Vector-based models of word meaning have become increasingly popular in cognitive science. The appeal of these models lies in their ability to represent meaning simply by using distributional information under the assumption that words occurring within similar contexts are semantically similar. Despite their widespread use, vector-based models are typically directed at representing words in isolation, and methods for constructing representations for phrases or sentences have received little attention in the literature. This is in marked contrast to experimental (...) evidence (e.g., in sentential priming) suggesting that semantic similarity is more complex than simply a relation between isolated words. This article proposes a framework for representing the meaning of word combinations in vector space. Central to our approach is vector composition, which we operationalize in terms of additive and multiplicative functions. Under this framework, we introduce a wide range of composition models that we evaluate empirically on a phrase similarity task. (shrink)

Artificial intelligence (AI) is becoming increasingly influential in most people’s lives. This raises many philosophical questions. One is what responsibility we have as individuals to guide the development of AI in a desirable direction. More specifically, how should this responsibility be distributed among individuals and between individuals and other actors? We investigate this question from the perspectives of five principles of distribution that dominate the discussion about responsibility in connection with climate change: effectiveness, equality, desert, need, and ability. (...) Since much is already written about these distributions in that context, we believe much can be gained if we can make use of this discussion also in connection with AI. Our most important findings are: (1) Different principles give different answers depending on how they are interpreted but, in many cases, different interpretations and different principles agree and even strengthen each other. If for instance ‘equality-based distribution’ is interpreted in a consequentialist sense, effectiveness, and through it, ability, will play important roles in the actual distributions, but so will an equal distribution as such, since we foresee that an increased responsibility of underrepresented groups will make the risks and benefits of AI more equally distributed. The corresponding reasoning is true for need-based distribution. (2) If we acknowledge that someone has a certain responsibility, we also have to acknowledge a corresponding degree of influence for that someone over the matter in question. (3) Independently of which distribution principle we prefer, ability cannot be dismissed. Ability is not fixed, however and if one of the other distributions is morally required, we are also morally required to increase the ability of those less able to take on the required responsibility. (shrink)

Distribution of responsibility is one of the main focus areas in discussions about climate change ethics. Most of these discussions deal with the distribution of responsibility for climate change mitigation at the international level. The aim of this paper is to investigate if and how these principles can be used to inform the search for a fair distribution of responsibility for climate change adaptation on the local level. We found that the most influential distribution principles on (...) the international level were in turn built on one or more of seven basic principles: (P1) equal shares, (P2) desert, (P3) beneficiary pays, (P4) ability, (P5) self-help, (P6) limited responsibility for the worst off, and (P7) status quo preservation. It was found that all the basic principles, but P1, P3, and P7, are to some extent translatable to local climate adaptation. Two major problems hamper their usefulness on the local level: (1) several categories of agents need to take on responsibility; and (2) emissions do not work as a base for all principles. P4, P5, and P6 are applicable to local adaptation without changes. P4 is of particular importance as it seems to solve the first problem. P2 is applicable only if the second problem is solved, which can be achieved by using risk of harm instead of emissions as the basis for desert. (shrink)

To gain legitimacy for climate change adaptation decisions, the distribution of responsibility for these decisions and their implementation needs to be grounded in theories of just distribution and what those a ected by decisions see as just. The purpose of this project is to contribute to sustainable spatial planning and the ability of local and regional public authorities to make well-informed and sustainable adaptation decisions, based on knowledge about both climate change impacts and the perceptions of (...) residents and civil servants on what constitutes a sustainable distribution of responsibility. Our aims are: (1) a better understanding of the practical implications of theories about just distribution of responsibility for the choice of local and regional climate adaptation measures; (2) knowledge about what residents and civil servants consider a sustainable distribution of responsibility for climate adaptation measures; and (3) a better understanding of conflicts concerning the distribution of responsibilities and systematic knowledge about the possibilities to manage them. In this interdisciplinary project, we study six municipalities and their residents, and two county administrative boards, all in Sweden, using mixed methods: value theory, document studies, interviews, focus groups, and surveys. (shrink)

According to the diversity-beats-ability theorem, groups of diverse problem solvers can outperform groups of high-ability problem solvers. We argue that the model introduced by Lu Hong and Scott Page is inadequate for exploring the trade-off between diversity and ability. This is because the model employs an impoverished implementation of the problem-solving task. We present a new version of the model which captures the role of ‘ability’ in a meaningful way, and use it to explore the trade-offs (...) between diversity and ability in scientific problem solving. (shrink)

An influential approach to engineering ethics is based on codes of ethics and the application of moral principles by individual practitioners. However, to better understand the ethical problems of complex technological systems and the moral reasoning involved in such contexts, we need other tools as well. In this article, we consider the role of imagination and develop a concept of distributed responsibility in order to capture a broader range of human abilities and dimensions of moral responsibility. We show that (...) in the case of Snorre A, a near-disaster with an oil and gas production installation, imagination played a crucial and morally relevant role in how the crew coped with the crisis. For example, we discuss the role of scenarios and images in the moral reasoning and discussion of the platform crew in coping with the crisis. Moreover, we argue that responsibility for increased system vulnerability, turning an undesired event into a near-disaster, should not be ascribed exclusively, for example to individual engineers alone, but should be understood as distributed between various actors, levels and times. We conclude that both managers and engineers need imagination to transcend their disciplinary perspectives in order to improve the robustness of their organisations and to be better prepared for crisis situations. We recommend that education and training programmes should be transformed accordingly. (shrink)

