scholarly journals Mapping the Passions: Toward a High-Dimensional Taxonomy of Emotional Experience and Expression

2019 ◽  
Vol 20 (1) ◽  
pp. 69-90 ◽  
Author(s):  
Alan Cowen ◽  
Disa Sauter ◽  
Jessica L. Tracy ◽  
Dacher Keltner
Keyword(s):  
Large Scale ◽  
Emotional Experience ◽  
Methodological Approach ◽  
Diagnostic Value ◽  
High Dimensional ◽  
Circumplex Model ◽  
Contextual Cues ◽  
Continuous Space ◽  
The Face ◽  
Valence And Arousal

What would a comprehensive atlas of human emotions include? For 50 years, scientists have sought to map emotion-related experience, expression, physiology, and recognition in terms of the “basic six”—anger, disgust, fear, happiness, sadness, and surprise. Claims about the relationships between these six emotions and prototypical facial configurations have provided the basis for a long-standing debate over the diagnostic value of expression (for review and latest installment in this debate, see Barrett et al., p. 1). Building on recent empirical findings and methodologies, we offer an alternative conceptual and methodological approach that reveals a richer taxonomy of emotion. Dozens of distinct varieties of emotion are reliably distinguished by language, evoked in distinct circumstances, and perceived in distinct expressions of the face, body, and voice. Traditional models—both the basic six and affective-circumplex model (valence and arousal)—capture a fraction of the systematic variability in emotional response. In contrast, emotion-related responses (e.g., the smile of embarrassment, triumphant postures, sympathetic vocalizations, blends of distinct expressions) can be explained by richer models of emotion. Given these developments, we discuss why tests of a basic-six model of emotion are not tests of the diagnostic value of facial expression more generally. Determining the full extent of what facial expressions can tell us, marginally and in conjunction with other behavioral and contextual cues, will require mapping the high-dimensional, continuous space of facial, bodily, and vocal signals onto richly multifaceted experiences using large-scale statistical modeling and machine-learning methods.

scholarly journals Behavioral brittleness: the case for strategic behavioral public policy

2021 ◽  
pp. 1-26
Author(s):  
Ruth Schmidt ◽  
Katelyn Stenger
Keyword(s):  
Public Policy ◽  
Problem Solving ◽  
Methodological Approach ◽  
Contextual Cues ◽  
Short Term ◽  
Strategic Approach ◽  
The Face ◽  
The Creation ◽  
Impact Problem

Abstract Despite widespread recognition that behavioral public policy (BPP) needs to move beyond nudging if the field is to achieve more significant impact, problem-solving approaches remain optimized to achieve tactical success and are evaluated by short-term metrics with the assumption of stable systems. As a result, current methodologies may contribute to the development of solutions that appear well formed but become ‘brittle’ in the face of more complex contexts if they fail to consider important contextual cues, broader system forces, and emergent conditions, which can take three distinct forms: contextual, systemic, and anticipatory brittleness. The Covid-19 pandemic and vaccination rollout present an opportunity to identify and correct interventional brittleness with a new methodological approach – strategic BPP (SBPP) – that can inform the creation of more resilient solutions by embracing more diverse forms of evidence and applied foresight, designing interventions within ecosystems, and iteratively developing solutions. To advance the case for adopting a SBPP and ‘roughly right’ modes of inquiry, we use the Covid-19 vaccination rollout to define a new methodological roadmap, while also acknowledging that taking a more strategic approach may challenge current BPP norms.

scholarly journals $$\hbox {CDBTune}^{+}$$: An efficient deep reinforcement learning-based automatic cloud database tuning system

2021 ◽  
Author(s):  
Ji Zhang ◽  
Ke Zhou ◽  
Guoliang Li ◽  
Yu Liu ◽  
Ming Xie ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Large Scale ◽  
Feedback Mechanism ◽  
Database Management System ◽  
High Dimensional ◽  
High Quality ◽  
Continuous Space ◽  
Cloud Databases ◽  
Policy Gradient ◽  
End To End

