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The literature argues that a real digital transformation of firms requires holistic changes of the business model. Despite knowledge about this ambitious goal, understanding of how digital business model transformation can be achieved is still very limited. In this article, we explore how firms achieve digital business model transformation. We apply a case study design to investigate how incumbents have changed their respective business model dimensions during digital transformation. Our findings center on interview data and complementary archival records from 15 cases. We present a framework for digital business model transformation along the dimensions of value proposition, value creation, and value capture. Our results emphasize the importance of a preparatory phase in which the strategic course is set. Furthermore, our findings demonstrate that transforming a company's business model is most effective when a single person, namely the Chief Digital Officer, is responsible. Our findings contribute to the business model literature, by providing a more holistic view on how business model innovation can be utilized during digital transformation.

We present a solution to egocentric 3D body pose estimation from monocular images captured from downward looking fish-eye cameras installed on the rim of a head mounted VR device. This unusual viewpoint leads to images with unique visual appearance, with severe self-occlusions and perspective distortions that result in drastic differences in resolution between lower and upper body. We propose an encoder-decoder architecture with a novel multi-branch decoder designed to account for the varying uncertainty in 2D predictions. The quantitative evaluation, on synthetic and real-world datasets, shows that our strategy leads to substantial improvements in accuracy over state of the art egocentric approaches. To tackle the lack of labelled data we also introduced a large photo-realistic synthetic dataset. xR-EgoPose offers high quality renderings of people with diverse skintones, body shapes and clothing, performing a range of actions. Our experiments show that the high variability in our new synthetic training corpus leads to good generalization to real world footage and to state of theart results on real world datasets with ground truth. Moreover, an evaluation on the Human3.6M benchmark shows that the performance of our method is on par with top performing approaches on the more classic problem of 3D human pose from a third person viewpoint., 14 pages. arXiv admin note: substantial text overlap with arXiv:1907.10045

Clients can develop feelings of romantic or sexual attraction to their therapists. From a cognitive-behavioral perspective, how should therapists handle these situations? Although the topic of client attraction is comprehensively covered in the psychoanalytic and psychodynamic literature, it is woefully neglected in our cognitive-behavioral therapy (CBT) focused training programs and literature. This paper aims to address this gap by using CBT principles to provide explanations for why clients develop feelings of attraction to their therapists. In addition, this paper offers general guidelines for how to manage client attraction from a CBT perspective. Three case vignettes are used to illustrate those concepts. Recommendations for future research and training in this area are also provided.

Spectral clustering is a well-known clustering algorithm for unsupervised learning, and its improved algorithms have been successfully adapted for many real-world applications. However, traditional spectral clustering algorithms are still facing many challenges to the task of unsupervised learning for large-scale datasets because of the complexity and cost of affinity matrix construction and the eigen-decomposition of the Laplacian matrix. From this perspective, we are looking forward to finding a more efficient and effective way by adaptive neighbor assignments for affinity matrix construction to address the above limitation of spectral clustering. It tries to learn an affinity matrix from the view of global data distribution. Meanwhile, we propose a deep learning framework with fully connected layers to learn a mapping function for the purpose of replacing the traditional eigen-decomposition of the Laplacian matrix. Extensive experimental results have illustrated the competitiveness of the proposed algorithm. It is significantly superior to the existing clustering algorithms in the experiments of both toy datasets and real-world datasets.

Explicitly or implicitly, psychopathology is often defined in terms of statistical deviance, requiring that an affected individual is sufficiently distant from the norm in some dimension of psychological or neural function. In recent decades, the dominant paradigm in psychiatric research has focused primarily on deviance in neural function, treating psychopathology as disease of the brain. We argue that these conceptualizations are misguided. We recently proposed a novel theory of psychopathology, based in cybernetics and drawing additionally from neuroscience, psychometrics, and personality theory (DeYoung & Krueger, 2018a). In this theory, deviations from the norm in psychological and neural functioning serve as important risk factors for psychopathology but are not in themselves necessary or sufficient to identify psychopathology, which requires the presence of cybernetic dysfunction. Psychopathology is defined as persistent failure to move toward one’s goals, due to failure to generate effective new goals, interpretations, or strategies when existing ones prove unsuccessful. We argue that adopting a cybernetic theory to replace conceptualizations of psychopathology as statistical deviance or brain disease would facilitate improvements in measurement, diagnosis, prevention, and treatment of psychopathology.

