Miracle-dz/UniFAR-FTUs huggingface dataset:
The Tyrosine Kinase Inhibitor Sunitinib Affects Ovulation but Not Ovarian Reserve in Mouse: A Preclinical Study

The aim of the study was to evaluate ovarian toxicity of tyrosine kinase inhibitor (TKI) sunitinib, since only scarce data are available on gonadal function after this treatment. Six-week-old female mice received orally, once daily, vehicle or sunitinib (50 mg/kg/d) during 5 weeks. Fertility parameters were analyzed from ovulation to litter assessment. Sunitinib exposure significantly reduced (i) corpora lutea number per ovary (1.1 ± 0.38 in sunitinib group versus 4 ± 0.79 in control group, p<0.01) and (ii) serum Anti Müllerian hormone (AMH) levels in sunitinib treated mice (12.01 ± 1.16) compared to control mice (14.33 ± 0.87 ng/ml, p< 0.05). However, primordial and growing follicles numbers per ovary were not different in both groups. After treatment withdrawal, female mice in both groups were able to obtain litters. These data could be helpful to counsel clinicians and patients, when fertility preservation methods are discussed, before TKI treatment in girls and young women.
Planning Personalised Museum Visits

In this paper, we consider the problem of designing personalised museum visits. Given a set of preferences and constraints a visitor might express on her visit, the aim is to compute the tour that best matches her requirements. The museum visits problem can be expressed as a planning problem, with cost optimization. We show how to bound the number of steps required to find an optimal solution, via the resolution of an instance of the shortest complete walk problem. We also point out an alternative encoding of the museum visits problem as an optimization problem with pseudo-Boolean constraints and a linear objective function. We have evaluated several constraints solvers, a planner and a tailored solver on a number of benchmarks, representing various instances of the museum visits problem corresponding to real museums. Our empirical results show the feasibility of both the planning and the constraint programming approaches. Optimal solutions can be computed for short visits and ``practically good'' solutions for much longer visits.
PGP 9.5 immunocytochemical staining for pancreatic endocrine tumors

Aims/hypothesis: Protein gene product 9.5 (PGP 9.5) is a marker for neuroendocrine cells but has not been used for pancreatic islet cells and pancreatic endocrine tumors (PETs). Antibodies for PGP 9.5 are now commercially available for immunocytochemical study, with which immunostaining may be able to differentiate between benign and malignant PETs. Results: All 4 kinds of normal islet cells were positively immunostained for PGP 9.5—moderately positive for β-cells and strongly positive for δ-cells, whereas ganglion cells were immunostained more strongly than islet cells. Nine of 12 insulinomas were moderately to strongly positive for PGP 9.5. Two glucagonomas, 3 of 6 pancreatic polypeptidomas (PPomas), 3 of 9 gastrinomas, and 2 of 4 non-functioning PETs were negative for PGP 9.5. Materials and Methods: Thirty-four PETs were immunocytochemically stained for PGP 9.5 using a rabbit polyclonal antibody together with immunostaining for 4 pancreatic hormones, chromogranin A (CgA), and gastrin. PETs consisted of 12 insulinomas, 2 glucagonomas, 1 somatostatinoma (SRIFoma), 6 PPomas, 9 gastrinomas, and 4 non-functioning PETs. Conclusion/Interpretation: PGP 9.5 immunostaining was universally positive for 4 kinds of islet cells and was moderately to strongly positive for 9 of 12 (75%) insulinomas. All 22 non-β-cell PETs were negative or weakly positive for PGP 9.5, and thus negative or weakly positive PGP 9.5 immunostaining may be used as a marker for potential malignancy and poor prognosis for non-β-cell PETs.
Computationally Inexpensive Tracking Control of High-Speed Trains With Traction/Braking Saturation

