Network Of Experts Research Articles

Nurseries of the revolution: international seed trials and the transformation of staple food crops

ABSTRACT This paper examines the role of nurseries in the Green Revolution. Nurseries were sets of seeds assembled to test particular traits and sent to breeders around the world to trial. Focusing on wheat nurseries of the 1960s and 70s, I highlight the materials that were central to their distribution, as well as the breeders who planted them. Through this analysis, I trouble the common narrative of the Green Revolution as emerging from centers of international agricultural science, showing the networks of expertise, seed transfer, field trials, and data collection that underpinned this process of agricultural transformation.

A large-scale group decision making method based on spatial information aggregation and empathetic relationships of experts

Large-scale group decision making (LSGDM) involving a large number of experts has attracted more and more scholars’ attention. Many LSGDM methods assumed that experts were independent to make evaluations, but the development of social media promotes the communication among experts, which makes experts no longer independent. In addition, existing LSGDM methods mainly adopted aggregation strategies such as the weighted average operator and arithmetic average operator to integrate the opinion of experts in a cluster, which makes the aggregation results cannot reflect the real opinion of the expert group. To address these issues, considering the empathetic network of experts, this study proposes an LSGDM method based on a new aggregation method for expert space information. Firstly, we determine objective weights of experts according to the objective empathetic relationships among experts. Then, the Steiner-Weber point problem is used as a prototype to establish an aggregation method called the spatial optimal aggregation (SOA) method to fuse the spatial information of experts. The model is solved by the genetic algorithm. Finally, an illustrative example about the selection of the most urgent risk in the transportation of COVID-19 vaccines is presented to show the validity and practicability of the proposed model.

Peace Corps Networks: Activating Volunteers for a Lifetime

The United States Peace Corps plays an important role in sustainable development and soft diplomacy across the globe through its vast network of cross-national partnerships and personal relationships. Peace Corps volunteers are trained to serve as catalysts for grassroots development, bolstering community initiatives with their network of expertise and resources. While personal connections between volunteers and their communities can sometimes last beyond a volunteer's service, the web of connections created through Peace Corps service has a long-term impact on both volunteers and host communities. The grassroots, "people-investing-in-people" nature of the Peace Corps creates an agile network that can respond both to acute crises and long-term challenges. This article explores the formation and impact of these Peace Corps networks and argues that ongoing investment in the Peace Corps and its global response initiatives is an investment in a more peaceful future.

Expertise, translation, and pandemics

Sociologists have much to learn from recent anthropological accounts of expertise in global health. This review surveys three recent ethnographies from Fearnley (2020), Keck (2020), and Porter (2019) to examine how global pushes for biosecurity and zoonotic disease surveillance are unfolding in the global periphery. Collectively, these accounts of global health programs in Mainland China, Hong Kong, Taiwan, Singapore, and Vietnam show how global forms of expertise are translated into local contexts, running up against resistance and creating new alternate networks of expertise to overcome these barriers. While this focus on translation examines how practices of biosecurity originating from the Global North are implemented elsewhere and are transformed in the process, in preparation for future pandemics, global health experts should also consider how to collect, assemble, and translate local expertise so that it is legible to global science and policymakers faraway.

Spinal tumours: recommendations of the Polish Society of Spine Surgery, the Polish Society of Oncology, the Polish Society of Neurosurgeons, the Polish Society of Oncologic Surgery, the Polish Society of Oncologic Radiotherapy, and the Polish Society of Orthopaedics and Traumatology

PurposeThe purpose of these recommendations is to spread the available evidence for evaluating and managing spinal tumours among clinicians who encounter such entities.MethodsThe recommendations were developed by members of the Development Recommendations Group representing seven stakeholder scientific societies and organizations of specialists involved in various forms of care for patients with spinal tumours in Poland. The recommendations are based on data yielded from systematic reviews of the literature identified through electronic database searches. The strength of the recommendations was graded according to the North American Spine Society’s grades of recommendation for summaries or reviews of studies.ResultsThe recommendation group developed 89 level A-C recommendations and a supplementary list of institutions able to manage primary malignant spinal tumours, namely, spinal sarcomas, at the expert level. This list, further called an appendix, helps clinicians who encounter spinal tumours refer patients with suspected spinal sarcoma or chordoma for pathological diagnosis, surgery and radiosurgery. The list constitutes a basis of the network of expertise for the management of primary malignant spinal tumours and should be understood as a communication network of specialists involved in the care of primary spinal malignancies.ConclusionThe developed recommendations together with the national network of expertise should optimize the management of patients with spinal tumours, especially rare malignancies, and optimize their referral and allocation within the Polish national health service system.

