Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of changes in volume of individual lower-limb muscles using magnetic resonance imaging (during bed-rest)

Muscle size in the lower limb is commonly assessed in neuromuscular research as it correlates with muscle function and some approaches have been assessed for their ability to provide valid estimates of muscle volume. Work to date has not examined the ability of different measurement approaches (such as cross-sectional area (CSA) measures on magnetic resonance (MR) imaging) to accurately track changes in muscle volume as a result of an intervention, such as exercise, injury or disuse. Here we assess whether (a) the percentage change in muscle CSA in 17 lower-limb muscles during 56 days bed-rest, as assessed by five different algorithms, lies within 0.5% of the muscle volume change and (b) the variability of the outcome measure is comparable to that of muscle volume. We find that an approach selecting the MR image with the highest muscle CSA and then a series of CSA measures, the number of which depended upon the muscle considered, immediately distal and proximal, provided an acceptable estimate of the muscle volume change. In the vastii, peroneal, sartorius and anterior tibial muscle groups, accurate results can be attained by increasing the spacing between CSA measures, thus reducing the total number of MR images and hence the measurement time. In the two heads of biceps femoris, semimembranosus and gracilis, it is not possible to reduce the number of CSA measures and the entire muscle volume must be evaluated. Using these approaches one can reduce the number of CSA measures required to estimate changes in muscle volume by ∼60%. These findings help to attain more efficient means to track muscle volume changes in interventional studies.
Influence of dynamic elements in stable tissue phantoms on laser speckle decorrelation times

In this report the decorrelation of a speckle pattern created by the transmission of laser light through a stable tissue phantom with a scattering fluid flowing through a tube inside is discussed. After the introduction, theory is developed and adapted from literature in chapter 2 to describe this process. This is done along three lines. First, in section 2.1, an equation based on one-dimensional diffusion theory to calculate the amount of transmitted light that went through the tube in the sample is derived and discussed. As is shown in section 2.2, with this equation, the normalized autocorrelation function of the speckle pattern can be expressed in terms of the geometrical parameters of the sample and the intermediate scattering function as follows: where is the radius of the tube, is the radius of the illuminated area, is an instrumental factor ranging between 0 and 1 and is the intermediate scattering function. Two existing models are adapted in section 2.3 to find an expression for the intermediate scattering function . One is generally used in Laser Doppler Flowmetry (LDF) and includes both Brownian and translational movement. The other is based on Diffusing Wave Spectroscopy (DWS) and incorporates only Brownian motion. These models, which result in very distinctive autocorrelation functions, are compared and discussed in this same section. As a third and more basic theoretical approach, laminar flow of a fluid in a tube was considered in section 2.4. An equation was derived for the time scale of decorrelation effects caused by translation of the fluid: where is the wavelength of the light used and Q is the discharge. Though this equation gives no predictions about the shape or half times of the autocorrelation function, it gives an upper limit of the time scales on which decorrelation caused by translational motion of the fluid can take place. A final conclusion and discussion of the theoretical chapter 2 is given in section 2.5. Chapter 3 covers the experimental aspects of this research. In section 3.1, the predictions coming from the different models are discussed. Apart from the fact that the shapes of the autocorrelation functions from the LDF and DWS model differ, the time scales also differ a lot: for a 2.2 mm diameter tube, half times are in the range of 10-8 s for the LDF model, and in the range of 10-5 s for the DWS model. Meanwhile, the tube flow considerations give an upper limit to the time scales of decorrelation caused by fluid motion in the range of 10-4 s for the discharges considered in this report (excluding Q = 0). Section 3.2 explains the setup used in the experiments and gives relevant specifications (material parameters, camera specifications etc.). The experimental results are shown and discussed in the following section, 3.3. The experiments were done on two Delrin slabs, one with a 2.2 mm and the
The Transcriptional Landscape of the Mammalian Genome

This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5′ and 3′ boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.
Regulation of Membrane-Associated Mucins in the Human Corneal Epithelial Cells by Dexamethasone

