Miracle-dz/UniFAR-FTUs huggingface dataset:
Linguistic and psychomotor development in children with chromosome 14 deletions

The present study focussed on a specific type of rare genetic condition: chromosome 14 deletions. Children with this genetic condition often show developmental delays and brain and neurological problems, although the type and severity of symptoms varies depending on the size and location of the deleted genetic material. The specific aim of the present study was to describe the developmental trajectories of language skills in a group of children with linear 14q deletions. Four children with an interstitial deletion of the long arm of chromosome 14 were followed for 1 year. Data collected from psychomotor and linguistic assessments highlight a large individual variability. Considering the children's genetic and clinical conditions, findings revealed that the size of the deleted area is not related to outcome. However, the developmental trajectories of language development are deeply influenced by the presence of clinical conditions, such as autism spectrum disorders.
Wavelet decomposition techniques and Hardy inequalities for function spaces on cellular domains

A rather tricky question is the construction of wavelet bases on domains for suitable function spaces (Sobolev, Besov, Triebel-Lizorkin type). In his monograph from 2008, Triebel presented an approach how to construct wavelet (Riesz) bases in function spaces of Besov and Triebel-Lizorkin type on cellular domains, in particular on the cube. However, he had to exclude essential exceptional values of the smoothness parameter $s$, for instance the theorems do not cover the Sobolev space W_2^1(Q) on the n-dimensional cube Q for n at least 2. Triebel also gave an idea how to deal with those exceptional values for the Triebel-Lizorkin function space scale on the cube Q: He suggested to introduce modified function spaces for the critical values, the so-called reinforced spaces. In this paper we start examining these reinforced spaces and transfer the crucial decomposition theorems necessary for establishing a wavelet basis from the non-critical values to analogous results for the critical cases now decomposing the reinforced function spaces of Triebel-Lizorkin type.
One-sided secrecy over the two-way wiretap channel

This paper studies the one-sided secrecy of a full-duplex two-way wiretap channel. It is motivated by a practical communication scenario, where two legitimate users communi­cate with each other in the presence of an external eavesdropper and only one of the users wishes to keep its message confidential from the external eavesdropper for the sake of privacy. As a general result, we establish an achievable rate region via cooperative jamming and random binning mechanisms. An outer bound of the one-sided secrecy rate region is also derived for the two-way wiretap channel with one-sided secrecy. Besides, numerical results are provided for binary-input deterministic channels. In particular, the one-sided secrecy capacity region for the binary XOR channel is fully characterized. In general, channel prefixing demonstrates its advantage in enlarging the achievable one-sided secrecy rate region.
Network Attack Detection Based on Combination of Neural, Immune and Neuro-Fuzzy Classifiers

The paper considers an approach for detection of anomalous patterns of network connections using artificial neural networks, immune systems, neuro-fuzzy classifiers and their combination. The principal component analysis is proposed to optimize the assigned problem. The architecture of the intrusion detection system, based on the application of the proposed methods, is described. The main advantage of the developed approach to intrusion detection is a multi-level analysis technique: first, signature based analysis is carried out, then a combination of adaptive detectors is involved. A number of computational experiments is performed. These experiments demonstrate the effectiveness of the chosen methods in terms of false positive, true positive and correct classification rates.
EFFECT OF LIGHT CURING MODES AND ETHANOL IMMERSION MEDIA ON THE SUSCEPTIBILITY OF A MICROHYBRID COMPOSITE RESIN TO STAINING

The aim of this in vitro study was to evaluate the susceptibility of a hybrid composite resin (Filtek Z250 – 3M ESPE) to staining, when light cured in four different modes and immersed in two different media. Composite resin specimens were randomly prepared and polymerized according to the experimental groups (conventional - 550 mW/cm2 / 30 seconds; soft start - 300mW/cm2/ 10 seconds + 550 mW/cm2 / 20 seconds; high intensity - 1060 mW/cm2 – 10 seconds; pulse delay – 550 mW/cm2 – 1 seconds + 60 seconds of waiting time + 550 mW/cm2 – 20 seconds) and immersed in one of two media (distilled water or absolute ethanol) for 24h. Next, the specimens were immersed in a 2% methylene blue solution for 12 hours. Afterwards, the specimens were washed and prepared for the spectrophotometric analysis. For statistical analysis, two-way ANOVA (4×2) and Tukey's test were performed on the data at 0.05 confidence level. Soft start showed the least staining, and was statistically different from the high intensity and pulse delay light curing modes (p<0.05). Conventional light curing unit did not show statistically significant differences from any other groups (p>0.05). There were no significant differences between the two immersion media (p>0.05). The soft start polymerization mode showed lower susceptibly of the composite resin to staining than high intensity and pulse delay, irrespective of the immersion medium.
S-Crucial and Bicrucial Permutations with Respect to Squares

