This study assessed the knowledge and perception of human biological materials (HBM) and biorepositories among three study groups in South Korea. The relationship between the knowledge and the perception among different groups was also examined by using factor and regression analyses. In a self‐reporting survey of 440 respondents, the expert group was found more likely to be knowledgeable and positively perceived than the others. Four factors emerged: Sale and Consent, Flexible Use, Self‐Confidence, and Korean Bioethics and Biosafety Action restriction (...) perception. The results indicate that those who are well aware of the existence of biobanks were more positively inclined to receive the Sale and Consent perception. As a result of the need for high quality HBMs and the use of appropriate sampling procedures for every aspect of the collection and use process, the biorepository community should pay attention to ethical, legal, and policy issues. (shrink)

This study assessed the knowledge and perception of human biological materials (HBM) and biorepositories among three study groups in South Korea. The relationship between the knowledge and the perception among different groups was also examined by using factor and regression analyses. In a self‐reporting survey of 440 respondents, the expert group was found more likely to be knowledgeable and positively perceived than the others. Four factors emerged: Sale and Consent, Flexible Use, Self‐Confidence, and Korean Bioethics and Biosafety Action restriction (...) perception. The results indicate that those who are well aware of the existence of biobanks were more positively inclined to receive the Sale and Consent perception. As a result of the need for high quality HBMs and the use of appropriate sampling procedures for every aspect of the collection and use process, the biorepository community should pay attention to ethical, legal, and policy issues. (shrink)

In this issue of the American Journal of Bioethics, Kraft and colleagues (2018) provide important insights into the role trust plays in donor's decisions to contribute data and samples to local bio...

This study assessed the knowledge and perception of human biological materials (HBM) and biorepositories among three study groups in South Korea. The relationship between the knowledge and the perception among different groups was also examined by using factor and regression analyses. In a self-reporting survey of 440 respondents, the expert group was found more likely to be knowledgeable and positively perceived than the others. Four factors emerged: Sale and Consent, Flexible Use, Self-Confidence, and Korean Bioethics and Biosafety Action restriction (...) perception. The results indicate that those who are well aware of the existence of biobanks were more positively inclined to receive the Sale and Consent perception. As a result of the need for high quality HBMs and the use of appropriate sampling procedures for every aspect of the collection and use process, the biorepository community should pay attention to ethical, legal, and policy issues. (shrink)

Human contact networks constitute a multitude of individuals and pairwise contacts among them. However, the dynamic nature, which generates the evolution of human contact networks, of contact patterns is unknown yet. Here, we analyse three empirical datasets and identify two crucial mechanisms of the evolution of temporal human contact networks, i.e., the activity state transition laws for an individual to be socially active and the contact establishment mechanism that active individuals adopt. We consider both of the two (...) mechanisms to propose a temporal network model, the so-called memory-driven model, of human contact networks. Then, we study the susceptible-infected spreading processes on empirical human contact networks as well as four corresponding temporal network models and compare the full prevalence time of SI processes with various infection rates on the networks. The full prevalence time of SI processes in the MD model is the same as that in real-world human contact networks. Moreover, we find that the individual activity state transition promotes the spreading process, while the contact establishment of active individuals suppresses the prevalence. Besides, we observe that individuals who establish social ties with a small exploring rate are still able to induce an endemic which prevails in the networks. The study offers new insights to predict and control the diffusion processes on networks. (shrink)

Shows how digital capitalism has shaped human rights practices What happens to the cultural politics of human rights when atrocities are rendered calculable, abuses are transformed into data, and victims become vectors? As human rights organisations have increasingly embraced information technologies this 'datafication' of rights has become both a reality and a pressing concern, one inextricably tangled up with questions regarding the broader political valences of human rights. Combining contemporary social and cultural theory with archival research (...) and original ethnographic work, Josh Bowsher resituates recent critiques of human rights within ongoing theoretical discussions concerning informational capitalism, digital culture and the politics of data. Critically analysing the contemporary human rights movement as an informational politics, Bowsher provides a new conceptual agenda for both exploring and overcoming the limits of human rights in an era shaped by the data flows, network infrastructures and informational logic of late capitalism. Josh Bowsher is Lecturer in Sociology at Brunel University. (shrink)