AbstractConfiguration tuning is vital to optimize the performance of a database management system (DBMS). It becomes more tedious and urgent for cloud databases (CDB) due to diverse database instances and query workloads, which make the job of a database administrator (DBA) very difficult. Existing solutions for automatic DBMS configuration tuning have several limitations. Firstly, they adopt a pipelined learning model but cannot optimize the overall performance in an end-to-end manner. Secondly, they rely on large-scale high-quality training samples which are hard to obtain. Thirdly, existing approaches cannot recommend reasonable configurations for a large number of knobs to tune whose potential values live in such high-dimensional continuous space. Lastly, in cloud environments, existing approaches can hardly cope with the changes of hardware configurations and workloads, and have poor adaptability. To address these challenges, we design an end-to-end automatic CDB tuning system, $${\texttt {CDBTune}}^{+}$$ CDBTune + , using deep reinforcement learning (RL). $${\texttt {CDBTune}}^{+}$$ CDBTune + utilizes the deep deterministic policy gradient method to find the optimal configurations in a high-dimensional continuous space. $${\texttt {CDBTune}}^{+}$$ CDBTune + adopts a trial-and-error strategy to learn knob settings with a limited number of samples to accomplish the initial training, which alleviates the necessity of collecting a massive amount of high-quality samples. $${\texttt {CDBTune}}^{+}$$ CDBTune + adopts the reward-feedback mechanism in RL instead of traditional regression, which enables end-to-end learning and accelerates the convergence speed of our model and improves the efficiency of online tuning. Besides, we propose effective techniques to improve the training and tuning efficiency of $${\texttt {CDBTune}}^{+}$$ CDBTune + for practical usage in a cloud environment. We conducted extensive experiments under 7 different workloads on real cloud databases to evaluate $${\texttt {CDBTune}}^{+}$$ CDBTune + . Experimental results showed that $${\texttt {CDBTune}}^{+}$$ CDBTune + adapts well to a new hardware environment or workload, and significantly outperformed the state-of-the-art tuning tools and DBA experts.

Age Advantages of Emotional Experience during the COVID-19 Pandemic are Robust, but Diminished Compared to Pre-pandemic Conditions

2020 ◽  
Author(s):  
Rui Sun ◽  
Disa Sauter
Keyword(s):  
Older Adults ◽  
Large Scale ◽  
Negative Emotion ◽  
Emotional Experience ◽  
Negative Emotions ◽  
Older Individuals ◽  
Selection Strategies ◽  
Scale Test ◽  
Prolonged Stress

Getting old is generally seen as unappealing, yet aging confers considerable advantages in several psychological domains (North & Fiske, 2015). In particular, older adults are better off emotionally than younger adults, with aging associated with the so-called “age advantages,” that is, more positive and less negative emotional experiences (Carstensen et al., 2011). Although the age advantages are well established, it is less clear whether they occur under conditions of prolonged stress. In a recent study, Carstensen et al (2020) demonstrated that the age advantages persist during the COVID-19 pandemic, suggesting that older adults are able to utilise cognitive and behavioural strategies to ameliorate even sustained stress. Here, we build on Carstensen and colleagues’ work with two studies. In Study 1, we provide a large-scale test of the robustness of Carstensen and colleagues’ finding that older individuals experience more positive and less negative emotions during the COVID-19 pandemic. We measured positive and negative emotions along with age information in 23,629 participants in 63 countries in April-May 2020. In Study 2, we provide a comparison of the age advantages using representative samples collected before and during the COVID-19 pandemic. We demonstrate that older people experience less negative emotion than younger people during the prolonged stress of the COVID-19 pandemic. However, the advantage of older adults was diminished during the pandemic, pointing to a likely role of older adults use of situation selection strategies (Charles, 2010).

Scientific-methodological approach to the substantiation of the rational seasonal scenario of using combine harvesters by large-scale agricultural producers

2020 ◽  
pp. 205-217
Author(s):  
V. Skibchyk ◽  
V. Dnes ◽  
R. Kudrynetskyi ◽  
O. Krypuch
Keyword(s):  
Large Scale ◽  
System Analysis ◽  
Methodological Approach ◽  
Production Unit ◽  
Agricultural Producers ◽  
New Approach ◽  
Rational Use ◽  
Road Map ◽  
Analysis And Synthesis ◽  
Combine Harvesters

