Romanian Academy

We introduce a new dataset, Human3.6M, of 3.6 Million accurate 3D Human poses, acquired by recording the performance of 5 female and 6 male subjects, under 4 different viewpoints, for training realistic human sensing systems and for evaluating the next generation of human pose estimation models and algorithms. Besides increasing the size of the datasets in the current state-of-the-art by several orders of magnitude, we also aim to complement such datasets with a diverse set of motions and poses encountered as part of typical human activities (taking photos, talking on the phone, posing, greeting, eating, etc.), with additional synchronized image, human motion capture, and time of flight (depth) data, and with accurate 3D body scans of all the subject actors involved. We also provide controlled mixed reality evaluation scenarios where 3D human models are animated using motion capture and inserted using correct 3D geometry, in complex real environments, viewed with moving cameras, and under occlusion. Finally, we provide a set of large-scale statistical models and detailed evaluation baselines for the dataset illustrating its diversity and the scope for improvement by future work in the research community. Our experiments show that our best large-scale model can leverage our full training set to obtain a 20% improvement in performance compared to a training set of the scale of the largest existing public dataset for this problem. Yet the potential for improvement by leveraging higher capacity, more complex models with our large dataset, is substantially vaster and should stimulate future research. The dataset together with code for the associated large-scale learning models, features, visualization tools, as well as the evaluation server, is available online at http://vision.imar.ro/human3.6m.

DOCUMENT REVIEWERS: Luis Alcocer (Mexico), Christina Antza (Greece), Mustafa Arici (Turkey), Eduardo Barbosa (Brazil), Adel Berbari (Lebanon), Luís Bronze (Portugal), John Chalmers (Australia), Tine De Backer (Belgium), Alejandro de la Sierra (Spain), Kyriakos Dimitriadis (Greece), Dorota Drozdz (Poland), Béatrice Duly-Bouhanick (France), Brent M. Egan (USA), Serap Erdine (Turkey), Claudio Ferri (Italy), Slavomira Filipova (Slovak Republic), Anthony Heagerty (UK), Michael Hecht Olsen (Denmark), Dagmara Hering (Poland), Sang Hyun Ihm (South Korea), Uday Jadhav (India), Manolis Kallistratos (Greece), Kazuomi Kario (Japan), Vasilios Kotsis (Greece), Adi Leiba (Israel), Patricio López-Jaramillo (Colombia), Hans-Peter Marti (Norway), Terry McCormack (UK), Paolo Mulatero (Italy), Dike B. Ojji (Nigeria), Sungha Park (South Korea), Priit Pauklin (Estonia), Sabine Perl (Austria), Arman Postadzhian (Bulgaria), Aleksander Prejbisz (Poland), Venkata Ram (India), Ramiro Sanchez (Argentina), Markus Schlaich (Australia), Alta Schutte (Australia), Cristina Sierra (Spain), Sekib Sokolovic (Bosnia and Herzegovina), Jonas Spaak (Sweden), Dimitrios Terentes-Printzios (Greece), Bruno Trimarco (Italy), Thomas Unger (The Netherlands), Bert-Jan van den Born (The Netherlands), Anna Vachulova (Slovak Republic), Agostino Virdis (Italy), Jiguang Wang (China), Ulrich Wenzel (Germany), Paul Whelton (USA), Jiri Widimsky (Czech Republic), Jacek Wolf (Poland), Grégoire Wuerzner (Switzerland), Eugene Yang (USA), Yuqing Zhang (China).

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Scikit-learn is an increasingly popular machine learning li- brary. Written in Python, it is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts. In this paper, we present and discuss our design choices for the application programming interface (API) of the project. In particular, we describe the simple and elegant interface shared by all learning and processing units in the library and then discuss its advantages in terms of composition and reusability. The paper also comments on implementation details specific to the Python ecosystem and analyzes obstacles faced by users and developers of the library.

Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.

