87value/wos11967 huggingface dataset:
Due to lack of the Source-network-Ioad global perception and multiple time-scale situation awareness, the current distribution network cannot meet the requirements of the active distribution network (ADN) such as active control and active management. An ADN situation awareness system based on distributed monitoring and multi-source information fusion is proposed in this paper. By constructing a multi-level distributed monitoring system based on Internet of Things (lOT) technology, monitoring objects of distribution network are expanded to achieve global awareness in spatial scale. In the light of the randomness and volatility risk of distribution network operation, it is necessary to enhance observability of situation awareness in time scale. Thus, the situation awareness technology of distribution network based on multi-source information fusion is provided, which is constituted of the multi-source information fusion, source-load forecasting, fast simulation analysis, risk assessment and warning and visualization modules. Finally, the operation cockpit visualization technology enables operators to efficiently capture accurate distribution network security situation trend. The ADN Situation Awareness System Demonstration Project is currently being carried out by State Grid Jiangsu Power Company, the actual operation indicates that it can effectively enhance the operation situation awareness and risk early-warning capability.
Self-evaluative emotions depend on internalized social standards and motivate social action. However, there is a lack of empirical research documenting the impact of self-evaluative emotion on 3- and 4-year-olds' prosociality. Extant research relates children's experiences of guilt to empathetic concern and making amends. However, the relationship between guilt and both concern and making amends is potentially reductive. Empathetic concern involves similar bodily expressions to guilt, and amend making is used to distinguish guilt from shame in children. This is the first study to relate the development of both positive and negative self-evaluative emotions to empathetic concern and prosocial choice (making amends and spontaneous help). Results confirm that the broad capacity for self-evaluative emotion is established during the preschool years and relates to empathetic concern. Moreover, these social emotions can be used to predict prosocial choice. Making amends was best predicted by empathetic concern and by children's responses to achievement (pride following success and lack of shame following failure). Alongside moral pride, pride in response to achievement and resilience to shame was also the best predictor of spontaneous help. The data support the idea that young children's prosocial choices may be partially driven by the affective drive to maintain an ideal self. Psychologists have emphasized that in order to be adaptive, self-evaluative emotion should be guilt oriented rather than shame oriented. However, the adaptive role of pride has been neglected. We call on future research to redress the focus on negative self-evaluation in moral development and further explore the prosocial potential of pride. (C) 2016 Elsevier Inc. All rights reserved.
Nonverbal behavior plays an important role in any human-human interaction. Teaching-an inherently social activity-is not an exception. So far, the effect of nonverbal behavioral cues accompanying lecture delivery was investigated in the case of traditional ex-cathedra lectures, where students and teachers are co-located. However, it is becoming increasingly more frequent to watch lectures online and, in this new type of setting, it is still unclear what the effect of nonverbal communication is. This article tries to address the problem and proposes experiments performed over the lectures of a popular web repository (Videolectures). The results show that automatically extracted nonverbal behavioral cues (prosody, voice quality and gesturing activity) predict the ratings that Videolectures users assign to the presentations.
Ownership of a smartphone has never been easier nowadays, and it is supported by the fact that most of the people around us have a smartphone or an equivalent smart device. What is smartphone and why is it a smart? A smartphone by definition is as the name suggests, it is a phone is smart enough to not only be limited to the features and capabilities of a traditional cellular phone but also perform what a smart device can. And in recent years, the device that is deemed as the most intelligent device is the computer as it is the most advance piece of technology that is commercially available to the general public. Why this is so, is because in our opinion it has revolutionized how most if not all of the societies of today work. Hence what makes a smartphone is the mobile operating system that it is built upon, which is similar to a computer. It is becoming more and more of a common sight nowadays and this is because they are being offered at a price where more people are able to afford, hence they are reaching the hands of ceiling of the lower income families, all the way up to the higher income families. Back then, pure play devices were mostly simple in terms of how it function and works, hence if possible, we could suggest that the security aspect was never or rather has never been an issue other than the alteration of data after operation such as the tape of video recorders or images captured but never in the process, in the sense that there were no interruptions during operation, most likely is because it was clear and visible, but nowadays when you combine all of those devices into a complex entity, we tend to leave a hole in the cloth somewhere that we did not or rather can't see due to the overwhelming amount of other things that we have. In this paper we discuss the current state of the commercially available operating systems of the two biggest names in smart devices, namely iOS and Android; and measure how secure and/or vulnerable (susceptible) are they to malwares and the nature of the mobile ad hoc network. We first analyze the integrity of the core of a smart device, the operating system and then use it to evaluate the effectiveness of their techniques and defenses of preventing and identifying malwares.
