Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks

Rotation-invariant face detection, i.e. detecting faces with arbitrary rotation-in-plane (RIP) angles, is widely required in unconstrained applications but still remains as a challenging task, due to the large variations of face appearances. Most existing methods compromise with speed or accuracy to handle the large RIP variations. To address this problem more efficiently, we propose Progressive Calibration Networks (PCN) to perform rotation-invariant face detection in a coarse-to-fine manner. PCN consists of three stages, each of which not only distinguishes the faces from non-faces, but also calibrates the RIP orientation of each face candidate to upright progressively. By dividing the calibration process into several progressive steps and only predicting coarse orientations in early stages, PCN can achieve precise and fast calibration. By performing binary classification of face vs. non-face with gradually decreasing RIP ranges, PCN can accurately detect faces with full 360Â° RIP angles. Such designs lead to a real-time rotation-invariant face detector. The experiments on multi-oriented FDDB and a challenging subset of WIDER FACE containing rotated faces in the wild show that our PCN achieves quite promising performance.
Entropy-based abnormal activity detection fusing RGB-D and domotic sensors

The automatic detection of anomalies in Active and Assisted Living (AAL) environments is important for monitoring the wellbeing and safety of the elderly at home. The integration of smart domotic sensors (e.g. presence detectors) and those ones equipping modern mobile robots (e.g. RGB-D cameras) provides new opportunities for addressing this challenge. In this paper, we propose a novel solution to combine local activity levels detected by a single RGB-D camera with the global activity perceived by a network of domotic sensors. Our approach relies on a new method for computing such a global activity using various presence detectors, based on the concept of entropy from information theory. This entropy effectively shows how active a particular room or environment's area is. The solution includes also a new application of Hybrid Markov Logic Networks (HMLNs) to merge different information sources for local and global anomaly detection. The system has been tested with a comprehensive dataset of RGB-D and domotic data containing data entries from 37 different domotic sensors (presence, temperature, light, energy consumption, door contact), which is made publicly available. The experimental results show the effectiveness of our approach and its potential for complex anomaly detection in AAL settings.
An ICA-based method for the segmentation of pigmented skin lesions in macroscopic images

Segmentation is an important step in computer-aided diagnostic systems for pigmented skin lesions, since that a good definition of the lesion area and its boundary at the image is very important to distinguish benign from malignant cases. In this paper a new skin lesion segmentation method is proposed. This method uses Independent Component Analysis to locate skin lesions in the image, and this location information is further refined by a Level-set segmentation method. Our method was evaluated in 141 images and achieved an average segmentation error of 16.55%, lower than the results for comparable state-of-the-art methods proposed in literature.
A wearable system for the seismocardiogram assessment in daily life conditions

Seismocardiogram (SCG) is the recording of the minute body accelerations induced by the heart activity, and reflects mechanical aspects of heart contraction and blood ejection. So far, most of the available systems for the SCG assessment are designed to be used in a laboratory or in controlled behavioral and environmental conditions. In this paper we propose a modified version of a textile-based wearable device for the unobtrusive recording of ECG, respiration and accelerometric data (the MagIC system), to assess the 3d sternal SCG in daily life. SCG is characterized by an extremely low magnitude of the accelerations (in the order of g × 10−3), and is masked by major body accelerations induced by locomotion. Thus in daily life recordings, SCG can be measured whenever the subject is still. We observed that about 30 seconds of motionless behavior are sufficient for a stable estimate of the average SCG waveform, independently from the subject's posture. Since it is likely that during spontaneous behavior the subject may stay still for at least 30 seconds several times in a day, it is expected that the SCG could be repeatedly estimated and tracked over time through a prolonged data recording. These observations represent the first testing of the system in the assessment of SCG out of a laboratory environment, and open the possibility to perform SCG studies in a wide range of everyday conditions without interfering with the subject's activity tasks.
The Patterning of Sub‐500 nm Inorganic Oxide Structures

Elastomeric perfluoropolyether molds are applied to pattern arrays of sub-500 nm inorganic oxide features. This versatile soft-lithography technique can be used to pattern a wide range of materials; in this work inorganic oxides including TiO2 , SnO2 , ZnO, ITO, and BaTiO3 are patterned on a variety of substrates with different aspect ratios. An example of TiO2 posts is shown in the figure.
Weight cycling and mortality among middle-aged or older women.

