Miracle-dz/UniFAR-FTUs huggingface dataset:
SIRENE: supervised inference of regulatory networks

MOTIVATION Living cells are the product of gene expression programs that involve the regulated transcription of thousands of genes. The elucidation of transcriptional regulatory networks is thus needed to understand the cell's working mechanism, and can for example, be useful for the discovery of novel therapeutic targets. Although several methods have been proposed to infer gene regulatory networks from gene expression data, a recent comparison on a large-scale benchmark experiment revealed that most current methods only predict a limited number of known regulations at a reasonable precision level. RESULTS We propose SIRENE (Supervised Inference of Regulatory Networks), a new method for the inference of gene regulatory networks from a compendium of expression data. The method decomposes the problem of gene regulatory network inference into a large number of local binary classification problems, that focus on separating target genes from non-targets for each transcription factor. SIRENE is thus conceptually simple and computationally efficient. We test it on a benchmark experiment aimed at predicting regulations in Escherichia coli, and show that it retrieves of the order of 6 times more known regulations than other state-of-the-art inference methods. AVAILABILITY All data and programs are freely available at http://cbio. ensmp.fr/sirene.
Intrafractional Tracking Accuracy of a Transperineal Ultrasound Image Guidance System for Prostate Radiotherapy

Purpose: The aim of this study is to evaluate the tracking accuracy of a commercial ultrasound system under relevant treatment conditions and demonstrate its clinical utility for detecting significant treatment deviations arising from inadvertent intrafractional target motion. Methods: A multimodality male pelvic phantom was used to simulate prostate image-guided radiotherapy with the system under evaluation. Target motion was simulated by placing the phantom on a motion platform. The tracking accuracy of the ultrasound system was evaluated using an independent optical tracking system under the conditions of beam-on, beam-off, poor image quality with an acoustic shadow introduced, and different phantom motion cycles. The time delay between the ultrasound-detected and actual phantom motion was investigated. A clinical case example of prostate treatment is presented as a demonstration of the utility of the system in practice. Results: Time delay between the motion phantom and ultrasound tracking system is 223 ± 45.2 milliseconds including video and optical tracking system frame rates. The tracking accuracy and precision were better with a longer period. The precision of ultrasound tracking performance in the axial (superior–inferior) direction was better than that in the lateral (left–right) direction (root mean square errors are 0.18 and 0.25 mm, respectively). The accuracy of ultrasound tracking performance in the lateral direction was better than that in the axial direction (the mean position errors are 0.23 and 0.45 mm, respectively). Interference by radiation and image quality do not affect tracking ability significantly. Further, utilizing the tracking system as part of a clinical study for prostate treatment further verified the accuracy and clinical appropriateness. Conclusions: It is feasible to use transperineal ultrasound daily to monitor prostate motion during treatment. Our results verify the accuracy and precision of an ultrasound system under typical external beam treatment conditions and further demonstrate that the tracking system was able to identify important prostate shifts in a clinical case.
Admissible consensualization for singular swarm systems with time delays

Under dynamic output feedback consensus protocols with time delays, admissible consensus problems for highorder linear time-invariant singular swarm systems are investigated. The admissible consensus problem is transformed into admissible problems of multiple singular subsystems by state decomposition. Linear matrix inequality (LMI) criterions for admissible consensualization are presented, which can guarantee scalability of swarm systems since they only involve four LMI constraints. Furthermore, an explicit expression of the consensus function is given, and the impacts of time delays, protocol states and interaction topologies on the consensus function are shown. Moreover, numerical sumulations are given to demonstrate theoretical results.
An Action-Oriented Approach to Business Education.

Argues that expertise based solely on rational, quantitative approaches to decision making problematic in rapidly changing business environments that arrest the tools of forecasting, analysis and planning. Where managers must take action in the face of considerable ambiguity, they must justify decisions on “gut instincts”, “best guesses” and other qualitative considerations. Unfortunately, traditional management education is primarily based on quantitative approaches to analysis and planning that may be ineffectual in ambiguous environments. Discusses an alternative approach to management education and training that seeks to blend analytic rigour with insight, intuition, creativity and learning‐by‐doing. Compares assumptions underlying traditional and action‐oriented approaches, and provides examples that suggest how management education and training can enhance their relevance by balancing quantitative and qualitative methods of decision making.
CW PM Multiwatts Yb-Doped Fiber Laser Directly Emitting at Long Wavelength