The interrelationship between rural, rurality and social innovation still remains underexplored even though there has been considerable work within the individual discourses of social innovation and rural studies. This paper aims at broadening the scope of this interrelationship by exploring the nuanced dynamics and complexities of rural lifeworld and the experiences and knowledges of actors that shape the understanding of rural social innovation. At the core of this analysis lies two key ideas including a) an understanding that rural groups' and communities' complexities and marginalities might not be adequately understood without addressing the complex ways in which identities of caste, race, gender, ethnicity and class intersect and b) that the locally-rooted solutions resulting from these concerns are usually underrepresented in the social innovation literature and the relevance of the same needs to be recognized. This reimagining of rural social innovation is located within the theoretical perspectives of intersectionality and feminist perspective and the epistemologies of the South focusing on ‘ecologies of knowledges’ that are capable of complexifying and adding to the contemporary debates on social innovation. From an understanding of the above, the authors argue that strategies and innovations grounded on the specific groups' and communities' own knowledge and rhythm within complex rural contexts needs be recognized as social innovation.

Does Subjective Evaluation of Probability Impact Asset Prices? The Nobel Prize–winning capital asset pricing model (CAPM) predicts that expected excess return of any asset is positively proportional to its exposure to the overall market: the beta, leading to an upward-sloping security market line. However, this prediction is contradicted by empirical studies that the return–beta slope is often flat or even downward-sloping, a puzzle called the “beta anomaly.” The CAPM is premised upon the notion that market participants are all rational, including that they are able to objectively evaluate probabilities. However, evidence abounds that individuals are often unable to do so, examples being purchase of lottery tickets and insurance products, in which the extremely small probabilities of winning or losing big are exaggerated. This phenomenon of distorting probabilities at both tails is called “probability weighting” (PW), which is a key component of modern behavioral finance. The paper “Beta and Coskewness Pricing: Perspective from Probability Weighting” approaches the beta anomaly through PW. It offers an explanation of the beta anomaly via a new theoretical CAPM involving PW and an extensive empirical study.

This article investigates how the implementation of a national space strategy in partnership with supranational organizations affects the development of service ecosystems of Earth Observation (EO)...

The ongoing COVID-19 pandemic has a major precedent almost exactly a century ago: the world-famous H1N1 influenza virus pandemic, sometimes known to the general public as the Spanish flu. From a history of medicine perspective, it is possible to underline many potential common traits between the two. In this article, hygiene and prophylaxis strategies are analyzed in a review of the most popular Italian general medical journals at the time of Spanish flu, Il Policlinico being the most representative of them. The analysis included 40 original journal articles as well as important references to the most influential coeval national manuals and international journals. The main issues in the context of public hygiene are prophylaxis with quinine and quinine derivatives, vaccinations, face masks, disinfection, and social distancing. We draw a comparison between these and the most recent international World Health Organization and Italian national guidelines on the topic. Sadly, little has changed since those times in terms of most of the prevention techniques, even with technical improvements, showing how shortsighted doctors and physicians can be when dealing with medical history. (Am J Public Health. 2021;111(10):1815–1823. https://doi.org/10.2105/AJPH.2021.306412 )

The emigrant writer V. Barka proves to us that during those years he worked and lived there were no opportunities to write works on Christian problems in Ukraine, only abroad due to various cultural-religious, socio-political reasons. V. Barkа’s novel «Paradise» is fi lled with religious nominations, which we differentiate into different subgroups. The lexico-semantic subgroups of religious termino-vocabulary was analyzed in the article. It is found out, that the author of the analyzed work repeatedly illustrates demonological vocabulary, uses it to denote of evil power and enriches the work with religious synonymous and antonymous words. However, an analysis of recent research witness that the question of the research of names for the designation of religious vocabulary in the novel “Paradise” has not yet been learned. Therefore, we set ourselves an aim to analyze the layers of religious vocabulary in worked out work. The purpose of the article is to differentiate the names of religious lexemes in the novel “Paradise” by certain thematic subgroups, to confi rm with illustrative theses, to display peculiarities of the formation of demonological vocabulary. Nominations to designation of demonological vocabulary were fi led as such, that devoid of moral-ethics norms, positive traits, and they doing only bad, sinful acts in the work under review. B. Barka the main focus concentrates on the following biblical antinomies: paradise / hell, man / beast, good / evil, life / death, faith / disbelief, righteous / sinner, sinful / righteous. Perspective henceforth we perceive the analysis of verbs on the notation of religious concepts, as well as the research of religious vocabulary in the works of V. Barka.