Transcranial Photobiomodulation has demonstrated its ability to alter electrophysiological activity in the human brain. However, it is unclear how tPBM modulates brain electroencephalogram networks and is related to human cognition. In this study, we recorded 64-channel EEG from 44 healthy humans before, during, and after 8-min, right-forehead, 1,064-nm tPBM or sham stimulation with an irradiance of 257 mW/cm2. In data processing, a novel methodology by combining group singular value decomposition with the exact low-resolution brain electromagnetic tomography was implemented (...) and performed on the 64-channel noise-free EEG time series. The gSVD+eLORETA algorithm produced 11 gSVD-derived principal components projected in the 2D sensor and 3D source domain/space. These 11 PCs took more than 70% weight of the entire EEG signals and were justified as 11 EEG brain networks. Finally, baseline-normalized power changes of each EEG brain network in each EEG frequency band were quantified during the first 4-min, second 4-min, and post tPBM/sham periods, followed by comparisons of frequency-specific power changes between tPBM and sham conditions. Our results showed that tPBM-induced increases in alpha powers occurred at default mode network, executive control network, frontal parietal network and lateral visual network. Moreover, the ability to decompose EEG signals into individual, independent brain networks facilitated to better visualize significant decreases in gamma power by tPBM. Many similarities were found between the cortical locations of SVD-revealed EEG networks and fMRI-identified resting-state networks. This consistency may shed light on mechanistic associations between tPBM-modulated brain networks and improved cognition outcomes. (shrink)

This paper examines social network size in contemporary Western society based on the exchange of Christmas cards. Maximum network size averaged 153.5 individuals, with a mean network size of 124.9 for those individuals explicitly contacted; these values are remarkably close to the group size of 150 predicted for humans on the basis of the size of their neocortex. Age, household type, and the relationship to the individual influence network structure, although the proportion of kin remained relatively (...) constant at around 21%. Frequency of contact between network members was primarily determined by two classes of variable: passive factors (distance, work colleague, overseas) and active factors (emotional closeness, genetic relatedness). Controlling for the influence of passive factors on contact rates allowed the hierarchical structure of human social groups to be delimited. These findings suggest that there may be cognitive constraints on network size. (shrink)

Minds are said to be systematic: the capacity to entertain certain thoughts confers to other related thoughts. Although an important property of human cognition, its implication for cognitive architecture has been less than clear. In part, the uncertainty is due to lack of precise accounts on the degree to which cognition is systematic. However, a recent study on learning transfer provides one clear example. This study is used here to compare transfer in humans and feedforward networks. Simulations and analysis (...) show, that while feedforward networks with shared weights are capable of exhibiting transfer, they cannot support the same degree of transfer as humans. One interpretation of these results is that common connectionist models lack explicit internal representations permitting rapid learning. (shrink)

Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human observers. (...) To this end, we exploit a neural network metric in the output of a biologically inspired Self- Organizing Map Quantization Error (SOM-QE). Shape pairs with perfect geometry mirror symmetry but a non-homogenous appearance, caused by local variations in hue, saturation, or lightness within and/or across the shapes in a given pair produce, as shown here, a longer choice response time (RT) for “yes” responses relative to symmetry. These data are consistently mirrored by the variations in the SOM-QE from unsupervised neural network analysis of the same stimulus images. The neural network metric is thus capable of detecting and scaling human symmetry uncertainty in response to patterns. Such capacity is tightly linked to the metric’s proven selectivity to local contrast and color variations in large and highly complex image data. (shrink)