Аnnotation Purpose. To increase the efficiency of technological processes of grain harvesting by large-scale agricultural producers due to the rational use of combine harvesters available on the farm. Methods. In the course of the research the methods of system analysis and synthesis, induction and deduction, system-factor and system-event approaches, graphic method were used. Results. Characteristic events that occur during the harvesting of grain crops, both within a single production unit and the entire agricultural producer are identified. A method for predicting time intervals of use and downtime of combine harvesters of production units has been developed. The roadmap of substantiation the rational seasonal scenario of the use of grain harvesters of large-scale agricultural producers is developed, which allows estimating the efficiency of each of the scenarios of multivariate placement of grain harvesters on fields taking into account influence of natural production and agrometeorological factors on the efficiency of technological cultures. Conclusions 1. Known scientific and methodological approaches to optimization of machine used in agriculture do not take into account the risks of losses of crops due to late harvesting, as well as seasonal natural and agrometeorological conditions of each production unit of the farmer, which requires a new approach to the rational use of rational seasonal combines of large agricultural producers. 2. The developed new approach to the substantiation of the rational seasonal scenario of the use of combined harvesters of large-scale agricultural producers allows taking into account the costs of harvesting of grain and the cost of the lost crop because of the lateness of harvesting at optimum variants of attraction of additional free combine harvesters. provides more profit. 3. The practical application of the developed road map will allow large-scale agricultural producers to use combine harvesters more efficiently and reduce harvesting costs. Keywords: combine harvesters, use, production divisions, risk, seasonal scenario, large-scale agricultural producers.

A Fast Clustering Algorithm for Large-scale and High Dimensional Data

2009 ◽  
Vol 35 (7) ◽  
pp. 859-866
Author(s):  
Ming LIU ◽  
Xiao-Long WANG ◽  
Yuan-Chao LIU
Keyword(s):  
Large Scale ◽  
Clustering Algorithm ◽  
High Dimensional Data ◽  
High Dimensional

Ban Ki-moon, 2007–2016

2018 ◽  
Author(s):  
Richard Gowan
Keyword(s):  
United States ◽  
Decision Making ◽  
Security Council ◽  
Large Scale ◽  
Central African Republic ◽  
The United States ◽  
Cautious Approach ◽  
Peacekeeping Operations ◽  
Council Decision ◽  
The Face

During Ban Ki-moon’s tenure, the Security Council was shaken by P5 divisions over Kosovo, Georgia, Libya, Syria, and Ukraine. Yet it also continued to mandate and sustain large-scale peacekeeping operations in Africa, placing major burdens on the UN Secretariat. The chapter will argue that Ban initially took a cautious approach to controversies with the Council, and earned a reputation for excessive passivity in the face of crisis and deference to the United States. The second half of the chapter suggests that Ban shifted to a more activist pressure as his tenure went on, pressing the Council to act in cases including Côte d’Ivoire, Libya, and Syria. The chapter will argue that Ban had only a marginal impact on Council decision-making, even though he made a creditable effort to speak truth to power over cases such as the Central African Republic (CAR), challenging Council members to live up to their responsibilities.

The face of future: Face expressions during future thinking

2021 ◽  
pp. 174702182199299
Author(s):  
Mohamad El Haj ◽  
Emin Altintas ◽  
Ahmed A Moustafa ◽  
Abdel Halim Boudoukha
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Emotional Experience ◽  
Future Scenarios ◽  
Future Thinking ◽  
Analysis Software ◽  
Emotional Facial Expressions ◽  
Facial Analysis ◽  
The Face ◽  
Face Expressions

Future thinking, which is the ability to project oneself forward in time to pre-experience an event, is intimately associated with emotions. We investigated whether emotional future thinking can activate emotional facial expressions. We invited 43 participants to imagine future scenarios, cued by the words “happy,” “sad,” and “city.” Future thinking was video recorded and analysed with a facial analysis software to classify whether facial expressions (i.e., happy, sad, angry, surprised, scared, disgusted, and neutral facial expression) of participants were neutral or emotional. Analysis demonstrated higher levels of happy facial expressions during future thinking cued by the word “happy” than “sad” or “city.” In contrast, higher levels of sad facial expressions were observed during future thinking cued by the word “sad” than “happy” or “city.” Higher levels of neutral facial expressions were observed during future thinking cued by the word “city” than “happy” or “sad.” In the three conditions, the neutral facial expressions were high compared with happy and sad facial expressions. Together, emotional future thinking, at least for future scenarios cued by “happy” and “sad,” seems to trigger the corresponding facial expression. Our study provides an original physiological window into the subjective emotional experience during future thinking.

scholarly journals Reframing refugee crisis: A “European crisis of migration” or a “crisis of protection”?

