomarkers and to subclassify breast cancer patients. However, there is no suitable IHC platform for multiplex assay toward personalized cancer therapy. Here, we report a microfluidics-based multiplexed IHC (MMIHC) platform that significantly improves IHC performance in reduction of time and tissue consumption, quantification, consistency, sensitivity, specificity and cost-effectiveness. Methodology/Principal Findings By creating a simple and robust interface between the device and human breast tissue samples, we not only applied conventional thin-section tissues into on-chip without any additional modification process, but also attained perfect fluid control for various solutions, without any leakage, bubble formation, or cross-contamination. Four biomarkers, estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), progesterone receptor (PR) and Ki-67, were examined simultaneously on breast cancer cells and human breast cancer tissues. The MMIHC method improved immunoreaction, reducing time and reagent consumption. Moreover, it showed the availability of semi-quantitative analysis by comparing Western blot. Concordance study proved strong consensus between conventional whole-section analysis and MMIHC (n = 105, lowest Kendall's coefficient of concordance, 0.90). To demonstrate the suitability of MMIHC for scarce samples, it was also applied successfully to tissues from needle biopsies. Conclusions/Significance The microfluidic system, for the first time, was successfully applied to human clinical tissue samples and histopathological diagnosis was realized for breast cancers. Our results showing substantial agreement indicate that several cancer-related proteins can be simultaneously investigated on a single tumor section, giving clear advantages and technical advances over standard immunohistochemical method. This novel concept will enable histopathological diagnosis using numerous specific biomarkers at a time even for small-sized specimens, thus facilitating the individualization of cancer therapy.
A simulation methodology for assessing the impact of spatial/pattern dependent interconnect parameter variation on circuit performance

In this paper, we illustrate a methodology for determining the impact of interconnect pattern dependent variation on circuit performance. The methodology helps enable first pass prediction and can handle large layouts using methods which are reasonably compatible with existing CAD tools. We illustrate the relative utility of the methodology using two case studies. Both studies are drawn from industrial relevant problems: unwanted skew in a balanced clock tree and capacitance variation of a critical net in an SRAM array.
Approximating Large Frequency Moments with O(n1-2/k) Bits

In this paper we consider the problem of approximating frequency moments in the streaming model. Given a stream $D = \{p_1,p_2,\dots,p_m\}$ of numbers from $\{1,\dots, n\}$, a frequency of $i$ is defined as $f_i = |\{j: p_j = i\}|$. The $k$-th \emph{frequency moment} of $D$ is defined as $F_k = \sum_{i=1}^n f_i^k$. In this paper we give an upper bound on the space required to find a $k$-th frequency moment of $O(n^{1-2/k})$ bits that matches, up to a constant factor, the lower bound of Woodruff and Zhang (STOC 12) for constant $\epsilon$ and constant $k$. Our algorithm makes a single pass over the stream and works for any constant $k > 3$.
On Covering Codes and Upper Bounds for the Dimension of Simple Games

Consider a situation with n agents or players, where some of the players form a coalition with a certain collective objective. Simple games are used to model systems that can decide whether coalitions are successful (winning) or not (losing). A simple game can be viewed as a monotone boolean function. The dimension of a simple game is the smallest positive integer d such that the simple game can be expressed as the intersection of d threshold functions, where each threshold function uses a threshold and n weights. Taylor and Zwicker have shown that d is bounded from above by the number of maximal losing coalitions. We present two new upper bounds both containing the Taylor-Zwicker bound as a special case. The Taylor-Zwicker bound implies an upper bound of (n choose n/2). We improve this upper bound significantly by showing constructively that d is bounded from above by the cardinality of any binary covering code with length n and covering radius 1. This result supplements a recent result where Olsen et al. showed how to construct simple games with dimension |C| for any binary constant weight SECDED code C with length n. Our result represents a major step in the attempt to close the dimensionality gap for simple games.
RADIOPACITY EVALUATION OF ROOT-END FILLING MATERIALS BY DIGITIZATION OF IMAGES

The purpose of this study was to evaluate the radiopacity of 5 root-end filling materials (white MTA-Angelus, grey MTA-Angelus, IRM, Super EBA and Sealer 26). Five specimens (10 mm diameter X 1 mm thickness) were made from each material and radiographed next to an aluminum stepwedge varying in thickness from 2 to 16 mm. Radiographs were digitized and the radiopacity of the materials was compared to that of the aluminum stepwedge using VIXWIN 2000 software in millimeters of aluminum (mm Al). Data were analyzed statistically by ANOVA and Tukey's test at 5% significance level. Radiopacity values varied from 3 mm Al to 5.9 mm Al. Sealer 26 and IRM presented the highest radiopacity values (p<0.05), while white/grey MTA and Super EBA presented the lowest radiopacity values (p<0.05). The tested root-end filling materials presented different radiopacities, white/grey MTA and Super EBA being the least radiopaque materials.
Single Document Summarization Based on Triangle Analysis of Dependency Graphs