The problem of the position and velocity tracking control of high-speed trains becomes interesting yet challenging when simultaneously considering inevitable factors such as the resistive friction and aerodynamic drag forces, the interactive impacts among the vehicles, and the nonlinear traction/braking notches inherent in train systems. In this paper, a multiple point mass with a single-coordinate dynamic model that reflects resistive and transient impacts is derived, and based on this, computationally inexpensive robust adaptive control designs with optimal task distribution for speed and position tracking are proposed under traction/braking nonlinearities and saturation limitations. It is shown that the proposed method is not only robust to external disturbances, aerodynamic resistance, mechanical resistance, and transient impacts but adaptive to unknown system parameters as well. The effectiveness of the proposed approach is also confirmed through numerical simulations.
Automatic Generation of Interactive Cooking Video with Semantic Annotation

Videos are one of the most frequently used forms of multimedia resources. People want to interact with videos to find a specific part or to obtain relevant information. To support user interactions, current videos should be transformed to interactive videos. This paper proposes an interactive cooking video system to generate automatically interactive cooking videos. To do this, the proposed system performs semantic video annotation on cooking videos. Semantic video annotation process includes three parts: synchronization between recipes and corresponding cooking videos based on a caption-recipe alignment algorithm, information extraction on food recipes using lexico-syntactic patterns, and semantic entity interconnection between recognized entities and semantic web entities. Cooking video annotation ontology is modeled to handle annotation data. To evaluate the proposed system, comparative experiments are performed on the caption-recipe alignment algorithm. The accuracy of information extraction and semantic entity interconnection is also measured. Experimental results show that the proposed system is superior to compared algorithms in alignment perspectives. Information extraction and semantic interconnection method also achieve high accuracy over 95%, respectively. Consequently, the proposed system generates interactive cooking videos in high accuracy and support user interactions by providing a user interface which allows users to easily find specific scenes and obtain detailed information on objects users have interested in.
Intrusion detection system based on multi-strategy pruning algorithm of the decision tree

The decision tree is an effective classification method in data mining. Using this method, the intrusion detection system can be more accurate and efficient to process network data. However, faced with a large network data set, the scale of decision tree is often complex and hard to understand. This paper presents a multi-strategy pruning algorithm to trim the tree. This method can improve the efficiency and accuracy of intrusion detection system.
Small Dimension Pde for Discrete Asian Options

This paper presents an efficient method for pricing discrete Asian options in presence of smile and non-proportional dividends. Using an homogeneity property, we show how to reduce an n0 dimensional problem to a one- or two-dimensional one. We examine different numerical specifications of our dimension reduced PDE using a Crank–Nicholson method (interpolation method, grid boundaries, time and space steps) as well as the extension to the case of non-proportional discrete dividends, using a jump condition. We benchmark our results with Quasi Monte-Carlo simulation and a multi-dimensional PDE
Opportunities for concurrent dynamic analysis with explicit inter-core communication

Multicore is now the dominant processor trend, and the number of cores is rapidly increasing. The paradigm shift to multicore forces the redesign of the software stack, which includes dynamic analysis. Dynamic analyses provide rich features to software in various areas, such as debugging, testing, optimization, and security. However, these techniques often suffer from excessive overhead, which make it less practical. Previously, this overhead has been overcome by improved processor performance as each generation gets faster, but the performance requirements of dynamic analyses in the multicore era cannot be fulfilled without redesigning for parallelism. Scalable design of dynamic analysis is a challenging problem. Not only must the analysis itself must be parallel, but the analysis must also be decoupled from the application and run concurrently. A typical method of decoupling the analysis from the application is to send the analysis data from the application to the core that runs the analysis thread via buffering. However, buffering can perturb application cache performance, and the cache coherence protocol may not be efficient, or even implemented, with large numbers of cores in the future. This paper presents our initial effort to explore the hardware design space and software approach that will alleviate the scalability problem for dynamic analysis on multicore. We choose to make use of explicit inter-core communication that is already available in a real processor, the TILE64 processor and evaluate the opportunity for scalable dynamic analyses. We provide our model and implement concurrent call graph profiling as a case study. Our evaluation shows that pure communication overhead from the application point of view is as low as 1%. We expect that our work will help design scalable dynamic analyses and will influence the design of future many-core processors.
Understanding the Links among neuromedin U Gene, beta2-adrenoceptor Gene and Bone Health: An Observational Study in European Children