We demonstrate that the key components of cognitive architectures (declarative and procedural memory) and their key capabilities (learning, memory retrieval, probability judgment, and utility estimation) can be implemented as algebraic operations on vectors and tensors in a high‐dimensional space using a distributional semantics model. High‐dimensional vector spaces underlie the success of modern machine learning techniques based on deep learning. However, while neural networks have an impressive ability to process data to find patterns, they do not typically model high‐level (...) cognition, and it is often unclear how they work. Symbolic cognitive architectures can capture the complexities of high‐level cognition and provide human‐readable, explainable models, but scale poorly to naturalistic, non‐symbolic, or big data. Vector‐symbolic architectures, where symbols are represented as vectors, bridge the gap between the two approaches. We posit that cognitive architectures, if implemented in a vector‐space model, represent a useful, explanatory model of the internal representations of otherwise opaque neural architectures. Our proposed model, Holographic Declarative Memory (HDM), is a vector‐space model based on distributional semantics. HDM accounts for primacy and recency effects in free recall, the fan effect in recognition, probability judgments, and human performance on an iterated decision task. HDM provides a flexible, scalable alternative to symbolic cognitive architectures at a level of description that bridges symbolic, quantum, and neural models of cognition. (shrink)

The pervasive use of distributional semantic models or word embeddings for both cognitive modeling and practical application is because of their remarkable ability to represent the meanings of words. However, relatively little effort has been made to explore what types of information are encoded in distributional word vectors. Knowing the internal knowledge embedded in word vectors is important for cognitive modeling using distributional semantic models. Therefore, in this paper, we attempt to identify the knowledge encoded in word vectors by (...) conducting a computational experiment using Binder et al.'s (2016) featural conceptual representations based on neurobiologically motivated attributes. In an experiment, these conceptual vectors are predicted from text‐based word vectors using a neural network and linear transformation, and prediction performance is compared among various types of information. The analysis demonstrates that abstract information is generally predicted more accurately by word vectors than perceptual and spatiotemporal information, and specifically, the prediction accuracy of cognitive and social information is higher. Emotional information is also found to be successfully predicted for abstract words. These results indicate that language can be a major source of knowledge about abstract attributes, and they support the recent view that emphasizes the importance of language for abstract concepts. Furthermore, we show that word vectors can capture some types of perceptual and spatiotemporal information about concrete concepts and some relevant word categories. This suggests that language statistics can encode more perceptual knowledge than often expected. (shrink)

In the selection of job candidates who have the mental ability to become professional ATCOs, psychometric testing has been a ubiquitous activity in the ATM domain. To contribute to psychometric research in the ATM domain, we investigated the extent to which spatial orientation ability (SOA), as conceptualized in the spatial cognition and navigation literature, predicted air traffic conflict detection performance in a simulated free route airspace (FRA) environment. The implementation of free route airspace (FRA) over the past few (...) years, notably in Europe, have facilitated air traffic services by giving greater flexibility to aviation operators in planning and choosing preferred air routes that can lead to quicker arrivals. FRA offers enhanced system safety and efficiency, but these benefits can be outweighed by the introduction of air traffic conflicts that are geometrically more complex. Such conflicts can arise from increased number and distribution of conflict points, as well as from elevated uncertainty in aircraft maneuvering (for instance, during heading changes). Overall, these issues will make conflict detection more challenging for air traffic controllers (ATCOs). Consequently, there is a need to select ATCOs with suitably high levels of spatial orientation ability (SOA) to ensure flight safety under FRA implementation. In this study, we tested 20 participants who are eligible for ATCO job application, and found that response time-based performance on a newly developed, open access, computerized spatial orientation test (SOT) predicted time to loss of minimum separation (tLMS) performance on an air traffic conflict detection task (AT-CDT) we designed. We found this predictive relationship to be significant to a moderately large extent under scenarios with high air traffic density (raw regression coefficient = 0.58). Moreover, we demonstrated our AT-CDT as a valid test in terms of eliciting well-known mental workload and spatial learning effects. We explained these findings in light of similar or overlapping mental processes that were most likely activated optimally under task conditions featuring approximately equal numbers of outcome-relevant stimuli. We conclude by discussing the further application of the SOT to the selection of prospective ATCOs who can demonstrate high levels of conflict detection performance in FRA during training simulations. (shrink)

Preoperative diagnosis of gastric cancer and primary gastric lymphoma is challenging and has important clinical significance. Inspired by the inductive reasoning learning of the human brain, transfer learning can improve diagnosis performance of target task by utilizing the knowledge learned from the other domains (source domain). However, most studies focus on single-source transfer learning and may lead to model performance degradation when a large domain shift exists between the single-source domain and target domain. By simulating the multi-modal information learning and (...) transfer mechanism of human brain, this study designed a multisource transfer learning feature extraction and classification framework, which can enhance the prediction performance of the target model by using multisource medical data (domain). First, this manuscript designs a feature extraction network that takes the maximum mean difference based on the Wasserstein distance as an adaptive measure of probability distribution and extracts the domain-specific invariant representations between source and target domain data. Then, aiming at the random generation of parameters bringing uncertainties to prediction accuracy and generalization ability of extreme learning machine network, the 1-norm regularization is used to implement sparse constraints of the output weight matrix and improve the robustness of the model. Finally, some experiments are carried out on the data of two medical centers. The experimental results show that the area under curves (AUCs) of the method are 0.958 and 0.929 in the two validation cohorts, respectively. The method in this manuscript can provide doctors with a better diagnostic reference, which has certain practical significance. (shrink)

We analyze a recent trend in epistemic logic which consists in studying construction of knowledge from the agents’ observational abilities. It is based on the intuition that an agent’s knowledge comes from three possible sources: her observations, communication with other agents, and inference. The approaches mainly focus on the former two and suppose that the object of observations are propositional variables and that agents learn from public announcements. This allows to model knowledge in a more compact and intuitive way (...) than with Hintikka’s semantics. However, the semantics that one can find in the literature come with some counter-intuitive validities such as common knowledge of visibilities or the knowledge operator distributing over disjunctions. We propose a solution of each of these two issues and illustrate them with well-known toy examples of epistemic logic. (shrink)

Chaos distributes with a covert method to condense the dynamic of complexity and satisfies the security requirements of a cryptographic system. This study gives an ability online/offline ID-based short signature scheme using conformable fractional chaotic maps. Furthermore, we establish its security under IBSS existential unforgeability of identity-based short signature under chosen message attack in the random oracle model. Some of the stimulating preparations of obtainable processes are that they give a multiperiod application of the offline storage, which (...) licenses the agent to recycle the offline pre-registered data in time series, rather than one-period usage in all past IBSS processes. (shrink)