Building a statewide network of MOUD expertise using tiered ECHO® mentoring opportunities

BackgroundExpanding access to workforce training for opioid use disorder (OUD) treatment continues to be a priority. This study explored the use of tiered mentoring opportunities within an ECHO® model to expand treatment capacity and develop a statewide network of medications for OUD (MOUD) expertise. ECHO® engages participants in a virtual community to learn best practices through case-based learning and interactions with experts. MethodsWe studied two incentivized Illinois MOUD ECHO® training programs by examining aggregate demographic and prescribing data across eight training cohorts (n = 199 participants). Participants (n = 51) in the last two cohorts were evaluated with expanded pre- and post-training surveys. Qualitative interviews were completed with a subset (n = 13) to examine effects observed in the survey data. ResultsFor the whole group, we found a geographic expansion of the participants’ prescribing capacity that reached into rural and other underserved areas in Illinois. Participants in the last two cohorts reported both increased self-efficacy for OUD treatment and increased connectedness to the addiction treatment community in Illinois. Participants who progressed through the tiered mentorship roles were found to exhibit stepwise increases in reported self-efficacy and connectedness measures. ConclusionAn incentivized ECHO® program yielded substantive outcomes in terms of increased prescribing capacity across the state. The use of tiered mentoring opportunities enabled participants to develop MOUD expertise and support novice providers in a growing statewide network. There is potential to train professionals to a high level of expertise when the ECHO® model is combined with a mentorship pathway.

The health of influenza surveillance and pandemic preparedness in the wake of the COVID-19 pandemic.

The COVID-19 pandemic is the first to have emerged when Next Generation Sequencing was readily available and it has played the major role in following evolution of the causative agent, Severe Acute Respiratory Syndrome Coronavirus 2. Response to the pandemic was greatly facilitated though use of existing influenza surveillance networks: World Health Organization (WHO) Global Influenza Surveillance and Response System (GISRS), focussing largely on human influenza, and the OFFLU network of expertise on avian influenza established by the Food and Agricultural Organization of the United Nations (FAO) and the World Organization for Animal Health (WOAH). Data collection/deposition platforms associated with these networks, notably WHO's FluNet and the Global Initiative on Sharing All Influenza Data (GISAID) were/are being used intensely. Measures introduced to combat COVID-19 resulted in greatly decreased circulation of human seasonal influenza viruses for approximately 2 years, but circulation continued in the animal sector with an upsurge in the spread of highly pathogenic avian influenza subtype H5N1 with large numbers of wild bird deaths, culling of many poultry flocks and sporadic spill over into mammalian species, including humans, thereby increasing pandemic risk potential. While there are proposals/implementations to extend use of GISRS and GISAID to other infectious disease agents (e.g. Respiratory Syncytial Virus and Monkeypox), there is need to ensure that influenza surveillance is maintained and improved in both human and animal sectors in a sustainable manner to be truly prepared (early detection) for the next influenza pandemic.

HINTS: A methodology for IoT network technology and configuration decision

The last decade has seen the explosion of the Internet of Things (IoT), which is enabling a range of new applications based on the connection of physical objects to the Internet. The growing diversity of IoT connectivity technologies is bringing new challenges to IoT solution designers. Indeed, it is increasingly difficult to choose and configure the network technology for a given use-case. In this article, we formalize and investigate the design optimization problem for selecting and configuring the IoT connectivity technology of an application that can evolve over time. Finding the right abstractions and the good balance between performance and evaluation complexity to compare networking options is a key research challenge. To address this problem we propose to separate the concerns of IoT application architects from those of network experts and to provide a methodology, HINTS, to help designers in making customized decision. HINTS combines IoT application requirements and goals abstraction, IoT network modeling, discrete-event network simulation and a multiple attribute decision making method. The application of the methodology on three use-cases highlights how it helps in (i) selecting the best network technology option, (ii) defining an appropriate configuration and (iii) anticipating the behavior when device density or workload intensity scales up. The main contribution of this paper is to propose the first formal approach and associated algorithm to automatically optimize the design of the IoT connectivity of an application. Results show that it can yield up to a factor two improvement in the solution performance.