We study the impact of standard active double-clad (DC) fiber characteristics and laser architectures on the generation of long-wavelength Yb-doped high-power fiber lasers around 1154 nm. Both theoretical and experimental works have been performed highlighting that Yb-doped fiber lasers can emit efficiently in multiwatts operation at wavelengths higher than 1150 nm. This study has been focused on the use of standard all-fiber active and passive components as well as on the use of standard DC Yb-doped fibers without any spectral filtering except cavity mirrors.
Clustering-based algorithms for single-hidden-layer sigmoid perceptron

Gradient-descent type supervised learning is the most commonly used algorithm for design of the standard sigmoid perceptron (SP). However, it is computationally expensive (slow) and has the local-minima problem. Moody and Darken (1989) proposed an input-clustering based hierarchical algorithm for fast learning in networks of locally tuned neurons in the context of radial basis function networks. We propose and analyze input clustering (IC) and input-output clustering (IOC)-based algorithms for fast learning in networks of globally tuned neurons in the context of the SP. It is shown that "localizing'' the input layer weights of the SP by the IC and the IOC minimizes an upper bound to the SP output error. The proposed algorithms could possibly be used also to initialize the SP weights for the conventional gradient-descent learning. Simulation results offer that the SPs designed by the IC and the IOC yield comparable performance in comparison with its radial basis function network counterparts.
Direct Expressive Voice Training Based on Semantic Selection

This work aims at creating expressive voices from audiobooks using semantic selection. First, for each utterance of the audiobook an acoustic feature vector is extracted, including iVectors built on MFCC and on F0 basis. Then, the transcription is projected into a semantic vector space. A seed utterance is projected to the semantic vector space and the N nearest neighbors are selected. The selection is then filtered by selecting only acoustically similar data. The proposed technique can be used to train emotional voices by using emotional keywords or phrases as seeds, obtaining training data semantically similar to the seed. It can also be used to read larger texts in an expressive manner, creating specific voices for each sentence. That later application is compared to a DNN predictor, which predicts acoustic features from semantic features. The selected data is used to adapt statistical speech synthesis models. The performance of the technique is analyzed objectively and in a perceptive experiment. In the first part of the experiment, subjects clearly show preference for particular expressive voices to synthesize semantically expressive utterances. In the second part, the proposed method is shown to achieve similar or better performance than the DNN based prediction. Copyright © 2016 ISCA.
Non-parametric estimation of population size changes from the site frequency spectrum

Abstract Changes in population size is a useful quantity for understanding the evolutionary history of a species. Genetic variation within a species can be summarized by the site frequency spectrum (SFS). For a sample of size n, the SFS is a vector of length n − 1 where entry i is the number of sites where the mutant base appears i times and the ancestral base appears n − i times. We present a new method, CubSFS, for estimating the changes in population size of a panmictic population from an observed SFS. First, we provide a straightforward proof for the expression of the expected site frequency spectrum depending only on the population size. Our derivation is based on an eigenvalue decomposition of the instantaneous coalescent rate matrix. Second, we solve the inverse problem of determining the changes in population size from an observed SFS. Our solution is based on a cubic spline for the population size. The cubic spline is determined by minimizing the weighted average of two terms, namely (i) the goodness of fit to the observed SFS, and (ii) a penalty term based on the smoothness of the changes. The weight is determined by cross-validation. The new method is validated on simulated demographic histories and applied on unfolded and folded SFS from 26 different human populations from the 1000 Genomes Project.
PREDICTION ERRORS IN NONSTATIONARY AUTOREGRESSIONS OF INFINITE ORDER

Assume that observations are generated from nonstationary autoregressive (AR) processes of infinite order. We adopt a finite-order approximation model to predict future observations and obtain an asymptotic expression for the mean-squared prediction error (MSPE) of the least squares predictor. This expression provides the first exact assessment of the impacts of nonstationarity, model complexity, and model misspecification on the corresponding MSPE. It not only provides a deeper understanding of the least squares predictors in nonstationary time series, but also forms the theoretical foundation for a companion paper by the same authors, which obtains asymptotically efficient order selection in nonstationary AR processes of possibly infinite order.
Differential Instant Radiosity for mixed reality

In this paper we present a novel plausible realistic rendering method for mixed reality systems, which is useful for many real life application scenarios, like architecture, product visualization or edutainment. To allow virtual objects to seamlessly blend into the real environment, the real lighting conditions and the mutual illumination effects between real and virtual objects must be considered, while maintaining interactive frame rates (20–30fps). The most important such effects are indirect illumination and shadows cast between real and virtual objects. Our approach combines Instant Radiosity and Differential Rendering. In contrast to some previous solutions, we only need to render the scene once in order to find the mutual effects of virtual and real scenes. The dynamic real illumination is derived from the image stream of a fish-eye lens camera. We describe a new method to assign virtual point lights to multiple primary light sources, which can be real or virtual. We use imperfect shadow maps for calculating illumination from virtual point lights and have significantly improved their accuracy by taking the surface normal of a shadow caster into account. Temporal coherence is exploited to reduce flickering artifacts. Our results show that the presented method highly improves the illusion in mixed reality applications and significantly diminishes the artificial look of virtual objects superimposed onto real scenes.
Women and economy: complex inequality in a post-industrial landscape