Statistical learning refers to the ability to identify structure in the input based on its statistical properties. For many linguistic structures, the relevant statistical features are distributional: They are related to the frequency and variability of exemplars in the input. These distributional regularities have been suggested to play a role in many different aspects of language learning, including phonetic categories, using phonemic distinctions in word learning, and discovering non-adjacent relations. On the surface, these different aspects share few commonalities. (...) Despite this, we demonstrate that the same computational framework can account for learning in all of these tasks. These results support two conclusions. The first is that much, and perhaps all, of distributional statistical learning can be explained by the same underlying set of processes. The second is that some aspects of language can be learned due to domain-general characteristics of memory. (shrink)

While COVID-19 vaccines provide light at the end of the tunnel in a difficult time, they also bring forth the complex ethical issue of global vaccine distribution. The current unequal global distribution of vaccines is unjust towards the vulnerable living in low-income countries. A vaccine tax should be introduced to remedy this. Under such a scheme, a small fraction of the money spent by a country on vaccines for its own population would go into a fund, such as (...) COVAX, dedicated to buying vaccines and distributing them to the world’s poorest. A vaccine tax would provide a much-needed injection of funds to remedy the unequal distribution of vaccines. The tax allows for a distribution that, to a lesser degree, reflects the ability to pay and is superior to a donation-based model because it minimises the opportunity for free-riding. (shrink)

In this well-argued little volume, the author carefully states and criticizes the prevailing theories of distributive justice, then goes on to articulate his own original and nuanced account. His bases for criticizing other theories and justifying his own are the common intuitions people have about what is just and what is not. Thus much of his criticism takes the form of showing that a theory sanctions certain distributions as just which we would all regard as unjust. Bowie defines the problem (...) of distributive justice in terms of conflict of competing claims: the question about just distribution arises only when there are not enough goods and services to satisfy everyone’s desires for them. In criticizing current theories of justice, utilitarianism, egalitarianism, and socialism, Bowie shows that all three types of theory are too exclusive in that they distribute on the basis of one value only, and thus cannot rationally decide conflicts which arise from values other than the one they are based on. Thus utilitarianism cannot do justice to the claims of equality; egalitarianism to the claims of freedom from coercion; socialism to the claims of liberty, merit, or ability. (shrink)

In response to the big data era trend, statistics has become an indispensable part of mathematics education in junior high school. In this study, a pre-test and a post-test were developed for the six attributes of the data distribution characteristic. This research then used the cognitive diagnosis model to learn about the poorly mastered attributes and to verify whether cognitive diagnosis can be used for targeted intervention to improve students' abilities effectively. One hundred two eighth graders participated in the (...) experiment and were divided into two groups. Among them, the intervention materials read by the experimental group students only contained attributes that they could not grasp well. In contrast, the reading materials of the control group were non-targeted. The results of the study showed the following: The variance and the weighted average were poorly mastered by students in the pre-test; compared with the control group, the average test score of the experimental group was significantly improved; in terms of attributes, the experimental group students' mastery of variance and the weighted average was significantly improved than the pre-test, while the control group's mastery was not. Based on this, some teaching suggestions were put forward. (shrink)

Le développement de l'individualisme et les orientations actuelles du design des technologies de l'information et de la communication se combinent pour ancrer réflexivement un modèle de l'action fondé sur le modèle de la distribution. L'acteur délègue une partie des choix de plus en plus nombreux qui lui incombent à son environnement artefactuel. Dans le champ de la communication interpersonnelle, ceci se traduit par le développement d'une gestion relationnelle basée sur la « présence connectée ». Dans le domaine des communautés (...) épistémiques de type OpenSource, les individus se mobilisent souvent sur un mode de réactivité immédiate plus que par délibération individuelle. La question se pose alors du statut moral et de la possibilité d'analyser de manière indépendante un collectif et un espace public d'individus hyper-connectés, organisés, outillés et adaptés plus pour réagir rapidement que réfléchir longuement.Development of individualism and the current guidelines for the design of information technology and communications combine to anchor a model of reflexive action based on the model of the distribution. The actor delegates some choices more numerous its obligations to its environment artifactual. In the field of interpersonal communication, this translates into the development of a relationship management based on "connected presence". In the field of epistemic communities like OpenSource, individuals often involve a more immediate response mode by individual deliberation. The question then arises the moral status and the ability to analyze independently a collective and public space of hyper-connected individuals, organized, equipped and adapted to respond more quickly than think long. (shrink)

Bayesian paradigm has been widely acknowledged as a coherent approach to learning putative probability model structures from a finite class of candidate models. Bayesian learning is based on measuring the predictive ability of a model in terms of the corresponding marginal data distribution, which equals the expectation of the likelihood with respect to a prior distribution for model parameters. The main controversy related to this learning method stems from the necessity of specifying proper prior distributions for (...) all unknown parameters of a model, which ensures a complete determination of the marginal data distribution. Even for commonly used models, subjective priors may be difficult to specify precisely, and therefore, several automated learning procedures have been suggested in the literature. Here we introduce a novel Bayesian learning method based on the predictive entropy of a probability model, that can combine both subjective and objective probabilistic assessment of uncertain quantities in putative models. It is shown that our approach can avoid some of the limitations of the earlier suggested objective Bayesian methods. (shrink)

In this paper, we develop a 3D-individual-based model to understand effect of various small-scale mechanisms in phytoplankton cells, on the cellular aggregation process. These mechanisms are: spatial interactions between cells due to their chemosensory abilities, a molecular diffusion and a demographical process. The latter is considered as a branching process with a density-dependent death rate to take into account the local competition on resources. We implement the IBM and simulate various scenarios under real parameter values for phytoplankton cells. To (...) quantify the effects of the different processes quoted above on the spatial and temporal distribution of phytoplankton, we used two spatial statistics: the Clark–Evans index and the group belonging percentage. Our simulation study highlights the role of the branching process with a weak-to-medium competition in reinforcing the aggregating structure that forms from attraction mechanisms, and shows by contrast that aggregations cannot form when competition is high. (shrink)