Fasting is one of the simplest metabolic challenges that can be performed in humans. We here report for the first time a comprehensive analysis of the human fasting metabolome obtained from analysis of plasma and urine samples in a small cohort of healthy volunteers, using nuclear magnetic resonance (NMR), gas chromatography- and liquid chromatography-mass spectrometry (GC-MS and LC-MS). Intra- and inter-individual variation of metabolites was on measurement of four overnight fasting samples collected from each volunteer over a four week period. One additional sample per volunteer was collected following a prolonged fasting period of 36 h. Amongst a total of 377 quantified entities in plasma around 44% were shown to change significantly in concentration when volunteers extended fasting from 12 to 36 h. In addition to known markers (plasma free fatty acids, glycerol, ketone bodies) that reflect changes in the body's fuel management under fasting conditions a wide range of new entities such as alpha-aminobutyrate as well as other amino and keto acids were identified as fasting markers. Based on multiple correlations amongst the metabolites and selected hormones in plasma such as leptin or insulin-like-growth-factor-1 (IGF-1), a robust metabolic network with coherent regulation of a wide range of metabolites could be identified. The metabolomics approach described here demonstrates the plasticity of human metabolism and identifies new and robust markers of the fasting state.
Autism spectrum disorders (ASDs) are known to be characterized by restricted and repetitive behaviors and interests and by impairments in social communication and interactions mainly including theory of mind (ToM) processes. The cerebellum has emerged as one of the brain regions affected by ASDs. As the cerebellum is known to influence cerebral cortex activity via cerebello-thalamo-cortical (CTC) circuits, it has been proposed that cerebello-cortical disconnection could in part underlie autistic symptoms. We used resting-state (RS) functional magnetic resonance imaging (fMRI) to investigate the potential RS connectivity changes between the cerebellar dentate nucleus (DN) and the CTC circuit targets, that may contribute to ASD pathophysiology. When comparing ASD patients to controls, we found decreased connectivity between the left DN and cerebral regions known to be components of the ToM network and the default mode network, implicated in specific aspects of mentalizing, social cognition processing, and higher order emotional processes. Further, a pattern of overconnectivity was also detected between the left DN and the supramodal cerebellar lobules associated with the default mode network. The presented RS-fMRI data provide evidence that functional connectivity (FC) between the dentate nucleus and the cerebral cortex is altered in ASD patients. This suggests that the dysfunction reported within the cerebral cortical network, typically related to social features of ASDs, may be at least partially related to an impaired interaction between cerebellum and key cortical social brain regions.
Tinnitus (ringing in the ear) is characterized by the perception of a sound in the absence of a corresponding acoustic stimulus. While many affected people habituate to the phantom sound, others are severely bothered and impaired in their quality of life. It is assumed that the latter group is characterized by a deficient noise cancelling mechanism in the brain. To train tinnitus patients to focus on target sounds and hence to suppress irrelevant background sounds, we developed a mobile serious game application, which is presented in this paper. The application runs on three mobile operating systems. We describe its goals and architecture as well as results from an evaluation study. Study results indicate that the gaming approach is feasible for training affected patients in focusing on directional hearing and, thereby, to suppress their tinnitus. Compared to traditional hearing training, advances of this approach are anytime availability, higher enjoyment, immediate feedback, and the option to stepwise increase game difficulty. From this, we expected an increased patient motivation and adherence as well as improved training and learning effects.
The third-person effect (TPE) hypothesis states that people typically perceive the media messages to have greater influence on others than on themselves. Though this self-other perceptual bias has been shown to be robust across a variety of message contexts, past research has typically utilized Caucasian college student samples. The current study addresses this shortcoming in the literature by examining whether the TPE hypothesis holds for low-income, low-education, Spanish-speaking female adults with regard to the perceived effects of health news coverage. Our findings showed that most participants chose equal to others when estimating health news effects on themselves instead of less than others or more than others. Results from ordinal logistic regression showed that the propensity toward TPE was related to optimistic bias and certain indicators of acculturation. Our findings suggest the need for future TPE research in Hispanic populations and further efforts to investigate TPE from an intercultural perspective.
This study aims to analyze the possible relationships between emotional intelligence and nonverbal communication. A sample of 177 Psychology students completed the TEIQue-SF Emotional Intelligence Questionnaire. The resulting scores were used to divide the sample into three groups based on the mean plus or minus one standard deviation to analyze differences between the extreme groups. The two extreme groups (N= 30) were individually recorded performing the same activity. Three minute clips of each recording were used by expert judges to rate the nonverbal communication of each participant. Both the correlation and Student t test of differences between means confirm that the higher the emotional intelligence, the better the nonverbal communication. Other interesting results are also presented.