Neuromedin U, encoded by the NMU gene, is a hypothalamic neuropeptide that regulates both energy metabolism and bone mass. The beta-2 adrenergic receptor, encoded by the ADRB2 gene, mediates several effects of catecholamine hormones and neurotransmitters in bone. We investigated whether NMU single nucleotide polymorphisms (SNPs) and haplotypes, as well as functional ADRB2 SNPs, are associated with bone stiffness in children from the IDEFICS cohort, also evaluating whether NMU and ADRB2 interact to affect this trait. A sample of 2,274 subjects (52.5% boys, age 6.2±1.8 years) from eight European countries, having data on calcaneus bone stiffness index (SI, mean of both feet) and genotyping (NMU gene: rs6827359, rs12500837, rs9999653; ADRB2 gene: rs1042713, rs1042714), was studied. After false discovery rate adjustment, SI was significantly associated with all NMU SNPs. rs6827359 CC homozygotes showed the strongest association (recessive model, Δ = −1.8, p = 0.006). Among the five retrieved haplotypes with frequencies higher than 1% (range 2.0–43.9%), the CCT haplotype (frequency = 39.7%) was associated with lower SI values (dominant model, Δ = −1.0, p = 0.04) as compared to the most prevalent haplotype. A non-significant decrease in SI was observed in in ADRB2 rs1042713 GG homozygotes, while subjects carrying SI-lowering genotypes at both SNPs (frequency = 8.4%) showed much lower SI than non-carriers (Δ = −3.9, p<0.0001; p for interaction = 0.025). The association was more evident in preschool girls, in whom SI showed a curvilinear trend across ages. In subgroup analyses, rs9999653 CC NMU or both GG ADRB2 genotypes were associated with either lower serum calcium or β-CrossLaps levels (p = 0.01). This study in European children shows, for the first time in humans, a role for NMU gene through interaction with ADRB2 gene in bone strength regulation, more evident in preschool girls.
VISUAL INVENTORY OF ROAD SIGN NO-BLOCKING OF PASSAGEWAY

: This paper describes a method to detect and identify the Italian road sign for no-blocking of passageway. The approach detects the sign in the image by color processing and multi-layer perceptron neural network. The approach locates the region of interest within the image, using color segmentation, then the signal of restricted no stopping is identiﬁed using shape and color information, and ﬁnally the text label is recognized with a state diagram and test on the shape of the words. It is important to examine also the text label passo-carrabile as an additional test and to differentiate this speciﬁc sign among all other prohibition signs. The obtained results show the feasibility of the system.
MoIO: Run-time monitoring for I/O protocol violations in storage device drivers

Bugs affecting storage device drivers include the so-called protocol violation bugs, which silently corrupt data and commands exchanged with I/O devices. Protocol violations are very difficult to prevent, since testing device driver is notoriously difficult. To address them, we present a monitoring approach for device drivers (MoIO) to detect HO protocol violations at run-time. The approach infers a model of the interactions between the storage device driver, the OS kernel, and the hardware (the device driver protocol) by analyzing execution traces. The model is then used as a reference for detecting violations in production. The approach has been designed to have a low overhead and to overcome the lack of source code and protocol documentation. We show that the approach is feasible and effective by applying it on the SATA/AHCI storage device driver of the Linux kernel, and by performing fault injection and long-running tests.
Geometry-covering Jammer Localization based on Distance Comprehension in Wireless Sensor Networks