Contributions on localisation often focus on interactions between local organisations and the international community, with limited attention for dynamics within the locally led part of the response themselves. The humanitarian response in the non-government-held areas of Syria is considered a key example of localisation, in which the health sector has taken a leading role. Drawing on fieldwork among Syrian medical-humanitarian organisations conducted in southern Turkey, this paper offers a view from below on the localisation debate. It provides a nuanced perspective on 'the local', showcasing how localisation is interpreted and expressed among Syrian NGOs themselves, and within their interaction with each other. It shows how most organisations have moved to a hybrid model emphasising their local and international character, resisting simplistic classifications. However, despite the sometimes strategic nature of its invocation, localisation does not lose its relevance as a lived experience, especially for local field staff. This article is protected by copyright. All rights reserved.

Purpose of the article is to show that colour names form concept periphery of the landscape, enrich, expose in general, making it more important in small prose ofI. Bunin.Art concept that is born in the writing and continues its life beyond the one isalways obeyed to the necessity of detail the phenomena of nature, landscapes andtheir elements refl ection. It is revealed in a small prose of the writer as an integral systemic formation represented by colour lexemes not only with conventional but alsowith associative semantics.Conceptual comprehension of the landscape in I. Bunin’s small prose is connectedwith the understanding that nature can exist only in the context of the human worldview.The variety of details and their colourist features makes it possible for the writer to show the unique beauty of the surrounding world, inner richness, the intensity of the spiritual life and the depth of the characters’ emotions. The colour marking palette in I. Bunin’s prose is extremely rich, vividly individual. The artist is looking for new means of emotional infl uence. In perspective it is advised to analyse the concept “landscape” in I. Bunin’s poetry. The presented methodology can become the basis for studying the category of coloration in different author styles.

Different forms of coworking spaces have spread worldwide that use various artifacts (e.g., office settings, decor, furniture, equipment) to strengthen autonomy, flexibility, spontaneous interactions, and intrinsic motivation. However, the various manifestations of coworking spaces limit clearly defined boundary conditions for their successful implementation and demand a profound understanding of the interactions that take place among actors and artifacts. Using a flexible pattern matching approach, our study explains that artifacts can contour and create the possibilities for actors and define the borders, e.g., when, where, and with whom to communicate and work in coworking spaces. Our findings indicate that actors and artifacts are constitutively entangled in coworking spaces and play a key role in the community development process by fostering a shared understanding and identity, mutual interdependency, and common practices.

Indoor navigation is essential to a wide spectrum of applications in the era of mobile computing. Existing vision-based technologies suffer from both start-up costs and the absence of semantic information for navigation. We observe an opportunity to leverage pervasively deployed surveillance cameras to deal with the above drawbacks and revisit the problem of indoor navigation with a fresh perspective. In this paper, we propose \sysname, a system that enables public surveillance cameras, as indoor navigating satellites, to locate users on the floorplan, tell users with semantic information about the surrounding environment, and guide users with navigation instructions. However, enabling public cameras to navigate is non-trivial due to 3 factors: absence of real scale, disparity of camera perspective, and lack of semantic information. To overcome these challenges, \sysname leverages POI-assisted framework and adopts a novel coordinate transformation algorithm to associate public and mobile cameras, and further attaches semantic information to user location. Extensive experiments in 4 different scenarios show that \sysname achieves a localization accuracy of 0.48m and a navigation success rate of 90.5%, outperforming the state-of-the-art systems by over 30%. Benefitting from our solution, all areas with public cameras can upgrade to smart spaces with visual navigation services.

A growing body of literature reveals that the emergence of hubris is by no means a rare phenomenon in leadership contexts. Despite having been repeatedly proven that hubris has both beneficial and detrimental manifestations in leadership behaviors, its positioning as a harmful cognitive bias continues to echo across disciplines. To unify the fragmented hubris tradition, this paper synthesizes existing literature and identifies three perspectives on hubristic leadership: an innovation perspective, an internal coordination and commercialization perspective, and a risk management perspective. The aggregation of these perspectives into a unifying theoretical framework indicates that the type of leadership behavior together with the predictability of its outcomes account for the ambivalent manifestations of hubris across leadership behaviors. Future research opportunities are discussed on this basis.