A permutation is square-free if it does not contain two consecutive factors of length two or more that are order-isomorphic. A permutation is bicrucial with respect to squares if it is square-free but any extension of it to the right or to the left by any element gives a permutation that is not square-free. Avgustinovich et al. studied bicrucial permutations with respect to squares, and they proved that there exist bicrucial permutations of lengths $8k+1, 8k+5, 8k+7$ for $k\ge 1$. It was left as open questions whether bicrucial permutations of even length, or such permutations of length $8k+3$ exist. In this paper, we provide an encoding of orderings which allows us, using the constraint solver Minion, to show that bicrucial permutations of even length exist, and the smallest such permutations are of length 32. To show that 32 is the minimum length in question, we establish a result on left-crucial (that is, not extendable to the left) square-free permutations which begin with three elements in monotone order. Also, we show that bicrucial permutations of length $8k+3$ exist for $k=2,3$ and they do not exist for $k=1$. Further, we generalize the notions of right-crucial, left-crucial, and bicrucial permutations studied in the literature in various contexts, by introducing the notion of $P$-crucial permutations that can be extended to the notion of $P$-crucial words. In S-crucial permutations, a particular case of $P$-crucial permutations, we deal with permutations that avoid prohibitions, but whose extensions in any position contain a prohibition. We show that S-crucial permutations exist with respect to squares, and minimal such permutations are of length 17. Finally, using our software, we generate relevant data showing, for example, that there are 162,190,472 bicrucial square-free permutations of length 19.
Modeling syllable duration in Indian languages using support vector machines

In this paper we propose support vector machines (SVM) for predicting the durations of the syllables in Indian languages. In this work SVM regression models are used for modeling the durations of the syllables and SVM classification models are used for categorizing the syllables based on duration. Analysis is performed on broadcast news data in the languages Hindi, Telugu and Tamil, in order to predict the duration of syllables in these languages using SVM regression model. The input to the SVM consists of a set of phonological, positional and contextual features extracted from the text. We also propose two-stage duration models for improving the prediction accuracy. From the studies it was found that about 86% of the syllable durations are predicted within 25% of the actual duration. The performance of the duration models are evaluated using objective measures such as mean absolute error (/spl mu/), standard deviation (/spl sigma/) and correlation coefficient (/spl gamma/).
An Example-Based Method of Touching String Segmentation

In the work, an example-based method of touching string segmentation is proposed. Using Markov random field, the candidate patches based on the compatibility of the neighbour patches are selected. The outputs of the MRF after the iterative belief propagation form a segmentation probability map. The cut position is extracted from the map. Experiment results are presented and demonstrate the effectiveness of our algorithm.
Descriptive Complexity and Finite Models

Feel lonely? What about reading books? Book is one of the greatest friends to accompany while in your lonely time. When you have no friends and activities somewhere and sometimes, reading book can be a great choice. This is not only for spending the time, it will increase the knowledge. Of course the b=benefits to take will relate to what kind of book that you are reading. And now, we will concern you to try reading descriptive complexity and finite models as one of the reading material to finish quickly.
High-Performance Reserve Calculations for Life Insurance Portfolios

We describe a software design for efficient reserve computations for life insurance and pension products, described using a flexible and precise notation that is both machine-readable and human-readable; in effect, a domain-specific language for actuaries. Mathematically, this notation is based on continuous-time Markov models. First, from a collection of such product descriptions and from assumptions about transition intensities (e.g. survival, disability) and yield curves, the software can generate instances of Thiele’s differential equation that characterize the reserve or other quantities of interest. Secondly, these differential equations can be solved efficiently in a variety of ways. We use numerical solvers and can therefore calculate reserves for advanced pension products, for which the Thiele equations do not have closed-form solutions. Our computationally most advanced solver generates product-specific CUDA C code for graphics processors. Experience shows that this can speed up the solution by a factor of around 100 over standard desktop computer hardware, while retaining the same accuracy. With this approach, actuaries can develop and describe advanced and non-standard pension and life insurance products, yet still efficiently compute reserves and other quantities of interest. This is possible for large portfolios of contracts and large numbers of stress scenarios. Core to this is the use of modern programming language technology, including domain-specific languages and code generation for a variety of hardware platforms.
Multivariate DoE Optimization of Asymmetric Flow Field Flow Fractionation Coupled to Quantitative LC-MS/MS for Analysis of Lipoprotein Subclasses