Nowadays, the development of human society and daily life are inseparable from the power supply. Therefore, people also put forward higher requirements for the reliability of distribution network, but power companies can only passively deal with distribution network failures, which is a bottleneck for the improvement of distribution network reliability. The Internet of Things is the best solution for online equipment status monitoring and basic data sharing for large, widely distributed, relatively fixed, and large numbers of equipment. (...) The construction of the IoT for power distribution equipment faces many important problems, including the selection of networking, equipment selection, and interaction standards. When researching the implementation plan, research on the distribution of IoT market was carried out. Based on the grid, the idea of optimizing the investment selection plan of the power distribution using IoT was discussed, and a result verification model was established. After the completion of the theoretical part, a case study of medium-voltage distribution grid equipment management and medium-voltage distribution network equipment management based on the grid was carried out by taking a real enterprise application situation as an example. Realizing fault diagnosis of distribution network will not only provide decision support for operation and maintenance of distribution network for power companies, but also have great economic and social benefits. Aiming at the shortcomings of single data mining method in distribution network fault diagnosis, hybrid data mining method is proposed. First, rough set theory is used to reduce the original fault data and form a simplified rule set. Because of the non-linearity of distribution network fault and the strong learning ability, adaptability, and robustness of Bayesian network, Bayesian network can be used to classify distribution network faults. Therefore, a simplified fault diagnosis system is established in this paper, and its correctness is confirmed. Then, the learning and training are carried out by using Bayesian network to call the simplest rule set, which has the characteristics of short learning and training time and high diagnostic accuracy. (shrink)

In this paper, we investigate the model of decentralized groupwise e-commerce through regional chains combined with edge computing algorithms and design and implement it. A blockchain-based architecture for remote sensing resource and service transactions is proposed. The architecture utilizes the characteristics of nontamperable and traceable data on the blockchain to solve the problem of mutual distrust between the transaction parties, uses MongoDB for data retrieval and filtering to solve the problem that it is difficult to query flexibly on the (...) blockchain, uses the file platform to save public resources to solve the problem that it is very expensive or even infeasible to store images or large texts in the blockchain, and ensures remote sensing resources and services related to the effective storage of images and description texts. The Ethernet features are described and analyzed to assess their suitability as a technical basis for the corresponding solutions. To assess the ability of the Ethernet-based system to solve solvable problems, its practical use cases are analyzed. The results of the analysis show that five main issues need to be addressed when applying Ethernet to e-commerce, namely, low scalability, lack of distributed storage, lack of convenience, reliability, and functional integrity. To exploit the idea of using blockchain technology to solve complex problems and to overcome the challenges identified in the existing Ethernet-based implementation solutions, an optimization idea is proposed by creating a multiblockchain architecture based multimodule solution in the Ethernet framework. Finally, the application prospects of the proposed information system are discussed. (shrink)

Malian farmers’ traditional system for managing seed of sorghum, an indigenous crop of vital importance for food security and survival, can be conceptualized as a commons. Although this system maintains a wide range of varieties and helps ensure access to seed, its ability to create and widely disseminate new varieties to meet evolving opportunities and challenges is limited. A network of farmer groups, public breeding programs, and development organizations collaborating in decentralized creation and dissemination of sorghum varieties in Mali (...) is examined regarding (1) how the network developed and what activities it conducts; (2) the resulting varietal diversity, varietal performance and organizational models; and (3) the elements of the traditional seed system that were maintained, strengthened or transformed. A single-case study approach was used that relies on published literature, official catalogues of released varieties and a database of farmer seed-cooperative requests for foundation seed. The functioning of the network and its varietal-, seed-, and organizational- outcomes are documented and the elements of the traditional sorghum seed system that are maintained or strengthened are analyzed. The evolution of the network’s reliance on commoning as a social process and its strengthening of core Seed Commons features are discussed with a view to the network’s contributions to targeted development outcomes and potential replicability. The case demonstrates how creating a framework for collaboration, enabling actors and organizations to take on collective responsibility while maintaining distributed decision-making at local level, opens opportunities for transforming farming- and food-systems towards sustainability and resilience. (shrink)

The aim of this study is to assess the role of readers’ proficiency and of the base-word distributional properties on eye-movement behavior. Sixty-two typically developing children, attending 3rd, 4th, and 5th grade, were asked to read derived words in a sentence context. Target words were nouns derived from noun bases (e.g., umorista, ‘humorist’), which in Italian are shared by few derived words, and nouns derived from verb bases (e.g., punizione, ‘punishment’), which are shared by about 50 different inflected forms and (...) several derived words. Data showed that base and word frequency affected first-fixation duration for nouns derived from noun bases, but in an opposite way: Base frequency had a facilitative effect on first fixation, whereas word frequency exerted an inhibitory effect. These results were interpreted as a competition between early accessed base words (e.g., camino, chimney) and target words (e.g., caminetto, fireplace). For nouns derived from verb bases, an inhibitory base frequency effect but no word frequency effect were observed. These results suggest that syntactic context, calling for a noun in the target position, lead to an inhibitory effect when a verb base was detected, and made it difficult for readers to access the corresponding base+suffix combination (whole word) in the very early processing phases. Gaze duration was mainly affected by word frequency and length: for nouns derived from noun bases, this interaction was modulated by proficiency, as length effect was stronger for less proficient readers, while they were processing low-frequency words. For nouns derived from verb bases, though, all children, irrespective of their reading ability, showed sensitivity to the interaction within frequency of base+suffix combination (word frequency) and target length. Results of this study are consistent with those of other Italian studies that contrasted noun and verb processing, and confirm that distributional properties of morphemic constituents have a significant impact on the strategies used for processing morphologically complex words. (shrink)

