Miracle-dz/UniFAR-FTUs huggingface dataset:
MODELING AND CONTROL OF PINCHING 2 D OBJECT WITH ARBITRARY SHAPE BY A PAIR OF ROBOT FINGERS UNDER ROLLING CONSTRAINTS

Abstract. Modeling and control of grasping an object with arbitrary shape by a pair of robot fingers with hemispherical ends in a horizontal plane are proposed in a mathematical and computational standpoint. The curvature of an object contour is variable due to the change of the contact point between the finger tip and object surface. Therefore, not only the time parameter “t” but also the arclength parameter “s” are needed to describe motion of the overall fingersobject system. It is shown that Euler-Lagrange’s equation of motion of the overall fingers-object system should be accompanied with the first-order differential equation of arclength parameter “s”, which traces out the object contour and at the same time the finger-tip circle. A control input, which is of the same category as the control input called “blind grasping”, is proposed to stabilize rotational motion of the object. The control input does neither use the kinematics information of the object nor any external sensing. Finally numerical simulations evaluate the effectiveness of the proposed model and control input.
EXAUSTÃO EMOCIONAL E RECONHECIMENTO DE EMOÇÕES NA FACE E VOZ EM MÉDICOS

This study examined the emotion recognition of pain, sadness, and happiness in the face and voice by General Practice Doctors, as a fuction of their perceived emotional exhaustion. The sample consisted of 72 physicians, and the study carried out in two stages. In the first stage, several questionnaires applied, including the Maslach Burnout Inventory to assess participant's emotional exhaustion. One week later, two tasks were presented: a facial emotion recognition (task 1) and a vocal emotion recognition in facial expressions (task 2). As expected, participants were faster and displayed a high recognition accuracy for happiness, followed by pain, in both tasks. In task 2, there was a lower accuracy, specially in the recognition of sadness, and a higher bias in the recognition of vocal pain expressions. The results from this second task were dependent on emotional exhaustion: physicians with higher emotional exhaustion were faster and showed high recognition accuracy. Overall, the results sugested a high sensitivity of
From Web to Map: Exploring the World of Music

Ever growing music collections ask for novel ways of organization. The traditional browsing of folder hierarchies or search by title and album tends to be insufficient to maintain an overview of a collection of orders of thousands of tracks. Methods based on song similarity offer an alternative to keyword-based search. In this work we propose to use a high-dimensional map of the "world of music" as a data structure for music retrieval and exploration of personal collections. Our approach does not require expensive analysis of audio signals and scales to hundreds of thousands of tracks. The techniques presented in this work can be used in a variety of applications, ranging from automatic DJs to file sharing on mobile devices. As a concrete example, we have developed a Web-application that allows users to visualize and navigate through their music collections and create playlists by specifying trajectories.
Moving object detection based on improved Gaussian mixture model

Gaussian mixture model (GMM) has been widely used for robustly modeling complicated backgrounds. A novel algorithm which can effectively resolve the problems of disturbance caused by noise and illumination mutation is proposed in this paper. Edge Gaussian mixture model method is combined with improved Neighborhood-based difference method to solve these problems and improve the performance of moving object detection. Experimental results indicate that the proposed method has great capacity in restraining noise and dealing with illumination mutation, and it is more efficient and robust than the traditional methods. The proposed method provides a reliable basis to the phase of target tracking and categorization.
A MDE Approach for Heterogeneous Models Consistency

To design a complex system, we often proceed via separation of viewpoints. Each viewpoint is described by a model that represents a domain expertise. Those partial models are generally heterogeneous (i.e conform to different metamodels) and thus performed by different designers. We proposed a matching process that links partial models through a virtual global model in order to create a complete view of the system. As models evolve, we should consider the impact of changing an element involved in a correspondence on other models to keep the coherence of the global view. So, we have defined a process that automatically identify changes, classify them and treat their potential repercussions on elements of other partial models in order to maintain the global model consistency.
Cardiovascular and eye activity measures as indices for momentary changes in mental effort during simulated flight