COST Action to address challenges facing people with intellectual disabilities accessing cancer prevention and response services across Europe – Introducing CUPID - Cancer- Understanding Prevention in Intellectual Disabilities.

COST Actions are grants provided by the European Union to support the establishment of networks of expertise to explore and address a scientific or social issue that impacts across Europe. This article introduces and describes one such action that started in October 2022 - CUPID - will address issues of policy and equity of access to cancer prevention initiatives by people with intellectual disabilities compared to the general population in Europe. With 82 individual members drawn from 30 countries CUPID will establish an interdisciplinary network of stakeholders representing carers, service providers, advocacy groups, educators, healthcare professionals, researchers and people with intellectual disabilities. The CUPID COST Action will be implemented over four years and will identify what needs to be addressed by the European Union and health and social services to improve cancer prevention among people with intellectual disabilities.

An Analysis of the Categories and Structures of Expertise for Students’ Cognitive States

Knowledge networks play an important role in the process of knowledge acquisition and sharing by students. An analysis of their complex structural features is required for the connectivity between students and knowledge. Existing research lacks insight into the internal structural features of knowledge networks constructed from expertise. There is also a lack of effective methods for constructing personalised knowledge networks for students' cognitive states. This paper analyses the categories and structures of expertise for students' cognitive states, and presents in detail a grey prediction algorithm to identify students' cognitive states. Then, the paper presents a typological description of the knowledge nodes in the expertise network for students' cognitive states, and analyses the knowledge network structure from the perspectives of paths and statistical properties. After that, the paper gives a method for analysing the knowledge flow of the expertise network. The experimental results validate the effectiveness of the proposed method.

Naisvankien sopeutumisesta yhteiskuntaan Venäjällä

Definitions of social inclusion commonly include concepts like respect, diversity, shared goals and values, as well as a feeling of belonging to a community. Another term, which is similar in meaning and used more often in academic literature is resocialization. Generally, resocialization involves measures taken during and after a prison sentence to help ex-prisoners avoid recidivism. The term “resocialization” was introduced to the lexicon of academic psychology by American social psychologists Daniel B. Kennedy and August Kerber (1990) to signify an individual’s “secondary” entry into a sociocultural environment following either “defective” socialization (resocialization of ex-prisoners) or a change in sociocultural surroundings (resocialization of migrants). The resocialization of ex-prisoners is an important step on the way to decreasing recidivism rates, which in turn leads to a safer society. The sociologist Coline Cardi studies society’s perception of female-inflicted violence. Her work shows that society places far greater demands on women than on men, and that women are perceived more often as victims than as perpetrators of violence. This puts female offenders in double violation of the norm: by committing a crime, a woman contravenes the social norm as well as the legal norm. In Russia, where motherhood, marriage and family life are still considered the main instruments of self-realisation for women, incarceration can be a serious ordeal. The paper presented results of the pilot project on Nordic-Rus­sian co-op­er­a­tion for the so­cial in­teg­ra­tion, pre­ven­tion of mar­gin­al­isa­tion, and hu­man rights pro­tec­tion of fe­male pris­on­ers.  This project (1/8/2018 – 31/10/2019), funded by the Nordic Council of Ministers' Nordic-Russian co-operation programme, was led by me. Its ambition was to establish a Nordic-Russian network of experts, which would ensure exchange of experience and best practices.