Abnormal behavior detection of social security funds is a method to analyze large-scale data and find abnormal behavior. Although many methods based on spectral clustering have achieved many good results in the practical application of clustering, the research on the spectral clustering algorithm is still in the early stage of development. Many existing algorithms are very sensitive to clustering parameters, especially scale parameters, and need to manually input the number of clustering. Therefore, a density-sensitive similarity measure is introduced in (...) this paper, which is obtained by introducing new parameters to transform the Gaussian function. Under this metric, the distance between data points belonging to different classes will be effectively amplified, while the distance between data points belonging to the same class will be reduced, and finally, the distribution of data will be effectively clustered. At the same time, the idea of Eigen gap is introduced into the spectral clustering algorithm, and the verified gap sequence is constructed on the basis of Laplace matrix, so as to solve the problem of the number of initial clustering. The strong global search ability of artificial bee colony algorithm is used to make up for the shortcoming of spectral clustering algorithm that is easy to fall into local optimal. The experimental results show that the adaptive spectral clustering algorithm can better identify the initial clustering center, perform more effective clustering, and detect abnormal behavior more accurately. (shrink)

This article sets forth a solidaristic approach to global distribution of vaccines against the SARS‐CoV‐2 virus. Our approach draws inspiration from African ethics and from the characterization of the Covid‐19 crisis as a syndemic, a convergence of biosocial forces that interact with one another to produce and exacerbate clinical disease and prognosis. The first section elaborates the twin ideas of syndemic and solidarity. The second section argues that these ideas lend support to global health alliances to distribute vaccines beyond (...) national borders. The third section introduces ethical criteria to guide global distribution, emphasizing priority to low‐ and middle‐income countries, which have the least ability to obtain vaccines on their own. It also justifies giving priority to people at high risk of infection and high risk of severe disease and death. (shrink)

Emotion recognition plays an important part in human-computer interaction. Currently, the main challenge in electroencephalogram -based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network to construct a transfer model for EEG-based emotion recognition. Specifically, deep features from the topological graph, which preserve topological information from EEG signals, are extracted using a deep neural network. These features are then (...) passed through TDANN for two-level domain confusion. The first level uses the maximum mean discrepancy to reduce the distribution discrepancy of deep features between source domain and target domain, and the second uses the domain adversarial neural network to force the deep features closer to their corresponding class centers. We evaluated the domain-transfer performance of the model on both our self-built data set and the public data set SEED. In the cross-day transfer experiment, the ability to accurately discriminate joy from other emotions was high: sadness, anger, and fear on the self-built data set. The accuracy reached 74.93% on the SEED data set. In the cross-subject transfer experiment, the ability to accurately discriminate joy from other emotions was equally high: sadness, anger, and fear on the self-built data set. The average accuracy reached 87.9% on the SEED data set, which was higher than WGAN-DA. The experimental results demonstrate that the proposed TDANN can effectively handle the domain transfer problem in EEG-based emotion recognition. (shrink)

Modern cities form city networks through complex social ties. City network research is widely applied to guide regional planning, infrastructure construction, and resource allocation. China put forward the Yellow River Basin Development Strategy in 2019, but no research has been conducted on regional social connections among cities. Based on the gravity model modified by two-way “time distance” between cities, this is the first study to empirically examine the intensity and structure of the entire city network in the Yellow River (...) basin using the social network analysis method and ArcGIS software. The connection rules of the cross-city transfer of city officials in the basin are also investigated to illustrate the official ties between cities. The results suggest that the intensity of two-way connections between cities is generally low in the Yellow River basin and there is a positive correlation between city network development level and regional economic development level. The development gap between cities on the north and south banks is larger than that between the east and west regions, and some cities in the middle and upper reaches of the river are marginalized in the network. The status of the central cities in the Yellow River basin is distinct, but their connecting and leading abilities are not strong, showing an inverted T-shaped spatial distribution. The subgroups of city networks have strong internal connections, while the connection among subgroups is weak and the development shows a partitioned and fragmented pattern, making it difficult to form linkages among the upper, middle, and lower reaches. The “beaded chain” spatial development strategy can be adopted in the river basin planning, giving priority to strengthening the links within subgroups of cities and among adjacent subgroups, building central city chains, and reinforcing the overall basin management. (shrink)

Action must be taken to combat climate change. Yet, how the costs of climate action should be allocated among states remains a question. One popular answer—the polluter-pays principle (PPP)—stipulates that those responsible for causing the problem should pay to address it. While intuitively plausible, the PPP has been subjected to withering criticism in recent years. It is timely, following the Paris Agreement, to develop a new version: one that does not focus on historical production-based emissions but rather allocates climate (...) burdens in proportion to each state’s annual consumption-based emissions. This change in carbon accounting results in a fairer and more environmentally effective principle for distributing climate duties. (shrink)

I argue that the propensity interpretation of fitness, properly understood, not only solves the explanatory circularity problem and the mismatch problem, but can also withstand the Pandora’s box full of problems that have been thrown at it. Fitness is the propensity (i.e., probabilistic ability, based on heritable physical traits) for organisms or types of organisms to survive and reproduce in particular environments and in particular populations for a specified number of generations; if greater than one generation, “reproduction” includes (...) descendants of descendants. Fitness values can be described in terms of distributions of propensities to produce varying number of offspring and can be modeled for any number of generations using computer simulations, thus providing both predictive power and a means for comparing the fitness of different phenotypes. Fitness is a causal concept, most notably at the population level, where fitness differences are causally responsible for differences in reproductive success. Relative fitness is ultimately what matters for natural selection. (shrink)

Shortages of generic, injectable chemotherapeutics have been increasing in prevalence since 2006. Due to the lack of access to first-line, lifesaving treatments, physicians have been forced to ration chemotherapy between patients. Although the scarcity has been managed with good intentions, it has been done in an ad hoc manner, without the benefit of an ethically grounded and standardized schema. Using an approach based on the “accountability for reasonableness” method by Daniel and Sabin, I establish a framework and protocol for (...) rationing that is specific to chemotherapy. Prior to the state of true shortage, I present guidelines for the use of an adequate supply of chemotherapy with knowledge of upcoming scarcity. Within the rationing framework itself, I first prioritize emergency use of chemotherapeutics and those already receiving treatment at the time of shortage. I advocate for stratifying patients based on the prognostic indicators of their cancer type, using a combination of clinical-trial-based initial response and longer term survival, followed by the patients’ line of treatment. All patients who are not able to receive their “best” treatment must receive a sequent, next-best treatment, and their treatment team must have the ability to appeal to a rationing committee in special circumstances. I reject the ideas of stratification based on the intention of the treatment, perceived quality of life, pre-existing condition not impacting performance status, the classical “sickest first” argument, and giving preference to pediatric cases. Lastly, I advocate for any system of rationing to be transparent to those it affects and acknowledge the difficulties it presents to patients and physicians alike. (shrink)