This study examines effects of momentary changes in mental effort on cardiovascular and eye activity measures. A total of 19 male pilots performed an instrument flight task. Task load was manipulated by having the pilots perform flight manoeuvres of varying complexity. Multilevel analyses demonstrated clear effects of momentary changes in mental effort on both the cardiovascular and the eye activity measures. An increase in task load resulted in an increase of heart rate and a decrease in heart rate variability, mean dwell time and fixation duration. Heart rate differentiated between resting period and task execution. Heart rate variability from short data segments provided more insight in intermediate levels of mental effort. The eye activity measures were sensitive to intermediate levels of mental effort as well. Attitude changes resulted in an increase of mean dwell time and mean fixation duration. Task analysis is required to use eye measures as valid indices of mental effort. Having indications of the effects of changing mental demands during daily work of operators is of great importance nowadays. This paper presents an approach to estimate such effects on the basis of heart rate and eye activity measures. In particular, the use of averaged short-term heart rate variability measures is a relatively new aspect.
Evaluation of a Multicommuted Flow System for Photometric Environmental Measurements

A portable flow analysis instrument is described for in situ photometric measurements. This system is based on light-emitting diodes (LEDs) and a photodiode detector, coupled to a multipumping flow system. The whole equipment presents dimensions of 25 cm × 22 cm × 10 cm, weighs circa 3 kg, and costs 650 €. System performance was evaluated for different chemistries without changing hardware configuration for determinations of (i) Fe3+ with SCN-, (ii) iodometric nitrite determination, (iii) phenol with sodium nitroprusside, and (iv) 1-naphthol-N-methylcarbamate (carbaryl) with p-aminophenol. The detection limits were estimated as 22, 60, 25, and 60 ng mL -1 for iron, nitrite, phenol, and carbaryl at the 99.7% confidence level with RSD of 2.3, 1.0, 1.8, and 0.8%, respectively. Reagent and waste volumes were lower than those obtained by flow systems with continuous reagent addition. Sampling rates of 100, 110, 65, and 72 determinations per hour were achieved for iron, nitrite, phenol, and carbaryl determinations
Pieri rules for the K-theory of cominuscule Grassmannians

Abstract We prove Pieri formulas for the multiplication with special Schubert classes in the K-theory of all cominuscule Grassmannians. For Grassmannians of type A this gives a new proof of a formula of Lenart. Our formula is new for Lagrangian Grassmannians, and for orthogonal Grassmannians it proves a special case of a conjectural Littlewood–Richardson rule of Thomas and Yong. Recent work of Clifford, Thomas, and Yong has shown that the full Littlewood–Richardson rule for orthogonal Grassmannians follows from the Pieri case proved here. We describe the K-theoretic Pieri coefficients both as integers determined by positive recursive identities and as the number of certain tableaux. The proof is based on a computation of the sheaf Euler characteristic of triple intersections of Schubert varieties, where at least one Schubert variety is special.
A Novel Acoustic Feature Extraction Algorithm Based on Root Cepstrum Coefficients and CCBC for Robust Speech Recognition

Studies have shown that depending on speaker task and environmental conditions, recognizers are sensitive to noisy stressful environments. The focus of this study is to achieve robust recognition in diverse environmental conditions through extracting robust features. Central to the technique is Root Cepstrum Coefficients (RCC) method, instead of logarithm amplitude spectrum and discrete cosine transform of the conventional Mel Frequency Cepstral Coefficients (MFCC), but also using Two-dimensional Root Cepstrum Coefficients (TDRCC). This feature is called TDRCC-MFCC. And then, we consider incorporating Canonical Correlation Based Compensation (CCBC) to cope with the mismatch between training and test set. The mismatch between training and test conditions can be simply clustered into three classes: differences of speakers, changes of recording channel and effects of noisy environment. We evaluate the technique using Back-Propagation Neural Networks (BPNN) on two different tasks: one is in-car speech recognition task, another is different SNR speech recognition. The experimental results show that the novel feature has very good robustness and effectiveness relative to MFCC feature and the CCBC algorithm can make speech recognition system greatly robust to all three kinds of mismatch between training set and test set.
Temporal Expression Patterns of Genes Related to Sex Steroid Action in Sexually Dimorphic Nuclei During Puberty