Purpose: To study the influence of dexamethasone on membrane-associated mucins produced by human corneal epithelial cells. Methods: Human corneal epithelial cells were cultured in medium supplemented with various concentrations of dexamethasone (ranging from 10−8 to 10−6 M). Reverse transcription-polymerase chain reaction (RT-PCR) and Western blot analysis using monoclonal antibodies specific for human MUC1 (HMFG-1), MUC4 (1G8), and MUC16 (OC125) were performed to evaluate the effect of dexamethasone on membrane-associated mucin expression. The effect of glucocorticoid receptor antagonist (RU38486) on dexamethasone-induced mucin expression was estimated. Results: RT-PCR revealed that MUC1 and MUC16 gene expression were upregulated 48 hours after addition of dexamethasone and that MUC4 gene expression was downregulated in the same condition. Western blot analysis showed that MUC1 and MUC16 proteins were increased after addition of dexamethasone. However, MUC4 was not detected by anti-MUC4 monoclonal antibody (1G8) for ASGP-2 under our conditions. Treatment with RU38486 inhibited the changes of MUC1, MUC4, and MUC16 by dexamethasone; thus, the effect of dexamethasone on mucin expression is mediated by glucocorticoid receptors. Conclusions: This study shows that MUC1, MUC4, and MUC16 are regulated differently by dexamethasone in human corneal epithelial cells. External application of dexamethasone might affect the precorneal mucin.
Ultra-summarization (poster abstract): a statistical approach to generating highly condensed non-extractive summaries

Abstract Using current extractive summarization techniques, it is impossible to produce a coherent document summary shorter than a single sentence, or to produce a summary that conforms to particular stylistic constraints. Ideally, one would prefer to understand the document, and to generate an appropriate summary directly from the results of that understanding. Absent a comprehensive natural language understanding system, an approximation must be used. This paper presents an alternative statistical model of a summarization process, which jointly applies statistical models of the term selection and term ordering process to produce brief coherent summaries in a style learned from a training corpus.
Language adaptation and learning: Getting explicit about implicit learning

Linguistic adaptation is a phenomenon where language representations change in response to linguistic input. Adaptation can occur on multiple linguistic levels such as phonology (tuning of phonotactic constraints), words (repetition priming), and syntax (structural priming). The persistent nature of these adaptations suggests that they may be a form of implicit learning and connectionist models have been developed which instantiate this hypothesis. Research on implicit learning, however, has also produced evidence that explicit chunk knowledge is involved in the performance of these tasks. In this review, we examine how these interacting implicit and explicit processes may change our understanding of language learning and processing.
A general optimization procedure for stereotactic small‐beam multi‐isocentric radiotherapy

Clinical experience in single‐dose stereotactic radiotherapy of irregular complex lesions has shown that new developments in optimization procedures were necessary to improve dose distribution, making this conformal technique more efficient. We propose a conformal procedure for stereotactic radiotherapy of complex lesions treated with multiple isocenters based on the associated targets methodology. The successive steps of this conformal procedure are: (a) the determination of the number of subvolumes; (b) the choice of collimator diameters using a dosimetric data basis; (c) the search by the inverse SVD optimizer algorithm for the optimal irradiation space and the minibeam weights for each subvolume using singular value decomposition; (d) the basis of quantitative evaluation criteria for the choice of satisfactory solutions on dose‐volume histograms and clinical considerations. The efficiency of the SVD optimizer to planify multi‐isocentric treatments was examined in the case of an irregular lesion planified with two isocenters. The condition number of this dual isocentric configuration showed a more ill‐conditioned problem than in the monoisocentric case. Examining different reconstructed weighting vectors, we observed that optimal solutions are obtained with the first singular components and an important healthy tissue overdosage occurs when the number of singular components used in the SVD expansion increases. Our SVD optimization approach is a general procedure which can be applied to different radiotherapy techniques.
Limitations of state estimation based cyber attack detection schemes in industrial control systems

An experiment was conducted on a water treatment plant to investigate the effectiveness of using Kalman filter based attack detection schemes in a Cyber Physical System (CPS). Kalman filter was implemented with Chi-Square detector. Random, stealthy bias, and replay attacks were launched and results analysed. Analysis indicates that stealthy false data injection and replay attacks cannot be detected by legacy failure detection methods.
Whole Genome Association Study in a Homogenous Population in Shandong Peninsula of China Reveals JARID2 as a Susceptibility Gene for Schizophrenia

DNA pooling can provide an economic and efficient way to detect susceptibility loci to complex diseases. We carried out a genome screen with 400 microsatellite markers spaced at approximately 10 cm in two DNA pools consisting of 119 schizophrenia (SZ) patients and 119 controls recruited from a homogenous population in the Chang Le area of the Shandong peninsula of China. Association of D6S289, a dinucleotide repeat polymorphism in the JARID2 gene with SZ, was found and confirmed by individual genotyping (X2 = 17.89; P = .047). In order to refine the signal, we genotyped 14 single nucleotide polymorphisms (SNPs) covering JARID2 and the neighboring gene, DNTBP1, in an extended sample of 309 cases and 309 controls from Shandong peninsula (including the samples from the pools). However, rs2235258 and rs9654600 in JARID2 showed association in allelic, genotypic and haplotypic tests with SZ patients from Chang Le area. This was not replicates in the extended sample, we conclude that JARID2 could be a susceptibility gene for SZ.
Non-verbal speech processing for a communicative agent

