Miracle-dz/UniFAR-FTUs huggingface dataset:
High speed trot-running: Implementation of a hierarchical controller using proprioceptive impedance control on the MIT Cheetah

This paper presents implementation of a highly dynamic running gait with a hierarchical controller on the MIT Cheetah. The developed controller enables high-speed running of up to 6 m/s (Froude number of Fr ≈ 7.34) incorporating proprioceptive feedback and programmable virtual leg compliance of the MIT Cheetah. To achieve a stable and fast trot gait, we applied three control strategies: (a) programmable virtual leg compliance that provides instantaneous reflexes to external disturbance and facilitates the self-stabilizing shown in the passive dynamics of locomotion; (b) tunable stance-trajectory design, intended to adjust impulse at each foot-end in the stance phase in a high speed trot-running according to the equilibrium-point hypothesis; and (c) a gait-pattern modulation that imposes a desired cyclic gait-pattern taking cues from proprioceptive TD feedback. Based on three strategies, the controller is hierarchically structured. The control parameters for forward speeds, a specific gait-pattern, and desired leg trajectories are managed by a high-level controller. It consists of both a gait-pattern modulator with proprioceptive leg TD detection and a leg-trajectory generator using a Bèzier curve and a tunable amplitude sinusoidal wave. Instead of employing physical spring/dampers in the robot’s leg, the programmable virtual leg compliance is realized using proprioceptive impedance control in individual low-level leg controllers. To verify the developed controller, a robot dynamic simulator is constructed based on the model parameters of the MIT Cheetah. The controller parameters are tuned with the simulator to achieve self-stability, and then applied to the MIT Cheetah in an experimental environment. Using leg kinematics and applied motor current feedbacks, the MIT Cheetah achieved a stable trot-running gait in the sagittal plane.
Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising

The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy) and estimate the number of online views (mean error of 0.199). The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube.
Novel multifunctional near-infrared fluorescent nanoparticles: integrating nanotechnology and biophotonics

The objective of this study is to engineer a novel nanoparticlulate system for use in early tumor diagnosis. Indocyanine green (ICG)-loaded biodegradable nanoparticles were prepared by using biodegradable polymer, poly(DL-lactic-co-glycolic acid) (PLGA). The ICG entrapment, nanoparticle size, shape, zeta potential the release of ICG from nanoparticles was determined. Also, the effect of ICG entrapment on fluorescence spectra of ICG was measured. The engineered nanoparticles were nearly spherical in shape and efficiently entrapped ICG. The release profile of the nanoparticles was exponential. The entrapment of ICG in nanoparticles caused reduction in its peak fluorescence intensity and shifted its wavelength of peak fluorescence to higher values.
Automatic duration-related salience detection in Brazilian Portuguese read and spontaneous speech

This work presents an automatic prosodic salience detector algorithm which does not require the use of language-specific duration values. It is implemented in two steps: automatic detection of vowel onsets (VO) followed by the detection of normalized VO-to-VO duration peaks. The algorithm’s performance is compared to that of a semi-automatic version. Perceived salience is also compared. For both fast and slower read speech, precision and accuracy of perceived word salience are between61 and80 %. In a larger corpus of read and storytelling speech, precision is generally higher than 70 %, whereas accuracy is higher than80 % when the automatic version is compared with the semi-automatic one. The automatic algorithm’s performance is found to be similar to that of the prominence detector reported in [12].
Nonlinear Finite Element Analysis of Laminated Composite Doubly Curved Shells in Hygrothermal Environment

In the present investigation, the geometrically nonlinear analysis of laminated doubly curved shells in a hygrothermal environment is presented using the finite element method. The laminated composite shells may be exposed to moisture and temperature during their service life. Hygrothermal effects induce residual stresses and the laminated shell may undergo large bending deformation. The shell geometry used in the formulation is derived using the orthogonal curvilinear coordinate system. Based on the principle of virtual work the nonlinear finite element equations are derived. A total Lagrangian approach associated to the arc-length method is implemented to solve the equilibrium equations. The present results are found to compare well with those available in the open literature and parametric studies are performed to analyze the nonlinear deflections of [0°/±45°/90°]s laminated spherical, cylindrical and conoidal shell panels under hygrothermal condition.
Optimization of the Sliding Window Size for Protein Structure Prediction