Sex steroids play a major role in sexually dimorphic brain development during not only the perinatal period but also the pubertal period. We previously showed that, in male mice, the estrogen receptor-α (Esr1) and aromatase (Cyp19a1) genes are essential to the sexually dimorphic formation of the anteroventral periventricular nucleus (AVPV) and the principal nucleus of the bed nucleus of the stria terminalis (BNSTp), but the estrogen receptor-β (Esr2) gene is not necessary. We also showed that the androgen receptor (Ar) gene is essential to the sexually dimorphic formation of the BNSTp. These genes are expressed in the AVPV and BNSTp of perinatal mice. However, it remains unknown whether these genes are expressed in the AVPV and BNSTp during puberty, and whether the expression, if any, differs by sex, age, and brain region. Here, we dissected the AVPV and BNSTp from Nissl-stained brain sections of male and female mice on postnatal day (PD) 20 (prepuberty), PD30 (puberty onset in females), PD40 (puberty onset in males), and PD60 (young adult) using a laser microdissection system. We then examined the mRNA levels of Esr1, Esr2, Cyp19a1, and Ar in these brain regions. In the AVPV, Esr1 mRNA levels were greater in females than males during PD20–60. Esr2 and Ar mRNA expressions did not differ between sexes. Ar mRNA levels were higher at PD30 than PD20. Cyp19a1 mRNA was not detected in the AVPV at PD20–60. In the BNSTp, Esr1 and Esr2 mRNA levels were higher in females than in males during PD20–60, although the mRNA levels of Cyp19a1 and Ar did not differ between sexes. Additionally, we revealed that orchiectomy at PD20 induced a failure of normal formation of the male BNSTp and testosterone replacement in the prepubertal period rescued the effect of orchiectomy at PD20. Taken together, it is suggested that pubertal testosterone transported to the AVPV is not converted to estradiol there and does not act via ESR1 and ESR2. By contrast, the formation of the male BNSTp may be affected by testicular testosterone during puberty via AR and/or via ESR1 after conversion to estradiol by CYP19A1.
Where to be wary: The impact of widespread photo-taking and image enhancement practices on users' geo-privacy

Today's geo-location estimation approaches are able to infer the location of a target image using its visual content alone. These approaches exploit visual matching techniques, applied to a large collection of background images with known geo-locations. Users who are unaware that visual retrieval approaches can compromise their geo-privacy, unwittingly open themselves to risks of crime or other unintended consequences. Private photo sharing is not able to protect users effectively, since its inconvenience is a barrier to consistent use, and photos can still fall into the wrong hands if they are re-shared. This paper lays the groundwork for a new approach to geo-privacy of social images: Instead of requiring a complete change of user behavior, we investigate the protection potential latent in users existing practices. We carry out a series of retrieval experiments using a large collection of social images (8.5M) to systematically analyze where users should be wary, and how both photo taking and editing practices impact the performance of geo-location estimation. We find that practices that are currently widespread are already sufficient to protect single-handedly the geo-location ('geo-cloak') up to more than 50% of images whose location would otherwise be automatically predictable. Our conclusion is that protecting users against the unwanted effects of visual retrieval is a viable research field, and should take as its starting point existing user practices.
Selection of preimplantation embryos using time‐lapse microscopy in in vitro fertilization: State of the technology and future directions

In this review, our aim is to give an overview of the state of the technology and clinical outcomes of time‐lapse microscopy in improving embryo selection as a key step in in vitro fertilization (IVF). Using traditional incubators, morphologic assessment of the fertilized embryos is limited to snapshots at a few discrete points in time, reducing the amount of information that could potentially be obtained. Time‐lapse monitoring overcomes this limitation without exposing the embryos to environmental changes. Moreover, time‐lapse may introduce new dynamic markers of embryo competence as well as a versatile embryo evaluation and provides novel information regarding human embryo development. In the last few years, various algorithms have been developed correlating the kinetics of early embryo development to blastocyst formation, implantation potential, chromosomal content and live birth rate. There is not yet a universally accepted algorithm, and significant knowledge gaps remain that can provide opportunities for further research in this field.
Data‐driven Evaluation of Visual Quality Measures