Although Australia has comparatively few individuals seeking asylum, it has had a mandatory detention policy in place since 1992. This policy has been maintained by successive governments despite the overwhelmingly negative impact mandatory detention has on mental health. For mental health professionals working in this environment, a number of moral, ethical, and human rights issues are raised. These issues are discussed here, with a focus on dual loyalty conflicts and drawing on personal experience, the bioethics and human rights (...) literature, and recent parliamentary inquiries. For those who continue to work in this environment, future directions are also discussed. (shrink)

Human skin detection is an essential phase in face detection and face recognition when using color images. Skin detection is very challenging because of the differences in illumination, differences in photos taken using an assortment of cameras with their own characteristics, range of skin colors due to different ethnicities, and other variations. Numerous methods have been used for human skin color detection, including the Gaussian model, rule-based methods, and artificial neural networks. In this article, we introduce a novel (...) technique of using the neural network to enhance the capabilities of skin detection. Several different entities were used as inputs of a neural network, and the pros and cons of different color spaces are discussed. Also, a vector was used as the input to the neural network that contains information from three different color spaces. The comparison of the proposed technique with existing methods in this domain illustrates the effectiveness and accuracy of the proposed approach. Tests were done on two databases, and the results show that the neural network has better precision and accuracy rate, as well as comparable recall and specificity, compared with other methods. (shrink)

A network of gene regulation organized in a hierarchical and combinatorial manner is crucially involved in the development of the neural network, and has to be considered one of the main substrates of genetic change in its evolution. Though qualitative features may emerge by way of the accumulation of rather unspecific quantitative changes, it is reasonable to assume that at least in some cases specific combinations of regulatory parts of the genome initiated new directions of evolution, leading to (...) novel capabilities of the brain. These notions are applied, in this paper, to the evolution of the capability of cognition-based human empa­thy. It is suggested that it has evolved as a secondary effect of the evolution of strategic thought. Development of strategies depends on abstract representations of one’s own pos­sible future states in one’s own brain to allow assessment of their emotional desirability, but also on the representation and emotional evaluation of possible states of others, allowing anticipation of their behaviour. This is best achieved if representations of others are con­nected to one’s own emotional centres in a manner similar to self-representations. For this reason, the evolution of the human brain is assumed to have established representations with such linkages. No group selection is involved, because the quality of strategic thought affects the fitness of the individual. A secondary effect of this linkage is that both the actual states and the future perspectives of others elicit vicarious emotions, which may contribute to the motivations of altruistic behaviour. (shrink)

Network neuroscience provides a systems approach to the study of the brain and enables the examination of interactions measured at different temporal and spatial scales. We review current methods to quantify the structure of brain networks and compare that structure across different clinical cohorts, cognitive states, and subjects. We further introduce the emerging mathematical concept of multilayer networks and describe the advantages of this approach to model changing brain dynamics over time. We conclude by offering several concrete examples of (...) how multilayer network approaches to neuroimaging data provide novel insights into brain structure and evolving function. (shrink)

Research on human-animal interaction has skyrocketed in the last decade. Rapid urbanization has led scientists to investigate its impact on several species living in the vicinity of humans. Domesticated dogs (Canis lupus familiaris) are one such species that interact with humans and are also called man’s best friend. However, when it comes to the free-ranging population of dogs, interactions become quite complicated. Unfortunately, studies regarding free-ranging dog-human interactions are limited even though the majority of the world’s dog population (...) is free-ranging. In this study, we observed twelve groups of free-ranging dogs in their natural habitat, the streets. We divided the study areas into two zones, namely – intermediate and high flux, based on human activity or movement. Six groups from each of the zones were observed mostly during daytime. We used social network analysis (SNA) to explore the dog-dog (intraspecific) and dog-human (interspecific) interactions. It was surprising to observe higher instances of interspecific interactions than the intraspecific ones, irrespective of the zones. Humans, in significantly higher occasions, initiated both positive and negative interactions in comparison to dogs. Our findings conclude that humans are a crucial part of the interaction network of Indian free-ranging dogs. (shrink)

Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in (...) predicting brain signals in response to images taken from various brain datasets (e.g., single cell responses or fMRI data). However, these behavioral and brain datasets do not test hypotheses regarding what features are contributing to good predictions and we show that the predictions may be mediated by DNNs that share little overlap with biological vision. More problematically, we show that DNNs account for almost no results from psychological research. This contradicts the common claim that DNNs are good, let alone the best, models of human object recognition. We argue that theorists interested in developing biologically plausible models of human vision need to direct their attention to explaining psychological findings. More generally, theorists need to build models that explain the results of experiments that manipulate independent variables designed to test hypotheses rather than compete on making the best predictions. We conclude by briefly summarizing various promising modeling approaches that focus on psychological data. (shrink)

The investigation of visual categorization has recently been aided by the introduction of deep convolutional neural networks (CNNs), which achieve unprecedented accuracy in picture classification after extensive training. Even if the architecture of CNNs is inspired by the organization of the visual brain, the similarity between CNN and human visual processing remains unclear. Here, we investigated this issue by engaging humans and CNNs in a two‐class visual categorization task. To this end, pictures containing animals or vehicles were modified to (...) contain only low/high spatial frequency (HSF) information, or were scrambled in the phase of the spatial frequency spectrum. For all types of degradation, accuracy increased as degradation was reduced for both humans and CNNs; however, the thresholds for accurate categorization varied between humans and CNNs. More remarkable differences were observed for HSF information compared to the other two types of degradation, both in terms of overall accuracy and image‐level agreement between humans and CNNs. The difficulty with which the CNNs were shown to categorize high‐passed natural scenes was reduced by picture whitening, a procedure which is inspired by how visual systems process natural images. The results are discussed concerning the adaptation to regularities in the visual environment (scene statistics); if the visual characteristics of the environment are not learned by CNNs, their visual categorization may depend only on a subset of the visual information on which humans rely, for example, on low spatial frequency information. (shrink)

We have considered a simple word game called the word-morph. After making our participants play a stipulated number of word-morph games, we have analyzed the experimental data. We have given a detailed analysis of the learning involved in solving this word game. We propose that people are inclined to learn landmarks when they are asked to navigate from a source to a destination. We note that these landmarks are nodes that have high closeness-centrality ranking.

While the effect of humanitarian intervention on the recurrence and intensity of armed conflict in a crisis zone has received significant scholarly attention, there has been comparatively less work on the negative externalities of introducing peacekeeping forces into conflict regions. This article demonstrates that large foreign forces create one such externality, namely a previously non-existent demand for human trafficking. Using Kosovo, Haiti, and Sierra Leone as case studies, we suggest that the injection of comparatively wealthy soldiers incentivizes the creation (...) of criminal networks by illicit actors. We theorize further that the magnitude of increase in trafficking should be directly proportional to the size of the foreign force, with larger forces producing larger increases. We find that both hypotheses hold with varying levels of confidence across our three case studies. Despite the benevolent intent of peacekeeping missions, the possibility that they may contribute to human trafficking for the purpose of sexual exploitation runs counter to the spirit of such interventions. This is especially problematic given that trafficking rings, once established, may be adapted to provide weapons and narcotics, thereby planting the seed of further destabilization. (shrink)

In this article, we propose to comprehend the corruption mechanisms of tender bidding processes in terms of Human Resource Management (HRM) practices within informal networks. Taking the context of Kazakhstan, we analyze the behavior of individual actors as members of informal networks. Our analysis shows that both corruption and anti-corruption mechanisms can be explained in terms of HRM practices such as (camouflaged) recruitment (e.g., of powerful government officials via network ties), compensation (e.g., kickbacks for corruption; social recognition or (...) shame for anti-corruption) and performance management (e.g., demonstrative punishment for corruption; extreme formalization, peer pressure or social sanctions for anti-corruption). (shrink)

In this article, we propose to comprehend the corruption mechanisms of tender bidding processes in terms of Human Resource Management practices within informal networks. Taking the context of Kazakhstan, we analyze the behavior of individual actors as members of informal networks. Our analysis shows that both corruption and anti-corruption mechanisms can be explained in terms of HRM practices such as recruitment, compensation and performance management.

