Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic and accurate pitch marking of speech signal using an expert system based on logical combinations of different algorithms outputs

An expert system comprising a new pitch marking algorithm based on the estimation of the ideal excitation signal, using energy equalization of harmonics of the fundamental frequency present in speech, and three other competent tools is devised and explained in this paper. This expert system uses simple logical combinations of these tools outputs. The behaviour of a human expert is taken into account in developing the post-processing that is necessary to complete each tool and to further improve the results of their combinations. It is noted that, in most cases, combining the results of the new tool and the Childers method, itself based on what goes on behind hand marking by a human expert, is satisfactory. However, accurate and complete pitch marking is best achieved with all four outputs at the expense of some higher processing time.
The Influence of User Interface Attributes on Aesthetics

Abstract In this paper we present an empirical study among 40 participants which investigates the relationship between various factors of user interface aesthetics on the one hand, and the influence of the user interface attributes, symmetry, colorfulness as well as visual complexity on user interface aesthetics on the other hand. The user interface aesthetics will be classified in intuitive aesthetics (1st impression with a presentation time of 500 ms) and reflective aesthetics (reflective long-term impression after a longer presentation). Reflective aesthetics is further classified in classical aesthetics (common attractiveness) as well as expressive aesthetics (creativity). For this study we have set up a corpus of 30 websites which are used as stimulus material. In a multi-step lab experiment, participants rate aesthetics and their subjective impression concerning user interface attributes using questionnaires. We are able to show that the intuitive aesthetic judgment correlates strongly with the reflective judgment. The symmetry of a website positively correlates with all definitions of aesthetics, especially with the classical or traditional interpretation in the sense of attractiveness. Visual complexity can be seen as the strongest predictor for the aesthetic judgement of users and it negatively correlates with all definitions. Concerning colorfulness, a preference for websites of a medium degree of colorfulness for the intuitive as well as the classical aesthetics can be stated. Concerning expressive aesthetics, websites of moderate to high colorfulness receive the best judgments. The relationships which we have found are finally discussed in the context of previous research and some implications for future user interface design are given.
Phonetic Realizations of /sr/ Clusters in Latin American Spanish

In Peninsular Ibero-Romance varieties that retain postnuclear lingual fricatives before non-rhotic consonants, loss of the fricative before trills is the norm in colloquial speech. The data in (1a-c) exemplify fricative deletion in Castilian Spanish, Catalan, and Portuguese, respectively, although impressionistic descriptions in the literature often suggest concomitant lengthening of the trill, [r], or a sequence of fricative r plus trill, [r] (Navarro Tomás 1980, Recasens 1993, Vázquez and Mendes 1971). As these examples show, the targets of deletion include alveolar, interdental, and alveopalatal fricatives, as well as the fricative portion of affricates. Portuguese varieties containing a uvular trill also assimilate a preceding alveopalatal fricative, as in (1c).
Case of seasonal reassortant A(H1N2) influenza virus infection, the Netherlands, March 2018

A seasonal reassortant A(H1N2) influenza virus harbouring genome segments from seasonal influenza viruses A(H1N1)pdm09 (HA and NS) and A(H3N2) (PB2, PB1, PA, NP, NA and M) was identified in March 2018 in a 19-months-old patient with influenza-like illness (ILI) who presented to a general practitioner participating in the routine sentinel surveillance of ILI in the Netherlands. The patient recovered fully. Further epidemiological and virological investigation did not reveal additional cases.
Automated High-Speed Traffic Monitoring and Violation Detection Using RFID Technology

Traffic monitoring is a wide area in research. Several methods exist for efficient real-time monitoring of the traffic, including RFID-based and CCTV camera-based systems. Several architectures for RFID-based systems have been proposed and utilized for traffic monitoring in some countries. As far as we know, none of the existing implementations utilize the RFID technology for traffic violation detection in high-speed roads. In this paper, a new architecture of using RFID technology in high-speed roads (highways and freeways) is presented; its problems and challenges are analyzed and a number of solutions are proposed. The proposed architecture consists of four hierarchical levels: Vehicle Identification, Row-level Processing, Road-level Processing, and Control Center. Each subsystem processes data of the detected vehicle at a higher level and passes the processed data to the next subsystem in a hierarchical manner. Also in this paper three sample algorithms are proposed in order to show how the architecture works in detecting traffic violations. Keywords—Traffic Violation Detection; Traffic Monitoring; Intelligent Transportation System; RFID Application; Road Control
Module-based Synthesis of Behavioral Verilog Descriptions to Asynchronous Circuits

In this paper we present a design tool for automatic synthesis of Verilog behavioral description of an asynchronous circuit into delay insensitive presynthesized library modules, using syntax directed techniques. Our design tool can also generate appropriate output to support implementing the circuit on ASICs and LUT-based FPGAs consequently rapid prototyping of the asynchronous circuit becomes readily available using the proposed tool. General Terms Design, Languages
Collaborative 6DoF Relative Pose Estimation for Two UAVs with Overlapping Fields of View