Visual quality measures seek to algorithmically imitate human judgments of patterns such as class separability, correlation, or outliers. In this paper, we propose a novel data‐driven framework for evaluating such measures. The basic idea is to take a large set of visually encoded data, such as scatterplots, with reliable human “ground truth” judgements, and to use this human‐labeled data to learn how well a measure would predict human judgements on previously unseen data. Measures can then be evaluated based on predictive performance—an approach that is crucial for generalizing across datasets but has gained little attention so far. To illustrate our framework, we use it to evaluate 15 state‐of‐the‐art class separation measures, using human ground truth data from 828 class separation judgments on color‐coded 2D scatterplots.
Astronomical calibration of the geological timescale: closing the middle Eocene gap

Abstract. To explore cause and consequences of past climate change, very accurate age models such as those provided by the astronomical timescale (ATS) are needed. Beyond 40 million years the accuracy of the ATS critically depends on the correctness of orbital models and radioisotopic dating techniques. Discrepancies in the age dating of sedimentary successions and the lack of suitable records spanning the middle Eocene have prevented development of a continuous astronomically calibrated geological timescale for the entire Cenozoic Era. We now solve this problem by constructing an independent astrochronological stratigraphy based on Earth's stable 405 kyr eccentricity cycle between 41 and 48 million years ago (Ma) with new data from deep-sea sedimentary sequences in the South Atlantic Ocean. This new link completes the Paleogene astronomical timescale and confirms the intercalibration of radioisotopic and astronomical dating methods back through the Paleocene–Eocene Thermal Maximum (PETM, 55.930 Ma) and the Cretaceous–Paleogene boundary (66.022 Ma). Coupling of the Paleogene 405 kyr cyclostratigraphic frameworks across the middle Eocene further paves the way for extending the ATS into the Mesozoic.
A Prediction Based Two-Layered Scheduling Approach for Uncertain Scheduling of Hot Strip Mill

In this paper, the uncertain scheduling problem of hot strip mill (HSM) is studied, in which the uncertainty of slab supply is considered. We propose a prediction based two-layered scheduling approach (PTLSA) which contains an offline optimization layer and an online adjustment layer. In the offline optimization layer, the arrival probability of each slab group is first predicted by the relevance vector machine (RVM), and then a hybrid harmony search (HHS) algorithm is proposed to generate a predictive rolling round. In the online adjustment layer, if some slab cannot arrive during the execution of the predictive rolling round, an online adjustment rule is designed to select another slab belonging to the same group in order to replace the one cannot arrive. Computational results on industrial data have demonstrated the effectiveness of PTLSA under the uncertain production environment.
Recovering Volatility from Option Prices by Evolutionary Optimization

We propose a probabilistic approach for estimating parameters of an option pricing model from a set of observed option prices. Our approach is based on a stochastic optimization algorithm which generates a random sample from the set of global minima of the in-sample pricing error and allows for the existence of multiple global minima. Starting from an IID population of candidate solutions drawn from a prior distribution of the set of model parameters, the population of parameters is updated through cycles of independent random moves followed by selection according to pricing performance. We examine conditions under which such an evolving population converges to a sample of calibrated models. The heterogeneity of the obtained sample can then be used to quantify the degree of ill-posedness of the inverse problem: it provides a natural example of a coherent measure of risk, which is compatible with observed prices of benchmark (vanilla) options and takes into account the model uncertainty resulting from incomplete identification of the model. We describe in detail the algorithm in the case of a diffusion model, where one aims at retrieving the unknown local volatility surface from a finite set of option prices, and illustrate its performance on simulated and empirical data sets of index options.
Modular Performance Analysis of Energy-Harvesting Real-Time Networked Systems