In spite of a growing body of research and data, human ageing remains a poorly understood process. Over 10 years ago we developed the Human Ageing Genomic Resources (HAGR), a collection of databases and tools for studying the biology and genetics of ageing. Here, we present HAGR's main functionalities, highlighting new additions and improvements. HAGR consists of six core databases: (i) the GenAge database of ageing-related genes, in turn composed of a dataset of >300 human ageing-related genes and a dataset with >2000 genes associated with ageing or longevity in model organisms; (ii) the AnAge database of animal ageing and longevity, featuring >4000 species; (iii) the GenDR database with >200 genes associated with the life-extending effects of dietary restriction; (iv) the LongevityMap database of human genetic association studies of longevity with >500 entries; (v) the DrugAge database with >400 ageing or longevity-associated drugs or compounds; (vi) the CellAge database with >200 genes associated with cell senescence. All our databases are manually curated by experts and regularly updated to ensure a high quality data. Cross-links across our databases and to external resources help researchers locate and integrate relevant information. HAGR is freely available online (http://genomics.senescence.info/).

This paper proposes a way to incorporate the idea of spiking neurons into the area of membrane computing, and to this aim we introduce a class of neural-like P systems which we call spiking neural P systems (in short, SN P systems). In these devices, the time (when the neurons fire and/or spike) plays an essential role. For instance, the result of a computation is the time between the moments when a specified neuron spikes. Seen as number computing devices, SN P systems are shown to be computationally complete (both in the generating and accepting modes, in the latter case also when restricting to deterministic systems). If the number of spikes present in the system is bounded, then the power of SN P systems falls drastically, and we get a characterization of semilinear sets. A series of research topics and open problems are formulated.

This book provides researchers and graduate students with a thorough introduction to the variational analysis of nonlinear problems described by nonlocal operators. The authors give a systematic treatment of the basic mathematical theory and constructive methods for these classes of nonlinear equations, plus their application to various processes arising in the applied sciences. The equations are examined from several viewpoints, with the calculus of variations as the unifying theme. Part I begins the book with some basic facts about fractional Sobolev spaces. Part II is dedicated to the analysis of fractional elliptic problems involving subcritical nonlinearities, via classical variational methods and other novel approaches. Finally, Part III contains a selection of recent results on critical fractional equations. A careful balance is struck between rigorous mathematics and physical applications, allowing readers to see how these diverse topics relate to other important areas, including topology, functional analysis, mathematical physics, and potential theory.

In light of future work challenges, actual human resource management (HRM) needs to be redesigned, including long-term development, regeneration, and renewal of human resources, passing from consuming to developing human resources by incorporating the concept of sustainability. Thus, sustainable HRM is seen as an extension of strategic human resources, presenting a new approach to human resource management. The labor market is constantly changing, atypical work acquiring a significant relevance, especially in these current times of coronavirus crisis restrictions. In Romania, promoting the law of teleworking transformed labor flexibility into a topic of interest, and became an increasingly vital requirement for employment and a motivating factor for Romanian employees. In such a context, this paper aims to investigate the link between employee development and worktime and workspace flexibility as relevant characteristics of sustainable HRM, job satisfaction and job performance among Romanian employees in order to identify how to redesign HRM in the face of “future work” challenges. Additionally, the paper aims to examine the impact of different types of flexibility—contractual, functional, working time, and workspace flexibility—in order to highlight the relevance of employee development and employee flexibility as important aspects of sustainable HRM in increasing the overall level of employee job satisfaction. In order to make this possible, an “employee flexibility composite indicator,” which takes into account different types of flexibility, has been developed using feedback from Romanian employees, which was gathered by a national representative survey using multiple correspondence analysis. Furthermore, the impact of both individual and employee flexibility on overall level of job satisfaction has been quantified using binary logistic regression models. Within the research, there is a particular focus on the impact of new types of workspaces (flex office, co-working, total home office, partial home office—FO, CW, HOT, HOP) on job performance, job satisfaction, organizational performance, professional growth and development, social and professional relationships, and personal professional performance as well as on the overall level of work motivation. The empirical results revealed that these new types of workspaces are highly appreciated by employees, generating a growing interest among them. Partial home working, the mix between working from home and working in a company’s office, has been considered an optimal solution in increasing organizational performance, social and professional relationships, learning and personal development, and the overall level of work motivation. The results of the multiple correspondence analysis highlighted a medium level of flexibility among those Romanian employees interviewed, with only one third of them exhibiting high levels of flexibility. The empirical analysis of logistic regression analysis pointed out the role of functional flexibility, working time, and workspace flexibility along with the flexibility composite indicator in increasing the level of job satisfaction in employees. Therefore, if the challenge is to redesign the actual human resource management in order to include the concept of sustainability, attention needs to be on a combination of employee development-flexible time and flexible places, leading to an increase in both employee job satisfaction and organizational performance as important outcomes of sustainable HRM.