Sliding window based methods are relatively often applied in prediction of various aspects related to protein structure. Despite their wide spread use, researchers did not establish a standard related to the size of the window, i.e., window sizes ranging between 7 and 17 residues were used in the past. To this end, this paper performs a computational study based on a probabilistic approach that aims at finding an optimal sliding window size. The results shows that formation of helical structure can be affected by amino acids (AAs) that are up to 9 positions away in the sequence, while the formation of coils and strands can be affected by AAs that are up to 3 and 6 positions away, respectively. Overall, our results suggest that a sliding window with 19 residues is optimal for secondary structure prediction, while for a specific prediction tasks, such as prediction of p-strands, a smaller window size is sufficient. Finally, the 20 AAs are categorized into five groups based on their influence of formation of the secondary structure. The finding related to the optimal window size was confirmed based on an independent experimental study related to the prediction of secondary protein structure
Shape‐memorized crosslinked ester‐type polyurethane and its mechanical viscoelastic model

A series of shape-memorized crosslinked ester-type polyurethanes (PUs), based on different compositions of 4,4′-diphenyl methane diisocyanate (MDI), poly(butylene adipate) glycol (PBAG) with different molecular weight (MW) and trimethylol propane (TMP), were synthesized. The morphology of samples was investigated by using DSC, WAXD, and dynamic mechanical analysis (DMA). It was found that the morphology of the soft segment, which was PBAG with a different MW, was in an amorphous state and no crystalline domain was found. By increasing the crosslinked density (varying the content of TMP) or decreasing the length of the soft segment (MW of PBAG), the glass transition temperature of studied samples increased. But the range of transition broadened and the modulus ratio E′−20°C)/E′+20°C) also decreased. The shape-memory behavior was studied by the bending test method adopted from the shape-memory alloy. The sample with high Tg showed not only a high recovered temperature (Tr) but also a high recovered rate (Vr) with a high modulus ratio. By introducing the chemical crosslinked structure, the deformed samples completely recovered their original shape and rendered shape-memory behavior under the complex deformation. The shape-memorized crosslinked ester-type PUs can be applied at different operating temperatures. A mechanical viscoelastic model is discussed for the shape-memory behavior of PUs, and the modified Bonart's viscoelastic model properly describes the mechanism of the shape memory of PUs. © 1999 John Wiley & Sons, Inc. J Appl Polym Sci 73: 1305–1319, 1999
Bidirectional Connectivity between Hemispheres Occurs at Multiple Levels in Language Processing But Depends on Sex

Our aim was to determine the direction of interhemispheric communication in a phonological task in regions involved in different levels of processing. Effective connectivity analysis was conducted on functional magnetic resonance imaging data from 39 children (ages 9–15 years) performing rhyming judgment on spoken words. The results show interaction between hemispheres at multiple levels. First, there is unidirectional transfer of information from right to left at the sensory level of primary auditory cortex. Second, bidirectional connections between superior temporal gyri (STGs) suggest a reciprocal cooperation between hemispheres at the level of phonological and prosodic processing. Third, a direct connection from right STG to left inferior frontal gyrus suggest that information processed in the right STG is integrated into the final stages of phonological segmentation required for the rhyming decision. Intrahemispheric connectivity from primary auditory cortex to STG was stronger in the left compared to the right hemisphere. These results support a model of cooperation between hemispheres, with asymmetric interhemispheric and intrahemispheric connectivity consistent with the left hemisphere specialization for phonological processing. Finally, we found greater interhemispheric connectivity in girls compared to boys, consistent with the hypothesis of a more bilateral representation of language in females than males. However, interhemispheric communication was associated with slow performance and low verbal intelligent quotient within girls. We suggest that females may have the potential for greater interhemispheric cooperation, which may be an advantage in certain tasks. However, in other tasks too much communication between hemispheres may interfere with task performance.
Joint Topic-Semantic-aware Social Recommendation for Online Voting

Online voting is an emerging feature in social networks, in which users can express their attitudes toward various issues and show their unique interest. Online voting imposes new challenges on recommendation, because the propagation of votings heavily depends on the structure of social networks as well as the content of votings. In this paper, we investigate how to utilize these two factors in a comprehensive manner when doing voting recommendation. First, due to the fact that existing text mining methods such as topic model and semantic model cannot well process the content of votings that is typically short and ambiguous, we propose a novel Topic-Enhanced Word Embedding (TEWE) method to learn word and document representation by jointly considering their topics and semantics. Then we propose our Joint Topic-Semantic-aware social Matrix Factorization (JTS-MF) model for voting recommendation. JTS-MF model calculates similarity among users and votings by combining their TEWE representation and structural information of social networks, and preserves this topic-semantic-social similarity during matrix factorization. To evaluate the performance of TEWE representation and JTS-MF model, we conduct extensive experiments on real online voting dataset. The results prove the efficacy of our approach against several state-of-the-art baselines.
Seamful Design and Ubicomp Infrastructure