BACKGROUND Controversy exists about whether weight cycling increases morbidity and mortality. METHODS To assess the independent association of weight cycling with mortality, we conducted a prospective study of 44 882 middle-aged or older women in the Nurses' Health Study who provided information on intentional weight losses between 1972 and 1992, survived until at least 1994, had a body mass index (calculated as weight in kilograms divided by height in meters squared) of at least 17, and had no history of cancer (other than nonmelanoma skin cancer) or heart disease. Women who reported they had intentionally lost at least 9.1 kg at least 3 times were classified as severe weight cyclers. Women who had intentionally lost at least 4.5 kg at least 3 times but did not meet the criteria for severe weight cycling were classified as mild weight cyclers. All-cause mortality and cardiovascular mortality were assessed. RESULTS Between 1972 and 1992, approximately 18.8% of the women were mild weight cyclers, and 8.0% were severe weight cyclers. During 12 years of follow-up, 2884 women died; of their deaths, 425 were due to cardiovascular events. Weight cyclers gained more weight during follow-up than noncyclers (P < .001). After adjusting for BMI at age 18 years, physical activity, smoking, postmenopausal hormone replacement therapy, alcohol intake, net weight change from age 18 years, and change in physical activity, there was no increase in risk of all-cause mortality among mild (relative risk [RR], 0.83; 95% confidence interval [CI], 0.75-0.93) or severe cyclers (RR, 0.89; 95% CI, 0.77-1.04). Similar results were observed for cardiovascular mortality and among women 70 years or younger. CONCLUSION Repeated intentional weight losses were not predictive of greater all-cause or cardiovascular mortality.
Brain-aware wireless networks: Learning and resource management

Human-centric applications such as virtual reality and immersive gaming will be central to the future wireless networks. Common features of such services include: a) their dependence on the human user's behavior and state and b) their need for more network resources compared to conventional cellular applications. To successfully deploy such applications over wireless and cellular systems, the network must be made cognizant of the human in the loop. In this paper, a concrete measure for the delay perception of human users in a wireless network is defined. Then, a new learning method called probability distribution identification is introduced to find a probabilistic model for this delay perception. A novel approach based on Lyapunov optimization is proposed for allocating radio resources to human users while considering their brain's delay perception model. Simulation results show that a brain-aware approach can yield savings of up to 37% in power compared to the system that only considers quality of service metrics.
Fabrication of designed materials using direct metal deposition

An investigation was made into the ability of Direct Metal Deposition (DMD) to fabricate multi-material objects designed to meet specific engineering purposes (Designed Materials.) One series of experiments looked into the ability of DMD to make a functionally gradient material from copper and nickel. It determined that the composition of powder fed to the work area matched the composition of the deposit. Gradients were demonstrated in the x- and z-direction. The second experiment tested the use of DMD to build a structure designed using Homogenization Design Method, a structural optimization technique. The structure of interest had an overall negative coefficient of thermal expansion as its design characteristic. Two structures were fabricated using DMD. Both showed initial contraction, followed by resumption of expansion after the temperature reached 75 °C in the x-direction, and over 200 °C in the y-direction.An investigation was made into the ability of Direct Metal Deposition (DMD) to fabricate multi-material objects designed to meet specific engineering purposes (Designed Materials.) One series of experiments looked into the ability of DMD to make a functionally gradient material from copper and nickel. It determined that the composition of powder fed to the work area matched the composition of the deposit. Gradients were demonstrated in the x- and z-direction. The second experiment tested the use of DMD to build a structure designed using Homogenization Design Method, a structural optimization technique. The structure of interest had an overall negative coefficient of thermal expansion as its design characteristic. Two structures were fabricated using DMD. Both showed initial contraction, followed by resumption of expansion after the temperature reached 75 °C in the x-direction, and over 200 °C in the y-direction.
Multivariate differentiation of parapatric and allopatric populations of threespine stickleback in the Sangan River watershed, Queen Charlotte Islands

A discriminant analysis was made of 17 morphometric and 10 meristic characters in the freshwater form (leiurus) of threespine stickleback (Gasterosteus aculeatus) from 16 localities in the Sangan River System on the Queen Charlotte archipelago and in the presumed ancestral form (trachurus) from a nearby locality in marine waters. While multivariate means were significantly different between trachurus and leiurus, there was even greater differentiation between the leiurus populations found in lakes, ponds, and streams, divergence which was independent of geographical distance between localities. Statistical removal of meristics, removal of body length, log transformation and size standardization of all morphometries did not substantially alter the discrimination of the populations. Two of the leiurus populations that overlap in a narrow zone appear to have achieved reproductive isolation.
Learning and Obeying Conflicting Norms in Stochastic Domains