Driven by the promise of leveraging the benefits of collaborative robot operation, this paper presents an approach to estimate the relative transformation between two small Unmanned Aerial Vehicles (UAVs), each equipped with a single camera and an inertial sensor, comprising the first step of any meaningful collaboration. Formation flying and collaborative object manipulation are some of the few tasks that the proposed work has direct applications on, while forming a variable-baseline stereo rig using two UAVs carrying a monocular camera each promises unprecedented effectiveness in collaborative scene estimation. Assuming an overlap in the UAVs' fields of view, in the proposed framework, each UAV runs monocular-inertial odometry onboard, while an Extended Kalman Filter fuses the UAVs' estimates and common image measurements to estimate the metrically scaled relative transformation between them, in realtime. Decoupling the direction of the baseline between the cameras of the two UAVs from its magnitude, this work enables consistent and robust estimation of the uncertainty of the relative pose estimation. Our evaluation on both on simulated data and benchmarking datasets consisting of real aerial data, reveals the power of the proposed methodology in a variety of scenarios. Video - https://youtu.be/AmkkaXa2601
Connect the dots by understanding user status and transitions

Human lives are composed by series of events and activities. Considerable research effort has been made to probe, sense, and understand them. In our research, we are interested in exploring the intrinsic string that connects all these events together, that is, user status and transitions. Such transitions can be reflected from multiple activity dimensions, ranging from our daily mobility trajectories, app usage sequences, to communication patterns and motion state switches. In this paper, we aim to identify whether a personalized model can be learned to capture various user states from different sensing dimensions and whether a unified view can be established to explain the state transitions that drive the changes in user context during day-to-day routines. To this end, we have explored two types of traces -- connected wifi sequences and cell location trajectories. We first model the states among these two individual dimensions. In the end, the identified states from both dimensions are linked together to recognize the spatial-temporal relationship between them. As we evaluate with the DeviceAnalyzer dataset, our method is able to recognize a range of states such as "at home", "working", "commute" and the trasitions between them, all in an unsupervised manner.
StackSync: Attribute‐based data sharing in file synchronization services

Personal Cloud (PC) storage services such as Dropbox or Google Drive have become increasingly popular in the last few years. Unfortunately, these services are still not secure. Even assuming “perfect” data confidentiality, securely sharing a folder in these services is still an issue, and this without mentioning the fact that the existing sharing mechanisms are typically too coarse‐grained by operating at the folder level. This is insufficient in many real situations where it is more natural to grant or deny access to files based on arbitrary user attributes and selected attributes of the file. In this research, we explore these issues and show that fine‐grained access control with strong privacy guarantees is practical in the PC. To investigate the potential practicality, we took our fully fledged open source implementation of a PC system and extended it to support fine‐grained private data sharing through attribute‐based encryption. The result was the first design and implementation of a file synchronization service, called StackSync, where the user retains complete control over his or her own data when sharing it. Never before, attribute‐based encryption had been implemented and tested on a real PC service. Our results show that StackSync is both secure and efficient for the PC.
A combined IEEE half and single precision floating point multipliers for deep learning

In deep learning, single precision floating point multipliers are widely used and the most power-hungry arithmetic operators. However, although multipliers are power intensive, they are necessary for applications that require multiplication. In this paper, we propose a novel combined IEEE half precision and single precision floating point multipliers for deep learning. Our design can be easily configured to run in the half precision mode for power saving or in the single precision mode for accuracy. Compared to conventional IEEE single precision multipliers, the combined multipliers require only a small amount of additional area and delay, while offer a significant reduction in power dissipation.
Cardiac-Activity Measures for Assessing Airport Ramp-Tower Controller’s Workload

Heart rate (HR) and heart rate variability (HRV) potentially offer objective, continuous, and non-intrusive measures of human-operator’s mental workload. Such measurement capability is attractive for workload assessment in complex laboratory simulations or safety-critical field testing. The present study compares mean HR and HRV data with self-reported subjective workload ratings collected during a high-fidelity human-in-the-loop simulation of airport ramp traffic control operations, which involve complex cognitive and coordination tasks. Mean HR was found to be weakly sensitive to the workload ratings, while HRV was not sensitive or even contradictory to the assumptions. Until more knowledge on stress response mechanisms of the autonomic nervous system is obtained, it is recommended that these cardiac-activity measures be used with other workload assessment tools, such as subjective measures.
Caregiver perceptions of a fruit and vegetable prescription programme for low-income paediatric patients

