Miracle-dz/UniFAR-FTUs huggingface dataset:
Multilingual speech to speech MT based chat system

This paper presents a chat application that make use of speech as interaction mode between users in their mother tongue. This system is based on Machine Translation (MT) which automatically translates a sentence from one language to other. Now-a-days, Chat has become increasingly important as an effective means to communicate in social networks. But in existing personal chat systems, chat services are text-based only. To circumvent this issue, innovative, practical XMPP-based chat system architecture is proposed in this paper that creates a Speech based chat services by integrating state-of-the-art technologies like Automatic Speech Recognition (ASR), Text to Speech (TTS) and Machine Translation (MT). The proposed system eliminates the need to have a common language for chat communication. In this chat system the user speak in their own language after selecting the language of their comfort. The audio will be recognized in real time. The text is translated to the language opted by end user and the system synthesizes it. Here, we discuss an interface prototype that can overcome the language barrier to some extent.
Nonvirally Modified Autologous Primary Hepatocytes Correct Diabetes and Prevent Target Organ Injury in a Large Preclinical Model

Background Current gene- and cell-based therapies have significant limitations which impede widespread clinical application. Taking diabetes mellitus as a paradigm, we have sought to overcome these limitations by ex vivo electrotransfer of a nonviral insulin expression vector into primary hepatocytes followed by immediate autologous reimplantation in a preclinical model of diabetes. Methods and Results In a single 3-hour procedure, hepatocytes were isolated from a surgically resected liver wedge, electroporated with an insulin expression plasmid ex vivo and reimplanted intraparenchymally under ultrasonic guidance into the liver in each of 10 streptozotocin-induced diabetic Yorkshire pigs. The vector was comprised of a bifunctional, glucose-responsive promoter linked to human insulin cDNA. Ambient glucose concentrations appropriately altered human insulin mRNA expression and C-peptide secretion within minutes in vitro and in vivo. Treated swine showed correction of hyperglycemia, glucose intolerance, dyslipidemia and other metabolic abnormalities for ≥47 weeks. Metabolic correction correlated significantly with the number of hepatocytes implanted. Importantly, we observed no hypoglycemia even under fasting conditions. Direct intrahepatic implantation of hepatocytes did not alter biochemical indices of liver function or induce abnormal hepatic lobular architecture. About 70% of implanted hepatocytes functionally engrafted, appeared histologically normal, retained vector DNA and expressed human insulin for ≥47 weeks. Based on structural tissue analyses and transcriptome data, we showed that early correction of diabetes attenuated and even prevented pathological changes in the eye, kidney, liver and aorta. Conclusions We demonstrate that autologous hepatocytes can be efficiently, simply and safely modified by electroporation of a nonviral vector to express, process and secrete insulin durably. This strategy, which achieved significant and sustained therapeutic efficacy in a large preclinical model without adverse effects, warrants consideration for clinical development especially as it could have broader future applications for the treatment of other acquired and inherited diseases for which systemic reconstitution of a specific protein deficiency is critical.
Learning User Behaviors for Advertisements Click Prediction

Predicting potential advertisement clicks of users are important for advertisement recommendation, advertisement placement, presentation pricing, and so on. In this paper, several machine learning algorithms including conditional random fields (CRF), support vector machines (SVM), decision tree (DT) and back-propagation neural networks (BPN) are developed to learn user’s click behaviors from advertisement search and click logs. In addition, four levels of features are extracted to represent user search and click intents. Given a user’s search session and a query, machine learning algorithms along with different features are proposed to predict if the user will click advertisements displayed for the query. We further study the impact of feature selection algorithms on the prediction models. Random subspace (RS), F-score (FS) and information gain (IG) are employed to search for a predictive subset of features. The experiments show that CRF model with the random subspace feature selection algorithm achieves the best performance.
BIOCHEMICAL AND CELL BIOLOGICAL STUDIES OF TRIM 37 DEFECTIVE IN MULIBREY NANISM

This thesis is based on the following original publications, which are referred to in the text by their Roman numerals I-IV. In addition, some unpublished data are presented. gene encodes a peroxisomal RING-B-Box-Coiled-Coil protein: Classification of Mulibrey nanism as a new peroxisomal disorder. (2005) TRIM37 defective in mulibrey nanism is a novel RING finger ubiquitin E3 ligase. Exp
The impact of national and parent company origin on world‐class manufacturing: Findings from Britain and Germany

