Miracle-dz/UniFAR-FTUs huggingface dataset:
Extrapair paternity in relation to sexual ornamentation, arrival date, and condition in a migratory bird

We tested the novel hypothesis that arrival date in migratory birds represents a reliable indicator of male quality that can be used by females as a cue in extrapair mating decisions. Secondary sexual characters are often condition-dependent, and competition for early arrival leads to condition-dependent migration. Hence, both secondary sexual characters and arrival date are predicted to be condition-dependent indicators of male phenotypic quality. We studied the relationship between expression of a secondary sexual character, arrival date, and condition, respectively, and extrapair paternity in a Spanish population of barn swallows, Hirundo rustica. By using microsatellite markers to determine paternity, we showed that 17.8% of all offspring (N e 674) and 32.4% of all broods (N e 170) were due to extrapair paternity. Quasi-parasitism (in which the male nest owner fathered the offspring, but the eggs were laid by another female) occurred in 2.6% of all nestlings and 2.9% of all broods. Individuals were consistent in the frequency of extrapair paternity among first, second, and third broods. Males with long outermost tail feathers, arriving early and in prime body condition, had little extrapair paternity in their nests. This was also the case when controlling for the confounding effects of male age. Partial correlation analysis was used to investigate the direct and indirect effects of tail length, arrival date, and body condition on extrapair paternity. Body condition accounted for most of the variance in extrapair paternity, whereas tail length and arrival date accounted for a smaller proportion of the variance. Body condition was strongly correlated with tail length and arrival date. However, because females cannot directly assess condition or arrival date (males arrive before females), females may obtain an indirect measure of condition and migration ability from tail length and other phenotypic traits of males. This suggests that extrapair paternity depends on the effects of condition, through its indirect effects on arrival date, tail length, and other variables. Copyright 2003.
Do Eye Movements During Shape Discrimination Reveal an Underlying Geometric Structure

Using a psychophysical approach coupled with eye-tracking measures, we varied length and width of shape stimuli to determine the objective parameters that corresponded to subjective determination of square/rectangle judgments. Participants viewed a two-dimensional shape stimulus and made a two-alternative forced-choice whether it was a square or rectangle. Participants’ gaze was tracked throughout the task to explore directed visual attention to the vertical and horizontal axes of space. Behavioral results provide threshold values for two-dimensional square/rectangle perception, and eye-tracking data indicated that participants directed attention to the major and minor principal axes. Results are consistent with the use of the major and minor principal axis of space for shape perception and may have theoretical and empirical implications for orientation via geometric cues.
Optimal User Scheduling in Energy Harvesting Wireless Networks

We consider a wireless network where multiple energy harvesting transmitters communicate with the common receiver in a time-sharing manner. In each slot, a transmitter can either harvest energy or send its data to the receiver. Given a time deadline, the goal is to maximize the sum rate of transmitters under random energy arrivals with both perfect and imperfect channel state information at the receiver. The original sum-rate maximization (SRM) problem is a non-convex mixed integer non-linear program (MINLP). To obtain the optimal scheduling policy, we first reduce the original optimization problem to a convex MINLP and solve it using the generalized Benders decomposition algorithm. We observe that the SRM problem results in an unfair rate allocation among transmitters, i.e., the transmitter closer to the receiver achieves a higher rate than that by the transmitter farther from the receiver. Hence, to induce fairness among transmitters, we consider the minimum-rate maximization (MRM) problem. For the bounded channel estimation error, we obtain a robust scheduling policy by solving the worst-case SRM and MRM problems. Finally, we compare the proposed policies with myopic policies studied in the literature and show that the former outperform the latter in terms of achievable rates.
Global optimization approach for the climbing problem of multi-stage launchers

This paper deals with a problem of trajectory optimization of the flight phases of a threestage launcher. The aim of this optimization problem is to minimize the consumption of ergols that is need to steer the launcher from the Earth to the GEO. Here we use a global optimization procedure based on Hamilton-Jacobi-Bellman (HJB) approach. An interesting by-product of the HJB approach is the synthesis of the optimal control in feedback form. Once the HJB equation is solved, for any starting point, the reconstruction of the optimal trajectory can be performed in real time. We aim at showing that combining several new techniques for the HJB approach we can obtain efficient solutions to a fully nonlinear control problem. The global optimization procedure proposed here takes also into account parametric optimisation that appears in the flight phases. Several recent advanced numerical techniques for HJB equations (high order finite difference schemes, parallel computing) are used to solve a 6-dimensional optimal control problem within a reasonable CPU time. This work has been carried out in the frame of CNES Launchers’ Research and Technology program
On-board state of health estimation for lithium-ion batteries based on random forest

