Miracle-dz/UniFAR-FTUs huggingface dataset:
Radiologic imaging of the inflammatory renal diseases : literature review

Background and aim: Inflammatory diseases of the kidney are a broad group of various renal pathologies. They are usually recognized by clinical symptoms and laboratory tests. However, radiology also has a role. The aim of this article is to assess radiologic imaging possibilities in diagnosis and follow-up of the most common inflammatory renal diseases. Materials and methods: A selective search was carried out for relevant studies regarding radiologic imaging of acute pyelonephritis, renal and perinephric abscesses, emphysematous pyelonephritis, emphysematous pyelitis, chronic pyelonephritis and glomerulonephritis. ClinicalKey, Cochrane Library, Medline (PubMed), ScienceDirect and SpringerLink databases were used. Results: Ultrasound is usually used as the initial imaging tool to evaluate patients with symptoms of acute pyelonephritis. However, computed tomography is the most appropriate imaging modality. If an abscess or gas-forming infection are suspected, CT is the modality of choice. The findings characteristic, yet not pathognomic to chronic pyelonephritis can be assessed using all of the previously mentioned imaging tools. In cases of glomerulonephritis, US and MRI are the most suitable. Conclusion: Radiology plays an important role in diagnosis of inflammatory renal diseases. Imaging allows to identify renal abnormalities and differentiate between a few feasible pathologies. It may also evaluate the activity of the disease. Moreover, it can assess sequelae, such as renal scarring and decreased renal function.
Sound localization with a neural network trained with the multiple extended Kalman algorithm

A three-layer neural network is used to solve the problem of extracting relative azimuth and elevation positional information from signals detected by two spatially separate, directional receivers. This is analogous to the ability of owls to localize the position of sound based solely on the properties of the signals reaching their ears. A simple model of the acoustical environment was used to generate simulated data for training the network. The neural network was trained using the multiple extended Kalman algorithm (MEKA). MEKA enabled the network to be trained without constant user intervention for adjustment of the critical parameters of the model. <<ETX>>
COUPLED FINITE ELEMENT ANALYSIS OF PRESSURE VESSEL CREEP FAILURE EXPERIMENTS

The hypothetical scenario of a severe accident with core meltdown and formation of a melt pool in the lower plenum of a Light Water Reactor (LWR) Pressure Vessel (RPV) can result in the failure of the RPV and the discharging of the melt to the containment. One accident management strategy could be to stabilize the in-vessel debris or melt pool configuration in the RPV as a major barrier against uncontrolled release of heat and radionuclides into the containment.
Why doesn ’ t why invert ? : Investigating the link between inversion and interpretation in adult and child grammar

This paper investigates the source of children’s delayed subjectauxiliary inversion in why questions, first observed by Labov and Labov (1978). Previous accounts ((Thornton, 2004), (Berk, 2003)) have analyzed this phenomenon as a syntactic difference between children and adults, predicting that children who do not invert with why do not have access to the full range of interpretations of twoclause why questions available to adults. We conduct two experiments to determine the relation between inversion and interpretation in both children who do invert and do not invert with why. We show that not only is a syntactic account unable to explain the child facts, but this type of account (as proposed for adults by Rizzi (2001)) is also insufficient in explaining the cross-linguistic variation across adult languages. We show that differences in inversion and interpretation must be accounted for by lexical variation of individual why words, not due to syntactic differences in whprojections.
Fermentation Quality and Chemical Composition of Napier Pakchong 1 Silage Supplemented with Lactic Acid Bacteria

Napier Pakchong 1 grass (Pennisetum purpureum x P. americanum cv. Pakchong 1) has been developed by the Nakhonratchasima Animal Nutrition Research and Development Center, Thailand (Sarian 2013). Napier Pakchong 1 grass is one of the most promising grasses available for ruminant production because of its high yield and high nutritional value (Cherdthong et al. 2015). However, forage is abundant during the rainy season, which grows well and there is more than enough for a cattle. While, in dry season is scarce. Preserving forage yield during the rainy season should be made in form silage. The preservative the nutrients in the silage can be achieved by speeding up the process of fermentation plants earlier than usual by causing anaerobic conditions faster. This can be done by adding the bacteria that can live in anaerobic conditions and has the ability to inhibit and destroy microbes that use oxygen to decrease such as lactic acid bacteria. Therefore, used of starter cultures such as lactic acid bacteria (LAB) can be increase the fermentation process faster. It was expected that inoculants containing LAB would lower pH more quickly and more effectively than naturally occurring epiphytic bacteria, which low pH inhibits the growth of many detrimental microorganisms and helps reduce proteolysis and other plant enzyme activity (Kleinmans et al., 2011). Therefore, the objective of this study were to evaluate effect of lactic acid bacteria supplementation on fermentation quality and chemical composition of Napier Pakchong 1 silage Fermentation Quality and Chemical Composition of Napier Pakchong 1 Silage Supplemented with Lactic Acid Bacteria
Carotenoids present in halotolerantBacillusspore formers

