Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of quantum nuclear delocalisation on NMR parameters from path integral molecular dynamics.

The influence of nuclear delocalisation on NMR chemical shifts in molecular organic solids is explored using path integral molecular dynamics (PIMD) and density functional theory calculations of shielding tensors. Nuclear quantum effects are shown to explain previously observed systematic deviations in correlations between calculated and experimental chemical shifts, with particularly large PIMD-induced changes (up to 23 ppm) observed for carbon atoms in methyl groups. The PIMD approach also enables isotope substitution effects on chemical shifts and J couplings to be predicted in excellent agreement with experiment for both isolated molecules and molecular crystals. An approach based on convoluting calculated shielding or coupling surfaces with probability distributions of selected bond distances and valence angles obtained from PIMD simulations is used to calculate isotope effects.
Protein phosphatase 2A promotes the transition to G0 during terminal differentiation in Drosophila

Protein phosphatase type 2A complex (PP2A) has been known as a tumor suppressor for over two decades, but it remains unclear exactly how it suppresses tumor growth. Here, we provide data indicating a novel role for PP2A in promoting the transition to quiescence upon terminal differentiation in vivo. Using Drosophila eyes and wings as a model, we find that compromising PP2A activity during the final cell cycle prior to a developmentally controlled cell cycle exit leads to extra cell divisions and delays entry into quiescence. By systematically testing the regulatory subunits of Drosophila PP2A, we find that the B56 family member widerborst (wdb) is required for the role of PP2A in promoting the transition to quiescence. Cells in differentiating tissues with compromised PP2A retain high Cdk2 activity when they should be quiescent, and genetic epistasis tests demonstrate that ectopic Cyclin E/Cdk2 activity is responsible for the extra cell cycles caused by PP2A inhibition. The loss of wdb/PP2A function cooperates with aberrantly high Cyclin E protein levels, allowing cells to bypass a robust G0 late in development. This provides an example of how loss of PP2A can cooperate with oncogenic mutations in cancer. We propose that the PP2A complex plays a novel role in differentiating tissues to promote developmentally controlled quiescence through the regulation of Cyclin E/Cdk2 activity. Summary: Protein phosphatase 2A controls cell cycle progression in the developing Drosophila eye and wing - inhibiting Cdk2/Cyclin E to induce the quiescent state.
IT Infrastructure: Structure, Properties and Processes

Studies related to IT infrastructure emphasize its changing and differing roles, functions and forms. This study reviews the literature related to IT infrastructure and combines its different elements into one holistic model. The model is further elaborated by using the concepts of structure, properties and processes. The model will help academics to find essential information about IT infrastructure and help practitioners to understand its importance and the possibilities related to leveraging it. After detailed analysis of the model, the study suggests that though topical literature presents a widely held common understanding of the elements existing within IT infrastructure, more research is needed to develop and unify definitions of old and new concepts related to the properties and processes of IT
Bio-Authentication based Secure Transmission System using Steganography

Biometrics deals with identity verification of an individual by using certain physiological or behavioral features associated with a person. Biometric identification systems using fingerprints patterns are called AFIS (Automatic Fingerprint Identification System). In this paper a composite method for Fingerprint recognition is considered using a combination of Fast Fourier Transform (FFT) and Sobel Filters for improvement of a poor quality fingerprint image. Steganography hides messages inside other messages in such a way that an "adversary" would not even know a secret message were present. The objective of our paper is to make a bio-secure system. In this paper bio-authentication has been implemented in terms of finger print recognition and the second part of the paper is an interactive steganographic system hides the user's data by two options- creating a songs list or hiding the data in an image.
Recursive Exponential Weighting for Online Non-convex Optimization

In this paper, we investigate the online non-convex optimization problem which generalizes the classic {online convex optimization problem by relaxing the convexity assumption on the cost function. For this type of problem, the classic exponential weighting online algorithm has recently been shown to attain a sub-linear regret of $O(\sqrt{T\log T})$. In this paper, we introduce a novel recursive structure to the online algorithm to define a recursive exponential weighting algorithm that attains a regret of $O(\sqrt{T})$, matching the well-known regret lower bound. To the best of our knowledge, this is the first online algorithm with provable $O(\sqrt{T})$ regret for the online non-convex optimization problem.
Incremental sentence compression using LSTM recurrent networks

Many of the current sentence compression techniques attempt to produce a shortened form of a sentence by relying on syntactic structure such as dependency tree representations. While the performance of sentence compression has been improving, these approaches require a full parse of the sentence before performing sentence compression, making it difficult to perform compression in real time. In this paper, we examine the possibilities of performing incremental sentence compression using long short-term memory (LSTM) recurrent neural networks (RNN). The decision of whether to remove a word is done at each time step, without waiting for the end of the sentence. Various RNN parameters are investigated, including the number of layers and network connections. Furthermore, we also propose using a pretraining method in which the network is pretrained as an autoencoder. Experimental results reveal that our method obtains compression rates similar to human references and a better accuracy than the state-of-the-art tree transduction models.
Do Antifibrinolytics Reduce Allogeneic Blood Transfusion in Orthopedic Surgery?