Precise estimation of state of health (SOH) for lithium-ion batteries is critical to improve the state of charge (SOC) estimation precision, guarantee safety and improve the usage lifetime. In this paper, considering actual usage of lithiumion battery in electrical vehicles (EVs), a novel SOH estimation method is proposed based on the dataset of partial charging voltage under the constant-current (CC) mode and current value under the constant voltage (CV) mode. A random forest (RF) model is built to perform the battery SOH estimation, whose number of regression trees and number of input variables per node are optimized by the out of bag (OOB) estimation. In addition, the support vector machine (SVM) and least squares support vector machine (LSSVM) are employed for comparison of the SOH estimation accuracy. The results show that RF can achieve more accurate estimation of SOH, compared with those based on the SVM and LSSVM.
Probabilistic Model-Driven Recovery in Distributed Systems

Automatic system monitoring and recovery has the potential to provide effective, low-cost ways to improve dependability in distributed software systems. However, automating recovery is challenging in practice because accurate fault diagnosis is hampered by monitoring tools and techniques that often have low fault coverage, poor fault localization, detection delays, and false positives. In this paper, we present a holistic model-based approach that overcomes these challenges and enables automatic recovery in distributed systems. To do so, it uses theoretically sound techniques including Bayesian estimation and Markov decision theory to provide controllers that choose good, if not optimal, recovery actions according to a user-defined optimization criteria. By combining monitoring and recovery, the approach realizes benefits that could not have been obtained by using them in isolation. We experimentally validate our framework by fault injection on realistic e-commerce systems.
User-Sensitive Recommendation Ensemble with Clustered Multi-Task Learning

This paper considers recommendation algorithm ensembles in a user-sensitive manner. Recently researchers have proposed various effective recommendation algorithms, which utilized different aspects of the data and different techniques. However, the "user skewed prediction" problem may exist for almost all recommendation algorithms -- algorithms with best average predictive accuracy may cover up that the algorithms may perform poorly for some part of users, which will lead to biased services in real scenarios. In this paper, we propose a user-sensitive ensemble method named "UREC" to address this issue. We first cluster users based on the recommendation predictions, then we use multi-task learning to learn the user-sensitive ensemble function for the users. In addition, to alleviate the negative effects of new user problem to clustering users, we propose an approximate approach based on a spectral relaxation. Experiments on real-world datasets demonstrate the superiority of our methods.
Nutrition transition in Morocco

Abstract Objective: To analyse the nutritional transition in Morocco. Design: Examination of Moroccan national survey data. Results: Morocco is undergoing a demographic, epidemiological and social transition. The urban population increased from 29% in 1960 to 53% in 1997. Per capita gross domestic product increased steadily from 1972 to 1999. Life expectancy at birth increased to 70 years in 1999 from 47 years in 1962. Both infant and juvenile mortalities have decreased, from 92/1000 and 69/1000 in 1982–87 to 46/1000 and 37/1000 in 1992–97, respectively. In parallel, the diet changed considerably: the intake of animal products increased while that of cereals and sugar remained relatively high, reflecting the specificity of Moroccan dietary habits. The rise in the consumption of meats and vegetables was accompanied by a steady consumption of bread, used to eat the sauce in which the meat and vegetables are cooked. Sugar is mainly used in tea, the very sweet, national drink consumed throughout the day. Under-nourishment persists among children under five (23% stunting and 10% underweight in 1997) while overweight is rising (9% in 1997 compared with 3% in 1987 for children under three). Among adults, overweight (body mass index (BMI) > 25 kgm−2) increased from 26% in 1984 to 36% in 1998. It is higher among women (32% in 1984 and 45% in 1998) than among males (19% in 1984 and 25% in 1998). It is also higher among urban populations (30% in 1984 and 40% in 1998) than rural populations (20% in 1984 and 29% in 1998). Obesity (BMI > 30 kgm−2) increased from 4% in 1984 to 10% in 1998. Overweight seems to be positively associated with economic status but negatively with education level. Conclusion: Overweight and obesity constitute major health problems in Morocco.
ethod development for the separation of monoclonal antibody harge variants in cation exchange chromatography , Part II : pH radient approach

The cation exhange pH gradient approach was evaluated for the characterization of 10 model monoclonal antibodies including panitumumab, natalizumab, cetuximab, bevacizumab, trastuzumab, rituximab, palivizumab, adalimumab, denosumab and ofatumumab. This work shows that retention and resolution can be modelled in cation exchange pH gradient mode, based on only four initial runs (i.e. two gradient times and two mobile phase temperature). Only 6 h were required for a complete method optimization when using a 100 mm × 4.6 mm strong cation exchange column. The accuracy of the predictions was excellent, with an average difference between predicted and experimental retention times of about 1%.
Supported Biomimetic Membranes for Pressure-Driven Water Purification

