Miracle-dz/UniFAR-FTUs huggingface dataset:
Panoramic 3 D Reconstruction Using Rotating Camera with Planar Mirrors

In this paper, we propose a novel approach for obtaining 3D information of panoramic (360 degrees) environments. We design an image acquisition rig composed with a camera and two planar mirrors. The regular image captured by the camera is separated into uncontinuous three regions by the mirrors arranged in front of the camera. By rotating the rig about a vertical axis with a constant velocity, we acquire a sampled spaciotemporal volume which is made of the sequential images captured by a uniform angular interval. We estimate a panoramic depth map, which has the same density (spatial resolution) as the regular images, by extracting trajectories of 3D points from the uniformly sampled spacio-temporal volume using a multibaseline stereo technique with considering occlusions. Our approach can be considered as stereo reconstruction from a large number of multiperspective panoramas acquired by three rotating cameras. Compared with a previous approach using two multiperspective panoramas from a single rotating camera, our approach has advantages as follows: A large baseline length is available; Matching errors due to image noise, repeated patterns, and occlusions are reduced by the multibaseline stereo technique; We use a certain amount of the angular interval for fast image accumulation, instead of a small interval required in the previous approach for dense depth estimation. Additionally, our approach is available as an image mosaicing technique to create dense multiperspective panoramas. Experimental results using both synthetic and real images show that our approach produces high quality panoramic 3D reconstruction.
A Case Study of Active, Continuous and Predictive Social Media Analytics for Smart City

Imagine you are in Milano for the Design Week. You have just spent a couple of days attending few nice events in Brera district. Which of the other hundreds of events spread around in Milano shall you attend now? This paper presents a system able to recommend venues to the visitors of such a city-scale event based on the digital footprints they left on Social Media. By combining deductive and inductive stream reasoning techniques with visitor-modeling functionality, this system semantically analyses and links visitors' social network activities to produce high-quality recommendations even when information about visitors' preferences for venues and events is sparse.
Multi-sensor based fall prediction method for humanoid robots

This paper proposes a multi-sensor based method to predict the falling of the humanoid in a reliable and agile manner. The fusion of multi-sensors such as an inertial measurement unit and foot pressure sensors are considered, which can be regarded as human's vestibular and proprioception. We define a set of feature-based fall indicator variables (FIVs) with manually extracted thresholds for four major disturbance scenarios, which are incorporated with an online threshold interpolation technique to manage generic disturbances. Indeed, a general falling is predicted by using a normalized value of the instantaneous and cumulative sum of each FIVs compared to a predefined set-value of the falling indication. The proposed method is evaluated by numerical experiments under 36 different scenarios, involving random disturbances applied at distinct heights. The results depict that the developed method is generic in terms of handling disturbances as well as different configurations of the robot and the use of fused FIVs performs better than that of a single FIV; in particular, the fusion with the foot pressure sensor based indicator increases the overall performance of the prediction.
Fundamental Frequency Estimation in the SMS analysis

The particular approach of SMS is based on modeling sounds as stable sinusoids (partials) plus noise (residual component), therefore analyzing sounds with this model and generating new sounds from the analyzed data. The analysis procedure detects partials by studying the time-varying spectral characteristics of a sound and represents them with time-varying sinusoids. These partials are then subtracted from the original sound and the remaining “residual” is represented as a time-varying filtered white noise component [1].
Hop-Based Energy Aware Routing Algorithm for Wireless Sensor Networks

Energy efficient routing is one of the key design issues to prolong the lifetime of wireless sensor networks (WSNs) since sensor nodes can not be easily re-charged once they are deployed. During routing process, the routes with only few hops or with too many hops are not energy efficient. Hop-based routing algorithms can largely improve the energy efficiency of multi-hop routing in WSNs because they can determine the optimal hop number as well as the corresponding intermediate nodes during multi-hop routing process under medium or high density network. In this paper, we not only focus on studying the relationship between energy consumption and hop number from theoretical point of view but also provide a practical selection criterion of the sub-optimal hop number under practical sensor network so as to minimize the energy consumption. We extend the theoretical deduction of optimal hop number and propose our Hop-based Energy Aware Routing (HEAR) algorithm which is totally distributed and localized. Simulation results show that our HEAR algorithm can reduce the average energy consumption about 10 times compared to the direct transmission algorithm and 2 to 10 times than other algorithms like LEACH and HEED under various network topologies.
Participation and Deliberation on the Internet: A Case Study of Digital Participatory Budgeting in Belo Horizonte