This paper studies the performance analysis problem of energy-harvesting real-time network systems in the Real-Time Calculus (RTC) framework. The behavior of an energy-harvesting node turns out to be a generalization of two known components in RTC: it behaves like an AND connector if the capacitor used to temporally store surplus energy has unlimited capacity and there is no energy loss, while it behaves like a greedy processing component (GPC) if the size of the capacitor is zero and thus surplus energy is lost or passed to other nodes immediately. In this paper, methods are developed to analyze the worst-case performance, in terms of delay and backlog, of energy-harvesting nodes as well as compute upper/lower bounds of their data and energy outputs. Moreover, with the proposed analysis methods, we disclose some interesting properties of the worst-case behaviors of energy-harvesting systems, which provide useful information to guide system design. Experiments are conducted to evaluate our theoretical contributions and also confirm that the disclosed properties are not just the result of our analysis, but indeed hold in realistic system behaviors.
VISUALIZATION OF FUNCTIONAL MAGNETIC RESONANCE IMAGES THROUGH SELF-ORGANIZING MAPS

Functional activations in the human brain are being studied through various imaging tools, and FMRI is a new tool with growing popularity. Comparison and interpretation of FMRI image sets collected from different people, through different imaging platforms, is a diff icult problem. In this paper, transformation of FMRI images to an abstract domain, SOM, is studied as a preliminary step for performing inter-subject image registration on abstract parameters in the future.
A toolkit enabling efficient, scalable and reproducible gene tagging in trypanosomatids

One of the first steps in understanding a protein's function is to determine its localization; however, the methods for localizing proteins in some systems have not kept pace with the developments in other fields, creating a bottleneck in the analysis of the large datasets that are generated in the post-genomic era. To address this, we developed tools for tagging proteins in trypanosomatids. We made a plasmid that, when coupled with long primer PCR, can be used to produce transgenes at their endogenous loci encoding proteins tagged at either terminus or within the protein coding sequence. This system can also be used to generate deletion mutants to investigate the function of different protein domains. We show that the length of homology required for successful integration precluded long primer PCR tagging in Leishmania mexicana. Hence, we developed plasmids and a fusion PCR approach to create gene tagging amplicons with sufficiently long homologous regions for targeted integration, suitable for use in trypanosomatids with less efficient homologous recombination than Trypanosoma brucei. Importantly, we have automated the primer design, developed universal PCR conditions and optimized the workflow to make this system reliable, efficient and scalable such that whole genome tagging is now an achievable goal.
Cordycepin Induced MA-10 Mouse Leydig Tumor Cell Apoptosis through Caspase-9 Pathway

In the present study, the apoptotic effect of cordycepin on MA-10 cells, a mouse Leydig tumor cell line, was investigated. Results demonstrated that the number of rounding-up cell increased by cordycepin (10 μM to 5 mM for 24 h), and cells with plasma membrane blebbing could be observed by 100 μM cordycepin. In viability test, MA-10 cell surviving rate significantly decreased as the dosage (10 μM to 5 mM) and duration (3–24 h) of cordycepin treatment increased (P < 0.05). Cordycepin at 100 μM and 1 mM for 24 h treatment induced significant DNA fragmentation (P < 0.05). In addition, the percentage of G1 and G2/M phase cell significantly declined by cordycepin (100 μM and 1 mM) for 24 h treatment, while the percentages of subG1 phase cell increased by 100 μM and/or 1 mM cordycepin in 6, 12 and 24 h treatments (P < 0.05), respectively, which highly suggested that cordycepin induced MA-10 cell apoptosis. In mechanism study with the treatments of caspases, c-Jun NH2 terminal kinase (JNK) or reactive oxygen species (ROS) inhibitors plus cordycepin for 24 h, only caspases inhibitor suppressed subG1 phase in MA-10 cells. Moreover, western blotting results showed that cordycepin induced caspase-9, -3 and -7 protein expressions, but not caspase-8, in time- and dose-dependent manners. In conclusion, cordycepin induced apoptosis in MA-10 mouse Leydig tumor cells through a caspase-9 and -3 and -7 dependent pathway.