Extractive document summarization is a fundamental technique for document summarization. Most well-known approaches to extractive document summarization utilize supervised learning where algorithms are trained on collections of "ground truth" summaries built for a relatively large number of documents. In this paper, we propose a novel algorithm, called Triangle Sum for key sentence extraction from single document based on graph theory. The algorithm builds a dependency graph for the underlying document based on co-occurrence relation as well as syntactic dependency relations. In such a dependency graph, nodes represent words or phrases of high frequency, and edges represent dependency-co-occurrence relations between them. The clustering coefficient is computed from each node to measure the strength of connection between a node and its neighbors in a dependency graph. By identifying triangles of nodes in the graph, a part of the dependency graph can be extracted as marks of key sentences. At last, a set of key sentences that represent the main document information can be extracted.
Book Review: Doing the Best I Can: Fatherhood in the Inner City

Chance, Beth, Dani Ben-Zvi, Joan Garfield, and Elsa Medina. 2007. “The Role of Technology in Improving Student Learning of Statistics. ” Teaching Innovations in Statistics Education Journal 1(1):1-26. Fink, Leon. 2005. “Making Textbooks Worthwhile. ” Chronicle of Higher Education 52(4):B12. Gray Wilson, Stephanie. 2013. “The Flipped Class: A Method to Address the Challenges of an Undergraduate Statistics Course. ” Teaching of Psychology 40(3): 193-99. Howery, Carla, and Havidan Rodriguez. 2006. “Integrating Data Analysis (IDA): Working with Sociology Departments to Address the Quantitative Literacy Gap. ” Teaching Sociology 34(1):23-38. Hulsizer, Michael R. , and Linda Woolf. 2009. A Guide to Teaching Statistics: Innovations and Best Practices, vol. 10. New York: Wiley. Moran, Timothy Patrick. 2005. “Conversation: The Sociology of Teaching Graduate Statistics. ” Teaching Sociology 33(3):263-84. Paxton, Pamela. 2006. “Dollars and Sense: Convincing Students That They Can Learn and Want to Learn Statistics. ” Teaching Sociology 34(1):65-70. Schacht, Steven P. 1990. “Statistics Textbooks: Pedagogical Tools or Impediments to Learning? ” Teaching Sociology 18(3):390-96. Strangfeld, Jennifer. 2013. “Promoting Active Student Learning: Student-led Data Gathering in Undergraduate Statistics. ” Teaching Sociology 41(2):199-206.
Basic Psychoanalytic Concepts On The Theory Of Instincts

Thank you for reading basic psychoanalytic concepts on the theory of instincts. Maybe you have knowledge that, people have search numerous times for their chosen readings like this basic psychoanalytic concepts on the theory of instincts, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they are facing with some harmful virus inside their laptop.
Understanding Viral Transmission Behavior via Protein Intrinsic Disorder Prediction: Coronaviruses

Besides being a common threat to farm animals and poultry, coronavirus (CoV) was responsible for the human severe acute respiratory syndrome (SARS) epidemic in 2002–4. However, many aspects of CoV behavior, including modes of its transmission, are yet to be fully understood. We show that the amount and the peculiarities of distribution of the protein intrinsic disorder in the viral shell can be used for the efficient analysis of the behavior and transmission modes of CoV. The proposed model allows categorization of the various CoVs by the peculiarities of disorder distribution in their membrane (M) and nucleocapsid (N). This categorization enables quick identification of viruses with similar behaviors in transmission, regardless of genetic proximity. Based on this analysis, an empirical model for predicting the viral transmission behavior is developed. This model is able to explain some behavioral aspects of important coronaviruses that previously were not fully understood. The new predictor can be a useful tool for better epidemiological, clinical, and structural understanding of behavior of both newly emerging viruses and viruses that have been known for a long time. A potentially new vaccine strategy could involve searches for viral strains that are characterized by the evolutionary misfit between the peculiarities of the disorder distribution in their shells and their behavior.
Enhancing the Self

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Numerical approximation of the general compressible Stokes problem

In this paper, we propose a discretization for the compressible Stokes problem with an equation of state of the form p = ϕ(ρ) (where p stands for the pressure, ρ for the density and ϕ is a superlinear nondecreasing function from R to R). This scheme is based on Crouzeix-Raviart approximation spaces. The discretization of the momentum balance is obtained by the usual finite element technique. The discrete mass balance is obtained by a finite volume scheme, with an upwinding of the density, and two additional terms. We prove the existence of a discrete solution and the convergence of this approximate solution to a solution of the continuous problem.
Comment prendre en compte les spécificités de "l'écriture SMS" pour l'analyse de sentiments ?