Jamming attacks could cause severe damage to Wireless Sensor Networks (WSNs). Once jamming attack occurs, the most urgent work is to get the position information of the jammer. Then safety measures to eliminate the jamming effects can be devised. In this paper, the jammer localization is conducted by geometric covering method to achieve a low energy consumption. And utilizing the power of the jamming signal received by the boundary nodes, a compensating method is composed to reduce the estimating error of the jamming area. At last the localization is conducted by extracting the minimum covering circle of the compensated victim area. Simulations are conducted to test the localization accuracy with the impact of node density, jamming region and radius. Results show that this localization method achieves both good precision and low energy consumption.
Unsupervised Training for Large Vocabulary Translation Using Sparse Lexicon and Word Classes

We address for the first time unsupervised training for a translation task with hundreds of thousands of vocabulary words. We scale up the expectation-maximization (EM) algorithm to learn a large translation table without any parallel text or seed lexicon. First, we solve the memory bottleneck and enforce the sparsity with a simple thresholding scheme for the lexicon. Second, we initialize the lexicon training with word classes, which efficiently boosts the performance. Our methods produced promising results on two large-scale unsupervised translation tasks.
A methodology for successful implementation of ERP in smaller companies

ERP (Enterprise Resources Planning) has been proven to be an effective tool that improves business performances for competiveness in the market. However, the success rate of implementing such a tool to a company has been fairly low. While issues and key success factors of such implementation have been addressed by many researchers, it has been noted that Small & Medium Enterprises (SMEs) face more challenges. In this paper, authors have developed and applied a proven methodology for SMEs to implement ERP system. The case study shows that the method is comprehensive and effective.
A pareto-compliant surrogate approach for multiobjective optimization

This paper discusses the idea of using a single Pareto-compliant surrogate model for multiobjective optimization. While most surrogate approaches to multi-objective optimization build a surrogate model for each objective, the recently proposed mono surrogate approach [3] aims at building a global surrogate model defined on the decision space and tightly characterizing the current Pareto set and the dominated region, in order to speed up the evolution progress toward the true Pareto set. This surrogate model is specified by combining a One-class Support Vector Machine (SVMs) to characterize the dominated points, and a Regression SVM to clamp the Pareto front on a single value. The aims of this paper are to identify issues of the proposed approach demanding further study and to raise the question of how to efficiently incorporate quality indicators, such as the hypervolume into the surrogate model.
Financial Crisis Dynamic Prediction Based on Sliding Window Technology and Mahalanobis-Taguchi System

In order to improve the prediction accuracy of current existing model, the financial crisis prediction dynamic model is proposed. By means of the data streams processing method, the sliding window technology is used for real-time updated samples in this paper, and then the optimal features of samples are selected by Mahalanobis-Taguchi System. The financial crisis prediction dynamic model is built on financial data of the Chinese listed companies. Experiment results show that dynamic selection of the samples and features can reduce the adverse effects of the concept drift in financial data streams. The prediction accuracy of the dynamic model based on sliding window technology and Mahalanobis-Taguchi System is better than the static prediction models.
The influence of home language on dual language toddlers’ comprehension in Norwegian

ABSTRACT The aim of the study is to investigate whether 33-month-old (toddlers) monolinguals (N = 902) and different groups of dual language learners (DLL) (N = 161) differ in majority language comprehension, Norwegian (L2). The three DLL groups vary regarding the amount of parental exposure to Norwegian. Language comprehension was assessed by authentic assessment in ECEC institutions with the systematic observation material TRAS. A parent questionnaire measured the amount of Norwegian exposure at home. The DLL’s comprehension in Norwegian were significantly lower than the monolingual’s. There was no difference in L2 skills between DLL toddlers from majority-speaking households (N = 30) and toddlers from households speaking a combination of the majority and minority language (N = 82), while toddlers from minority-speaking households (N = 49) scored significantly lower. Rather than the amount of L2 exposure, the results indicate that there might exist a threshold value of parental L2 input necessary to obtain good L2 skills.
Distributed algorithms for basis pursuit