_This practical and forward-focused book presents a framework that uses social infrastructure to produce effective and inclusive professional development options in education._ Although technology has increased our capacity for social networking both in the digital space and face-to-face, Kira J. Baker-Doyle contends that most professional development opportunities for educators are still fundamentally asocial. She calls for the adoption of humanizing network practices to create meaningful continuing education experiences that leverage the collective knowledge, expertise, and social capital of educators to (...) spark educational change. Baker-Doyle shows how the critical network literacy (CNL) framework overlays critical theory, multiliteracies theory, and social network theory in a way that encourages critical reflection and collaboration among participants. She draws from sources including empirical studies of teacher educators and teacher activists, meta-analytical studies of social network research in education, and professional experience with collective organizing efforts, to detail the many benefits of cultivating CNL in educational spaces. Baker-Doyle provides evidence of how the framework’s practices and protocols can increase transparency, improve representation, and incorporate affirming and restorative discourse. Her work demonstrates how CNL helps create environments that honor teachers’ social identities, their social networks, and the broader social context in which they work. This thought-provoking book is filled with exercises that reinforce social competencies, questions that prompt dialogue and understanding, and real-world examples that underscore the framework's relevance to key educational practices. The generous guidance offered in _Critical Network Literacy_ can be used as a launching point to promote innovation and leadership in teaching. (shrink)

Big Data research is currently split on whether and to what extent Twitter can be characterized as an informational or social network. We contribute to this line of inquiry through an investigation of digital humanities scholars’ uses and gratifications of Twitter. We conducted a thematic analysis of 25 semi-structured interview transcripts to learn about these scholars’ professional use of Twitter. Our findings show that Twitter is considered a critical tool for informal communication within DH invisible colleges, functioning at varying (...) levels as both an information network and a social network. We find that Twitter follow relationships reflect common academic interests and are closely tied to scholars’ pre-existing social ties and conference or event co-attendance. The concept of the invisible college continues to be relevant but requires revisiting. The invisible college formed on Twitter is messy, consisting of overlapping social contexts, scholars with different habits of engagement, and both formal and informal ties. Our research illustrates the value of using multiple methods to explore the complex questions arising from Big Data studies and points toward future research that could implement Big Data techniques on a small scale, focusing on sub-topics or emerging fields, to expose the nature of scholars’ invisible colleges made visible on Twitter. (shrink)

While the effect of humanitarian intervention on the recurrence and intensity of armed conflict in a crisis zone has received significant scholarly attention, there has been comparatively less work on the negative externalities of introducing peacekeeping forces into conflict regions. This article demonstrates that large foreign forces create one such externality, namely a previously non-existent demand for human trafficking. Using Kosovo, Haiti, and Sierra Leone as case studies, we suggest that the injection of comparatively wealthy soldiers incentivizes the creation (...) of criminal networks by illicit actors. We theorize further that the magnitude of increase in trafficking should be directly proportional to the size of the foreign force, with larger forces producing larger increases. We find that both hypotheses hold with varying levels of confidence across our three case studies. Despite the benevolent intent of peacekeeping missions, the possibility that they may contribute to human trafficking for the purpose of sexual exploitation runs counter to the spirit of such interventions. This is especially problematic given that trafficking rings, once established, may be adapted to provide weapons and narcotics, thereby planting the seed of further destabilization. (shrink)

As ecologically and socially oriented food initiatives proliferate, the significance of these initiatives with respect to conventional food systems remains unclear. This paper addresses the transformative potential of alternative food networks by drawing on insights from recent research on food and embodiment, diverse food economies, and more-than-human food geographies. I identify several synergies between these literatures, including an emphasis on the pedagogic capacities of AFNs; the role of the researcher; and the analytical and political value of using assemblage and (...) actor-network thinking to understand the far-reaching forces and power disparities confronting proponents of more ethical and sustainable food futures. (shrink)