The power grid is an important connection between power sources and users, responsible for supplying and distributing electric energy to users. Modern power grids are widely distributed and large in scale, and their security faces new problems and challenges. Information entropy theory is an objective weighting method that compares the information order of each evaluation index to judge the weight value. With the wide application of entropy theory in various disciplines, the subject of introducing entropy into the power system has (...) been gradually concerned. This article aims to study the smart terminal security technology of the power grid perception layer based on information entropy data mining. This article analyzes its related methods and designs a smart terminal for the power grid. On this basis, a data analysis platform is built and a safety plan is designed. The result is that the average absolute error, root mean square error, average absolute percentage error, and mean square error of the platform's power load forecast are 1.58, 1.96, 8.2%, and 3.93, respectively. These error values are within the ideal range, and the data processing ability is strong. The packet loss rate of the adversary's eavesdropping was tested, and the average packet loss rates at locations a, b, c, and d were 1.05, 1.2, 1.81, and 2.2%, respectively. Data packets will be definitely lost, so the platform is highly secure. (shrink)

This paper aims to contribute to the growing discussion about leadership in the contemporary Church of England with a particular interest in the complex interaction between social context and leadership practices. Implicit leadership theory is used to explore mutual expectations around distributed models of lay and ordained leadership as well as ‘ordinary’ members’ of congregation. Applying a qualitative research method, we conducted 32 semi-structured interviews in 6 Church of England parishes. Through the systematic analysis of relevant contextual factors at multiple (...) levels, we identify limited congruence between ideal leadership attributes and actual behavior. We contribute to the ILT literature by identifying ethical attributes, such as the ability to help others flourish, as particularly pertinent to the religious setting. We also identify the malleability of some leadership attributes. We further contribute to the literature on organizational studies in faith-based organizations by offering novel insights into the relationship between leadership, followership and contextual factors at local parish level which have significant practical implications for recruiting and training church leaders and followers. (shrink)

In this paper, we analyze and calculate the crowd density in a tourist area utilizing video surveillance dynamic information analysis and divide the crowd counting and density estimation task into three stages. In this paper, novel scale perception module and inverse scale perception module are designed to further facilitate the mining of multiscale information by the counting model; the main function of the third stage is to generate the population distribution density map, which mainly consists of three columns of (...) void convolution with different void rates and generates the final population distribution density map using the feature maps of different branch regressions. Also, the algorithm uses jump connections between the top convolution and the bottom void convolution layers to reduce the risk of network gradient disappearance and gradient explosion and optimizes the network parameters using an intermediate supervision strategy. The hierarchical density estimator uses a hierarchical strategy to mine semantic features and multiscale information in a coarse-to-fine manner, and this is used to solve the problem of scale variation and perspective distortion. Also, considering that the background noise affects the quality of the generated density map, the soft attention mechanism is integrated into the model to stretch the distance between the foreground and background to further improve the quality of the density map. Also, inspired by multitask learning, this paper embeds an auxiliary count classifier in the count model to perform the count classification auxiliary task and to increase the model’s ability to express semantic information. Numerous experimental results demonstrate the effectiveness and feasibility of the proposed algorithm in solving the problems of scale variation and perspective distortion. (shrink)

The laser chaos decision maker has been demonstrated to enable ultra-high-speed solutions of multiarmed bandit problems or decision-making in the GHz order. However, the underlying mechanisms are not well understood. In this paper, we analyze the chaotic dynamics inherent in experimentally observed laser chaos time series via surrogate data and further accelerate the decision-making performance via parameter optimization. We first evaluate the negative autocorrelation in a chaotic time series and its impact on decision-making detail. Then, we analyze the decision-making (...) class='Hi'>ability using three different surrogate chaos time series to examine the underlying mechanism. We clarify that the negative autocorrelation of laser chaos improves decision-making and that the amplitude distribution of the original laser chaos time series is not optimal. Hence, we introduce a new parameter for adjusting the amplitude distribution of the laser chaos to enhance the decision-making performance. This study provides a new insight into exploiting the supremacy of chaotic dynamics in artificially constructed intelligent systems. (shrink)

The purpose of this study was to examine the role of personality traits on academic performance. Furthermore, this study also aims at exploring the effects of virtual experience (mediator) and emotional intelligence (moderator) between personality traits and academic performance of the students. The findings imply that personality traits are the strong predictors of better academic performance. However, several personality traits do not have a positive impact on the academic performance. The study further suggests that students who have emotional abilities and (...) virtual experience are more likely to perform well in their academics. The population of this research consists of students in various colleges and universities in developing regions. Thus, the sample consists of bachelor's and master's students. Existing scales are adopted with minor changes to make it more suitable and understandable within the study context. A total of 319 questionnaires were distributed. Among these 365 questionnaires, 234 questionnaires were received and further used for the purpose of data analysis. This shows an encouraging response from the targeted sample. Education and productivity of the students are influenced by their personality as well as their emotional intelligence abilities. The findings imply that being extrovert is a strong predictor of student achievement and should be prioritized in intervention strategies. This personality feature is responsible for performance in addition to virtual learning experience. Despite its low overall relative value, agreeableness is a significant driver of student achievement. Along with ability and aptitude assessments, personality evaluations might be utilized as a secondary screening tool to identify adolescents at risk of underperformance and academic performance failure. Therefore, learning emotional skills would be beneficial to cope the modern challenges of the competitive educational environment. Virtual experience and being emotionally sound can help students to learn quickly and to be more adaptive into the new world of digitalization. The conclusions of the current study have significant consequences for educators and policymakers. They must accept that boosting emotional intelligence levels through teaching or training is a significant objective of contemporary education. The emotional intelligence abilities of the students related to culture may be shown in a variety of ways, from expectations toward students to interpersonal interactions with students, and from teaching techniques to evaluation methods. (shrink)