This paper presents a Manufacturing Execution System (e-Factory) developed to integrate manufacturing engineering, procurement, production planning, manufacturing and quality functions. e-Factory System supports the production preparation process. The main input of this process is data related with the three dimensions of Production. Product Data, Project Parameters and Plant Data. The outputs of the production preparation (c) 2012 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of Professor D. Mourtzis and Professor G. Chryssolouris.
S6Ks are major effectors of the mTOR (mammalian target of rapamycin) pathway, signaling for increased protein synthesis and cell growth in response to insulin, AMP/ATP levels, and amino acids. Deregulation of this pathway has been related to disorders and diseases associated with metabolism, such as obesity, diabetes, and cancer. S6K family is composed of two main members, S6K1 and S6K2, which comprise different isoforms resulted from alternative splicing or alternative start codon use. Although important molecular functions have been associated with p70-S6K1, the most extensively studied isoform, the S6K2 counterpart lacks information. In the present study, we performed immunoprecipitation assays followed by mass spectrometry (MS) analysis of FLAG-tagged p70-S6K1 and p54-S6K2 interactomes, after expression in HEK293 cells. Protein lists were submitted to CRAPome (Contaminant Repository for Affinity Purification) and SAINT (Significance Analysis of INTeractome) analysis, which allowed the identification of high-scoring interactions. By a comparative approach, p70-S6K1 interacting proteins were predominantly related to cytoskeleton and stress response, whereas p54-S6K2 interactome was more associated to transcription, splicing, and ribosome biogenesis. Moreover, we have found evidences for new targets or regulators of the S6K protein family, such as proteins NCL, NPM1, eIF2 alpha, XRCC6, PARP1, and ILF2/ILF3 complex. This study provides new information about the interacting networks of S6Ks, which may contribute for future approaches to a better understanding of the mTOR/S6K pathway.
It is now possible to detect the pathology of Alzheimer's disease (AD) many years before symptoms and signs otherwise become manifest. Biomarkers of disease include evidence of amyloid and tau in the cerebrospinal fluid and neuroimaging which (for instance) allows amyloid in the brain to be visualized. There is, thus, a preclinical state in which it is possible to identify Alzheimer's pathology long before there is clinical evidence of disease. Much research focuses on this preclinical state because it seems likely that treatments will be more effective before the disease is established. This means that researchers can discover Alzheimer's pathology some years before the person is at risk of developing the condition. In memory clinics, too, people may present with early (prodromal) symptoms which do not yet amount to a dementia syndrome (e.g. mild cognitive impairment), yet biomarker evidence that dementia is highly likely to develop. This is problematic because people will be required to consent to the disclosure of findings that indicate an uncertain risk of an alarming disease. We carried out a scoping review of the issues that arise in connection with a diagnosis of preclinical dementia. We identified four themes in the literature: stigma; ethical issues; psychological burden; and language. We shall discuss these themes and related issues that emerge to do with meaning, medicalization, virtues and values. More research is now required to understand these issues in detail, where the emphasis should be on the breadth of research, which must be biopsychosocial and ethical. (C) 2017 Elsevier B.V. All rights reserved.
This paper presents a network security laboratory to teach data analysis for detecting TCP/IP covert channels. The laboratory is mainly designed for students of electrical engineering, but is open to students of other technical disciplines with similar background. Covert channels provide a method for leaking data from protected systems, which is a major concern for big enterprises and governments. The inclusion of covert channels in the curricula of network security students and network data analysts is therefore considered a valuable extension. In the lab exercises presented, students learn how covert channels in TCP/IP network traffic can be hidden and detected. Since the detection of covert channels requires an in-depth understanding of protocol standards and typical behavior of TCP/IP flows, the lab also provides a playground in which students can deepen their communication networks knowledge. Students learn how to use and interpret statistical analysis to discover abnormal patterns and footprints in network data. They are also trained to deal with noisy scenarios that increase ambiguity and uncertainty. The laboratory was first implemented during the winter semester 2014 with a class of 18 students at TU Wien, Austria. This experience showed that students consolidated the targeted skills as well as increased their interest in the topics explored. All exercises and datasets for the introduced Network Security Advanced lab are made publicly available.