Presents the results of a study examining differences in world‐class manufacturing practices and performance between the UK and Germany, based on a sample of more than 500 German and British manufacturing plants. Suggests that although German superiority persists in many areas, it may not be as great as generally assumed. While at the overall level, country‐of‐origin effects are important, many of the plant sites sampled were part of multinational organizations. Also examines how much of the difference in manufacturing practices and performance at the site level might be attributed to foreign direct investment in manufacturing. Concludes that parent origin does have a significant effect at the site level.
A Multivariate Map-Comparison Method for Spatial Evaluation of Model Experiments and Model-Data Comparison — A Synthesis Tool for CMIP-6 Illustrated Using Results from SeaRISE

Numerical simulations resultant from the Ice Sheet Model Intercomparison Project (ISMIP6), the Sea-Ice Model Intercomparison Project (SIMIP) and other components of the Coupled Model Intercomparison Project 6 (CMIP6) will produce many different spatial variables, from a number of models, a number of experiments and for several scenarios. The typical approaches for analysis of multi-variate multi-model spatial experiment results, or maps, used to date are difference maps or 5 visual comparison based on a pair of the resultant maps or alternatively plots of a summarizing parameter (one value per map) if several maps are involved in a comparison. Here we introduce a multivariate map-comparison method for model evaluation and spatial model-data comparison, that is specifically designed to match the goals and geographic regions of ISMIP6 and SIMIP. The method employs an algebraic semi-norm defined in a space of any finite order over a spatial domain. The map comparison tool MAPCOMP facilitates spatial analysis of results from multi-variate multi-model experiments for any number 10
Stereotypical Science: Exploring High School Occupational Preferences for Science by Sex, Personality, and Cognitive Ability

Circumscription and Compromise theory suggests self-concept and sex stereotype explain occupational preferences, including preferences for science, technology, engineering and mathematics (STEM). Support exists for sex differences between males and females in both science degrees and science careers. The main thrust of observed sex differences in science lies in the development of occupational interest, as it has been suggested females are encouraged away from science due to stereotypes and social pressure. The present study evaluates high school juniors and seniors (n = 295) to explore their preference for science as indicated by science motivation, attitude, academic experience, and interest. Latent Profile Analysis was used to model profiles of preferences for science with a person-centered approach. Then, the impact of self-concept variables was explored and four profiles of science interest were identified. Sex differences were identified based on science interest, but were not always in favor of males. Covariate analysis indicates vocabulary ability and personality as significantly different for students in the high science interest profile. Implications of these results and future research directions are discussed.
Occurrence rate per bit for any control parameter on the logistic map over integers

We have been investigating behaviors of the logistic map over integers for constructing a pseudorandom number generator with the map. In the presented paper, we will give a 0/1-occurrence rate per bit for values by the logistic map over integers, and discuss suitable bit positions of a bit extraction for getting a pseudorandom bit sequence. First, we will show characteristic behaviors of occurrence rates of values by the map. Second, we will indicate any control parameter are classified into four types which have the distinguished 0/1-occurrence rate patterns. Third, we will show the 0/1-occurrence rate per bit for elements of a sequence generated by the map experimentally. Fourthly, we will introduce a part of the proof for the 0/1-occurrence rate per bit in the low-order bits. Finally, we will suggest suitable bit positions to be extracted for generating a pseudorandom bit sequence.
Context modeling and discovery using vector space bases

In this paper, context is modeled by vector space bases and its evolution is modeled by linear transformations from one base to another. Each document or query can be associated to a distinct base, which corresponds to one context. Also, algorithms are proposed to discover contexts from document, query or groups or them. Linear algebra can thus by employed in a mathematical framework to process context, its evolution and application.
Real-time background music monitoring based on content-based retrieval