Esse artigo busca avaliar trocas discursivas realizadas no forum online do orcamento participativo digital (OPD) de Belo Horizonte, Brasil. Para tanto, e formulado um modelo de analise das discussoes entre os cidadaos participantes do programa baseado nas teorias de democracia deliberativa. Sao analisadas as mensagens dos usuarios (n=375) postadas na ferramenta de comentarios do site do OPD. Os resultados apontam que os aspectos discursivos concernentes a reciprocidade e a reflexividade se mostraram relativamente escassos; entretanto, o respeito pelos outros interlocutores, bem como a construcao da justificativa dos pontos de vista expressos no forum, alcancaram indices elevados, mesmo nao havendo empowerment da ferramenta ou incentivo por parte da Prefeitura. Conclui-se que a internet pode, efetivamente, oferecer ambientes voltados para o estabelecimento de trocas discursivas qualificadas e que, mesmo nos casos onde ha baixos indices de deliberatividade, ha progressos importantes do ponto de vista do aprendizado a que sao expostos os usuarios.
Polyphonic sound event detection using multi label deep neural networks

In this paper, the use of multi label neural networks are proposed for detection of temporally overlapping sound events in realistic environments. Real-life sound recordings typically have many overlapping sound events, making it hard to recognize each event with the standard sound event detection methods. Frame-wise spectral-domain features are used as inputs to train a deep neural network for multi label classification in this work. The model is evaluated with recordings from realistic everyday environments and the obtained overall accuracy is 63.8%. The method is compared against a state-of-the-art method using non-negative matrix factorization as a pre-processing stage and hidden Markov models as a classifier. The proposed method improves the accuracy by 19% percentage points overall.
Navidget for immersive virtual environments

We present a novel interaction technique called Immersive Navidget for navigation in immersive virtual environments (VE), see Figure 1. This technique, based on Navidget, allows fast and easy 3D camera positioning from simple controls. In this paper, we focus on the technical issues that are induced by the VR setups and we propose solutions to adapt Navidget to the immersive context. We show that this new approach has many advantages for navigation in immersive VEs.
Relational Parametricity for Linear System F ◦

This paper presents a novel syntactic logical relation for System F◦, a simple variant of the linear polymorphic λcalculus. We define a logical relation for open values under both open linear and unrestricted contexts, then extend it for open terms with evaluation and open relation substitutions. Relations that instantiate type quantifiers are for open terms and types. We demonstrate the applicability of this logical relation through its soundness with respect to contextual equivalence, along with free theorems for linearity that are difficult to achieve by closed logical relations. When interpreting types on only closed terms, the model defaults to a closed logical relation that is both sound and complete with respect to contextual equivalence, and is sufficient to reason about isomorphisms of type encodings. The idea of using open logical relations also extends easily to more traditional formulations of polymorphic linear type systems that use the ! type constructor.
Addressing Early Life Sensitivity Using Physiologically Based Pharmacokinetic Modeling and In Vitro to In Vivo Extrapolation

Physiologically based pharmacokinetic (PBPK) modeling can provide an effective way to utilize in vitro and in silico based information in modern risk assessment for children and other potentially sensitive populations. In this review, we describe the process of in vitro to in vivo extrapolation (IVIVE) to develop PBPK models for a chemical in different ages in order to predict the target tissue exposure at the age of concern in humans. We present our on-going studies on pyrethroids as a proof of concept to guide the readers through the IVIVE steps using the metabolism data collected either from age-specific liver donors or expressed enzymes in conjunction with enzyme ontogeny information to provide age-appropriate metabolism parameters in the PBPK model in the rat and human, respectively. The approach we present here is readily applicable to not just to other pyrethroids, but also to other environmental chemicals and drugs. Establishment of an in vitro and in silico-based evaluation strategy in conjunction with relevant exposure information in humans is of great importance in risk assessment for potentially vulnerable populations like early ages where the necessary information for decision making is limited.
Enriched Population of PNS Neurons Derived from Human Embryonic Stem Cells as a Platform for Studying Peripheral Neuropathies