Six isolates of pigmented spore-forming bacteria were recovered from human faeces from subjects in Vietnam. 16S rRNA analysis demonstrated close association with known pigmented Bacillus species. All isolates were able to tolerate growth on 8% NaCl and were resistant to arsenate, characteristics that make them most related to Bacillus indicus . Two visible pigments were apparent, a yellow pigment found in vegetative cells and an orange pigment found only in spores. We used high-performance liquid chromatography to characterize and quantify these pigments and found them to be carotenoids. The biosynthetic pathway that generates them branches with one that could lead to the spore-associated orange pigmentation. Although these bacteria were found in faeces, the seafood-rich diet of Vietnam and the recovery of other pigmented Bacillus species from seafood and marine environments makes it highly probable that the true origin of these bacteria is from ingested seafood.
Number : WUCSE-2005-5 2005-0214 A Traveling Salesman ' s Approach to Clustering Gene Expression Data

Given a matrix of values, rearrangement clustering involves rearranging the rows of the matrix and identifying cluster boundaries within the linear ordering of the rows. The TSP+k algorithm for rearrangement clustering was presented in [3] and its implementation is described in this note. Using this code, we solve a 2,467-gene expression data clustering problem and identify “good” clusters that contain close to eight times the number of genes that were clustered by Eisen et al. (1998). Furthermore, we identify 106 functional groups that were overlooked in that paper. We make our implementation available to the general public for applications of gene expression data analysis. Availability: C++ source code is freely available at http://www.climer.us and http://www.cse.wustl.edu/∼zhang/ projects/software.html. Contact: sharlee@climer.us, zhang@cse.wustl.edu. Supplementary information: Algorithm and implementation details can be found at http://www.climer.us/paper08.pdf.
Autonomous Salient Visual Feature Detection Using Salient Points from both RGB and HSV Color Spaces for Visual SLAM in Indoor Environments

For successful SLAM, feature detection becomes an important issue. This paper proposes autonomous detection of salient visual features for visual SLAM in indoor environments. Visual feature candidates are generated by the SIFT keypoints and contour information. Then uniformity maps which measure the level of similarity with the candidates and entropy maps which measure the level of diversity of information are created. Uniformity and entropy maps are combined to make a saliency map which is represented as grayscale values. In the saliency map, it is possible to distinguish the salient visual features from the background. The robot estimates its pose using the detected visual features and builds a grid map of the unknown environment using a laser scanner. The positions of visual features are also represented in the grid map. Experimental results demonstrate that the algorithm proposed in this paper enables a robot to find visual features such as objects or groups of small objects with a stereo camera in unknown environments.
Estimation of the Iberian lynx ( ) population in the Doñana area , SW Spain , using capture-recapture analysis of camera-trapping data German Garrote

The Iberian lynx (Lynx pardinus) has a highly restricted geographic distribution, limited even within the Iberian Peninsula. The last national survey reported less than 200 remaining individuals, distributed in two isolated areas— Andújar-Cardeña and Doñana—and in consequence, the Iberian lynx was listed by the International Union for Conservation of Nature as “Critically Endangered”. In this study, we estimate the Iberian lynx population size in the Doñana area using capture–recapture analysis of cameratrapping data. A model with different capture probability for each individual (Mh) yielded an estimate of 26 Iberian lynxes (SE=5.26) more than 1 year old. It is considered that a small slant in the estimation of the number of individuals could exist due to the presence of dispersers inside the study area that were not detected. Our study shows: (1) a reduction in number since the 1980s (45 individuals), and falling below the theoretical threshold of genetic viability, (2) changes in the species’ spatial distribution in this area, and (3) as for other carnivore species, photographic capture–recapture methods are applicable for estimating the size of Iberian lynx populations
Ontologies and Classification: The Unavoidable Interplay Between Human Reasoning and Machine Reasoning

Artificial Intelligence (AI) is currently a vigorous subject widely studied and publicized. In recent times, we have seen notable AI advances that lead scientists to put the question if there is classification after arrival of the search engines. The question impacts Library and Information Science (LIS) insofar as in the data environments, there are no shelves, no physical constraints that demand the organization for which classification schemes were created. Indeed, some have defended that no prior scheme can say in advance what a user needs. This advances are made possible by AI algorithms that allow automatic reasoning. In this session, discuss to what extent automatic reasoning can replace human reasoning in classification. First, we introduce some essentials of both human reasoning and of AI. Then, we describe the operation and the reasoning produced by AI approaches – ontologies and machine learning – in addition to compare them with human classifying activity.
Mothers as Consumers of Childcare Centres Living up to the image of the ideal mother