In this paper, we discuss taking a ‘seamful’ design approach to ubicomp systems. Some features that we designers usually categorise as infrastructure problems may, to users, be useful interactional features. Examples include the edges and gaps in 802.11 coverage, and the patterns of where one can and cannot get GPS positioning. Sometimes we cannot smooth over or hide these ‘seams’. Seamfulness is about taking account of these reminders of the finite and physical nature of digital media. Seamful design involves deliberately revealing seams to users, and taking advantage of features usually considered as negative or problematic. We outline the origins of the seamful approach, offer two examples of seamful design, and finally discuss potential approaches to ‘design for appropriation’ whereby user activity drives infrastructural adaptation.
Investigation of Resonant Modes in Wideband Hybrid Omnidirectional Rectangular Dielectric Resonator Antenna

In this paper, resonant modes of the hybrid omnidirectional rectangular dielectric resonator (DR) antenna (DRA) are investigated. It is found that the omnidirectional mode of the rectangular DR is a combination of the higher-order TE∞121 and TEy211 modes. Omnidirectional patterns can be achieved by exciting the TE∞121and TEy211 modes of a rectangular DRA, which has a square cross-section, with equal amplitude and phase. Thus, the dielectric waveguide model (DWM) method can be used to predict the resonant frequency and field distributions of the omnidirectional mode of rectangular DRA. In addition, the resonance of feeding probe is also studied. And a wideband hybrid design is achieved by merging resonances of the rectangular DRA and feeding probe. Full-wave simulations and experimental measurements were carried out to verify the proposed idea. Both the simulated and measured results agree well with the calculated results.
INVESTIGATION OF THE MECHANICS OF SINGLE TOMATO FRUIT CELLS

The mechanical behavior of single tomato fruit cells has been characterized using high strain-rate microcompression testing. Single cells isolated by gentle washing from inner pericarp tissue were compressed to a wide range of deformations at a speed of 1500 μm/s, and then released. The cells were larger than any tested previously by microcompression, and had very low initial turgor. Force-deformation data were modeled to find cell wall material properties, assuming water loss during compression could be neglected because of fast compression. Repeat compression-release experiments were conducted to discover when cell deformation was no longer recoverable upon release. Cells from three commercially grown tomatoes were elastic to deformations of just over 11%. The elastic moduli of the cell walls were found by modeling to be 30 to 80 MPa, significantly lower than suspension-cultured cell walls. The cell walls yielded at about 2% wall strain. High-speed compression testing is a powerful tool for studying low turgor cells, such as those found during ripening.
Necessary Conditions for Tractability of Valued CSPs

The connection between constraint languages and clone theory has been a fruitful line of research on the complexity of constraint satisfaction problems. In a recent result, Cohen et al. [SIAM J. Comput. , 42 (2013), pp. 915--1939] have characterized a Galois connection between valued constraint languages and so-called weighted clones. In this paper, we study the structure of weighted clones. We extend the results of Creed and Živný from [Proceedings of the 17th International Conference on Principles and Practice of Constraint Programming, 2011, pp. 210--224] on types of weightings necessarily contained in every nontrivial weighted clone. This result has immediate computational complexity consequences as it provides necessary conditions for tractability of weighted clones and thus valued constraint languages. We demonstrate that some of the necessary conditions are also sufficient for tractability, while others are provably not.
Extending the spring-electrical model to overcome warping effects

The spring-electrical model based force directed algorithm is widely used for drawing undirected graphs, and sophisticated implementations can be very efficient for visualizing large graphs. However, our practical experience shows that in many cases, layout quality suffers as a result of non-uniform vertex density. This gives rise to warping effects in that vertices on the outskirt of the drawing are often closer to each other than those near the center, and branches in a tree-like graph tend to cling together. In this paper we propose algorithms that overcome these effects. The algorithms combine the efficiency and good global structure of the spring-electrical model, with the flexibility of the Kamada-Kawai stress model of in specifying the ideal edge length, and are very effective in overcoming the warping effects.
Spatio-temporal control of mutualism in legumes helps spread symbiotic nitrogen fixation