Background The absence of a suitable cellular model is a major obstacle for the study of peripheral neuropathies. Human embryonic stem cells hold the potential to be differentiated into peripheral neurons which makes them a suitable candidate for this purpose. However, so far the potential of hESC to differentiate into derivatives of the peripheral nervous system (PNS) was not investigated enough and in particular, the few trials conducted resulted in low yields of PNS neurons. Here we describe a novel hESC differentiation method to produce enriched populations of PNS mature neurons. By plating 8 weeks hESC derived neural progenitors (hESC-NPs) on laminin for two weeks in a defined medium, we demonstrate that over 70% of the resulting neurons express PNS markers and 30% of these cells are sensory neurons. Methods/Findings Our method shows that the hNPs express neuronal crest lineage markers in a temporal manner, and by plating 8 weeks hESC-NPs into laminin coated dishes these hNPs were promoted to differentiate and give rise to homogeneous PNS neuronal populations, expressing several PNS lineage-specific markers. Importantly, these cultures produced functional neurons with electrophysiological activities typical of mature neurons. Moreover, supporting this physiological capacity implantation of 8 weeks old hESC-NPs into the neural tube of chick embryos also produced human neurons expressing specific PNS markers in vivo in just a few days. Having the enriched PNS differentiation system in hand, we show for the first time in human PNS neurons the expression of IKAP/hELP1 protein, where a splicing mutation on the gene encoding this protein causes the peripheral neuropathy Familial Dysautonomia. Conclusions/Significance We conclude that this differentiation system to produce high numbers of human PNS neurons will be useful for studying PNS related neuropathies and for developing future drug screening applications for these diseases.
A blind image restoration algorithm based on nonlocal means and EM algorithm

In the classical image restoration problem, the point spread function (PSF) is known. However, in many cases the PSF is unknown. In this case, image restoration is called blind image restoration. Blind image restoration algorithms can be divided into two categories: First, we estimate PSF through the image feature, and then the image is restored with the estimated PSF; second, the identification of PSF and image restoration are combined. The EM algorithm belongs to the latter. But when there is large noise, the result of the EM algorithm is poor. The nonlocal means (NL-means) algorithm has excellent denoising ability. In this article, first of all we use the NL-means algorithm to filter the noisy image. Then we use the result as input to the EM algorithm, which can solve the instability problem of EM algorithm caused by large noise. Experimental results show that this method can recover the original image and the PSF accurately.
Bilateral kinematic indicators of the specific hip and knee postural adaptation of handball players

Purpose: Considering the everyday training, handball players promote specific postural adaptation. Determining of postural and functional unilateral sports inherent asymmetry could improve the performance and provide injury prevention. The aim of this study was to examine whether there were significant differences in hip and knee range of motion (ROM), in all planes, between stance and kicking leg of handball players. Methods: Research was conducted in the Laboratory for biomechanics of the Institute of Kinesiology at the Faculty of Kinesiology, University of Zagreb, during May 2016. Assessment was performed in 2 stages, on a randomized sample comprised of 25 male subjects, age ranging from 19 to 24 years with a mean 21.8. Participants were recruited from the population of students who train handball 10.44 ± 3 years. Based on the short version of the International Physical Activity Questionnaire (IPAQ), a high level of physical activity of the participants was determined. Kinematic measurements were performed through the Modified Thomas Test (MTT), which is standard for sagittal evaluation of the passive hip extension and knee flexion, giving the information on the flexibility of monoarticular and biarticular hip flexors, whose segmental postural adaptation can generate end movements in other planes. Therefore, the sample of variables were 4 angles: knee flexion and hip extension, rotation and abduction, all bilaterally.The research was performed using automatized optoelectronic kinematic measurement system ELITE 2002 (BTS Bioengineering Corp., Milano) with 8 cameras, frequency 100 Hz and 9 passive markers placed at bony prominences. Data processing was done using the Smart Analyzer software package. Since distribution showed normality, the t-test for independent samples was used. Calculations were performed using Statistica 12 software package. Results: Kicking leg was more mobile in the hip, through the extension ROM (2.36°, p=0.18), and especially in the frontal plane where significantly higher abduction angle was found (2.55°, p=0.03). Knee ROM was greater for the stance leg, although no significance was found (1.56°, p=0.45). Posture in the horizontal plane was neutral for both legs. Conclusions: Handball players are characterized by greater mobility of the kicking leg in the hip. With the exception of hip abduction, this study has not found that multi-year handball training forms a postural adaptation of the lower extremities with significant bilateral asymmetries. Bilateral kinematic indicators determined in this study could contribute to a better understanding of the role of segmental hip and knee movements in posture, postural adaptation and locomotion of handball players, and provide guidelines for the prevention and rehabilitation of neuromuscular deficits and their consequences.
Chapter 2 Random Dynamical Systems with Inputs