This thesis examines how mothers, in their evaluation of different types of childcare centres, deal with the image of the ideal mother – paying special attention to the symbolic meanings they attach to the different childcare centres in their consideration set. The research examines how women’s mother groups influence their preferences for certain childcare options, the connection between mothers’ actual and ideal identity, the influence of word of mouth and its impact on their behaviour in relation to the decision-making when choosing childcare. The theoretical framework for the thesis is based within sociological theories, more specifically the phenomenon of symbolic interactionism. Literature related to reference groups, symbolic consumption, identity construction and motherhood are seen in relation to the empirical findings. Erwin Goffman’s dramaturgical approach and his essay on face work inspire the analysis providing insight into the interaction in different mother groups and an understanding of how it influences both the mothers’ idea of an ideal mother and their preferences for certain childcare centres. The study is based on 3 focus group interviews with already established mother groups in Elsinore. With a qualitative approach the study gives insight into some mothers reflection in their choice of childcare and the role of their mother group in their decision-making process. The analysis shows that not only the final choice, but also the way they approach the information search carries symbolic meaning. Some symbolic meanings are shared and culturally constituted, whereas others reside purely within the mothers’ social environment, in particularly her mother group. The study also explores how experience from other mothers makes individuals doubt or reassure themselves in their choice and how statements in relation to childcare are constructed to correspond to fit into the mothers’ definition of an ideal mother. The purpose of this thesis is to support the municipality of Elsinore as providers of childcare centres in their competition with the private market. Providing them with an understanding of mothers’ reflections in relation to their choice of childcare and how this understanding can be used to develop and promote childcare centres, so they do not just fit the mothers’ actual identity, but become a service that the mothers would recommend as part of their ideal mother identity.
Multimegapoint FFT's running on workstation computers

The authors show that the data addressing required for an in-place fast Fourier transform (FFT) whose memory requirement significantly exceeds the physical memory size of a machine causes an unacceptable level of virtual memory disk access, commonly known as thrashing. In addition, a matrix-decomposition FFT is shown to replace the reordering of the large data set with matrix transpositions, using a two pass memory-efficient matrix transposition technique. The matrix FFT, combined with a file oriented matrix transpose, is shown to be an easy way to prevent thrashing. This method was applied to perform simulations of a 2/sup 23/ (8,388,608) point real-only FFT processor which will be used in NASA's Search for Extraterrestrial Intelligence program. <<ETX>>
Title : Investigation of the Leak Response of a Carbon-Fiber Laminate Loaded in Biaxial Tension for Proceedings of the American Society for Composites — Twenty-Eighth Technical Conference

Designers of pressurized structures have been reluctant to use composite materials because of concerns over leakage. Biaxial stress states are expected to be the worst-case loading condition for allowing leakage to occur through microcracks. To investigate the leakage behavior under in-plane biaxial loading, a cruciform composite specimen was designed that would have a relatively large test section with a uniform 1:1 biaxial loading ratio. A 7.6-cm-square test section was desired for future investigations of the leakage response as a result of impact damage. Many iterations of the cruciform specimen were evaluated using finite element analysis to reduce stress concentrations and maximize the size of the uniform biaxial strain field. The final design allowed the specimen to go to relatively high biaxial strain levels without incurring damage away from the test section. The specimen was designed and manufactured using carbon/epoxy fabric with a four-plythick, quasi-isotropic, central test section. Initial validation and testing were performed on a specimen without impact damage. The specimen was tested to maximum biaxial strains of approximately 4500με without apparent damage. A leak measurement system containing a pressurized cavity was clamped to the test section and used to measure the flow rate through the specimen. The leakage behavior of the specimen was investigated for pressure differences up to 172 kPa.
The Influence of Value Orientations on Service Quality Perceptions in a MonoCultural Context : An Empirical Study of Malay University Students

Service quality and culture studies have traditionally used polar opposite cultures to make their case. This paper argues that these cultural extremes conceal significant variations in culture and has implications for service design, delivery and quality. The study explores the existence of value variations within ostensibly homogenous groups. It is posited that the knowledge of these spectrum of value orientations will enhance the service marketers' ability to 'situate' services as they enter new markets or introduce service innovations. A study conducted among 712 Malay university students produced 2 significantly different value clusters. Variance analysis showed that these clusters labeled as True Traditionalist and Transitory Traditionalist have significantly different impact on service quality dimensions. The findings support the argument that service quality and culture studies must examine between as well as within culture variations.
Understanding Poverty in America