To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named 'Global Applications of Soil Erosion Modelling Tracker (GASEMT)', includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions.

In response to the energy demand triggered by developmental signals and environmental stressors, the cells launch the mitochondrial biogenesis process. This is a self-renewal route, by which new mitochondria are generated from the ones already existing. Recently, considerable progress has been made in deciphering mitochondrial biogenesis-related proteins and genes that function in health and in pathology-related circumstances. However, an outlook on the intracellular mechanisms shared by the main players that drive mitochondrial biogenesis machinery is still missing. Here, we provide such a view by focusing on the following issues: (a) the role of mitochondrial biogenesis in homeostasis of the mitochondrial mass and function, (b) the signalling pathways beyond the induction/promotion, stimulation and inhibition of mitochondrial biogenesis and (c) the therapeutic applications aiming the repair and regeneration of defective mitochondrial biogenesis (in ageing, metabolic diseases, neurodegeneration and cancer). The review is concluded by the perspectives of mitochondrial medicine and research.

The Galaxy And Mass Assembly (GAMA) survey is one of the largest contemporary spectroscopic surveys of low redshift galaxies. Covering an area of 286 deg 2 (split among five survey regions) down to a limiting magnitude of r < 19.8 mag, we have collected spectra and reliable redshifts for 238 000 objects using the AAOmega spectrograph on the Anglo-Australian Telescope. In addition, we have assembled imaging data from a number of independent surveys in order to generate photometry spanning the wavelength range 1 nm-1 m. Here, we report on the recently completed spectroscopic survey and present a series of diagnostics to assess its final state and the quality of the redshift data. We also describe a number of survey aspects and procedures, or updates thereof, including changes to the input catalogue, redshifting and re-redshifting, and the derivation of ultraviolet, optical and near-infrared photometry. Finally, we present the second public release of GAMA data. In this release, we provide input catalogue and targeting information, spectra, redshifts, ultraviolet, optical and near-infrared photometry, single-component Srsic fits, stellar masses, H-derived star formation rates, environment information, and group properties for all galaxies with r < 19.0 mag in two of our survey regions, and for all galaxies with r < 19.4 mag in a third region (72 225 objects in total). The data base serving these data is available at http://www.gama-survey.org/.