The complex activity of the human brain makes it difficult to get a big picture of how the brain works and functions as the mind. We examine pertinent studies, as well as evolutionary and embryologic evidence to support our theoretical model consisting of separate but interactive layers of human neural activity. The most basic layer involves default mode network (DMN)activity and cardiorespiratory oscillations. We propose that these oscillations support other neural activity and cognitive processes. The second layer (...) involves limbic system activity accompanied by corresponding changes in cardiorespiratory oscillations. The third layer consists of corticothalamic processing and involves higher cortical functions including awareness, cognition,and consciousness. These layers interact to form the complex neural activity of the human brain. Examining the origins and relationships of various neural and physiologic oscillations may provide better understanding of human neurophysiology and consciousness. (shrink)

Despite the lack of invariance problem (the many‐to‐many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side‐stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real‐world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use (...) them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two‐layer network that borrows one element from ASR, long short‐term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human‐like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR. (shrink)

Multifunctional agricultural systems seek to expand upon production-based benefits to enhance family wellbeing and animal health, reduce inputs, and improve environmental services such as biodiversity and water quality. However, in many countries a landscape-level conversion is uneven at best and stalled at worst. This is particularly true across the eastern rural landscape in the United States. We explore the role of social networks as drivers of system transformation within dairy production in the eastern United States, specifically rotational grazing as an (...) alternative management option. We hypothesize the importance of weak ties within farmer social networks as drivers of change. In Wisconsin, Pennsylvania, and New York, we conducted 53 interviews with confinement, low-intensity, and rotational grazing dairy producers as well as 35 interviews with associated network actors. Though confinement and grazier networks had similar proportions of strong and weak ties, confinement producers had more market-based weak ties, while graziers had more weak-ties to government agencies and other graziers in the region. These agency weak ties supported rotational graziers through information exchange and cost sharing, both crucial to farmers’ transitions from confinement-based production to grazing systems. While weak ties were integral to initial innovation, farmers did not maintain these relationships beyond their transition to grazing. Of equal importance, grazier weak-tie networks did not include environmental organizations, suggesting unrealized potential for more diverse networks based on environmental services. By understanding the drivers, we can identify barriers to expanding weak tie networks and emergent properties in order to create institutions and policies necessary for change. (shrink)

As ecologically and socially oriented food initiatives proliferate, the significance of these initiatives with respect to conventional food systems remains unclear. This paper addresses the transformative potential of alternative food networks by drawing on insights from recent research on food and embodiment, diverse food economies, and more-than-human food geographies. I identify several synergies between these literatures, including an emphasis on the pedagogic capacities of AFNs; the role of the researcher; and the analytical and political value of using assemblage and (...) actor-network thinking to understand the far-reaching forces and power disparities confronting proponents of more ethical and sustainable food futures. (shrink)

Although there have been many efforts in the last decade to reconcile the humanities and the information sciences, they have not radically changed the research standards prevailing in most humanistic departments. Against all appearances, the abrupt opening to quantitative methods in the digital humanities still has the character of a minority avant-garde movement. The article looks at the scientometric tradition, largely forgotten by the humanities, which may prove to be another interface bringing the two academic cultures back together. An account (...) of scientometric networks highlights the advantages and disadvantages of this orientation. The broader implications regarding the use of visual networks in the humanities are framed by the category of prostheticity, which aims to encapsulate their ambivalent status as both substitutes and cognitive enhancers. (shrink)

In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. (...) Theoretically, the two microphones cannot distinguish the front and rear directions. However, we use the original data of the two channels as the input of the convolutional neural network, and the resolution effect can reach more than 0.9. For comparison, we also chose the delay feature (GCC) for sound direction recognition. Finally, we also conducted experiments that used probability distributions to identify more directions. (shrink)