Many important harms result in large part from our collective omissions, such as harms from our omissions to stop climate change and famines. Accounting for responsibility for collective omissions turns out to be particularly challenging. It is hard to see how an individual contributes anything to a collective omission to prevent harm if she couldn’t have made a difference to that harm on her own. Some groups are able to prevent such harms, but it is highly contentious whether groups can (...) be loci of responsibility. This paper takes an existing and plausible framework of moral responsibility—one based on abilities—and scales it up to accommodate responsibility for collective omissions. This centrally involves identifying what the relevant collective abilities are and how they work. One significant benefit of this approach is that we can do this while remaining neutral on the debates about collective agency and collective responsibility by showing how individualist and collectivist versions of the theory work. Finally, I explore several further upshots of the scaled-up ability-based account, including that degrees of responsibility can be cashed out in terms of strengths of the relevant abilities, which has both theoretical and applied implications. (shrink)

Within modern liberal political philosophy, discussions on justice have been centered upon an individualism-based distributive justice and the ‘fair share’ due to each person. According to the liberal theory of justice, the individual is an entity of rational reason and moral autonomy and considers the interests of others and of the community from a viewpoint that is focused on one’s own interests. As practical principles of justice, the principle of desert has attempted to separate the individual’s natural and inherent (...) abilities (merit) from the individual’s intentional efforts (desert); while the principle of needs has transmuted into a set of minimum exclusivity rights to protect the individual’s autonomy from serious harm and injury. Procedural justice theorists such as Rawls have attempted to invalidate the merit of the individual in an attempt to establish the identity of individuals whom are independent of the community, in the effort to promote their ideas on how to mitigate the social inequality that results from natural arbitrariness. The requirement to finalize this logical process is astrong moral reason equipped individual with the capacity of rational action. However, paradoxically, the logic of excessive reason has created an individual who isexclusive-rights-empowered but becomes ‘isolated and selfish’. The issues resulting from this situation are, first, the rational individual who is equipped with moral autonomynow becomes hidden behind a system-guaranteed set of exclusive rights; and second, the individual who should have been a rational actor and actively participating in cooperation and reciprocal relationships, does not find it easy to overcome the temptations of becoming a strategically located but passive and selfish actor within the mass market order. The result is that individuals easily relinquish their moral autonomy and exhibit a tendency to focus on personal gain. This has resulted in an increase in the polarization of society, and an increase of conflict between classes; and has engendered a crisis in the common good of the family and the political community. The true ‘good life’ and the ‘well-ordered community’ cannot be obtained by individuals who are only interested in their ‘share’, but requires ‘good citizens’ who are concerned about the happiness of others and of the society. When we are able to understand that the rational and selfish individual is necessarily non-self-sufficient; and acknowledge that there is a need for mutual philia with others, we will then be able to overcome rational reason and embrace civic friendship. The good citizen of a healthy community that is based on civic friendship, is an individual who has assimilated the virtue of justice, and will be able to aid inovercoming the limitations of modern liberalism, assist in the resolution of the pressing societal and individualistic crises and contribute to theestablishment of a ‘well-ordered community’. (shrink)

A distributed neural network model called SPEC for processing sentences with recursive relative clauses is described. The model is based on separating the tasks of segmenting the input word sequence into clauses, forming the case‐role representations, and keeping track of the recursive embeddings into different modules. The system needs to be trained only with the basic sentence constructs, and it generalizes not only to new instances of familiar relative clause structures but to novel structures as well. SPEC exhibits plausible (...) memory degradation as the depth of the center embeddings increases, its memory is primed by earlier constituents, and its performance is aided by semantic constraints between the constituents. The ability to process structure is largely due to a central executive network that monitors and controls the execution of the entire system. This way, in contrast to earlier subsymbolic systems, parsing is modeled as a controlled high‐level process rather than one based on automatic reflex responses. (shrink)

In the space of possible worlds, there might be a best possible world (a uniquely best world or a world tied for best with some other worlds). Or, instead, for every possible world, there might be a better possible world. Suppose that the latter is true, i.e., that there is no best world. Many have thought that there is then an argument against the existence of God, i.e., the existence of an omnipotent, omniscient and morally perfect being; we will call (...) such arguments no-best-world arguments. In this paper, we discuss ability-based objections to such arguments; an ability-based objection to a no-best world argument claims that the argument fails because one or more of its premises conflict with a plausible principle connecting the applicability of some type of moral evaluation to the agent’s possession of a relevant ability. In particular, we formulate and evaluate an important new ability-based objection to the most promising no-best world argument. (shrink)

Many have argued that individuals should receive income in proportion to their contribution to society. Others have believed that it would be fairer if people received income in proportion to the effort they expend in so contributing, since people have much greater control over their level of effort than their productivity. I argue that those who believe this are normally also committed, despite appearances, to increasing the social product — which undermines any sharp distinction between effort- and productivity-based distributive (...) proposals. However, effort-based proposals do emphasise more the importance of people having control over factors affecting their income. The second set of problems I consider is how to implement policies which hold true to this emphasis. I show that there are major problems with the accuracy of using any objective criteria to measure the level of effort a person is expending. Moreover, once any such criteria are employed the problem of ‘moral hazard’arises because people modify their behaviour in such a way as to maximise their income while minimising their effort. This violates the original motivation for using effort. Because of this and other empirical considerations, I argue that productivity may well be a better criterion on which to distribute income even if one is motivated by the same concerns which have prompted effort-based proposals. (shrink)