Abstract. The deep polar ice cores provide reference records commonly employed in global correlation of past climate events. However, temporal divergences reaching up to several thousand years (ka) exist between ice cores over the last climatic cycle. In this context, we are hereby introducing the Antarctic Ice Core Chronology 2012 (AICC2012), a new and coherent timescale developed for four Antarctic ice cores, namely Vostok, EPICA Dome C (EDC), EPICA Dronning Maud Land (EDML) and Talos Dome (TALDICE), alongside the Greenlandic NGRIP record. The AICC2012 timescale has been constructed using the Bayesian tool Datice (Lemieux-Dudon et al., 2010) that combines glaciological inputs and data constraints, including a wide range of relative and absolute gas and ice stratigraphic markers. We focus here on the last 120 ka, whereas the companion paper by Bazin et al. (2013) focuses on the interval 120–800 ka. Compared to previous timescales, AICC2012 presents an improved timing for the last glacial inception, respecting the glaciological constraints of all analyzed records. Moreover, with the addition of numerous new stratigraphic markers and improved calculation of the lock-in depth (LID) based on δ15N data employed as the Datice background scenario, the AICC2012 presents a slightly improved timing for the bipolar sequence of events over Marine Isotope Stage 3 associated with the seesaw mechanism, with maximum differences of about 600 yr with respect to the previous Datice-derived chronology of Lemieux-Dudon et al. (2010), hereafter denoted LD2010. Our improved scenario confirms the regional differences for the millennial scale variability over the last glacial period: while the EDC isotopic record (events of triangular shape) displays peaks roughly at the same time as the NGRIP abrupt isotopic increases, the EDML isotopic record (events characterized by broader peaks or even extended periods of high isotope values) reached the isotopic maximum several centuries before. It is expected that the future contribution of both other long ice core records and other types of chronological constraints to the Datice tool will lead to further refinements in the ice core chronologies beyond the AICC2012 chronology. For the time being however, we recommend that AICC2012 be used as the preferred chronology for the Vostok, EDC, EDML and TALDICE ice core records, both over the last glacial cycle (this study), and beyond (following Bazin et al., 2013). The ages for NGRIP in AICC2012 are virtually identical to those of GICC05 for the last 60.2 ka, whereas the ages beyond are independent of those in GICC05modelext (as in the construction of AICC2012, the GICC05modelext was included only via the background scenarios and not as age markers). As such, where issues of phasing between Antarctic records included in AICC2012 and NGRIP are involved, the NGRIP ages in AICC2012 should therefore be taken to avoid introducing false offsets. However for issues involving only Greenland ice cores, there is not yet a strong basis to recommend superseding GICC05modelext as the recommended age scale for Greenland ice cores.

Abstract. An accurate and coherent chronological framework is essential for the interpretation of climatic and environmental records obtained from deep polar ice cores. Until now, one common ice core age scale had been developed based on an inverse dating method (Datice), combining glaciological modelling with absolute and stratigraphic markers between 4 ice cores covering the last 50 ka (thousands of years before present) (Lemieux-Dudon et al., 2010). In this paper, together with the companion paper of Veres et al. (2013), we present an extension of this work back to 800 ka for the NGRIP, TALDICE, EDML, Vostok and EDC ice cores using an improved version of the Datice tool. The AICC2012 (Antarctic Ice Core Chronology 2012) chronology includes numerous new gas and ice stratigraphic links as well as improved evaluation of background and associated variance scenarios. This paper concentrates on the long timescales between 120–800 ka. In this framework, new measurements of δ18Oatm over Marine Isotope Stage (MIS) 11–12 on EDC and a complete δ18Oatm record of the TALDICE ice cores permit us to derive additional orbital gas age constraints. The coherency of the different orbitally deduced ages (from δ18Oatm, δO2/N2 and air content) has been verified before implementation in AICC2012. The new chronology is now independent of other archives and shows only small differences, most of the time within the original uncertainty range calculated by Datice, when compared with the previous ice core reference age scale EDC3, the Dome F chronology, or using a comparison between speleothems and methane. For instance, the largest deviation between AICC2012 and EDC3 (5.4 ka) is obtained around MIS 12. Despite significant modifications of the chronological constraints around MIS 5, now independent of speleothem records in AICC2012, the date of Termination II is very close to the EDC3 one.

The design and synthesis of double network (DN) hydrogels that can mimic the properties and/or structure of natural tissue has flourished in recent years, overcoming the bottlenecks of mechanical performance of single network hydrogels and extending their potential applications in various fields. In recent years, such bioinspired DN hydrogels with extraordinary mechanical performance, excellent biocompatibility, and considerable strength have been demonstrated to be promising candidates for biomedical applications, such as tissue engineering and biomedicine. In this minireview, we provide an overview of the recent developments of bioinspired DN hydrogels defined as DN hydrogels that mimic the properties and/or structure of natural tissue, ranging from, e.g., anisotropically structured DN hydrogels, via ultratough energy dissipating DN hydrogels to dynamic, reshapable DN hydrogels. Furthermore, we discuss future perspectives of bioinspired DN hydrogels for biomedical applications.