In this paper, we describe music monitoring in TV broadcasting based on content-based retrieval. A part of audio signals is sequentially extracted from TV broadcasting as a retrieval key, and a music DB that stores a great number of musical pieces is retrieved by this key based on content-based retrieval, and a musical piece is identified sequentially. In this way, we are able to carry out music monitoring. There are three necessary requirements important for realization of the music monitoring. They are robustness against non-stationary noise, real-time processing of large-scale music DB retrieval, and high granularity of the retrieval key. As a method of realizing robustness against non-stationary noise, we propose a partially similar retrieval method which improves retrieval accuracy by using the moment in which no superfluous noise is produced during the existence of non-stationary noise. In order to realize real-time processing of large-scale music DB retrieval, we adopt a coarse-to-fine strategy, and propose a spectral peaks hashing method which performs high-speed refining by using hashing. To calculate a hash value in this hashing, frequency channel numbers of the spectral peaks are used. In order to realize high granularity of the retrieval key, it is necessary to solve the problem of retrieval accuracy degradation associated with heightening the granularity. To improve this accuracy, we propose a detection-by-continuity method which uses music continuity. Moreover, by using music continuity to correct the starting point and the terminal point of a musical piece in TV broadcasting, the retrieval accuracy is improved further. In order to evaluate the effectiveness of the proposed methods, we performed experiments using a music DB which stores over 28,000 musical pieces (over 1800 hours) and TV broadcasting audio signals containing music and background music (BGM). The granularity of the retrieval key was set at about 0.5 seconds. Through these experiments, We verified that music monitoring was possible for over 90% of the total time of music and BGM used in TV broadcasting, and that real-time processing was possible.
Fast Track Confirmation for Multi-Target Tracking with Doppler Measurements

In this paper, a one-point track initiation method is derived for conventional target tracking systems where noisy sensor measurements of both target position and Doppler are available. Tentative tracks are initiated using position measurements from every single scan and the associated Doppler measurements are incorporated to reduce the velocity uncertainties of these initiated track states. The proposed track initiation method is capable of reducing the computational requirements of the system quadratically compared to the classical two-point method when false measurements are present. We further demonstrate that a tracking system which incorporates Doppler measurements both for track initiation and measurement-to-track association can greatly reduce the number of false tracks that are generated and provides greater flexibility for confirming true tracks without sacrificing the system's performance in terms of the number of confirmed false tracks. As a consequence, a tracking system that incorporates the proposed method will exhibit a much shorter true track confirmation delay than a similar system based on the standard approach.
AESTHETICS: Analytics with Strings, Things, and Cats

This paper describes an advanced news analytics and exploration system that allows users to visualize trends of entities like politicians, countries, and organizations in continuously updated news articles. Our system improves state-of-the-art text analytics by linking ambiguous names in news articles to entities in knowledge bases like Freebase, DBpedia or YAGO. This step enables indexing entities and interpreting the contents in terms of entities. This way, the analysis of trends and co-occurrences of entities gains accuracy, and by leveraging the taxonomic type hierarchy of knowledge bases, also in expressiveness and usability. In particular, we can analyze not only individual entities, but also categories of entities and their combinations, including co-occurrences with informative text phrases. Our Web-based system demonstrates the power of this approach by insightful anecdotic analysis of recent events in the news.
Command-based iterative learning control for compensation of servo lag and friction effects

A command-based iterative learning control (ILC) architecture is proposed to compensate for friction effect and to reduce tracking error caused by servo lag. The proposed methodology utilizes the learning algorithm which updates the input commands based on the tracking errors from the previous machining process. It is shown that, for tracking a circle, the quadrant protrusions caused by friction can be reduced substantially by the updated command containing a concave shape located at the crossing of the zero velocity. Finally, analytical simulation and experimental results demonstrate that the command-based ILC algorithm can enhance the tracking performance significantly
Life in lights: Tracking mitochondrial delivery to lysosomes in vivo

ABSTRACT The past decade has seen an intensive and concerted research effort into the molecular regulation of mitophagy, the selective autophagy of mitochondria. Cell-based studies have implicated mitophagy in the pathology of diverse conditions ranging from cancer to neurodegeneration. However, a definitive link between mitophagy and the etiology of human disease remains to be demonstrated. Moreover, we do not know how pervasive mammalian mitophagy is in vivo and fundamental questions remain unanswered. For example, is mitophagy common to all tissues under basal conditions or does it only occur in highly oxidative tissues under stress? This paucity of knowledge is largely due to a lack of experimentally tractable tools that can measure and monitor mitophagy in tissues. Our recent work describes the development of mito-QC, a mouse model to study mitophagy at single cell resolution in vivo.
Reconstruction from 360 x 360 Mosaics 1

We are studying the geometry of a 360 x 360 mosaic image formation. A 360 x 360 mosaic camera model and a calibration procedure are proposed. It is shown that only one point correspondence is needed in order to acquire epipolarily rectified images. The 360 x 360 mosaic camera model is therefore determined by only one intrinsic parameter. It is shown that the relation between coordinates estimated with different values of intrinsic 360 x 360 mosaic camera parameters is a scaling of all scene point coordinates with additional nonlinear changes in the z coordinates of the scene points. Experimental results verifying the reconstruction of real scene points are presented.
Post-deployment Reintegration Measure: Psychometric Replication and Preliminary Validation Results