A believable life-like agent must appear to understand what is said to it, or what is being said around it, even if this is not actually the case. It must be able to follow a conversation and to understand what is happening in a discourse, even though the verbal content of the dialogue may be too complex (or too noisy) to be recognised. This paper describes the platform design and details the description language being used for the ‘SCOPE’ non-verbal speech-processing research currently being carried out at ATR for such a communicative robotic agent.
Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions

We show how to improve the accuracy of real-time forecasts from models that include au-toregressive terms by estimating the models on ‘lightly-revised’data instead of using data from the latest-available vintage. Forecast accuracy is improved by reorganizing the data vintages employed in the estimation of the model in such a way that the vintages used in estimation are of a similar maturity to the data in the forecast loss function. The size of the expected reductions in mean squared error depend on the characteristics of the data revision process. Empirically, we …nd RMSFE gains of 2-4% when forecasting output growth and in‡ation with AR models, and gains of the order of 8% with ADL models.
Constructional Apraxia in Alzheimer’s Disease: Association with Occipital Lobe Pathology and Accelerated Cognitive Decline

The functional impact and progression of occipital lobe pathology in sporadic late onset Alzheimer’s disease (AD) is barely explored. It is accepted that the primary and association visual areas are affected relatively late, in the neocortical stages of AD. We analysed 60 prospectively assessed AD patients in whom global cognitive deterioration and constructional apraxia were evaluated longitudinally using the CAMDEX. Radioactive immunohistochemistry was used to assess the amount of AD-related pathology in Brodmann areas 18 and 17. Braak staging of each case was also carried out. This study showed that in AD patients constructional apraxia is associated with higher expression of hyperphosphorylated tau. Additionally our findings indicate that early constructional apraxia is a predictor of accelerated cognitive decline in AD.
Location of a Person by Means of Sensors' Network

The different algorithm of data classification and clustering to identify the subject on the room is introduced. The aim is to provide a learning approach for pattern classification of presence sensors data. The focus system is on its application to find the best method for identification the subject location using a specific category of data simulated. The main features of the system include: automatic rule generation, automatic ranges generation, learning and adaptability capability. Simulation values concerning a different cluster methods results are presented. The system successfully detected the location in X and Y axes and body temperature. Its response time in identification suggests the feasibility in real-time applications.
Integration of statistical collocation segmentations in a phrase-based statistical machine translation system

This study evaluates the impact of integrating two different collocation segmentations methods in a standard phrase-based statistical machine translation approach. The collocation segmentation techniques are implemented simultaneously in the source and target side. Each resulting collocation segmentation is used to extract translation units. Experiments are reported in the English-to-Spanish Bible task and promising results (an improvement over 0.7 BLEU absolute) are achieved in translation quality.
A State of the Art of Word Sense Induction: A Way Towards Word Sense Disambiguation for Under-Resourced Languages (État de l’art de l’induction de sens: une voie vers la désambiguïsation lexicale pour les langues peu dotées) [in French]

Word Sense Disambiguation (WSD), the process of automatically identifying the meaning of a polysemous word in a sentence, is a fundamental task in Natural Language Processing (NLP). Progress in this approach to WSD opens up many promising developments in the field of NLP and its applications. Indeed, improvement over current performance levels could allow us to take a first step towards natural language understanding. Due to the lack of lexical resources it is sometimes difficult to perform WSD for under-resourced languages. This paper is an investigation on how to initiate research in WSD for under-resourced languages by applying Word Sense Induction (WSI) and suggests some interesting topics to focus on.
Modeling application performance by convolving machine signatures with application profiles

This paper presents a performance modeling methodology that is faster than traditional cycle-accurate simulation, more sophisticated than performance estimation based on system peak-performance metrics, and is shown to be effective on a class of High Performance Computing benchmarks. The method yields insight into the factors that affect performance on single-processor and parallel computers.
Assessing Metacognitive Awareness And Learning Strategies As Positive Predictors For Success In A Distance Learning Class /Uzaktan Eğitim Sınıfında Başarının Pozitif Yordayıcısı Olarak Bilişötesi Farkındalık Stratejisi Ve Öğrenme Stratejilerinin Değerlend