Studies have shown that antifibrinolytic (aprotinin, tranexamic acid, or ϵ-aminocaproic acid) reduce blood loss in orthopedic surgery. However, most lacked sufficient power to evaluate the efficacy and safety on clinical outcomes. This meta-analysis aims to evaluate whether intravenous antifibrinolytics, when compared with placebo, reduce perioperative allogeneic erythrocyte transfusion requirement in adults undergoing orthopedic surgery and whether it might increase the risk of venous thromboembolism. From MEDLINE, EMBASE, and the Cochrane Controlled Trials Register, the authors identified 43 randomized controlled trials in total hip and knee arthroplasty, spine fusion, musculoskeletal sepsis, or tumor surgery performed to July 2005 (for aprotinin, 23 trials with 1,268 participants; tranexamic acid, 20 with 1,084; ϵ-aminocaproic acid, 4 with 171). Aprotinin and tranexamic acid reduced significantly the proportion of patients requiring allogeneic erythrocyte transfusion according to a transfusion protocol. The odds ratio was 0.43 (95% confidence interval, 0.28–0.64) for aprotinin and 0.17 (0.11–0.24) for tranexamic acid. Results suggest a dose–effect relation with tranexamic acid. ϵ-Aminocaproic acid was not efficacious. Unfortunately, data were too limited for any conclusions regarding safety. Although the results suggest that aprotinin and tranexamic acid significantly reduce allogeneic erythrocyte transfusion, further evaluation of safety is required before recommending the use of antifibrinolytics in orthopedic surgery.
Automatic document summarizer

The need for automatic summarization becomes crucial with the exponential increase of data available on www and digital libraries, which makes the search for relevant pieces of information a difficult task. Therefore, needless to say, an automatic summarizer would save a lot to user and operators. However, the development of such systems is also shown to be very challenging due to inherent difficulty in dealing with natural language processing, the subjectivity of the evaluation process and the limitation of the mathematical models. This paper puts forward a proposal for an automatic summarizer system, which explicitly makes use of the semantic relatedness of document sentences using WordNet taxonomy.On the other hand, several other attributes are taken into account in the design stage, which include similarity to user's query, if any, which allows us to integrate some personalization to the outcome, similarity to the document title, location and frequency of co-occurrence. The developed summarizer also enables some search abilities, where three distinct search platforms were integrated (Lucene, GTP and Xapian). The obtained results were compared to MEAD summarizer.
TEXT MINING APPLICATIONS

Representation of semantic information contained in the words is needed for any Arabic Text Mining applications. More precisely, the purpose is to better take into account the semantic dependencies between words expressed by the co-occurrence frequencies of these words. There have been many proposals to compute similarities between words based on their distributions in contexts. In this paper, we compare and contrast the effect of two preprocessing techniques applied to Arabic corpus: Rootbased (Stemming), and Stem-based (Light Stemming) approaches for measuring the similarity between Arabic words with the well known abstractive model -Latent Semantic Analysis (LSA)with a wide variety of distance functions and similarity measures, such as the Euclidean Distance, Cosine Similarity, Jaccard Coefficient, and the Pearson Correlation Coefficient. The obtained results show that, on the one hand, the variety of the corpus produces more accurate results; on the other hand, the Stem-based approach outperformed the Root-based one because this latter affects the words meanings.
Review on materials, microsensors, systems and devices for high-temperature and harsh-environment applications

The considerable investment in silicon technology has rarely addressed device use in harsh environments such as high temperatures, aggressive media, and radiation exposure. A clear future requirement is to save weight, volume, and reduce costs in "unfriendly" environments like high temperatures. This can be achieved either by cooling systems or by electronic microsystem components suited to withstand high temperatures. The current status of cooling systems, harsh-environment sensors, and microsystems in view of markets, realized devices, material, properties, process maturity, and packaging technologies are reviewed. Possible semiconductor candidates for high-temperature applications are discussed. The main obstacles for the future of high-temperature and harsh-environment microsystems is highlighted.
Human Computer Interface Through Biometric Iris Recognition System