Environmental dynamism, as exemplified by the rate of change and the degree of instability of the environment, plays a considerable role in determining whether firms will adopt green process innovation (GPI). Although environmental dynamism may offer new development opportunities, it also increases the risks and uncertainties associated with market potential and technology prospects. Integrating works on organizational adaptation theory and the framework of technology push, market pull, and regulatory push/pull, we examine the effects of environmental dynamism on GPI, with a focus on the moderating effects of supply chain cooperation. Examining a sample of 210 manufacturing firms in China, we find that GPI is positively related to technological dynamism but negatively associated with regulatory dynamism. In addition, supply chain cooperation weakens the association between environmental dynamism and GPI: specifically, supply chain cooperation reduces both the positive effect of technological dynamism and the negative effect of regulatory dynamism on GPI. These findings offer a new explanation for the ambiguous viewpoints and results by providing finer-grained insights on how and under which situation environmental dynamism impacts GPI.

Imagery rescripting (IR) has been proven effective in several studies applied to different disorders. It is unclear, however, what the elements of change are according to patients and therapists and whether they agree on this. In this study, we examined the perspectives of patients and therapists and their degree of agreement regarding the elements of change in IR for posttraumatic stress disorder due to childhood trauma. Patients who showed a substantial decrease in symptoms on the Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5) after a maximum of 12 sessions of IR, as well as their therapists, were approached. Ten patients and nine therapists provided in-depth interviews about the elements of change in the treatment they had received or conducted. A qualitative analysis of the results was used. One element of change was mentioned by all but one interviewee—namely, caring for the child by the therapist when the therapist rescripts the traumatic event. All except two interviewees mentioned that when the therapist rescripts, speaking up to the perpetrator was important. Both aspects were also important when patients did the rescripting themselves. All patients mentioned the positive connection they had with the therapist and the encouragement they received from him or her was important. There was only moderate agreement between patient and therapist regarding the most important element of change, although overall both patients and therapists believed the same elements were of importance. To our knowledge this is the first study in which the elements of change viewed by patients and therapists are investigated in relationship to one another. Despite the fact that this study does not provide definite answers of what works, the perspective of patients and therapists needs to be taken into account when IR for posttraumatic stress disorder is further developed.

This paper proposes two new measures of illiquidity for real estate markets, utilising concepts from asset pricing. Segregating real estate through a regional lens, we provide an in-depth analysis of real estate returns and illiquidity for the US and UK. Our results provide statistically significant and economically meaningful evidence that real estate illiquidity predicts real estate returns out-of-sample over and above a variety of control variables.

Through digitalization, online platforms facilitate suppliers to meet market demand with customized offerings, but this business model’s value-creation potential is often hampered by market frictio...

The scientific advancement in urbanised locations with the relation of the lower classes and discovery to Secularized culture is boosting the growth of food delivery applications and restaurant industries in India. The convenience of users is the primary objective aspect of such, while the second thing that these software's are also beneficial for the development of the market in eating and food supply, as the use of the online platform is a place where the restaurant owner is prepared to attract as many users as he can by allowing them to see the entire food menu in accordance with item name, price, photo, etc. Apps for food delivery have proven to be a big success in India as people are very well about all its operations and services. As one can order food for any type of occasion, it is one of the most comfortable and trusted options available. This helps to save time, resources, fuel and efforts for people, which is one of the key reasons why this industry is thriving and will tend to do so. Therefore, part of my initiative would be to review the theoretical background in various aspects of food sector apps, business models and various factors affecting adoption of food delivery apps that have never been addressed before.