We previously demonstrated 2 statistically distinct factors of degeneration in Alzheimer's disease: one strongly related to white matter damage and age interpreted asage-and vascular-related, and the other related to cortical atrophy thought to representneurodegenerative changes associated with Alzheimer's disease. Those factors are now replicated in a distinct cross-sectional data set of 364 participants from the Alzheimer's Disease Neuroimaging Initiative and their interpretation is improved using correlations with CSF biomarkers. Furthermore, we now show that changes in both factors over 2 years are independently associated with decline in MinieMental State Examination score in a longitudinal subset of 116 individuals with mild cognitive impairment. Progression in theage-and vascularrelated factor was greater for individuals with 2 APOE epsilon 4 alleles and linked to a greater attributable change in MinieMental State Examination than theneurodegenerative factor. These results suggest benefits of targeting white matter and vascular health to complement interventions focused on the neurodegenerative aspect of the disease, even in individuals with little discernable vascular comorbidity. (C) 2017 Elsevier Inc. All rights reserved.
When travelling through a new environment people can and do make very quick judgements about the local conditions. This paper explores the idea that such judgements are affected by the travel mode they use. We hypothesise that drivers generate a more superficial impression of the things they observe than those who walk because they are exposed to less information. This prediction is based on social psychological research that demonstrates that information that becomes available in thin slices affects superficial judgements. A survey study (n = 644) demonstrated that perceptions of a less affluent area are indeed negatively related to more driving and positively related to more walking, but only for those who do not live there. Perceptions of a neighbouring affluent area are positively related to more driving. Two experimental studies (n = 245 and n = 91) demonstrated that explicit (but not implicit) attitudes towards a group of young people in an ambiguous social situation are more negative when they are viewed from the perspective of a car user in particular in relation to a pedestrian perspective. These findings suggest that mode use may affect communities by influencing social judgements. (C) 2013 Elsevier Ltd. All rights reserved.
Symmetric-key cryptography can resist the potential post-quantum attacks expected with the not-so-faraway advent of quantum computing power. Hash-based, code-based, lattice-based, and multivariate-quadratic equations are all other potential candidates, the merit of which is that they are believed to resist both classical and quantum computers, and applying Shor's algorithm-the quantum-computer discrete-logarithm algorithm that breaks classical schemes-to them is infeasible. In this article, we propose, assess, and benchmark reliable constructions for stateless hash-based signatures. Such architectures are believed to be one of the prominent post-quantum schemes, offering security proofs relative to plausible properties of the hash function; however, it is well known that their confidentiality does not guarantee reliable architectures in the presence natural and malicious faults. We propose and benchmark fault diagnosis methods for this post-quantum cryptography variant through case studies for hash functions and present the simulations and implementations results (through application-specific integrated circuit evaluations) to show the applicability of the presented schemes. The proposed approaches make such hash-based constructions more reliable against natural faults and help protecting them against malicious faults and can be tailored based on the resources available and for different reliability objectives.
This paper addresses the need to enhance transparency in ambient intelligent environments by developing more natural ways of interaction, which allow the users to communicate easily with the hidden networked devices rather than embedding obtrusive tablets and computing equipment throughout their surroundings. Ambient intelligence vision aims to realize digital environments that adapt to users in a responsive, transparent, and context-aware manner in order to enhance users' comfort. It is, therefore, appropriate to employ the paradigm of computing with words (CWWs), which aims to mimic the ability of humans to communicate transparently and manipulate perceptions via words. One of the daily activities that would increase the comfort levels of the users (especially people with disabilities) is cooking and performing tasks in the kitchen. Existing approaches on food preparation, cooking, and recipe recommendation stress on healthy eating and balanced meal choices while providing limited personalization features through the use of intrusive user interfaces. Herein, we present an application, which transparently interacts with users based on a novel CWWs approach in order to predict the recipe's difficulty level and to recommend an appropriate recipe depending on the user's mood, appetite, and spare time. The proposed CWWs framework is based on linear general type-2 (LGT2) fuzzy sets, which linearly quantify the linguistic modifiers in the third dimension in order to better represent the user perceptions while avoiding the drawbacks of type-1 and interval type-2 fuzzy sets. The LGT2-based CWWs framework can learn from user experiences and adapt to them in order to establish more natural human-machine interaction. We have carried numerous real-world experiments with various users in the University of Essex intelligent flat. The comparison analysis between interval type-2 fuzzy sets and LGT2 fuzzy sets demonstrates up to 55.43% improvement when general type-2 fuzzy sets are used than when interval type-2 fuzzy sets are used instead. The quantitative and qualitative analysis both show the success of the system in providing a natural interaction with the users for recommending food recipes where the quantitative analysis shows the high statistical correlation between the system output and the users' feedback; the qualitative analysis presents social science evaluation confirming the strong user acceptance of the system.