This work introduces a notion of random dynamical systems with inputs, providing several basic definitions and results on equilibria and convergence. It also presents a “converging input to converging state” (“CICS”) result, a concept that plays a key role in the analysis of stability of feedback interconnections, for monotone systems.
Multiple Mechanisms of Anti-Cancer Effects Exerted by Astaxanthin

Astaxanthin (ATX) is a xanthophyll carotenoid which has been approved by the United States Food and Drug Administration (USFDA) as food colorant in animal and fish feed. It is widely found in algae and aquatic animals and has powerful anti-oxidative activity. Previous studies have revealed that ATX, with its anti-oxidative property, is beneficial as a therapeutic agent for various diseases without any side effects or toxicity. In addition, ATX also shows preclinical anti-tumor efficacy both in vivo and in vitro in various cancer models. Several researches have deciphered that ATX exerts its anti-proliferative, anti-apoptosis and anti-invasion influence via different molecules and pathways including signal transducer and activator of transcription 3 (STAT3), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and peroxisome proliferator-activated receptor gamma (PPARγ). Hence, ATX shows great promise as chemotherapeutic agents in cancer. Here, we review the rapidly advancing field of ATX in cancer therapy as well as some molecular targets of ATX.
The Potential of Painting: Unlocking Disenfranchised Grief for People Living With Dementia

As part of the Creative Well program at a local health board, one of the authors qualitatively investigated how painting can access a means of communication for people living with dementia. In a workshop setting within a gallery environment, participants living with dementia were facilitated on a one-to-one basis the opportunity to paint alongside the researcher. During the workshops, a number of experiences were articulated. These included experiences of illness, crisis, and loss. They were captured through observations, interviews, visual art, and video to contribute to new understandings and models of engagement through art for people living with dementia and their carers. Focusing on theory and practice in arts-based research and the social sciences, this article investigates the potential of painting to unlock experiences such as disenfranchised grief for people living with dementia. The conclusions of this article do not measure how and if participants felt disenfranchised grief but rather provide an alternative to augment the body of knowledge surrounding how people living with dementia can communicate feelings of disenfranchised grief through painting.
A Latent-Class Model for Clustering Incomplete Linear and Circular Data in Marine Studies

Identication of representative regimes of wave height and direc- tion under dierent wind conditions is complicated by issues that relate to the specication of the joint distribution of variables that are dened on linear and circular supports and the occurrence of missing values. We take a latent-class approach and jointly model wave and wind data by a nite mixture of conditionally independent Gamma and von Mises distributions. Maximum-likelihood estimates of parameters are obtained by exploiting a suitable EM algorithm that allows for missing data. The proposed model is validated on hourly marine data obtained from a buoy and two tide gauges in the Adriatic Sea.
Plasmid Flux in Escherichia coli ST131 Sublineages, Analyzed by Plasmid Constellation Network (PLACNET), a New Method for Plasmid Reconstruction from Whole Genome Sequences

Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ–proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.
A multiple hill climbing approach to software module clustering

Automated software module clustering is important for maintenance of legacy systems written in a 'monolithic format' with inadequate module boundaries. Even where systems were originally designed with suitable module boundaries, structure tends to degrade as the system evolves, making re-modularization worthwhile. This paper focuses upon search-based approaches to the automated module clustering problem, where hitherto, the local search approach of hill climbing has been found to be most successful. In the paper we show that results from a set of multiple hill climbs can be combined to locate good 'building blocks' for subsequent searches. Building blocks are formed by identifying the common features in a selection of best hill climbs. This process reduces the search space, while simultaneously 'hard wiring' parts of the solution. The paper reports the results of an empirical study that show that the multiple hill climbing approach does indeed guide the search to higher peaks in subsequent executions. The paper also investigates the relationship between the improved results and the system size.
The Covariance Structure of Earnings in Great Britain, 1991-1999

I analyse the dynamic structure of earnings in Great Britain for the period 1991-99 by decomposing the earnings covariance structure into its permanent and transitory components. According to the British Household Panel Study data, earnings inequality of male full-time employees increases over the 1990s. However, earnings mobility may have also increased. That is, for this period earnings persistence falls. This evidence is at odds with previous literature on earnings dynamics both for Britain and other OECD countries. Moreover, human capital and job related characteristics account for nearly all persistent earnings differences and the transitory component is highly persistent. Copyright The London School of Economics and Political Science 2003.