Abstract Objective The physical and social environments that surround children should support good health. However, challenges with food security and access prevent many children from consuming a healthy diet, which is critical to proper growth and development. The present study sought to gain a better understanding of primary care initiatives to address these issues in a low-income setting. Design Following the relocation of a paediatric clinic to a farmers’ market building and the implementation of a fruit and vegetable prescription programme, researchers conducted thirty-two semi-structured interviews with caregivers. Researchers elicited caregivers’ perceptions of clinic co-location with the farmers’ market; experiences with the prescription programme; opinions of the farmers’ market; and perceived impact on child consumption of fresh produce. Interview recordings were transcribed for textual analysis. Using thematic analysis, researchers examined qualitative data to identify patterns across transcripts and formulate emerging themes. Researchers concluded when data saturation was reached. Setting Flint, Michigan, USA. Subjects The majority of participants were female (91 %) and African American (53 %). Results Four recurrent themes emerged during interviews: (i) convenience of relocation; (ii) attitude towards prescription programme; (iii) challenges with implementation; and (iv) perceived impact of combined interventions. Caregivers indicated that the co-location and prescription programme increased family shopping at the farmers’ market, improved access to high-quality produce and improved food security. Conclusions A fruit and vegetable prescription programme involving a partnership between a farmers’ market and paediatric clinic was perceived as effective in improving food security, food access and child consumption of fresh fruits and vegetables.
Coevolution of virulence and immunosuppression in multiple infections

This preprint has been reviewed and recommended by Peer Community In Evolutionary Biology (http://dx.doi.org/10.24072/pci.evolbiol.100043). Many components of host-parasite interactions have been shown to affect the way virulence (i.e., parasite-induced harm to the host) evolves. However, coevolution of multiple parasite traits is often neglected. We explore how an immunosuppressive mechanism of parasites affects and coevolves with virulence through multiple infections. Applying the adaptive dynamics framework to epidemiological models with coinfection, we show that immunosuppression is a double-edged-sword for the evolution of virulence. On one hand, it amplifies the adaptive benefit of virulence by increasing the abundance of coinfections through epidemiological feedbacks. On the other hand, immunosuppression hinders host recovery, prolonging the duration of infection and elevating the cost of killing the host. The balance between the cost and benefit of immunosuppression varies across different background mortality rates of hosts. In addition, we find that immunosuppression evolution is influenced considerably by the precise trade-off shape determining the effect of immunosuppression on host recovery and susceptibility to further infection. These results demonstrate that the evolution of virulence is shaped by immunosuppression while highlighting that the evolution of immune evasion mechanisms deserves further research attention.
Agreement Between Visual Assessment and 2-Dimensional Analysis During Jump Landing Among Healthy Female Athletes.

CONTEXT Altered movement patterns, including increased frontal-plane knee movement and decreased sagittal-plane hip and knee movement, have been associated with several knee disorders. Nevertheless, the ability of clinicians to visually detect such altered movement patterns during high-speed athletic tasks is relatively unknown. OBJECTIVE To explore the association between visual assessment and 2-dimensional (2D) analysis of frontal-plane knee movement and sagittal-plane hip and knee movement during a jump-landing task among healthy female athletes. DESIGN Cross-sectional study. SETTING Gymnasiums of participating volleyball teams. PATIENTS OR OTHER PARTICIPANTS A total of 39 healthy female volleyball players (age = 21.0 ± 5.2 years, height = 172.0 ± 8.6 cm, mass = 64.2 ± 7.2 kg) from Divisions I and II of the Israeli Volleyball Association. MAIN OUTCOME MEASURE(S) Frontal-plane knee movement and sagittal-plane hip and knee movement during jump landing were visually rated as good, moderate, or poor based on previously established criteria. Frontal-plane knee excursion and sagittal-plane hip and knee excursions were measured using free motion-analysis software and compared among athletes with different visual ratings of the corresponding movements. RESULTS Participants with different visual ratings of frontal-plane knee movement displayed differences in 2D frontal-plane knee excursion ( P < .01), whereas participants with different visual ratings of sagittal-plane hip and knee movement displayed differences in 2D sagittal-plane hip and knee excursions ( P < .01). CONCLUSIONS Visual ratings of frontal-plane knee movement and sagittal-plane hip and knee movement were associated with differences in the corresponding 2D hip and knee excursions. Visual rating of these movements may serve as an initial screening tool for detecting altered movement patterns during jump landings.
Discriminative Deep Feature Learning for Facial Emotion Recognition

Emotion recognition is an important task in facial expression analysis with various potential applications. The goal of this task is to classify facial images into seven classes: disgust, neutral, sad, happy, fear, surprise and angry. In this paper, we propose a discriminative deep feature learning approach with dense convolutional networks (DenseNet) for facial emotion recognition. Particularly, we employ an auxiliary loss, namely center loss, to regulate the training process of neural networks in order to reduce the intra-class variation of the deep features and, hence, to enhance the discriminative power of the learned networks. The experimental results show that our proposed approach achieves superior performance in comparison with other recent state- of-the-art methods on the well-known FERC-2013 dataset.
Visual Cues : What Combinations Make for a Better User Review ?