The desalination technology of choice today is reverse osmosis (RO). In this process saline water is forced using mechanical pressure across a membrane that can selectively pass water and reject almost all ions and most neutral molecules. Reverse osmosis proved to be robust and most energy efficient technology that can be exploited for a wide range of water sources. Nevertheless water desalination is still an energy intensive process. Theoretical calculations show that the minimum required energy for seawater desalination is about 1 kW hr m-3, whereas the most energy optimized plants require 2-4 kWh m-3, suggesting that there is much room for improving the membranes performance and energy efficiency (Shannon et al. 2008). Despite the numerous improvements the RO membranes have gone through over the last 5 decades, they are still inferior to cell membranes both in terms of permeability and, especially, selectivity. The fast and selective water transport in biological membranes is achieved by means of aquaporins, specialized trance-membrane proteins. The osmotic water permeability of aquaporins was shown to be in the range of 6×10-14 11×10-14 cm3 sec-1 channel-1 for AQP1 (Saparov et al. 2001) and their ion rejection exceeds by far the ion rejection of the most advanced commercial membranes. Estimates show that a biomimetic lipid bilayer with incorporated aquaporins with a lipids to protein ratio (LPR) of 50, would yield a membrane with a hydraulic permeability of ~9 – 16.5 L m-2 hr-1 bar-1 whereas the permeability of seawater RO membrane does not exceed 2 L m-2 hr-1 bar-1 (Kaufman, Berman & Freger 2010). Biological membranes are also known to reject small molecules, such as urea or boric acid, which are poorly removed by commercial membranes (Borgnia et al. 1999). The combination of ultra-selectivity with extremely high water permeability makes biomimetic membranes highly attractive for water purification applications. It is important to emphasize that water transport through biological membranes, usually existing as microscopic free-standing self-supporting structures, is usually driven by electrochemical potential gradients, i.e. osmotic pressure or electric field (Tanaka, Sackmann 2005). However, for practical membrane applications, such as water purification, the use of hydraulic pressure as a driving force and planar membranes of macroscopic dimensions, the common configuration in membrane technology, will be far more preferable. However, the preparation of such biomimetic membranes poses a number of challenging questions, such as: how can one prepare a large and defect-free biomimetic planar membrane? can they be made to withstand hydraulic pressures? how can aquaporins be incorporated in such membranes? will aquaporins keep their activity under a hydraulic pressure gradient?
RULLS: Randomized Union of Locally Linear Subspaces for Feature Engineering

Feature engineering plays an important role in the success of a machine learning model. Most of the effort in training a model goes into data preparation and choosing the right representation. In this paper, we propose a robust feature engineering method, Randomized Union of Locally Linear Subspaces (RULLS). We generate sparse, non-negative, and rotation invariant features in an unsupervised fashion. RULLS aggregates features from a random union of subspaces by describing each point using globally chosen landmarks. These landmarks serve as anchor points for choosing subspaces. Our method provides a way to select features that are relevant in the neighborhood around these chosen landmarks. Distances from each data point to $k$ closest landmarks are encoded in the feature matrix. The final feature representation is a union of features from all chosen subspaces. The effectiveness of our algorithm is shown on various real-world datasets for tasks such as clustering and classification of raw data and in the presence of noise. We compare our method with existing feature generation methods. Results show a high performance of our method on both classification and clustering tasks.
The Effects of Moderate Intensity Strength Training Coupled with Blood Flow Restriction: A 12 Week Intervention

i ACKNOWLEDGEMENTS . iii TABLE OF CONTENTS . iii LIST OF TABLES . vi LIST OF FIGURES . vii LIST OF APPENDICES . viii LIST OF ABBREVIATIONS . ix Chapter
GraphIt - A High-Performance DSL for Graph Analytics

The performance bottlenecks of graph applications depend not only on the algorithm and the underlying hardware, but also on the size and structure of the input graph. Programmers must try different combinations of a large set of techniques to develop the best implementation for a specific algorithm and type of graph. Existing graph frameworks lack flexibility, supporting only a limited set of optimizations. This paper introduces GraphIt, a new DSL for graph computations that generates fast implementations for algorithms with different performance characteristics running on graphs with different sizes and structures. GraphIt separates what is computed (algorithm) from how it is computed (schedule). Programmers specify the algorithm using an algorithm language, and performance optimizations are specified using a scheduling language. The algorithm language simplifies expressing the algorithms. We formulate graph optimizations, including edge traversal direction, data layout, parallelization, cache, NUMA, and kernel fusion optimizations, as tradeoffs among locality, parallelism, and work-efficiency. The scheduling language enables programmers to easily search through this complicated tradeoff space by composing together optimizations. We also built an autotuner to automatically find high-performance schedules. The compiler uses a new scheduling representation, the graph iteration space, to model, compose, and ensure the validity of the large number of optimizations. GraphIt outperforms the next fastest of six state-of-the-art shared-memory frameworks (Ligra, Green-Marl, GraphMat, Galois, Gemini, and Grazelle) on 24 out of 32 experiments by up to 4.8$\times$, and is never more than 43% slower than the fastest framework on the other experiments. GraphIt also reduces the lines of code by up to an order of magnitude compared to the next fastest framework.
Wireless Interconnect in Multilayer Chip-Area-Networks for Future Multimaterial High-Speed Systems Design