Mutualism is of fundamental importance in ecosystems. Which factors help to keep the relationship mutually beneficial and evolutionarily successful is a central question. We addressed this issue for one of the most significant mutualistic interactions on Earth, which associates plants of the leguminosae family and hundreds of nitrogen (N2)-fixing bacterial species. Here we analyze the spatio-temporal dynamics of fixers and non-fixers along the symbiotic process in the Cupriavidus taiwanensis–Mimosa pudica system. N2-fixing symbionts progressively outcompete isogenic non-fixers within root nodules, where N2-fixation occurs, even when they share the same nodule. Numerical simulations, supported by experimental validation, predict that rare fixers will invade a population dominated by non-fixing bacteria during serial nodulation cycles with a probability that is function of initial inoculum, plant population size and nodulation cycle length. Our findings provide insights into the selective forces and ecological factors that may have driven the spread of the N2-fixation mutualistic trait.
In-vivo synthetic aperture flow imaging in medical ultrasound

A new method for acquiring flow images using synthetic aperture techniques in medical ultrasound is presented. The new approach makes it possible to have a continuous acquisition of flow data throughout the whole image simultaneously, and this can significantly improve blood velocity estimation. Any type of filter can be used for discrimination between tissue and blood flow without initialization, and the number of lines used for velocity estimation is limited only by the nonstationarity of the flow. The new approach is investigated through both simulations and measurements. A flow rig is used for generating a parabolic laminar flow, and a research scanner is used for acquiring RF data from individual transducer elements. A reference profile is calculated from a mass flow meter. The parabolic velocity profile is estimated using the new approach with a relative standard deviation of 2.2% and a mean relative bias of 3.4% using 24 pulse emissions at a flow angle of 45 degrees. The 24 emissions can be used for making a full-color flow map image. An in-vivo image of flow in the carotid artery for a 29-year-old male also is presented. The full image is acquired using 24 emissions.
Meteor/Sopremo: An Extensible Query Language and Operator Model

Recently, quite a few query and scripting languages for MapReduce-based systems have been developed to ease formulating complex data analysis tasks. However, existing tools mainly provide basic operators for rather simple analyses, such as aggregating or ltering. Analytic functionality for advanced applications, such as data cleansing or information extraction can only be embedded in user-dened functions where the semantics is hidden from the query compiler and optimizer. In this paper, we present a language that treats application-specic functions as rst-class operators, so that operator semantics can be evaluated and exploited for optimization at compile time. We present Sopremo, a semantically rich operator model, and Meteor, an extensible query language that is grounded in Sopremo. Sopremo also provides a programming framework that allows users to easily develop and integrate extensions with their respective operators and instantiations. Meteor’s syntax is operator-oriented and uses a Json-like data model to support applications that analyze semi- and unstructured data. Meteor queries are translated into data ow programs of operator instantiations, i.e., concrete implementations of the involved Sopremo operators. Using a real-world example, we show how operators from dierent applications can be combined for writing complex analytical queries.
Dynamic Modelling of Tooth Deformation Using Occlusal Kinematics and Finite Element Analysis

Background Dental biomechanics based on finite element (FE) analysis is attracting enormous interest in dentistry, biology, anthropology and palaeontology. Nonetheless, several shortcomings in FE modeling exist, mainly due to unrealistic loading conditions. In this contribution we used kinematics information recorded in a virtual environment derived from occlusal contact detection between high resolution models of an upper and lower human first molar pair (M1 and M1, respectively) to run a non-linear dynamic FE crash colliding test. Methodology MicroCT image data of a modern human skull were segmented to reconstruct digital models of the antagonistic right M1 and M1 and the dental supporting structures. We used the Occlusal Fingerprint Analyser software to reconstruct the individual occlusal pathway trajectory during the power stroke of the chewing cycle, which was applied in a FE simulation to guide the M1 3D-path for the crash colliding test. Results FE analysis results showed that the stress pattern changes considerably during the power stroke, demonstrating that knowledge about chewing kinematics in conjunction with a morphologically detailed FE model is crucial for understanding tooth form and function under physiological conditions. Conclusions/Significance Results from such advanced dynamic approaches will be applicable to evaluate and avoid mechanical failure in prosthodontics/endodontic treatments, and to test material behavior for modern tooth restoration in dentistry. This approach will also allow us to improve our knowledge in chewing-related biomechanics for functional diagnosis and therapy, and it will help paleoanthropologists to illuminate dental adaptive processes and morphological modifications in human evolution.