This article looks at the workplace, home and welfare/state to explore intergenerational, dynamic inequality experienced by women around paid work. Based in a former coalfield, it brings women's paid work centre stage and resonates with the experiences of women (and men) living and working in other post-industrial places that grew out of a particular industry, suffered the trauma of industrial closure, redundancy and job loss, and coping with a new economy shaped by low pay and insecurity. To examine the dynamic element of inequality, the article draws upon Walby's (2009, Globalisation and Inequalities: Complexity and Contested Modernities, London: Sage) theory of ‘complex inequality’ to understand intersecting regimes of oppression. The article is based on ethnographic work in East Durham, England, including repeat in-depth group discussions with 31 women aged 16–90.
Novel Applications of Magnetic Resonance Imaging to Image Tissue Inflammation after Stroke

Experimental studies suggest that stroke‐induced brain damage progresses during subacute stages. Cerebral ischemic injury is associated with the induction of a series of inflammatory events, including the infiltration of circulating immune cells and activation of resident cells. Local brain inflammation is spatiotemporally related to the occurrence of delayed apoptotic cell death. Therefore, ischemia‐associated inflammation may not only play a major role in the pathogenesis of neurodegeneration associated with stroke, but may also mediate beneficial effects such as lesion demarcation, wound healing, and tissue regeneration especially via secretion of nerve growth factors. In this context, noninvasive imaging of inflammation associated with ischemic stroke lesions could have a predictive value and may be helpful for the development of cytoprotective drugs.
Cultivar Evaluation and Essential Test Locations Identification for Sugarcane Breeding in China

The discrepancies across test sites and years, along with the interaction between cultivar and environment, make it difficult to accurately evaluate the differences of the sugarcane cultivars. Using a genotype main effect plus genotype-environment interaction (GGE) Biplot software, the yield performance data of seven sugarcane cultivars in the 8th Chinese National Sugarcane Regional Tests were analyzed to identify cultivars recommended for commercial release. Fn38 produced a high and stable sugar yield. Gn02-70 had the lowest cane yield with high stability. Yz06-407 was a high cane yield cultivar with poor stability in sugar yield. Yz05-51 and Lc03-1137 had an unstable cane yield but relatively high sugar yield. Fn39 produced stable high sugar yield with low and unstable cane production. Significantly different sugar and cane yields were observed across seasons due to strong cultivar-environment interactions. Three areas, Guangxi Chongzuo, Guangxi Baise, and Guangxi Hechi, showed better representativeness of cane yield and sugar content than the other four areas. On the other hand, the areas Guangxi Chongzuo, Yunnan Lincang, and Yunnan Baoshan showed strong discrimination ability, while the areas Guangxi Hechi and Guangxi Liuzhou showed poor discrimination ability. This study provides a reference for cultivar evaluation and essential test locations identification for sugarcane breeding in China.
Mendelian Randomisation Study of Childhood BMI and Early Menarche

To infer the causal association between childhood BMI and age at menarche, we performed a mendelian randomisation analysis using twelve established “BMI-increasing” genetic variants as an instrumental variable (IV) for higher BMI. In 8,156 women of European descent from the EPIC-Norfolk cohort, height was measured at age 39–77 years; age at menarche was self-recalled, as was body weight at age 20 years, and BMI at 20 was calculated as a proxy for childhood BMI. DNA was genotyped for twelve BMI-associated common variants (in/near FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, ETV5, MTCH2, SEC16B, FAIM2 and SH2B1), and for each individual a “BMI-increasing-allele-score” was calculated by summing the number of BMI-increasing alleles across all 12 loci. Using this BMI-increasing-allele-score as an instrumental variable for BMI, each 1 kg/m2 increase in childhood BMI was predicted to result in a 6.5% (95% CI: 4.6–8.5%) higher absolute risk of early menarche (before age 12 years). While mendelian randomisation analysis is dependent on a number of assumptions, our findings support a causal effect of BMI on early menarche and suggests that increasing prevalence of childhood obesity will lead to similar trends in the prevalence of early menarche.
Automatic detection of conflicts in spoken conversations: Ratings and analysis of broadcast political debates