Biometric recognition system is better reliable, roubst technique than traditional recognition system. Biometric iris recognition system is most secure and reliable than other biometric recognition system. Hence, we use biometric iris recognition system is used to identify the human. In this paper, the proposed new segmentation methods described as: k-means algorithm, edge detection algorithm, hough circle algorithm, upper eyelid and lower eyelid localization, isolate speculare reflections and remove pupil regions. This proposed algorithm has found the recognition rate is 98.76% in minimum time. Keywords- Biometrics, upper eyelid localization, lower eyelid localization, pupil region, segmentation.
Seasonal variation of mortality, detectability, and body condition in a population of the adder (Vipera berus)

Abstract We analyzed seasonal variation in mortality rates in adult males and females of the European adder (Vipera berus), using data collected during a 13‐year capture–recapture study (2005–2017) in a large population. We concurrently obtained quantitative information on the seasonal variation in the detectability and body condition of adders. Our results show strong seasonality in body condition, encounter, and capture rates of adult adders, and these patterns differ markedly between sexes and between breeding and nonbreeding females. Seasonal variation in mortality rates was however virtually nonexistent in males and moderately low in both breeding and nonbreeding females. In addition, we found no evidence for among‐year differences in the seasonal mortality schedules of males and females. During periods of intensive basking, both males and pregnant females are highly visible for humans, but are not subject to strong natural mortality. This low susceptibility to predation is presumably induced by various factors, including the limitation of overt exposure to short periods of time and specific microhabitats, the dorsal coloration pattern that provides cryptic protection and possibly also an aposematic warning signal, and presumed seasonal differences in the foraging behavior and food requirements of natural predators. Our data provide some evidence that female adders, but not males, are relatively vulnerable to predation during the seasonal migrations between the hibernation and feeding habitats. Mortality in the females was not much elevated during their breeding years, but was notably highest in the spring of the ensuing nonbreeding year. After giving birth, reproductive females are extremely emaciated and have a weakened general condition. They then run the risk of dying from starvation either before, during, or after hibernation. The higher mortality after giving birth, that is sustained over a period of ca. 9 months, should be considered as an indirect and delayed survival cost of reproduction.
A study of a superconducting magnetic levitation system for an absolute determination of the magnetic flux quantum

A study of the equilibrium positions of a superconducting magnetic lévitation system which substitutes an electromagnetic energy for a mechanical energy is in progress for the absolute determination of the magnetic flux quantum Φ0. The study on a preliminary system at ppm-level resolution has been done and the reproducibility of the trajectory turned out to be of the order of 10 ppm. The problems of the present system and ideas for the next system at the sub-ppm level are discussed.
Matching human actors based on their texts: design and evaluation of an instance of the ExpertFinding framework

Bringing together human actors with similar interests, skills or expertise is a major challenge in community-based knowledge management. We believe that writing or reading textual documents can be an indicator for a human actor's interests, skills or expertise. In this paper, we describe an approach of matching human actors based on the similarity of text collections that can be attributed to them. By integrating standard methods of text analysis, we extract and match user profiles based on a large collection of documents. We present an instance of the ExpertFinder Framework which measures the similarity of these profiles by means of the Latent Semantic Indexing (LSI) algorithm. The quality of the algorithmic approach was evaluated by comparing its results with judgments of different human actors.
Intrusion Detection using C4.5: Performance Enhancement by Classifier Combination

Data Security has become a very critical part of any organizational information system. Intrusion Detection System (IDS) is used as a security measure to preserve data integrity and system availability from various attacks. This paper evaluates the performance of C4.5 classifier and its combination using bagging, boosting and stacking over NSL- KDD dataset for IDS. This dataset set consists of selected records of the complete KDD dataset.
LIVE SPEAKER IDENTIFICATION IN MEETINGS – “ WHO IS SPEAKING NOW ? ”

The following paper presents an application that fuses the currently artificially separated tasks of speaker identification and speaker diarization. The presented method allows online identification of who is currently speaking using a single far-field microphone in a meeting scenario. It is able to recognize the current speaker after any two seconds of speech. An evaluation of the robustness of the algorithm using the AMI Meeting Corpus resulted in a Diarization Error Rate of 12.67 %.
Pitch determination using autocorrelation function in spectral domain

This paper proposes a pitch determination method utilizing the autocorrelation function in the spectral domain. The autocorrelation function is a popular measurement in estimating pitch in time domain. The performance of the method, however, is effected due to the position of dominant harmonics (usually the ﬁrst formant) and the presence of spurious peaks introduced in noisy conditions. We applied a series of operations to obtain a noise-compensated and ﬂattened version of the amplitude spectrum which takes a shape of harmonics train. Application of the autocorrelation function on this preconditioned spectrum produces a sequence where the true pitch peak can be readily located. Experiments on long speech signals spoken by a number of male and female speakers have been conducted. Experimental results demonstrate the merit of the proposed method when compared with other popular methods
Audio-Based Cover Song Retrieval Using Approximate Chord Sequences: Testing Shifts, Gaps, Swaps and Beats