The Basis Pursuit (BP) problem consists in finding a least `1 norm solution of the underdetermined linear system Ax = b. It arises in many areas of electrical engineering and applied mathematics. Applications include signal compression and modeling, estimation, fitting, and compressed sensing. In this paper, we explore methods for solving the BP in a distributed environment, i.e., when the computational resources and the matrix A are distributed over several interconnected nodes. Special instances of this distributed framework include sensor networks and distributed memory and/or processor platforms. We consider two distribution paradigms: either the columns or the rows of A are distributed across the nodes. The several algorithms that we present impose distinct requirements on the degree of connectivity of the network and the per-node computational complexity.
Dynamic modeling and intuitive control strategy for an "X4-flyer"

This paper describes an intuitive control strategy for a four rotors vertical take-off and landing (VTOL) remote-controlled vehicle known as the "X4-flyer". A quasi-stationary flight dynamic modeling including gyroscopic effects due to the rotors dynamics is proposed. A nonlinear controller simplifying the vehicle manipulation and insuring quasi-stationary flight conditions is developed. The approach considers that the rotor dynamics are negligible compared to the body dynamics and develops a control law based on saturating the linear dynamics for bounding the vehicle orientation and limiting it to very small values. Experimental results show the success of this approach.
R-V Dynamics Illusion: Psychophysical Phenomenon Caused by the Difference between Dynamics of Real Object and Virtual Object

In Mixed-Reality (MR) space, it appeared that the sense of weight can be affected by a MR visual stimulation with a movable portion. We named this psychophysical influence caused by the difference between dynamics of the real object (R) and the virtual object (V) movement, the "R-V Dynamics Illusion. " There are many combinations of experiments that can be conducted. Previously, we conducted experiments of the case where the real object is rigid and the virtual object is dynamically changeable. In this paper, we conducted experiments of the case where the real object is liquid and both the real and the virtual objects are dynamically changeable. The results of the experiments showed that the subjects sensed weight differently when virtual object with a movable portion is superimposed onto a real liquid object.
Progressive SAR image compression using low complexity Bandlet transform and modified EZBC

In this paper, we introduce a progressive SAR image compression based on Bandlet transform (BT) and a modified Embedded Zero-Block Coding (EZBC) algorithm. Bandlet transform as a new developed adaptive multiresolution geometry analysis tool exhibits enormous potential in compression based on geometric regularity. Since in SAR images, important information is spread in the entire frequency spectrum, discrete wavelet transform (DWT) cannot provide optimal representation and instead Bandlet transform is employed to provide a sparse representation of the image. A modified version of EZBC algorithm is introduced to efficiently encode the Bandlet coefficient in a progressive manner in which fidelity of the reconstructed image in the decoder gradually improves as more bits are received and decoded. Numerical tests show that our method provide a significant improvement particularly for low bit rate SAR image compression.
Pre-replication complex proteins assemble at regions of low nucleosome occupancy within the Chinese hamster dihydrofolate reductase initiation zone

Genome-scale mapping of pre-replication complex proteins has not been reported in mammalian cells. Poor enrichment of these proteins at specific sites may be due to dispersed binding, poor epitope availability or cell cycle stage-specific binding. Here, we have mapped sites of biotin-tagged ORC and MCM protein binding in G1-synchronized populations of Chinese hamster cells harboring amplified copies of the dihydrofolate reductase (DHFR) locus, using avidin-affinity purification of biotinylated chromatin followed by high-density microarray analysis across the DHFR locus. We have identified several sites of significant enrichment for both complexes distributed throughout the previously identified initiation zone. Analysis of the frequency of initiations across stretched DNA fibers from the DHFR locus confirmed a broad zone of de-localized initiation activity surrounding the sites of ORC and MCM enrichment. Mapping positions of mononucleosomal DNA empirically and computing nucleosome-positioning information in silico revealed that ORC and MCM map to regions of low measured and predicted nucleosome occupancy. Our results demonstrate that specific sites of ORC and MCM enrichment can be detected within a mammalian intitiation zone, and suggest that initiation zones may be regions of generally low nucleosome occupancy where flexible nucleosome positioning permits flexible pre-RC assembly sites.