In this report we demonstrate a practical multivariate design of experiment (DoE) approach for asymmetric flow field-flow fractionation (AF4) method optimization using separation of lipoprotein subclasses as an example. First, with the aid of commercially available software, we built a full factorial screening design where the theoretical outcomes were calculated by applying established formulas that govern AF4 channel performance for a 5–35 nm particle size range of interest for lipid particles. Second, using the desirable ranges of instrumental parameters established from theoretical optimization, we performed fractional factorial DoE for AF4 separation of pure albumin and ferritin with UV detection to narrow the range of instrumental parameters and allow optimum size resolution while minimizing losses from membrane immobilization. Third, the optimal range of conditions were tested using response surface DoE for sub-fractionation of high and low density lipoproteins (HDL and LDL) in human serum, where the recovery of the analytes were monitored by fraction collection and isotope-dilution LC-MS/MS analysis of each individual fraction for cholesterol and apolipoproteins (ApoA-1 and ApoB-100). Our results show that DoE is an effective tool in combining AF4 theoretical knowledge and experimental data in finding the most optimal set of AF4 instrumental parameters for quantitative coupling with LC-MS/MS measurements.
Exploring and reducing the effects of orientation on text readability in volumetric displays

Volumetric displays, which provide a 360° view of imagery illuminated in true 3D space, are a promising platform for interactive 3D applications. However, presenting text in volumetric displays can be a challenge, as the text may not be oriented towards the user. This is especially problematic with multiple viewers, as the text could, for example, appear forwards to one user, and backwards to another. In a first experiment we determined the effects of 3D rotations on text readability. Based on the results, we developed and evaluated a new technique which optimizes text orientation for multiple viewers. This technique provided 33% faster group reading times in a collaborative experimental task.
Implied Volatility Skews and Stock Index Skewness and Kurtosis Implied by S&P 500 Index Option Prices

The Black-Scholes (1973) option pricing model is used to value a wide range of option contracts. However, the model often inconsistently prices deep in-themoney and deep out-of-the-money options. Options’ professionals refer to this phenomenon as a volatility ‘skew’ or ‘smile. ’ In this paper, we apply an extension of the Black-Scholes model developed by Jarrow and Rudd (1982) to an investigation of S&P 500 index option prices. We find that non-normal skewness and kurtosis in option-implied distributions of index returns contribute significantly to the phenomenon of volatility skews.
Puncturing ability of idealized canine teeth: edged and non‐edged shanks

Idealized edged and non-edged indenters, mimicking canine teeth, were used to puncture thin materials and thick materials. Less force was needed for the edged (triangular in cross section) indenter to penetrate thin Mylar, paper, leather, beetle elytra and turkey skin than the non-edged (circular in cross-section) indenter. Oak, grass and magnolia leaves responded equally to both indenters. In thick materials, the edged indenter punctured beetles, shrimp, bananas, and chicken fl esh more easily than the non-edged indenter. Apple, tomato and avocado were punctured equally well. The edged indenter directs cracks at the corners so that the material can fold away in the direction of puncture, whereas cracks form unpredictably with the non-edged indenter. Edged indenters have the advantage in many of the materials tested.
A Single Dose of Neuron-Binding Human Monoclonal Antibody Improves Spontaneous Activity in a Murine Model of Demyelination

Our laboratory demonstrated that a natural human serum antibody, sHIgM12, binds to neurons in vitro and promotes neurite outgrowth. We generated a recombinant form, rHIgM12, with identical properties. Intracerebral infection with Theiler's Murine Encephalomyelitis Virus (TMEV) of susceptible mouse strains results in chronic demyelinating disease with progressive axonal loss and neurologic dysfunction similar to progressive forms of multiple sclerosis. To study the effects of rHIgM12 on the motor function of TMEV-infected mice, we monitored spontaneous nocturnal activity over many weeks. Nocturnal behavior is a sensitive measure of rodent neurologic function because maximal activity changes are expected to occur during the normally active night time monitoring period. Mice were placed in activity boxes eight days prior to treatment to collect baseline spontaneous activity. After treatment, activity in each group was continuously recorded over 8 weeks. We chose a long 8-week monitoring period for two reasons: (1) we previously demonstrated that IgM induced remyelination is present by 5 weeks post treatment, and (2) TMEV-induced demyelinating disease in this strain progresses very slowly. Due to the long observation periods and large data sets, differences among treatment groups may be difficult to appreciate studying the original unfiltered recordings. To clearly delineate changes in the highly fluctuating original data we applied three different methods: (1) binning, (2) application of Gaussian low-pass filters (GF) and (3) polynomial fitting. Using each of the three methods we showed that compared to control IgM and saline, early treatment with rHIgM12 induced improvement in both horizontal and vertical motor function, whereas later treatment improved only horizontal activity. rHIgM12 did not alter activity of normal, uninfected mice. This study supports the hypothesis that treatment with a neuron-binding IgM not only protects neurons in vitro, but also influences functional motor improvement.
DNA Polymerase κ Is a Key Cellular Factor for the Formation of Covalently Closed Circular DNA of Hepatitis B Virus