2021 ◽  
pp. 239965442198970
Author(s):  
Maissaa Almustafa
Keyword(s):  
Large Scale ◽  
Global South ◽  
Global Media ◽  
Developing Regions ◽  
International Protection ◽  
High Commissioner ◽  
The Face ◽  
Global North ◽  
Displaced People ◽  
Resettlement Programs

The end of 2015 witnessed a global record in the number of forcibly displaced people fleeing because of wars and persecution. The unprecedented total of 65.3 million displaced individuals, out of which 21.3 million were refugees, was the highest number that the United Nations High Commissioner for Refugees (UNHCR) has recorded since its establishment in 1950. During the same year and in the face of this large-scale crisis, only 107,100 refugees were admitted for resettlement through official resettlement programs, whereas 3.2 million people applied for asylum globally. And in spite of the fact that the majority of the world refugees are hosted in ten developing regions, the dominant narrative in the global media was about the “unauthorized” arrival of more than one million asylum seekers in Europe by sea during 2015. This paper argues that the unexpected nature of refugees’ arrivals has proven that refugees were supposed to be contained in their camps in the Global South, deterred from reaching the territories of the Global North, represented here by Europe. Thus, the paper proposes that these arrivals are rather reflections of a crisis of protection that developed in the Global South where containment and deterrence strategies against refugees from the Global South exacerbate their inhumane displacement conditions in home regions. In the same context, the paper discusses how international protection structures have been reconstructed to serve the same goals of containment and deterrence, with the ultimate aim of putting people ‘back in place’ with minimal access to protection and rights.

Conservation of animal genetic resources: approaches and technologies for in situ and ex situ conservation

2008 ◽  
Vol 42 ◽  
pp. 71-85 ◽  
Author(s):  
J.A. Woolliams ◽  
O. Matika ◽  
J. Pattison
Keyword(s):  
Rural Communities ◽  
Genetic Resources ◽  
Large Scale ◽  
Production Systems ◽  
Regional Distribution ◽  
Livestock Production ◽  
Ex Situ ◽  
Animal Genetic Resources ◽  
The Face ◽  
Livestock Products

SummaryLivestock production faces major challenges through the coincidence of major drivers of change, some with conflicting directions. These are:1. An unprecedented global change in demands for traditional livestock products such as meat, milk and eggs.2. Large changes in the demographic and regional distribution of these demands.3. The need to reduce poverty in rural communities by providing sustainable livelihoods.4. The possible emergence of new agricultural outputs such as bio-fuels making a significant impact upon traditional production systems.5. A growing awareness of the need to reduce the environmental impact of livestock production.6. The uncertainty in the scale and impact of climate change. This paper explores these challenges from a scientific perspective in the face of the large-scale and selective erosion of our animal genetic resources, and concludes thai there is a stronger and more urgent need than ever before to secure the livestock genetic resources available to humankind through a comprehensive global conservation programme.

scholarly journals Data Quality Measures and Efficient Evaluation Algorithms for Large-Scale High-Dimensional Data

2021 ◽  
Vol 11 (2) ◽  
pp. 472
Author(s):  
Hyeongmin Cho ◽  
Sangkyun Lee
Keyword(s):  
Machine Learning ◽  
Data Quality ◽  
Large Scale ◽  
High Dimensional Data ◽  
Quality Measures ◽  
Training Data ◽  
Measure Data ◽  
High Dimensional ◽  
Small Scale ◽  
Class Separability

Machine learning has been proven to be effective in various application areas, such as object and speech recognition on mobile systems. Since a critical key to machine learning success is the availability of large training data, many datasets are being disclosed and published online. From a data consumer or manager point of view, measuring data quality is an important first step in the learning process. We need to determine which datasets to use, update, and maintain. However, not many practical ways to measure data quality are available today, especially when it comes to large-scale high-dimensional data, such as images and videos. This paper proposes two data quality measures that can compute class separability and in-class variability, the two important aspects of data quality, for a given dataset. Classical data quality measures tend to focus only on class separability; however, we suggest that in-class variability is another important data quality factor. We provide efficient algorithms to compute our quality measures based on random projections and bootstrapping with statistical benefits on large-scale high-dimensional data. In experiments, we show that our measures are compatible with classical measures on small-scale data and can be computed much more efficiently on large-scale high-dimensional datasets.

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