Wireless chip area network which enables wireless communication among chips fosters development in wireless communication and it is envisioned that future hardware system and developmental functionality will require multimaterial. However, the traditional system architecture is limited by channel bandwidth-limited interfaces, throughput, delay, and power consumption and as a result limits the efficiency and system performance. Wireless interconnect has been proposed to overcome scalability and performance limitations of multihop wired architectures. Characterization and modeling of channel become more important for specification of choice of modulation or demodulation techniques, channel bandwidths, and other mitigation techniques for channel distortion and interference such as equalization. This paper presents an analytical channel model for characterization, modeling, and analysis of wireless chip-to-chip or interchip interconnects in wireless chip area network with a particular focus on large-scale analysis. The proposed model accounts for both static and dynamic channel losses/attenuation in high-speed systems. Simulation and evaluation of the model with experimental data conducted in a computer desktop casing depict that proposed model matched measurement data very closely. The transmission of EM waves via a medium introduces molecular absorption due to various molecules within the material substance. This model is a representative of channel loss profile in wireless chip-area-network communication and good for future electronic circuits and high-speed systems design.
Low-memory convolutional neural networks through incremental depth-first processing

We introduce an incremental processing scheme for convolutional neural network (CNN) inference, targeted at embedded applications with limited memory budgets. Instead of processing layers one by one, individual input pixels are propagated through all parts of the network they can influence under the given structural constraints. This depth-first updating scheme comes with hard bounds on the memory footprint: the memory required is constant in the case of 1D input and proportional to the square root of the input dimension in the case of 2D input.
Fibrodysplasia Ossificans Progressiva: A Review with Presentation of a Case with Temporomandibular Extra-Articular Ankylosis

Fibrodysplasia Ossificans Progressiva (FOP) is a connective tissue disorder that progressively affects tendons, ligaments, aponeurosis, fasciae and muscles which undergo fibrous cell proliferation that progresses to mature bone. It has a prevalence of 1 case per 2 million habitants, having reported less than 1000 cases worldwide. In the maxillofacial region, it might originate extra-articular temporomandibular ankylosis by ossification of ligaments, muscles of the mastication, head and a neck muscles; the most commonly affected are the masseters and sternocleidomastoids. The purpose of this article is to review the Fibrodysplasia Ossificans Progressiva (FOP) and to present the case of a 12-year-old male patient with FOP that causes extra-articular temporomandibular ankylosis. There is no effective proven treatment or prevention and the life expectancy of these patients approaches the 40 years of age, so the management of patients with FOP must be performed with a multidisciplinary approach in which the various health professionals work in a coordinated and joint way to offer a better quality of life to these patients and thus better understand the progression of the disease.
Medium or Message: Communications Medium as a Determinant of Interpersonal Evaluation*

A review of studies of interpersonal attraction as related to the transmission of various nonverbal cues indicates that there is some evidence for a relationship, but the external validity of many of these studies is marred by the limited form of the communication allowed -usually one-way only -and by the unnatural and stereotyped nature of the communications. The use of various communications media is suggested as a method of overcoming these limitations, and an experiment demonstrating the effect of communications medium upon evaluations of a conversation and the conversation partner is reported. A post hoc hypothesis is advanced to explain an unexpected effect of conversation task in this experiment.
The Effect of PUFA-Rich Plant Oils and Bioactive Compounds Supplementation in Pig Diet on Color Parameters and Myoglobin Status in Long-Frozen Pork Meat

The study evaluated the effect of pig diet supplementation with rapeseed or linseed oil, and vitamin E or selenium, or both vitamin E and selenium on color parameters and myoglobin content of pork Semimembranosus muscle after long-term freezing storage during nine months. The influence of the type of the bioactive compounds added to pig diet on the content of myoglobin or oxymyoglobin, metmyoglobin and deoksymyoglobin in Semimembranosus m. was also assessed. The results indicate that the presence of oils rich in polyunsaturated fatty acids (PUFA) in pig diet improves the color of pork meat. Supplementation of dietary plant oils or dietary oils with antioxidants tended to increase significantly the concentration of oxymyoglobin and decrease the concentration of metmyoglobin in meat compared to the control group. The highest content of oxymyoglobin was observed in meat obtained from pigs fed diets with linseed oil. The best color scores (highest a* parameter) was noted for rapeseed oil group (with no addition of antioxidants). In conclusion, the addition of antioxidants to pigs’ forage supplemented with PUFA-rich oils is not recommended in order to improve color of long-term frozen pork.