This article uses the agency theory perspective to analyze governance, composed of a set of dimensions and measured by governance factors that influence donations to Brazilian environmental Nonprofit Organizations (NPOs). Data were collected predominantly from the documents available on the Internet, and the random sample consisted of 108 observations. We identified governance dimensions through Multiple Correspondence Analysis. From these dimensions, we verified, through Partial Least Squares Structural Equation Modeling, if governance affected donations. It was observed that governance positively affected donations and that public certifications provided to NPOs in Brazil did not moderate the relationship between governance and donations. These results showing that governance helps NPOs to have easier access to the donations market and that public certifications provided to NPOs do not contribute to increasing donations. These findings are important for practitioners and also to enrich the debate about public policies for the third sector in environments of low regulation. Resumo Este artigo analisa a governança composta como um conjunto de dimensões medidas por fatores de governança que influenciam as doações com restrições de doadores recebidas por Organizações Sem Fins Lucrativos (ONG) ambientais no Brasil, sob a perspectiva da teoria da agência. Os dados foram coletados predominantemente em documentos disponíveis na internet, e a amostra aleatória foi composta por 108 observações. Identificamos as dimensões de governança por meio da Análise de Correspondência Múltipla. A partir dessas dimensões, verificou-se, por meio de Partial Least Squares Structural Equation Modeling, se a governança afetou as doações. Observou-se que a governança afetou positivamente as doações e que as certificações públicas fornecidas às ONGs no Brasil não moderaram a relação entre governança e doações. Esses resultados mostram que a governança ajuda a ONG a ter acesso mais fácil ao mercado de doações e que as certificações públicas fornecidas à ONG não contribuem para o aumento das doações. Esses achados são importantes para os profissionais e também para enriquecer o debate sobre políticas públicas para o terceiro setor em ambientes pouco regulamentados.

The concept of Cyber Physical System (CPS) is widely used in different industries across the globe. In fact, it is the holistic approach towards dealing with cyber space and physical environments that do have inter-dependencies. In the existing systems, there was a separate approach for security of the two worlds (cyber and physical). However, it does not provide necessary security when security is employed independently. The research in this paper identifies the need for integrated security for CPS. Besides it throws light into different security challenges associated with CPS and the countermeasures that existed based on machine learning and deep learning techniques that come under Artificial Intelligence (AI) and data science. From the review of literature, it is understood that data science perspective is suitable for protecting CPS with required adaptive strategy. This paper provides several useful insights related to security analysis of CPS using machine learning. It paves way for further investigation and realize a comprehensive security framework to protect CPS from internal and external cyber-attacks.

Current works on image emotion distribution learning typically extract visual representations from the holistic image or explore emotion-related regions in the image from a global-wise perspective. However, different regions of an image contribute differently to the arousal of each emotion. Existing works do not deeply explore corresponding emotion-aware regions of each emotion in the image, nor do they fully capture the relationship between each emotion-aware region and the emotion labels. In this paper, we propose a novel attention based emotion distribution learning method, which can explore the emotion-related regions of images from the perspective of each emotion category, and can conduct region relationship learning. Specifically, we introduce a semantic guided attention detection network to generate class-wise attention maps for each emotion and a global-wise attention map for the holistic image. Meanwhile, an emotional graph-based network is adopted to capture the correlation between each region and the emotion distribution. Experiments on several benchmark datasets demonstrate the superiority of the proposed method compared to related works.

This paper is dedicated to the "50 Years of the Relevance Problem" - a long-neglected topic that begs attention from practical statisticians who are concerned with the problem of drawing inference from large-scale heterogeneous data., Comment: Revised (much-improved) version. The procedure (including all the datasets) is implemented in the R-package LPRelevance

Competition between Points of Interest (POIs) refers to the situation in which two POIs directly or indirectly provide similar services to secure businesses. A large portion of prior studies on competition analysis focuses on mining textual data, e.g., news articles and social comments. However, the increasing availability of human mobility and mobile query data enables a new paradigm for analyzing the competitive relationships among POIs, which remains largely unexplored. To this end, in this paper, we attempt to mine large-scale online map search query data for better understanding POI competitive relationships. Based on a co-query POI graph built from the map search query data, we develop a novel neural graphlet-based prediction framework to predict the competitive relationships among POIs. A unique perspective of our model is to infer latent POI competitive relationships by integrating multiple distinct factors, e.g., graphlet structure, geographical distance, and regional features, reflected in map search query data and POI data. Finally, we conduct extensive experiments on real-world datasets to demonstrate the effectiveness of the proposed framework, and show that our framework outperforms all baselines with a significant margin in all evaluation metrics.

This research aims to explain whether leader perfectionism toward employees fosters or hinders employee creativity. From a self-regulation perspective, we theorize that depending on employees’ locu...