Abstract The aim of this study is to investigate the effects of metacognitive awareness and learning strategies on students success in a distance learning class. The data were collected through Metacognitive Awareness Inventory (Schraw&Dennison, 1994) and Learning Strategies Questionnaire (Pintrich, P.R., Smith, D.A.F., Garcia, T. & McKeachie, W.J., 1993). The data were gathered from 126 undergaduate students. The results showed that 1. Metacognitive awareness and learning strategies has an important role on students' academic success in an online English course. 2. The subcale of metacognite awareness, evaluation strategy, was the positive predictor of academic success. 3. The subscales of MSLQ, organization and peer learning strategies were the positive predictors of academic success. Keywords: Metacognitive Awareness Strategy, Learning Strategy, Distance Learning, Academic acheivement Ozet Bu calismanin amaci uzaktan egitim sinifindaki ogrencilerin basarisinda bilisotesi farkindalik stratejisi ve ogrenme stratejisinin etkilerini arastirmaktir. Veriler “Metacognitive Awareness Inventory, (Schraw&Dennison, 1994) – Bilisotesi Farkindalik Envanteri- and Learning Strategies Questionnaire ( Pintrich, P.R., Smith, D.A.F., Garcia, T. & McKeachie, W.J., 1993)- Ogrenme Stratejileri Envanteri- olcekleri kullanilarak elde edilmistir. Veriler arastirmaya katilan 126 lisans ogrencisinden alinmistir. Arastirma sonucunda asagidaki sonuclara ulasilmistir. 1. Uzaktan egitimde verilen Ingilizce derslerinde bilisotesi farkindalik ve ogrenme stratejilerinin ogrenci basarisi uzerinde onemli bir rolu vardir. 2. Bilisotesi farkindalik stratejisinin alt boyutundan olan degerlendirme stratejisi akademik basarinin pozitif yordayicisidir. 3. Ogrenme Stratejilerinin alt boyutlarindan organizasyon ve akran ogrenme stratejileri ogrencinin akademik basarisinin yordayicilaridir. Anahtar Kelimeler: Bilisotesi Farkindalik Stratejisi, Ogrenme Stratejisi, Uzaktan ogrenme Akademik Basari
TroGuard: context-aware protection against web-based socially engineered trojans

Despite the increasing number of social engineering attacks through web browser applications, detection of socially engineered trojan downloads by enticed victim users remains a challenging endeavor. In this paper, we present TroGuard, a semi-automated web-based trojan detection solution, that notifies the user if the application she downloaded behaves differently than what she expected at download time. TroGuard builds on the hypothesis that in spite of millions of currently downloadable executables on the Internet, almost all of them provide functionalities from a limited set. Additionally, because each functionality, e.g., text editor, requires particular system resources, it exhibits a unique system-level activity pattern. During an offline process, TroGuard creates a profile dictionary of various functionalities. This profile dictionary is then used to warn the user if she downloads an executable whose observed activity does not match its advertised functionality (extracted through automated analysis of the download website). Our experimental results prove the above mentioned premise empirically and show that TroGuard can identify real-world socially engineered trojan download attacks effectively.
Improvement of color rendering ability for multi-chip LED packages by using Y2O3:Eu3+ phosphor

This study presents a novel solution, application of the red Y<sub>2</sub>O<sub>3</sub>:Eu<sup>3+</sup> dopant phosphor, for enhancing color rendering index to more 86 for multi-chip white LED lamps (MCW-LEDs) having correlated color temperature (CCT) of 7700 K. Besides, the impacts of the Y<sub>2</sub>O<sub>3</sub>:Eu<sup>3+</sup> phosphor on the attenuation of light through phosphor layers of the various packages is also demonstrated based on the Beer-Lambert law. Simulation results provide important conclusion for selecting and developing the phosphor materials in MCW-LEDs manufacturing.
RADIUS: A System for Detecting Anomalous Link Quality Degradation in Wireless Sensor Networks

To ensure proper functioning of a Wireless Sensor Network (WSN), it is crucial that the network is able to detect anomalies in communication quality (e.g., RSSI), which may cause performance degradation, so that the network can react accordingly. In this paper, we introduce RADIUS, a lightweight system for the purpose. The design of RADIUS is aimed at minimizing the detection error (caused by normal randomness of RSSI) in discriminating good links from weak links and at reaching high detection accuracy under diverse link conditions and dynamic environment changes. Central to the design is a threshold-based decision approach that has its foundation on the Bayes decision theory. In RADIUS, various techniques are developed to address challenges inherent in applying this approach. In addition, through extensive experiments, proper configuration of the parameters involved in these techniques is identified for an indoor environment. In a prototype implementation of the RADIUS system deployed in an indoor testbed, the results show that RADIUS is accurate in detecting anomalous link quality degradation for all links across the network, maintaining a stable error rate of 6.13% on average.