Overall, the typical American defined as poor by the government has a car, air conditioning, a refrigerator, a stove, a clothes washer and dryer, and a microwave. He has two color televisions, cable or satellite TV reception, a VCR or DVD player, and a stereo. He is able to obtain medical care. His home is in good repair and is not overcrowded. By his own report, his family is not hungry, and he had sufficient funds in the past year to meet his family’s essential needs. While this individual’s life is not opulent, it is equally far from the popular images of dire poverty conveyed by the press, liberal activists, and politicians.
Automatic Distinction between Natural and Automatically Generated Texts Using Morphological and Syntactic Information

Our work lies in the field of automatic metrics for assessing text quality. However, the task we had to solve is different from the usual tasks of this domain. The traditional and most common formulation of the task is to distinguish well-written texts from poorly written ones, in which case it is presupposed that any text to be assessed is written by a human. Normally, the type of the text is also known: a scientific publication, news, etc. We set a more general task: to distinguish normal texts written by man, on one hand, from automatically generated texts or automatically processed and intentionally damaged natural texts, on the other hand. An additional difficulty is that "normal" texts in our collection contain lists, fragments of tables, and examples of bad texts with mistakes. We started by parsing our data with our syntactic parser for Russian, after which we trained an algorithm using words with extracted morphological and syntactic information. Our best results show 78.1% recall, 94.6% precision and 85.5% f-measure.
Parallel Sentence Extraction Based on Unsupervised Bilingual Lexicon Extraction from Comparable Corpora

Parallel corpora are crucial for statistical machine translation (SMT); however, they are quite scarce for most language pairs and domains. As comparable corpora are far more available, many studies have been conducted to extract parallel sentences from them for SMT. Parallel sentence extraction relies highly on bilingual lexicons that are also very scarce. We propose an unsupervised bilingual lexicon extraction based parallel sentence extraction system that first extracts bilingual lexicons from comparable corpora and then extracts parallel sentences using the lexicons. Our bilingual lexicon extraction method is based on a combination of topic model and context based methods in an iterative process. The proposed method does not rely on any prior knowledge, and the performance can be improved iteratively. The parallel sentence extraction method uses a binary classifier for parallel sentence identification. The extracted bilingual lexicons are used for the classifier to improve the performance of parallel sentence extraction. Experiments conducted with the Wikipedia data indicate that the proposed bilingual lexicon extraction method greatly outperforms existing methods, and the extracted bilingual lexicons significantly improve the performance of parallel sentence extraction for SMT.
Hybrid verification method based on finger-knuckle analysis and keystroke dynamics

The increasing number of personal data leaks becomes one of the most important security issues hence the need to develop modern computer user verification methods. In the article, a potential of biometric methods fusion for continuous user verification was assessed. A hybrid approach for user verification based on fusion of keystroke dynamics and knuckle images analysis was presented. Verification is performed by a classification module where an ensemble classifier was used to verify the identity of a user. A proposed classifier works on a database which comprises of knuckle images and keyboard events for keystroke dynamics. The proposed approach was tested experimentally. The obtained results confirm that the proposed hybrid approach performs better than methods based on single biometric feature hence the introduced method can be used for increasing a protection level of computer resources against forgers and impostors. The paper presents results of preliminary research conducted to assess the potential of biometric methods fusion.
Improved vein pattern extracting algorithm and its implementation

This paper proposes an improved vein pattern extracting algorithm which compensates the loss of vein patterns in the edge area, gives more enhanced and stabilized vein pattern information, and shows better performance than the existing algorithm. Also, the problem arising from the iterative nature of the filtering preprocess in the existing algorithm is solved by designing a filter that is processed only one time so that a fast recognition speed and reduced hardware complexity is obtained. The proposed algorithm is implemented with a FPGA (field programmable gate array) device and the FAR (false acceptance rate) shows five times batter than the existing algorithm and the recognition speed is measured to be 100 [ms/person].
A Robust Online Learning Method for Object Tracking

In this paper, we present an robust object tracking method to deal with constantly appearance changing and partial occlusion. Our method is based on particle filtering framework which allow us to handle partial occlusion over a few frames as well as few false predictions caused by rapid appearance changing. An online multiple instance learning algorithm is embedded in the particle filtering framework to adaptively learn the changing appearance model of the object and background. Weighted sampling method and synthesized extension are introduced in the learning process to make the training model robust and avoid over-fitting. Experimental results prove that the proposed method outperforms the other state-of-the-art tracking via online boosting algorithms.