Artificial agents will need to be able to reason about and obey human moral and social norms. Additionally, agents must be able to learn norms, both from instruction (e.g., by natural language interaction with humans) and by observing the behavior of humans or other agents. This is necessary because (1) humans have many moral and social norms, perhaps too many to be able to pre-program; and (2) moral and social norms may vary between cultures, and across time. Both of these challenges – obeying moral and social norms, and learning them – are complicated by the fact that such norms may conflict. When an agent’s norms cannot all be satisfied, that agent should be able to “minimize the badness” of their behaviors in some principled way. Norm conflicts also make learning norms (e.g., from behavior) more difficult, since (1) the agent will need to learn preferences between norms as well as the norms themselves (in case of future conflict), and (2) the observed behaviors may be a compromise between inconsistent normative principles. Our work addresses the problem of learning (from behavior) and obeying potentially-conflicting norms in stochastic domains. In particular, we represent moral and social norms as statements in Linear Temporal Logic (LTL), and we employ the framework of Markov Decision Processes (MDPs).
The Curitiba Statement on Health Promotion and Equity: Italian version and analysis of criticalities.

BACKGROUND The Curitiba Statement of health promotion and equity is the main result of the World Conference on International Union for Health Promotion and Education (IUHPE - UIPES), held in May 2016 in Curitiba. The Curitiba Statement is the outcome of a participatory process, result of collaboration of all conference participants. The Curitiba Statement represents the continuity from Ottawa Charter for Health Promotion. This document remembers and asks to International Organizations, Governments, at all levels of the Institutions, the Health Sector, Citizens and Health Professionals and Researchers to change and eliminate all forms of discrimination and exclusion. STUDY DESIGN Description of the translation and validation process. METHODS The translation process from Spanish and English is based on the translation techniques enumerated by Fawcett in 1997: borrowing, calque, literal translation, transposition, modulation, reformulation, adaptation. RESULTS The translation process produced some critical issues shifting from English to Italian: the most critical words and expressions correspond to the more significant ones of the Curitiba Statement, and these issues are reflected in research, politics and practice. In particular, we analyzed the translation of Inequity, Advocate, and Players, and then discussed their use in different expressions in the original text. CONCLUSION Considering the Curitiba Statement's message has to be transversal, and it is addressed not only to Professionals but to all Citizens, researchers have made the choice of a clear translation for the Italian readers, not always similar to English form, but consistent and faithful in its content. To spread the culture and practice of Health Promotion, a deep attention in the translation of international documents could allow the propagation of ideas and strategies, from global to local.
Alignment of software product management and software architecture with discussion models

How to achieve alignment of software product management with software architecture and whether there is a business case for doing so is scientifically unknown. Yet, software architecture has large, direct impact on product success factors: creating a winning product and delivering value to customers. In this exploratory case study paper we identify the most critical processes for SPM and SA alignment: requirements gathering and refinement. These processes require effective communication supported by high level architectural views. Our respondents, however, rely on simple methods due to their negative experiences with formalized models. Based on these findings, we propose the Accurate Architectural Models Approach (AAMA) which prevents architectural model divergence.
Reduction methods in semidefinite and conic optimization

Conic optimization, or cone programming, is a subfield of convex optimization that includes linear, second-order cone, and semidefinite programming as special cases. While conic optimization problems arise in a diverse set of fields (including machine learning, robotics, and finance), efficiently solving them remains an active area of research. Developing methods that detect and exploit useful structure-such as symmetry, sparsity, or degeneracy-is one research topic. Such methods include facial and symmetry reduction, which have been successful in several applications, often reducing solve time by orders of magnitude. Nevertheless, theoretical and practical barriers preclude their general purpose use: to our knowledge, no solver uses facial or symmetry reduction as an automatic preprocessing step. This thesis addresses some of these barriers in three parts: the first develops more practical facial reduction techniques, the second proposes a more powerful and computationally efficient generalization of symmetry reduction (which we call Jordan reduction), and the third specializes techniques to convex relaxations of polynomial optimization problems. Throughout, we place emphasis on semidefinite programs and, more generally, optimization problems over symmetric cones. We also present computational results.
Air pollution and mortality from cardiovascular disease in a population living near by a steel producing plant in Brazil

This study aimed to evaluate the effects of air pollution on deaths from cardiovascular diseases of the Volta Redonda citizens, Brazil, from January 2002 to December 2006. This period was chosen to assess the impact of a national policy Environmental Health Surveillance related to Air Quality. The epidemiological study design was an ecological time series frame work using daily counts of deaths for cardiovascular diseases for the total population and the elderly. Daily levels of PM10, SO2 and O3, minimum temperature and relative humidity were regarded in the analysis. Generalized Additive Models under the Poisson assumption was the model framework. The results showed an increase risk of death for an increase of 10µg/m3 of PM10 at lag 2 of 3.67% (95%CI: 0.20 – 7.26%) in the total population and 5.23% (95%CI: 0.85 – 9.81%) for the elderly, respectively. As for exposures to SO2 and O3, the risk was not significant for the total population or for the elderly.
Estimating latent feature-feature interactions in large feature-rich graphs