User reviews have become a standard feature on most online shopping websites. Despite the availability of a large number of user reviews for a product, studies have shown that users typically read only the first few reviews. It is unclear what aspects of user reviews impact the decision of whether or not to purchase of a product or service. This study investigated which of the visual cues presented by user reviews are mostly likely to attract users’ attention and subsequently make the reviews have more impact on the purchasing decisions. A taxonomy was proposed for categorizing visual cues and applied in the design of a human subject experiment. Results from one online study conducted using the visual cue taxonomy were presented and the implications and benefits of considering it in the design of user review visualizations, from both a retailer and consumer’s perspective were discussed.
Genetic diversity and connectivity shape herbivore load within an oak population at its range limit

Host genetic diversity and genotypic identity have been reported to affect the abundance, species richness and species diversity of associated herbivore communities. Recent work, however, suggests that these effects are highly context-dependent and that the magnitude and direction of the effects may vary with e.g., spatial factors and the amount of genetic variation present in the host population. Here, we use observational data on a Finnish oak (Quercus robur) population to examine whether low genetic diversity within peripheral populations reduces the impact of host genotype on associated herbivore communities. We first compared measures of genetic variation within Finnish oak populations with those recorded in more central parts of the species' range, confirming that genetic variation within the Finnish populations is comparatively low. Despite this result, we found consistent imprints of host genetic diversity on herbivore communities: herbivore load, but not the species richness, increased with host genetic diversity in both years and both spatial scales examined. Spatial connectivity of hosts increased herbivore diversity as well as abundance. While the similarity of herbivore communities increased with the genetic similarity among hosts, the effect of geographic distance was stronger. Overall, our findings identify a major role for spatial context in structuring oak-associated herbivore communities—but we still trace detectable imprints of host genotype at multiple spatial scales even in this peripheral, genetically impoverished oak population.
Investigating the effect of nanofluid on optimal design of solar flat plate collector

In this work, a solar flat plate collector (FPC) was modelled and optimized. Configuration parameters of FPC were considered as design variables and optimization was performed to reach the best efficiency as well as annual cost. To improve the heat transfer rate, the CuO nanoparticle was used into the water in the tube side of FPC. The optimum results of nanofluid show a significant improvement in the both efficiency and annual cost compared by the base fluid. For example, 1.3% improvement in the efficiency was find in the nanofluid case compared with base fluid case for the constant value of cost=60$/year. On the other hand, 17.85% decreases in the annual cost was find in the nanofluid case compared with the case of pure water for the constant value of effficiency=62% Finally, optimum design parameters in each cases were compared and results were discussed.
Vegas: Software package for the atomistic simulation of magnetic materials

We present an open-source software package, Vegas, for the atomistic simulation of magnetic materials. Using the classical Heisenberg model and the Monte Carlo Metropolis algorithm, Vegas provides the required tools to simulate and analyze magnetic phenomena of a great variety of systems. Vegas stores the history of the simulation, i.e. the magnetization and energy of the system at every time step, allowing to analyze static and dynamic magnetic phenomena from results obtained in a single simulation. Also, standardized input and output file formats are employed to facilitate the simulation process and the exchange and archiving of data. We include results from simulations performed using Vegas, showing its applicability to study different magnetic phenomena.
Mesenchymal Stem Cells in Oriented PLGA/ACECM Composite Scaffolds Enhance Structure-Specific Regeneration of Hyaline Cartilage in a Rabbit Model

Articular cartilage lacks a blood supply and nerves. Hence, articular cartilage regeneration remains a major challenge in orthopedics. Decellularized extracellular matrix- (ECM-) based strategies have recently received particular attention. The structure of native cartilage exhibits complex zonal heterogeneity. Specifically, the development of a tissue-engineered scaffold mimicking the aligned structure of native cartilage would be of great utility in terms of cartilage regeneration. Previously, we fabricated oriented PLGA/ACECM (natural, nanofibrous, articular cartilage ECM) composite scaffolds. In vitro, we found that the scaffolds not only guided seeded cells to proliferate in an aligned manner but also exhibited high biomechanical strength. To detect whether oriented cartilage regeneration was possible in vivo, we used mesenchymal stem cell (MSC)/scaffold constructs to repair cartilage defects. The results showed that cartilage defects could be completely regenerated. Histologically, these became filled with hyaline cartilage and subchondral bone. Moreover, the aligned structure of cartilage was regenerated and was similar to that of native tissue. In conclusion, the MSC/scaffold constructs enhanced the structure-specific regeneration of hyaline cartilage in a rabbit model and may be a promising treatment strategy for the repair of human cartilage defects.