Automatic analysis of spoken conversations has recently searched for phenomena like agreement/disagreement in collaborative and non-conflictual discussions (e.g., meetings). This work adds a novel dimension investigating conflicts in spontaneous conversations. The study makes use of broadcasted political debates where conflicts naturally arise between participants. In the first part, an annotation scheme to rate the degree of conflict in conversations is described and applied to 12 hours of recordings. In the second part, the correlation between various prosodic/conversational features and the degree of conflict is investigated. In the third part, we perform automatic detection of the level of conflict based on those features showing an F-measure of 71.6% in three-level classification tasks.
Activation of Community Television and its Influence on Students’ Creative Thinking Level

The goal of the research was to examine whether a relation exists between students’ experience in community television and changes in their creative thinking ability. Community television is a tool that enables the expression of wishes, opinions, ideas, thoughts, experiences and skills via community television broadcasts. Learning in community television affords experience with different types of activities. Each role requires different skills and characteristics. In the present research we used job analysis to characterize the different experiences within the framework of community television. Job analysis is a technique for presenting detailed information on activities carried out within the framework of the job. The job analysis used in this research is based on a list of abilities, traits, skills and fields of knowledge from which the person suitable for the role should be chosen. The influence of students’ experience in community television on their creative thinking level was examined, as well as whether different experiences in community television have a different effect on the students’ creative thinking. The research population included 157 subjects who underwent a set of tests for evaluating their creative tendency (curiosity, originality, and general creativity score). All subjects experienced the production of a movie, while learning the secrets of television production and experiencing production roles according to their personal choice (director, editor, photographer, actor). The choice of experience was made according to each student’s personal choice, with the aim of enabling the expression via multiple intelligences. The tendency to creativity was measured using a tendency to creativity questionnaire [1]. After the learning and the process of producing the movie, the subjects took the same set of tests in order to examine the change that took place following this process. They were also interviewed in order to discover their opinions and feelings regarding the process they underwent. Analysis of the tests and the interviews indicates that students who experienced community television production roles improved their creative tendency level in all experience roles: director, editor, photographer and actor. An open experience system that integrates different levels of experience and active learning, autonomous learning and affords expression for multiple experiences with the aim of creating a common project in which all contribute their share towards the final product can develop the tendency for creativity among students.
Privacy-preserving handover mechanism in 4G

We propose a handover mechanism in the 4G heterogeneous network that preserves the privacy of the users. Since the base stations and relay nodes in 4G can be owned and operated by third parties, the footprints of the user can be exploited to obtain information about the movement and location of the users, which jeopardizes the user's privacy. To overcome this and hide the real user's ID, we propose to change the temporary identity (ID) of user equipment (UE) as well as the key that the UE uses in each access point to hide the real user's ID. Our analysis shows that the proposed mechanism is secure and efficient while preserving the privacy.
Immigration, Economic Disadvantage, and Homicide

In this article, the effect of recent immigration on homicide rates across city of Austin, Texas census tracts is examined. Since 1980, Austin's recent immigrant population increased by more than 580% across the metropolitan area and it is now considered a “pre-emerging” immigrant gateway city to the United States. Therefore the changing population dynamics in Austin provide an excellent opportunity to study the effect of recent immigration on homicide. After controlling for structural predictors of homicide and correcting for spatial autocorrelation, our findings indicate that recent immigration is not associated with homicide.
Effects of peroxidation products in thermoxidised dietary oil in female rats during rearing, pregnancy and lactation on their reproductive performance and the antioxidative status of their offspring

The present study was performed to investigate whether lipid peroxidation products in thermoxidised dietary oil fed during rearing, pregnancy and lactation influences the reproductive performance of female rats and the antioxidant status of their offspring. Twenty-four female rats were divided into two groups at 4 weeks of age. They were fed diets containing fresh or oxidised oil (the latter prepared by heating at a temperature of 50°C for 16 d) for 14 weeks. At the age of 12 weeks female rats were mated. The number of total pups and pups born alive was not different between both groups. However, individual pups and litters of dams fed oxidised oil were lighter at birth and gained less weight during the suckling period than those of dams fed fresh oil (P>0·05). Pups of dams fed oxidised oil contained less protein and more fat in their carcasses than those of dams fed fresh oil (P>0·05). The milk of dams fed oxidised oil had a lower concentration of triacylglycerols and a lower energy content than that of dams fed the fresh oil (P>0·05). The pups of dams fed oxidised oil had higher concentrations of lipid peroxidation products in the liver at birth and day 19 of lactation than those of dams fed fresh oil (P>0·05). In conclusion, the present study shows that feeding oxidised oil with a high concentration of lipid peroxidation products to female rats during rearing, pregnancy and lactation influences the development and antioxidant status of fetus and suckling pups.