Real-world complex networks describe connections between objects; in reality, those objects are often endowed with some kind of features. How does the presence or absence of such features interplay with the network link structure? Although the situation here described is truly ubiquitous, there is a limited body of research dealing with large graphs of this kind. Many previous works considered homophily as the only possible transmission mechanism translating node features into links. Other authors, instead, developed more sophisticated models, that are able to handle complex feature interactions, but are unfit to scale to very large networks. We expand on the MGJ model, where interactions between pairs of features can foster or discourage link formation. In this work, we will investigate how to estimate the latent feature-feature interactions in this model. We shall propose two solutions: the first one assumes feature independence and it is essentially based on Naive Bayes; the second one, which relaxes the independence assumption assumption, is based on perceptrons. In fact, we show it is possible to cast the model equation in order to see it as the prediction rule of a perceptron. We analyze how classical results for the perceptrons can be interpreted in this context; then, we define a fast and simple perceptron-like algorithm for this task, which can process $10^8$ links in minutes. We then compare these two techniques, first with synthetic datasets that follows our model, gaining evidence that the Naive independence assumptions are detrimental in practice. Secondly, we consider a real, large-scale citation network where each node (i.e., paper) can be described by different types of characteristics; there, our algorithm can assess how well each set of features can explain the links, and thus finding meaningful latent feature-feature interactions.
Development of Electron Holography and Its Applications to Fundamental Problems in Physics

We can now utilize the wave properties of electrons to conduct fundamental experiments on quantum mechanics because of the development of brighter electron beams as well as the ability directly to image the quantum world by utilizing the phase information of electrons. In this paper, we describe new possibilities that have been generated by electron-phase microscopy using electron microscopes equipped with coherent yet bright electron beams.
Comparative anatomy and development of pectoral and pelvic girdles in hylid anurans

The development of the tetrapod pectoral and pelvic girdles is intimately linked to the proximal segments of the fore‐ and hindlimbs. Most studies on girdles are osteological and provide little information about soft elements such as muscles and tendons. Moreover, there are few comparative developmental studies. Comparative data gleaned from cleared‐and‐stained whole mounts and serial histological sections of 10 species of hylid frogs are presented here. Adult skeletal morphology, along with bones, muscles, and connective tissue of both girdles and their association with the proximal portions of the anuran fore‐ and hindlimbs are described. The data suggest that any similarity could be attributable to the constraints of their ball‐and‐socket joints, including incorporation of the girdle and stylopodium into a single developmental module. An ancestral state reconstruction of key structures and developmental episodes reveals that several development events occur at similar stages in different species, thereby preventing heterochronic changes. The medial contact of the halves of the pectoral girdle coincides with the emergence of the forelimbs from the branchial chamber and with the total differentiation of the linkage between the axial skeleton and the girdles. The data suggest that morphogenic activity in the anterior dorsal body region is greater than in the posterior one, reflecting the evolutionary sequence of the development of the two girdles in ancient tetrapods. The data also document the profound differences in the anatomy and development of the pectoral and pelvic girdles, supporting the proposal that the pectoral and pelvic girdles are not serially homologous, as was long presumed.
Process-based approach reveals directional effects of environmental factors on movement between habitats.

1. Understanding the effects of environmental factors on animal distributions is a central issue in ecology. However, movement rules inferred from distribution patterns do not reveal the processes through which animal distribution is realized. 2. We investigated individual movement rules using a process-based approach. In experiments, coastal fish larvae (red drum, Sciaenops ocellatus) were matched with an intraspecific competitor of different sizes, and time series of habitat transition of individuals were fitted with a continuous-time Markov chain model to evaluate the effects of the presence of a competitor, behavioural interactions and habitat quality on the likelihoods of habitat transition. 3. The process-based approach revealed that these factors did not simply act as a 'slope' between habitats that makes it easier to go in one direction and more difficult to return. Rather, these factors modify the movement rules differently depending on the directions of the movement. 4. Individuals were less likely to enter a better habitat in the presence of a larger conspecific, more likely to shift to a poorer habitat when they received aggressive behaviour and more likely to stay in a better habitat in the presence of food. However, no effect was found on the transition intensity for moving in the opposite direction. 5. The process-based approach to evaluating movement rules of animals allowed us to see the contrasting directional effects of different factors on the underlying movement rules used by animals, as opposed to pattern-based fitting of observed distributions. Consideration of these rules would improve the existing habitat-choice models.