Citizen Science in News Media: Boundary Mediation of Public Participation in Health Expertise

In this article, I examine how scientific boundary work describes or represents citizen science as credible forms of expertise. Citizen science is an ambiguous concept, and I leverage that ambiguity to examine citizen science as a proxy for nonprofessional or noninstitutional scientific practices more generally. I argue that media representations of citizen science perform boundary work through different articulations of institutional “buy-in” to the legitimacy or credibility of citizen science. Using a discourse analysis of mainstream news media, I trace three framings of citizen science’s relationship to institutional networks, which I describe as subservient to, corrective to, and exceeding the norms of institutional expertise. I find that the perspectives of professional, credentialed scientists dominate public discourse concerning citizen science and perform different adjudications of how citizen science contributes to networks of expertise. By focusing on citizen science concerning human health and medicine, I additionally show how mainstream framings of citizen science engage with overlapping media representations of personal health responsibility and patient empowerment. I suggest that representations of citizen science as a form of “missing expertise” can conflict with portrayals of citizen science as “going too far” in the pursuit of treatments or interventions.

Presenting the RomAniDat data community and an archaeofaunal dataset for Roman Italy

The RomAniDat data community is a network of experts from diverse fields including archaeozoology, archaeology, and history, who collaborate on the collection of faunal data from the Roman period. Compiled data is made available via Pandora, a new technological platform that allows for the building of data communities where its members directly manage and curate data. RomAniDat members can submit data compilations with different structural metadata and assign to these a DOI. It is also possible to list external data compilations with previously assigned DOIs. Under RomAniDat, generalized metadata schemas are being developed to offer users standardized data views which combine separate compilations. These include references to both primary publications and data compilations. Here, we present a first metadata schema to visualize combined data from publications reporting on the distribution of faunal assemblages. We also present an archaeofaunal compilation for Roman Italy and briefly illustrate its research potential. RomAniDat can be used to identify data gaps and set future research agendas, as a tool for cultural heritage protection, and for multiple research purposes at various temporal and spatial scales.

A network of expertise

The article discusses an in-depth analysis of four assessment reports documenting the diagnostic procedure of Autism Spectrum Disorder (ASD henceforth) in pre-school-aged children in Sweden. Authored by professionals (child psychiatrists and child psychologists), the reports contain an account of different observations, interviews, and tests-results held throughout an ASD diagnostic procedure, as well as recommendations for treatments and interventions plan, and have a “mobile” function, meaning they reach other professionals and laypersons other than the child’s parents, making their influence long-lasting. The article’s overall aim is to demonstrate how professional knowledge is closely intertwined with parental knowledge, or parents’ unique “intimate expertise” (Lilley, 2011) in the written accounts making up the assessment reports, as professionals attempt to account for and establish an ASD diagnosis for a specific child. We conclude by arguing that such intertwined knowledge can be understood as materialization and an empirical demonstration of the network of autism expertise (Eyal, 2013), replacing previous historical forms of the appropriation of parental knowledge by professional actors during the procedure of ASD diagnosis in children (Eyal et al., 2010: 177).

Long-Tailed SAR Target Recognition Based on Expert Network and Intraclass Resampling

Long-Tailed SAR Target Recognition Based on Expert Network and Intraclass Resampling

Multiple POS Dependency-Aware Mixture of Experts for Frame Identification

Frame identification, which is finding the exact evoked frame for a target word in a given sentence, is a fundamental and crucial prerequisite for frame semantic parsing. It is generally seen as a classification task for target words, whose contextual representations are usually obtained using a neural network like BERT as an encoder, and enriched with a joint learning model or the knowledge of FrameNet. However, the distinction at a fine-grained level, such as the delicate differences in the information of syntax and PropBank roles caused by different parts-of-speech (POS) of target words, is neglected. We propose a Multiple POS Dependency-aware Mixture of Experts(MPDaMoE) network that integrates five types of information, consisting of the syntactic information of target words whose POS are nominal, adjectival, adverbial, or prepositional, and the PropBank role information of target words whose POS are only verbal. To better learn such information, a Mixture of Experts network is employed, in which every expert is a Graph Convolutional Network, to incorporate the different dependency information of target words. Our model outperforms state-of-the-art models in experiments on two benchmark datasets, which shows its effectiveness.