Abstract Risk management has reduced vulnerability to floods and droughts globally 1,2 , yet their impacts are still increasing 3 . An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data 4,5 . On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change 3 .

The first edition of this book appeared in 1981 as a direct continuation of Lectures of von Neumann Algebras (by Ş.V. Strătilă and L. Zsidó) and, until 2003, was the only comprehensive monograph on the subject. Addressing the students of mathematics and physics and researchers interested in operator algebras, noncommutative geometry and free probability, this revised edition covers the fundamentals and latest developments in the field of operator algebras. It discusses the group-measure space construction, Krieger factors, infinite tensor products of factors of type I (ITPFI factors) and construction of the type III_1 hyperfinite factor. It also studies the techniques necessary for continuous and discrete decomposition, duality theory for noncommutative groups, discrete decomposition of Connes, and Ocneanu's result on the actions of amenable groups. It contains a detailed consideration of groups of automorphisms and their spectral theory, and the theory of crossed products.

Abstract Ionic conductive hydrogels (ICHs) integrate the conductive performance and soft nature of tissue‐like materials to imitate the features of human skin with mechanical and sensory traits; thus, they are considered promising substitutes for conventional rigid metallic conductors when fabricating human‐motion sensors. However, the simultaneous incorporation of excellent stretchability, toughness, ionic conductivity, self‐healing, and adhesion via a simple method remains a grand challenge. Herein, a novel ICH platform is proposed by designing a phenylboronic acid‐ionic liquid (PBA‐IL) with multiple roles that simultaneously realize the highly mechanical, electrical, and versatile properties. This elaborately designed semi‐interpenetrating network ICH is fabricated via a facile one‐step approach by introducing cellulose nanofibrils (CNFs) into the PBA‐IL/acrylamide cross‐linked network. Ingeniously, the dynamic boronic ester bonds and physical interactions (hydrogen bonds and electrostatic interactions) of the cross‐linked network endow these hydrogels with remarkable stretchability (1810 ± 38%), toughness (2.65 ± 0.03 MJ m −3 ), self‐healing property (92 ± 2% efficiency), adhesiveness, and transparency. Moreover, the construction of this material shows that CNFs can synergistically enhance mechanical performance and conductivity. The wide working strain range (≈1000%) and high sensitivity (GF = 8.36) make this ICH a promising candidate for constructing the next generation of gel‐based strain sensor platforms.

The EU's 2020 Strategy is focused on three area of growth: smart, sustainable and inclusive that couldn’t be achieved without major contribution of skills, knowledge or value of people, common knew as human capital. It is difficult to believe that these goals could be realized without a good education and training system, a large diffusion of knowledge in manufacturing services, a creative industries and a great effort to create a research-intensive economy. Using a panel methodology, the paper tried to reveal the role of human capital as a factor of the growth and to argue that the slow investment in human capital should influence the sustainable development of the countries.

Human action recognition under low observational latency is receiving a growing interest in computer vision due to rapidly developing technologies in human-robot interaction, computer gaming and surveillance. In this paper we propose a fast, simple, yet powerful non-parametric Moving Pose (MP) framework for low-latency human action and activity recognition. Central to our methodology is a moving pose descriptor that considers both pose information as well as differential quantities (speed and acceleration) of the human body joints within a short time window around the current frame. The proposed descriptor is used in conjunction with a modified kNN classifier that considers both the temporal location of a particular frame within the action sequence as well as the discrimination power of its moving pose descriptor compared to other frames in the training set. The resulting method is non-parametric and enables low-latency recognition, one-shot learning, and action detection in difficult unsegmented sequences. Moreover, the framework is real-time, scalable, and outperforms more sophisticated approaches on challenging benchmarks like MSR-Action3D or MSR-DailyActivities3D.