Accurate power time-series prediction is an important application for building new industrialized smart cities. The gated recurrent units (GRUs) models have been successfully employed to learn temporal information for power time-series prediction, demonstrating its effectiveness. However, from a statistical perspective, these existing models are geometrically ergodic with short-term memory that causes the learned temporal information to be quickly forgotten. Meanwhile, these existing approaches completely ignore the temporal dependencies between the gradient flow in the optimization algorithm, which greatly limits the prediction accuracy. To resolve these issues, we propose a novel GRU model coupling two new mechanisms of selective state updating and adaptive mixed gradient optimization (GRU-SSU-AMG) to improve the accuracy of prediction. Specifically, a tensor discriminator is used for adaptively determining whether hidden state information needs to be updated at each time step for learning the extremely fluctuating information in the proposed selective GRU (SGRU). In addition, an adaptive mixed gradient (AdaMG) optimization method that mixes the moment estimations is proposed to further improve the capability of learning the temporal dependencies information. The effectiveness of the GRU-SSU-AMG has been extensively evaluated on five different real-world datasets. The experimental results show that the GRU-SSU-AMG achieves significant accuracy improvement compared with the state-of-the-art approaches.

3D hand shape and pose estimation from a single depth map is a new and challenging computer vision problem with many applications. Existing methods addressing it directly regress hand meshes via 2D convolutional neural networks, which leads to artefacts due to perspective distortions in the images. To address the limitations of the existing methods, we develop HandVoxNet++, i.e., a voxel-based deep network with 3D and graph convolutions trained in a fully supervised manner. The input to our network is a 3D voxelized-depth-map-based on the truncated signed distance function (TSDF). HandVoxNet++ relies on two hand shape representations. The first one is the 3D voxelized grid of hand shape, which does not preserve the mesh topology and which is the most accurate representation. The second representation is the hand surface that preserves the mesh topology. We combine the advantages of both representations by aligning the hand surface to the voxelized hand shape either with a new neural Graph-Convolutions-based Mesh Registration (GCN-MeshReg) or classical segment-wise Non-Rigid Gravitational Approach (NRGA++) which does not rely on training data. In extensive evaluations on three public benchmarks, i.e., SynHand5M, depth-based HANDS19 challenge and HO-3D, the proposed HandVoxNet++ achieves state-of-the-art performance. In this journal extension of our previous approach presented at CVPR 2020, we gain 41.09% and 13.7% higher shape alignment accuracy on SynHand5M and HANDS19 datasets, respectively. Our method is ranked first on the HANDS19 challenge dataset (Task 1: Depth-Based 3D Hand Pose Estimation) at the moment of the submission of our results to the portal in August 2020., 13 pages, 6 tables, 7 figures; project webpage: http://4dqv.mpi-inf.mpg.de/HandVoxNet++/. arXiv admin note: text overlap with arXiv:2004.01588

Cybercrime continues to cause increasing threat to business processes, eroding stakeholders’ trust in Internet technologies. In this article, we explore how six dominant algorithmic trust positions facilitate cognitive processing, which, in turn, can influence an organization's productivity and align its values and support structures for combating cybercrimes. This conceptual paper uses a cognitive perspective described as a throughput model. This modeling perspective captures several dominant algorithmic trust positions for organizations, providing a new, and powerful approach which seeks to enhance our understanding of the cognitive representation of decision-making processes. These trust positions are rational-based trust, rule-based trust, category-based trust, third-party based trust, role-based trust, and knowledge-based trust. Finally, we provide conclusion and implications for future research.

Realistic speech-driven 3D facial animation is a challenging problem due to the complex relationship between speech and face. In this paper, we propose a deep architecture, called Geometry-guided Dense Perspective Network (GDPnet), to achieve speaker-independent realistic 3D facial animation. The encoder is designed with dense connections to strengthen feature propagation and encourage the re-use of audio features, and the decoder is integrated with an attention mechanism to adaptively recalibrate point-wise feature responses by explicitly modeling interdependencies between different neuron units. We also introduce a non-linear face reconstruction representation as a guidance of latent space to obtain more accurate deformation, which helps solve the geometry-related deformation and is good for generalization across subjects. Huber and HSIC (Hilbert-Schmidt Independence Criterion) constraints are adopted to promote the robustness of our model and to better exploit the non-linear and high-order correlations. Experimental results on the public dataset and real scanned dataset validate the superiority of our proposed GDPnet compared with state-of-the-art model. The code is available for research purposes at http://cic.tju.edu.cn/faculty/likun/projects/GDPnet.