This paper presents a variation on the theme of using string alignment for MIR in the context of cover song identification in audio collections. Here, the strings are derived from audio by means of HMM-based chord estimation. The characteristics of the cover-song ID problem and the nature of common chord estimation errors are carefully considered. As a result strategies are proposed and systematically evaluated for key shifting, the cost of gap insertions and character swaps in string alignment, and the use of a beat-synchronous feature set. Results support the view that string alignment, as a mechanism for audiobased retrieval, cannot be oblivious to the problems of robustly estimating musically-meaningful data from audio.
The relationship between oral health and COPD exacerbations

Introduction: Poor oral health has been implicated as an independent risk factor for the development of COPD, but few studies have evaluated the association between oral health and COPD exacerbations. We aimed to determine if poor oral health is associated with COPD exacerbations and/or worse respiratory health. Methods: We performed a case-control study of oral health among COPD exacerbators and non-exacerbators. Cases (exacerbators) had experienced ≥1 exacerbation in the previous 12 months, while controls (non-exacerbators) had no exacerbations in the previous 24 months. We excluded those with <4 teeth. We evaluated the global oral health assessment, Oral Health Impact Profile (OHIP-5), dental symptoms/habits, and St. George’s Respiratory Questionnaire (SGRQ). In a subset, we performed blinded dental exams to measure bleeding on probing, probing depth, clinical attachment loss, periodontitis severity, plaque index, gingival index, and carries risk. We evaluated associations between oral health and COPD exacerbations using logistic regression. Linear regression was used to assess relationships between oral health and SGRQ scores. Results: Screened non-exacerbators (n=118) were significantly more likely to have <4 teeth, compared to screened exacerbators (n=100) (44% vs 30%, respectively; p=0.046). After excluding those with <4 teeth, there were 70 cases and 66 controls. Self-reported oral health and objective dental exam measures did not vary significantly between cases vs controls. However, the odds of severe COPD exacerbations requiring hospitalizations and/or emergency department visits trended higher in those with worse dental exam compared to those with better dental exam. Worse OHIP-5 was strongly associated with worse SGRQ scores. Conclusions: Oral health status was not related to COPD exacerbations, but was associated with self-reported respiratory health. Non-exacerbators were more likely to be edentate or have ≤4 teeth compared to exacerbators. Larger studies are needed to address oral health as a potential method to improve respiratory health in patients with COPD.
A NOVEL APPROACH AND SOFTWARE COMPONENT FOR SUPPORTING COMPETENCE-BASED LEARNING WITH SERIOUS GAMES

Digital educational games constitute a major opportunity for acquiring knowledge and competences in a different way than traditional classroom-and technology-based methods. This paper presents a novel approach for a game component that structures the game play in an adaptive way. This approach consists of a combination of three learning theories and techniques. First, Competence-based Knowledge Space Theory is used structure a knowledge domain into competences and game situations. Second, the Leitner system of flashcards is used to establish structured and timed repetition of competences to be acquired. Third, the Ebbinghaus forgetting curve is taken into account to model forgetting learned competences. This approach has been implemented as a game component in line with the games component architecture of the RAGE project. The design and development of this component followed the requirements of the French games company Kiupe that includes it in its environment of games and mini-games.
Computational Statistics and Data Analysis Gaussian Quadrature Approximations in Mixed Hidden Markov Models for Longitudinal Data: a Simulation Study

Keywords: Hidden Markov models Time-constant and time-varying random parameters Adaptive Gaussian quadrature Exponential family a b s t r a c t Mixed hidden Markov models represent an interesting tool for the analysis of longitudinal data. They allow to account for both time-constant and time-varying sources of unobserved heterogeneity, which are frequent in this kind of studies. Individual-specific latent features, which may be either constant or varying over time, are included in the linear predictor and lead to a general form of dependence between individual measurements. When a parametric (continuous) distribution is associated to time-constant random parameters, the estimation process requires the calculation of (multiple) integrals. These, generally, have not a closed form and should be numerically approximated. The aim is to compare the standard, the adaptive and the pseudo-adaptive Gaussian quadrature approximations by means of a large scale simulation study, where continuous and discrete responses with (conditional) density in the exponential family are considered. Simulation results show that the approximation error is often substantially reduced when the adaptive quadrature rules are considered in place of the standard one. Such an improvement comes at the cost of a higher computational complexity when the fully adaptive scheme is applied. It is shown that, when a sufficient number of repeated measurements per unit is available, the pseudo-adaptive quadrature represents a convenient compromise between quality of results and computational complexity.