Avec la croissance explosive des donnees textuelles issues des medias sociaux (forums, blogs et reseaux sociaux), l'exploitation de ces nouvelles sources d'information est devenue cruciale. Nos travaux se concentrent sur l'analyse des sentiments dans ce contexte des medias sociaux. Pour identifier des sentiments issus des messages (par exemple, tweets, SMS), des techniques originales de fouille de textes doivent etre proposees. Cet article presente une nouvelle methode qui integre les connaissances semantiques et lexicales pour l'analyse des sentiments. L'approche proposee donne un poids important aux "mots de sentiment" pour une tâche de classification. Notre etude compare deux corpus (88milSMS et DEFT'2015) afin de mettre en evidence les caracteristiques specifiques des donnees SMS dans le contexte des medias sociaux. (Resume d'auteur)
A Statistical View of Learning in the Centipede Game

In this article we evaluate the statistical evidence that a population of students learn about the sub-game perfect Nash equilibrium of the centipede game via repeated play of the game. This is done by formulating a model in which a player's error in assessing the utility of decisions changes as they gain experience with the game. We first estimate parameters in a statistical model where the probabilities of choices of the players are given by a Quantal Response Equilibrium (QRE) (McKelvey and Palfrey, 1995, 1996, 1998), but are allowed to change with repeated play. This model gives a better fit to the data than similar models previously considered. However, substantial correlation of outcomes of games having a common player suggests that a statistical model that captures within-subject correlation is more appropriate. Thus we then estimate parameters in a model which allows for within-player correlation of decisions and rates of learning. Through out the paper we also consider and compare the use of randomization tests and posterior predictive tests in the context of exploratory and confirmatory data analyses.
Randomized algorithms for the low-rank approximation of matrices

We describe two recently proposed randomized algorithms for the construction of low-rank approximations to matrices, and demonstrate their application (inter alia) to the evaluation of the singular value decompositions of numerically low-rank matrices. Being probabilistic, the schemes described here have a finite probability of failure; in most cases, this probability is rather negligible (10−17 is a typical value). In many situations, the new procedures are considerably more efficient and reliable than the classical (deterministic) ones; they also parallelize naturally. We present several numerical examples to illustrate the performance of the schemes.
NORMIT: a Web-enabled tutor for database normalization

The paper describes the design and development of NORMIT, an intelligent tutoring system (ITS) that teaches database normalization to university students. NORMIT is a Web-enabled system, and we discuss its architecture and techniques used to deal with multiple students. We also discuss constraint-based modeling (CBM), the underlying student and domain modelling approach. NORMIT is the first in the series of constraint-based tutors developed at ICTG that teaches a procedural task, and we comment on the suitability of CBM for such tasks. We also discuss the plans for the evaluation of the system and future work.
Novel Method of Synthesis of 5''-Phosphate 2'-O-ribosyl-ribonucleosides and Their 3'-Phosphoramidites

Synthesis of 5''-phosphate 2'-O-ribosylribonucleosides [Nr(p)] of four common ribonucleosides, and 3'-phosphoramidites of 5''-phosphate 2'-O-ribosyladenosine and 2'-O-ribosylguanosine using the H-phosphonate chemistry is described. An additional ring protected by benzoyl groups was incorporated into the main ribosyl ring in the reaction with 1-O-acetyl-2,3,5-tri-O-benzoyl-β-d-ribofuranose in the presence of SnCl4. The obtained 2'-O-ribosylribonucleosides (Nr) were applied in the subsequent transformations with selective deprotection. Ethanolamine was applied as a very convenient reagent for selective removal of benzoyl groups. Additionally, the tetraisopropyldisiloxane-1,3-diyl (TIPDSi) group was found to be stable under these deprotection conditions. Thus, the selectively deprotected 5''-hydroxyl group of Nr was transformed into an H-phosphonate monoester which was found to be stable under the following conditions: the removal of the TIPDSi group with triethylammonium fluoride and the dimethoxytritylation of the 5''-hydroxyl function. The 5''-H-phosphonate of Nr precursors was easily transformed to the corresponding dicyanoethyl 5''-O-phosphotriesters before phosphitylation, which gave 3'-phosphoramidite units of Nr(p) in high yield. The derived phosphoramidite units were used in an automated oligonucleotide synthesizer to produce dimer Ar(p)T via the phosphoramidite approach. The obtained products were fully deprotected under standard deprotection conditions giving dimers with a 5''-phosphate monoester function. Application of an alkaline phosphatase to prove the presence of an additional phosphate group was described.
Identifying pathological biomarkers: histochemistry still ranks high in the omics era

In recent years, omic analyses have been proposed as possible approaches to diagnosis, in particular for tumours, as they should be able to provide quantitative tools to detect and measure abnormalities in gene and protein expression, through the evaluation of transcription and translation products in the abnormal vs normal tissues. Unfortunately, this approach proved to be much less powerful than expected, due to both intrinsic technical limits and the nature itself of the pathological tissues to be investigated, the heterogeneity deriving from polyclonality and tissue phenotype variability between patients being a major limiting factor in the search for unique omic biomarkers. Especially in the last few years, the application of refined techniques for investigating gene expression in situ has greatly increased the diagnostic/prognostic potential of histochemistry, while the progress in light microscopy technology and in the methods for imaging molecules in vivo have provided valuable tools for elucidating the molecular events and the basic mechanisms leading to a pathological condition. Histochemical techniques thus remain irreplaceable in pathologist's armamentarium, and it may be expected that even in the future histochemistry will keep a leading position among the methodological approaches for clinical pathology.