Exploring large virtual environments, such as cities, is a central task in several domains, such as gaming and urban planning. VR systems can greatly help this task by providing an immersive experience; however, a common issue with viewing and navigating a city in the traditional sense is that users can either obtain a local or a global view, but not both at the same time, requiring them to continuously switch between perspectives, losing context and distracting them from their analysis. In this paper, our goal is to allow users to navigate to points of interest without changing perspectives. To accomplish this, we design an intuitive navigation interface that takes advantage of the strong sense of spatial presence provided by VR. We supplement this interface with a perspective that warps the environment, called UrbanRama, based on a cylindrical projection, providing a mix of local and global views. The design of this interface was performed as an iterative process in collaboration with architects and urban planners. We conducted a qualitative and a quantitative pilot user study to evaluate UrbanRama and the results indicate the effectiveness of our system in reducing perspective changes, while ensuring that the warping doesn't affect distance and orientation perception., Comment: Video: https://www.youtube.com/watch?v=M8BFZnxq-Qg

Callender claims that `time is the great informer' (Callender 2017, chapter 7), meaning that the direction(s) in which our `best' physical theories inform are temporal. This is intended to be a metaphysical claim, and as such expresses a relationship between the physical world and information-gathering systems such as ourselves. This paper gives two counterexamples to this claim, illustrating the fact that time and informative strength doubly dissociate, so the claim cannot be about physical theories in general. The first is a case where physical theories inform in directions that we have no reason to regard as temporal. The second is a case where our best physical theories fail to inform in directions that we have independent (pre-theoretic) reasons to regard as temporal. Taking these two cases into account suggests that the connection Callender makes between time and informativeness is perspectival. The second case demonstrates that, although scientists often seek information in temporal directions, the behaviour of the physical world can present serious difficulties for finding it. In response, this paper proposes a perspectival reading of Callender's claim, according to which the connection between time and informative strength has more to do with the aims and objectives of science than the workings of the physical world.

Graph-based clustering plays an important role in the clustering area. Recent studies about graph convolution neural networks have achieved impressive success on graph type data. However, in general clustering tasks, the graph structure of data does not exist such that the strategy to construct a graph is crucial for performance. Therefore, how to extend graph convolution networks into general clustering tasks is an attractive problem. In this paper, we propose a graph auto-encoder for general data clustering, which constructs the graph adaptively according to the generative perspective of graphs. The adaptive process is designed to induce the model to exploit the high-level information behind data and utilize the non-Euclidean structure sufficiently. We further design a novel mechanism with rigorous analysis to avoid the collapse caused by the adaptive construction. Via combining the generative model for network embedding and graph-based clustering, a graph auto-encoder with a novel decoder is developed such that it performs well in weighted graph used scenarios. Extensive experiments prove the superiority of our model., Comment: Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence

Knee points, characterized as a small improvement on one objective can lead to a significant degradation on at least one of the other objectives, are attractive to decision makers in multi-criterion decision-making. This paper presents a simple and effective knee point identification method to help decision makers identify solution(s) of interest from a given set of trade-off solutions thus facilitating posterior decision-making. Our basic idea is to sequentially validate whether a solution is a knee point or not by comparing its localized trade-off utility with others within its neighborhood characterized from a decomposition perspective. In particular, a solution is a knee point if and only if it has the best localized trade-off utility among its neighbors. We implement a GPU version that carries out the knee point identification in a parallel manner. This GPU version reduces the worst-case complexity from quadratic to linear. The performance of our proposed method is compared with five state-of-the-art knee point identification methods on 134 test problem instances and two real-world engineering design problems. Empirical results demonstrate its outstanding performance especially on problems with many local knee points. We further validate the usefulness of our proposed method for guiding evolutionary multi-objective optimization algorithms to search for knee points on the fly during the evolutionary process.