Abstract : An abrupt return home from a six-month overseas deployment to normal roles and activities can be a significant stressor for military personnel. Our initial scale development study revealed that the post-deployment reintegration experiences of Canadian Forces personnel were best characterized as distinct positive and negative aspects of four theoretical dimensions: personal, family, occupational, and cultural reintegration. In the present study, 474 Canadian Forces personnel coming back from an established peace support operation completed a revised version of our reintegration measure. We present further support for its multidimensionality, and psychometric quality. Moreover, the current research also provides preliminary evidence of validity as the measure is correlated in predicted ways with organizational commitment, coping strategies, symptomatology, and military-related stressors.
Prospective Risk Factors for Intense Grief in Family Members of Veterans Who Died of Terminal Illness

Many bereavement researchers focus on predicting and preventing complicated grief, a psychologically crippling, sometimes life-threatening response to loss that persists for lengthy periods, often with serious health consequences. Reviews of studies have identified specific risk factors (e.g., low social support, insecure attachment style) that predict high levels of complicated grief symptomatology. However, studies rarely investigate multiple risk factors in combination, and still more rarely trace factors observable during the end-of-life period and their predictive power for identifying intense grief in family members following the death. We therefore investigated several pre-loss risk factors for post-loss bereavement distress in 35 family members of Veterans who died of a terminal illness after receiving palliative care. Results revealed that being female, Caucasian, losing a spouse, and experiencing high anticipatory grief prior to the death, all predicted high levels of grief 6 to 10 weeks following the death. Moreover, psychosocial factors such as being highly dependent upon the Veteran, displaying high neuroticism, reporting low levels of social support, and being unable to make sense of the prognosis or death predicted more intense post-loss grief reactions.
On the Diophantine Equation X 2 + C = 2y

In this paper, we study the Diophantine equation x 2 + C = 2y n in positive integers x, y with gcd(x, y) = 1, where n ≥ 3 and C is a positive integer. If C ≡ 1 (mod 4) we give a very sharp bound for prime values of the exponent n; our main tool here is the result on existence of primitive divisors in Lehmer sequence due Bilu, Hanrot and Voutier. When C ≡ 1 (mod 4) we explain how the equation can be solved using the multi-Frey variant of the modular approach. We illustrate our approach by solving completely the equations x 2 + 17 a 1 = 2y n , x 2 + 5 a 1 13 a 2 = 2y n , and x 2 + 3 a 1 11 a 2 = 2y n .
The Impact of the Filter Bubble - A Simulation Based Framework for Measuring Personalisation Macro Effects in Online Communities

The term filter bubble has been coined to describe the situation of online users which---due to filtering algorithms---live in a personalised information universe biased towards their own interests.In this paper we use an agent-based simulation framework to measure the actual risk and impact of filter bubble effects occurring in online communities due to content or author based personalisation algorithms. Observing the strength of filter bubble effects allows for opposing the benefits to the risks of personalisation.In our simulation we observed, that filter bubble effects occur as soon as users indicate preferences towards certain topics.We also saw, that well connected users are affected much stronger than average or poorly connected users. Finally, our experimental setting indicated that the employed personalisation algorithm based on content features seems to bear a lower risk of filter bubble effects than one performing personalisation based on authors.
Competing systems in Philadelphia phonology

Abstract This is a study of the competition of linguistic systems within the speech community, tracing the opposition of distinct phonological configurations. Among younger Philadelphians oriented to higher education, the traditional short-a system is giving way to the nasal system, in which all prenasal vowels are tense. We present evidence that this shift occurs systematically in both the lax and tense allophones. The degree of conformity to each system is measured for 106 subjects by the Pillai statistic; community-wide patterns are revealed by regression modeling and bimodality diagrams. Adherence to the traditional system is greatest for White speakers who graduated from Catholic high schools, while the nasal system is strongest for graduates from elite schools with special admission requirements. African American students show no orientation to the traditional system, but parallel White students in the shift to the nasal system. The histories of students through the educational system show that the speaker's short-a system is largely determined during their middle and high school years, before entering college. Special admission interviews play a special role in this process, as brief speech events that strongly determine the person's linguistic environment for the years that follow.