What is it to have a mental disorder? The paper proposes an ability-based view of mental disorder. It argues that such a view is preferable to biological dysfunction views such as Wakefield’s Harmful Dysfunction Analysis and Boorse’s Biostatistical Theory. According to the proposed view, having a mental disorder is basically a matter of having a certain type of inability (or: an ability that is not sufficiently high): the inability to respond adequately to some of one’s available reasons (...) in some of one’s reasons-sensitive attitudes or actions, where the threshold of inability is determined by one’s being harmed. The relevant concepts of inability, reasons, and harm are sketched. The paper argues that the proposed view evades some problems of biological dysfunction views by remaining neutral on questions of causation and the evolution of the mind. Furthermore, it can capture better what is distinctively “mental” about mental disorder. On the proposed view, it is the rational relations among an individual’s attitudes and actions that are “disordered” and the relevant norms in mental disorder are the norms of reasons. As further merits, the view can account for degrees of disorder, incorporate biological as well as social aspects, and elucidate the relations among disorders, symptoms, and their causes. (shrink)

This article argues for a task-based approach to identifying and individuating cognitive systems. The agent-based extended cognition approach faces a problem of cognitive bloat and has difficulty accommodating both sub-individual cognitive systems ("scaling down") and some supra-individual cognitive systems ("scaling up"). The standard distributed cognition approach can accommodate a wider variety of supra-individual systems but likewise has difficulties with sub-individual systems and faces the problem of cognitive bloat. We develop a task-based variant of distributed cognition designed to (...) scale up and down smoothly while providing a principled means of avoiding cognitive bloat. The advantages of the task-based approach are illustrated by means of two parallel case studies: re-representation in the human visual system and in a biomedical engineering laboratory. (shrink)

It is usually taken as given that consciousness involves superior or more elaborate forms of information processing. Contemporary models equate consciousness with global processing, system complexity, or depth or stability of computation. This is in stark contrast with the powerful philosophical intuition that being conscious is more than just having the ability to compute. I argue that it is also incompatible with current empirical findings. I present a model that is free from the strong assumption that consciousness predicts superior (...) performance. The model is based on Bayesian decision theory, of which signal detection theory is a special case. It reflects the fact that the capacity for perceptual decisions is fundamentally limited by the presence and amount of noise in the system. To optimize performance, one therefore needs to set decision criteria that are based on the behaviour, i.e. the probability distributions, of the internal signals. One important realization is that the knowledge of how our internal signals behave statistically has to be learned over time. Essentially, we are doing statistics on our own brain. This ‘higherorder’ learning, however, may err, and this impairs our ability to set and maintain optimal criteria for perceptual decisions, which I argue is central to perception consciousness. I outline three possibilities of how conscious perception might be affected by failures of ‘higher-order’ representation. These all imply that one can have a dissociation between consciousness and performance. This model readily explains blindsight and hallucinations in formal terms, and is beginning to receive direct empirical support. I end by discussing some philosophical implications of the model. (shrink)

Intuitively, there is a close link between moral status and phenomenal consciousness. Taking the link seriously can serve as the basis of a proposal that appears to have a surprising number of theoretical benefits. This proposal is the moral option, according to which moral status is partly determinative of phenomenal consciousness, and phenomenal consciousness is sufficient for possession of a moral property I refer to as “moral status.” I argue for this view on the basis of its ability to (...) shed light on the distribution problem of determining which systems are phenomenally conscious. I explicate it by drawing on a theory of attributions of phenomenal consciousness, and considering its relationship to positions on the metaphysics of consciousness. I defend it against a series of objections, including three based on previous theories of the link between phenomenal consciousness and moral status. The moral option should, in my view, be a serious contender among theories of phenomenal consciousness. (shrink)

Phenomenal awareness, the ability to be aware of one's sensations and feelings, emerges from the capacity of evolved brains to represent their own cognitive processes by iterating and self-reapplying the cortical operations that generate representations of the outer world. Search for the neuronal substrate of awareness therefore converges with the search for the neuronal code through which brains represent their environment. The hypothesis is put forward that the mammalian brain uses two complementary representational strategies. One consists of the generation (...) of neurons responding selectively to particular constellations of features, and is based on selective recombination of inputs in hierarchically structured feed-forward architectures. The other relies on the dynamic association of large numbers of distributed neurons into functionally coherent cell assemblies which as a whole represent a content of cognition. Arguments and data are presented in favor of the second strategy as the one according to which meta-representations that support awareness are established. My hypothesis is that such distributed representations self-organize through transient synchronization of the oscillatory activity. Evidence showing that similar brain states are required both for the occurrence of these synchronization phenomena and for awareness is provided. (shrink)

Competence is central to informed consent and, therefore, to medical practice. In this context, competence is regarded as synonymous with decision-making capacity. There is wide consensus that competence should be approached conceptually by identifying the abilities needed for decision-making capacity. Incompetence, then, is understood as a condition in which certain abilities relevant to decision-making capacity are lacking. This approach has been helpful both in theory and practice. There is, however, another approach to incompetence, namely to relate it to mental disorder. (...) This approach has been followed in recent research that has shown, for instance, that in anorexia nervosa a person's values may be changed, resulting in ‘pathological’ values. We explore some advantages and disadvantages of both abilities-based and pathology-based approaches. We argue that both can be valuable for further clarification of the concept of competence and improving clinical practice. Given the current predominance of the abilities-based approach, we make a plea for a greater focus on pathology-based practice and research. (shrink)

Traditional welfare states were based on passive solidarity. Able bodied, healthy minded citizens paid taxes and social premiums, usually according to a progressive taxation logic following the ability to pay principle. Elderly, fragile, weak, unhealthy and disabled citizens were taken care of in institutions, usually in quiet parts of the country. During the nineteen eighties and nineties of the twentieth century, ideas changed. Professionals, patients and policy makers felt that it would be better for the weak and fragile (...) to live in mainstream society, rather than be taken care of in institutions outside society. This might be cheaper too. Hence policy measures were taken to accomplish deinstitutionalization. This article discusses the implications of deinstitutionalization for distributive justice. It is argued that the weakest among the weak and fragile stand to lose from this operation. For able bodied citizens deinstitutionalization entails a move from passive to active solidarity. Rather than just pay taxes they have to actively care for and help the needy themselves. The move from passive to active solidarity tends to take advantage of benevolent citizens and burden the socioeconomically disadvantaged. This may be a reason to reconsider the policy move toward deinstitutionalization. (shrink)