Internet gaming disorder (IGD), a condition warranting further study in the Diagnostic and Statistical Manual 5, has received considerable research attention in recent years (American Psychiatric Association, 2013). Characterized by problematic and repetitive use of Internetbased games, research suggests a complex etiology and that frequent usage, in and of itself, is not necessarily always problematic. Common motivations for intense usage, such as feelings of isolation, distress, and boredom may, in part, reflect an individual’s best attempts to navigate contact with the ‘ultimate’ anxieties identified by Yalom (1980). This article reviews the research pertaining to IGD, conceptualizes the disorder from an existentialhumanistic therapy (E-H) perspective, and concludes with an explanation of how E-H can offer a unique treatment perspective from which to work with clients struggling with problematic online gaming concerns within the context of the COVID-19 pandemic and beyond. © 2021 American Psychological Association

It is popular in psychology to hypothesize that representations of exact number are innately determined-in particular, that biology has endowed humans with a system for manipulating quantities which forms the primary representational substrate for our numerical and mathematical concepts. While this perspective has been important for advancing empirical work in animal and child cognition, here we examine six natural predictions of strong numerical nativism from a multidisciplinary perspective, and find each to be at odds with evidence from anthropology and developmental science. In particular, the history of number reveals characteristics that are inconsistent with biological determinism of numerical concepts, including a lack of number systems across some human groups and remarkable variability in the form of numerical systems that do emerge. Instead, this literature highlights the importance of economic and social factors in constructing fundamentally new cognitive systems to achieve culturally specific goals. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Being single and of marriageable age in a society where marriage is the norm invites perceptions of social undervaluation and vulnerability to social pressure to conform. The current study examines the reasons for more Indonesian adults remaining single, the perceived societal stigma related to this, and how they react to such undervaluing societal perceptions. Never-married Indonesian adults (N=350; Mage=29.79 ± 4.50) participated in this study, where their responses were analysed by thematic coding. The majority of participants stated that they were involuntarily single. The findings indicated four contexts within which they remained single: situational shortcomings, compliance with socially constructed marriage ideals, various perceptions of marriage, and unreadiness to marry. Participants mainly reacted to pressures with polite disregard, which reflected their cultural practice of avoiding conflict. This study provides an introduction to understanding the complexities and challenges for single people in Indonesia, which is still understudied.

To cope with discontinuous change, recent research advocates to implement ambidexterity in which firms pursue exploitative innovation and exploratory innovation simultaneously. While previous studies on the determinants of organizational ambidexterity focused primarily on the organizational characteristics and the behavior of top management teams, a growing body of research calls attention to the role of the paradoxical cognitive frame of top managers in managing organizational ambidexterity. This article examines whether CEO ambivalence—a paradoxical cognitive frame that accepts and accommodates the presence of both threats and opportunities of a strategic issue such as a crisis—drives or hinders organizational ambidexterity. Moreover, although both exploitation and exploration require the deployment of technological capability, whether technological capability inhibits or facilitates managerial cognition to adapt to environmental change remains a puzzle to be solved. Based on the theory of paradoxical cognitive frame, this article predicts that CEO ambivalence follows a U-shaped effect on organizational ambidexterity while technological capability amplifies the curvilinear effect. A longitudinal survey among 260 CEOs of Chinese firms provides empirical support to the hypotheses. The research findings contain rich theoretical and managerial implications.

This article puts intimate partner homicide (IPH) into a process perspective, and describes the latter two stages of the IPH process, that is, ‘changing the project’ and ‘the aftermath’. The focus of analysis is on the moment when the perpetrator chooses to kill the victim, and what s/he does and says in the wake of the killing. Fifty court files, from cases involving 40 male and 10 female perpetrators, underwent thematic analysis. Regarding the final trigger pertaining to changing the project, some situational factors that trigger male-perpetrated IPH seem to differ from the corresponding factors in female-perpetrated IPH. Feelings of rejection and jealousy seemed to be more common as triggers to kill for men than for women, while some cases of female-perpetrated IPH were linked to self-defence in response to IPV. Moreover, as noted previously, no female perpetrators displayed possessiveness. Regarding the aftermath, after the homicide the perpetrators generally contacted someone and admitted to having killed their partners. Only a few perpetrators denied culpability and even fewer, mainly male, perpetrators concealed their crimes and denied knowledge of them. However, even in cases where the perpetrator admitted to having killed their victims, their courtroom narratives were apparently constructed to minimise resposibility.