Hepatitis B virus (HBV) infection of hepatocytes begins by binding to its cellular receptor sodium taurocholate cotransporting polypeptide (NTCP), followed by the internalization of viral nucleocapsid into the cytoplasm. The viral relaxed circular (rc) DNA genome in nucleocapsid is transported into the nucleus and converted into covalently closed circular (ccc) DNA to serve as a viral persistence reservoir that is refractory to current antiviral therapies. Host DNA repair enzymes have been speculated to catalyze the conversion of rcDNA to cccDNA, however, the DNA polymerase(s) that fills the gap in the plus strand of rcDNA remains to be determined. Here we conducted targeted genetic screening in combination with chemical inhibition to identify the cellular DNA polymerase(s) responsible for cccDNA formation, and exploited recombinant HBV with capsid coding deficiency which infects HepG2-NTCP cells with similar efficiency of wild-type HBV to assure cccDNA synthesis is exclusively from de novo HBV infection. We found that DNA polymerase κ (POLK), a Y-family DNA polymerase with maximum activity in non-dividing cells, substantially contributes to cccDNA formation during de novo HBV infection. Depleting gene expression of POLK in HepG2-NTCP cells by either siRNA knockdown or CRISPR/Cas9 knockout inhibited the conversion of rcDNA into cccDNA, while the diminished cccDNA formation in, and hence the viral infection of, the knockout cells could be effectively rescued by ectopic expression of POLK. These studies revealed that POLK is a crucial host factor required for cccDNA formation during a de novo HBV infection and suggest that POLK may be a potential target for developing antivirals against HBV.
Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm

In real world applications, graphical statistical models are not only a tool for operations such as classification or prediction, but usually the network structures of the models themselves are also of great interest (e.g., in modeling brain connectivity). The false discovery rate (FDR), the expected ratio of falsely claimed connections to all those claimed, is often a reasonable error-rate criterion in these applications. However, current learning algorithms for graphical models have not been adequately adapted to the concerns of the FDR. The traditional practice of controlling the type I error rate and the type II error rate under a conventional level does not necessarily keep the FDR low, especially in the case of sparse networks. In this paper, we propose embedding an FDR-control procedure into the PC algorithm to curb the FDR of the skeleton of the learned graph. We prove that the proposed method can control the FDR under a user-specified level at the limit of large sample sizes. In the cases of moderate sample size (about several hundred), empirical experiments show that the method is still able to control the FDR under the user-specified level, and a heuristic modification of the method is able to control the FDR more accurately around the user-specified level. The proposed method is applicable to any models for which statistical tests of conditional independence are available, such as discrete models and Gaussian models.
Dense spatio-temporal features for non-parametric anomaly detection and localization

In this paper we propose dense spatio-temporal features to capture scene dynamic statistics together with appearance, in video surveillance applications. These features are exploited in a real-time anomaly detection system. Anomaly detection is performed using a non-parametric modelling, evaluating directly local descriptor statistics, and an unsupervised or semi-supervised approach. A method to update scene statistics, to cope with scene changes that typically happen in real world settings, is also provided. The proposed method is tested on publicly available datasets and compared to other state-of-the-art approaches.
Monetary Policy Evaluation with Noisy Information

This paper investigates the implications of noisy information regarding the measurement of economic activity for the evaluation of monetary policy. A common implicit assumption in such evaluations is that policymakers observe the current state of the economy promptly and accurately and can therefore adjust policy based on this information. However, in reality, decisions are made in real time when there is considerable uncertainty about the true state of affairs in the economy. Policy must be made with partial information. Using a simple model of the U.S. economy, I show that failing to account for the actual level of information noise in the historical data provides a seriously distorted picture of feasible macroeconomic outcomes and produces inefficient policy rules. Naive adoption of policies identified as efficient when such information noise is ignored results in macroeconomic performance worse than actual experience. When the noise content of the data is properly taken into account, policy reactions are cautious and less sensitive to the apparent imbalances in the unfiltered data. The resulting policy prescriptions reflect the recognition that excessively activist policy can increase rather than decrease economic instability.
Study on observer-based robust control of the vehicle lateral dynamics via TS model with unmeasurable premise variables

This paper introduces a fuzzy observer-based control approach for the vehicle lateral dynamics. The Takagi-Sugeno (TS) fuzzy model is utilized to describe the dynamics of a nonlinear time-varying lateral system. Based on the fuzzy model, a fuzzy observer is developed to estimate the side slip angle using the yaw velocity measurement. The objective of this study is twofold: first, the observer-based controller is designed to improve the stability of the vehicle although perturbations related to the nonlinearities of the contact force models, the variations of the adherence coefficients, etc. Second, the proposed strategy takes into account the unmeasurable membership functions of the TS formulation in the design of the observer.