Men's mental health and interventions tailored to masculinity: a scoping review

Masculinity norms, characterized by specific behaviors, thoughts and emotions that are considered socially appropriate for both Eastern and Western men, have been perceived as obstacles to seeking professional help, especially in situations where men are mentally distressed. This scoping review aimed to gain insight into the different factors that affect men’s mental health and explore the different types of interventions tailored to masculinity conventions. Research published between January 2018 and June 2023 was examined using keywords to extract relevant studies from PubMed, CINAHL, SCOPUS and Web of Science, with discussion and cross-checking by both authors. Twelve studies consisting of six randomized-controlled trials, four qualitative studies and two mixed method studies were identified. A variety of interventions were identified in this review, including soccer-related physical activity-based interventions, online interventions, therapeutic counseling interventions that integrate interviews and cognitive-behavioral group therapy, and interventions using expert networks. The need for online interventions that consider traditional masculinity norms in encouraging help-seeking behavior, and the effectiveness of support groups in providing a safe space for men to discuss their mental health, are key findings. As a public health issue, men’s mental well-being is substantially significant, and tailored interventions are needed to support men’s mental health. Therefore, the implementation of effective interventions and the active role of policy makers in promoting mental health awareness for men is also required. Based on these findings, strategies to engage men in mental health services, strengthen social support networks, and challenge harmful male stereotypes within healthcare settings and communities should be considered.

Social Engineering Attack Classifications on Social Media Using Deep燣earning

In defense-in-depth, humans have always been the weakest link in cybersecurity. However, unlike common threats, social engineering poses vulnerabilities not directly quantifiable in penetration testing. Most skilled social engineers trick users into giving up information voluntarily through attacks like phishing and adware. Social Engineering (SE) in social media is structurally similar to regular posts but contains malicious intrinsic meaning within the sentence semantic. In this paper, a novel SE model is trained using a Recurrent Neural Network Long Short Term Memory (RNN-LSTM) to identify well-disguised SE threats in social media posts. We use a custom dataset crawled from hundreds of corporate and personal Facebook posts. First, the social engineering attack detection pipeline (SEAD) is designed to filter out social posts with malicious intents using domain heuristics. Next, each social media post is tokenized into sentences and then analyzed with a sentiment analyzer before being labelled as an anomaly or normal training data. Then, we train an RNN-LSTM model to detect five types of social engineering attacks that potentially contain signs of information gathering. The experimental result showed that the Social Engineering Attack (SEA) model achieves 0.84 in classification precision and 0.81 in recall compared to the ground truth labeled by network experts. The experimental results showed that the semantics and linguistics similarities are an effective indicator for early detection of SEA.

Od prisluškivanja činovnika do istraživanja međunarodnog društva

The paper analyses historical developments in the discipline of the history of international relations, from its origins in the nineteenth century until present day. It provides an overview of numerous approaches and topics that have driven its development over the previous two centuries. The article focuses on the evolution of the history of international relations in its American and Western European variations. In the first part, the origin and the activity of diplomatic history are examined in the context of the emergence of professional historiography. At that time, diplomatic history narrowly focused on studying the political and diplomatic relations between states and was the most prominent topic in political and intellectual discourse. Its significance further intensified following the First World War, when the topic of war guilt emerged as one of the major interwar political issues. In the second part, the study discusses the evolution of diplomatic history into a broader international history, emphasizing social, economic and ideological aspects. The shift happened as a result of the rising interest in social and economic history following World War II and manifested itself throughout specific discussions in various countries. It was also marked by increased uneasiness and self-criticism that historians of international affairs have become prone to. Following that, the paper explores the impact of new theoretical approaches and thematic concerns, that emerged as a result of the cultural turn, on the practice and the shape of international history. It now includes not only interstate relations, but also a diverse set of actors such as international organizations, multinational corporations, non-governmental organizations and networks of researchers, scientists and experts, all of which have been studied through the lenses of ideas, ideology, gender, beliefs, language, memory, value and perceptions.

An Improvement in Dynamic Behavior of Single Phase PM Brushless DC Motor Using Deep Neural Network and Mixture of Experts

An Improvement in Dynamic Behavior of Single Phase PM Brushless DC Motor Using Deep Neural Network and Mixture of Experts