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Brokerage in intra-organizational networks is critical to performance, but women exhibit less brokerage in their social networks and receive lower performance returns to the brokerage they exhibit than men do. We uncover a condition under which the gender gaps in network advantage are entirely negated: mobility. When women move between units of the organization, they increase their brokerage more than mobile men do. Further, such mobility eliminates the gender gap in returns to brokerage. Using a rich dataset including the personnel records, monthly performance, and email communications of thousands of employees in a large financial institution, we find support for our arguments by comparing the networks and objective performance of those who changed jobs with matched non-movers prior to and following each job change. In probing why this might be the case, we find that women movers are more likely to maintain communication ties to colleagues from their previous roles and that these persistent ties give them a discernible and gender-role-congruent explanation for connecting otherwise disconnected units and benefiting from network brokerage. Our results illuminate important mechanisms by which social network dynamics and mobility affect gender inequality and performance in organizations. [ABSTRACT FROM AUTHOR]

The Byzantine lead seals of the Barber Institute of Fine Arts number in total 146 pieces, mostly collected in the region of Trebizond. They offer valuable insights into the middle Byzantine society of the Pontos region, which despite its location on the easternmost borders was connected with other, even more remote, regions of the empire. The majority of these seals come from local officials and reflect their local preoccupations, perhaps as a backlash to the dominant culture of the capital. Fifteen selected pieces from the collection are published here and provided with commentary. [ABSTRACT FROM AUTHOR]

Telesurgery is expected to improve medical access in areas with limited resources, facilitate the rapid dissemination of new surgical procedures, and advance surgical education. While previously hindered by communication delays and costs, recent advancements in information technology and the emergence of new surgical robots have created an environment conducive to societal implementation. In Japan, the legal framework established in 2019 allows for remote surgical support under the supervision of an actual surgeon. The Japan Surgical Society led a collaborative effort, involving various stakeholders, to conduct social verification experiments using telesurgery, resulting in the development of a Japanese version of the "Telesurgery Guidelines" in June 2022. These guidelines outline requirements for medical teams, communication environments, robotic systems, and security measures for communication lines, as well as responsibility allocation, cost burden, and the handling of adverse events during telesurgery. In addition, they address telementoring and full telesurgery. The guidelines are expected to be revised as needed, based on the utilization of telesurgery, advancements in surgical robots, and improvements in information technology. [ABSTRACT FROM AUTHOR]

The objective of this article is to shed light on the history of the Reformation in 17th-century Geneva. The lens through which this study is conducted is that of religious publishing activity, which was significantly managed by the Company of Pastors and Professors. The role of the Company in religious publishing is inextricably linked to the unique status of the Church of Geneva within the broader context of the Reformation. The Company's institutional archives offer insight into the issues at stake in the printed book matters. This article focuses on the role of the Company in local censorship, which diminished over the period under study. The Company's censorship function enabled it to exert concrete influence on the global scale of Reformed publishing. This influence was the consequence of the Company's ecclesiastical and theological authority. This authority derived from the status of the Church of Geneva as the principal church and birthplace of the Reformation in the 16th century. An analysis of the metaphors signifying and symbolizing this role in the printed books themselves underlines the pre-eminence of the Church of Geneva in 17th-century Reformation. [ABSTRACT FROM AUTHOR]

Communities across Southeast Asia face challenges posed by natural disasters, including floods, which disproportionately impact vulnerable populations. In light of the growing frequency and severity of extreme weather events attributed to climate change, there is a pressing need to explore and strengthen community flood resilience. Community resilience is pivotal in mitigating flood-related damages and fostering successful recovery efforts. This paper examines the socio-economic and environmental factors shaping community resilience in flood-prone areas of Southeast Asia. Socio-demographic determinants, exposure to floods, social cohesion, communication networks, socio-economic status, and cultural diversity significantly influence resilience capabilities, with disparities exacerbating socio-economic inequality. The interplay of these factors underscores the complexity of community disaster resilience, with some factors acting as moderators, mediators, or confounders in shaping outcomes. The paper highlights that understanding the dynamics of community resilience formation is imperative for informed policy interventions to enhance disaster preparedness and response in flood-prone areas of Southeast Asia. The contributors to flood resilience are interrelated with social determinants of health, underscoring the vital role of broader socio-economic and environmental factors in shaping community well-being. Future research should explore the relationships within these complex dynamics to guide effective resilience-building strategies tailored to local contexts.

Knowledge about how producers subjectively assess and communicate about different information resources can help optimize Agricultural Extension efforts. In particular, how do growers use different information resources when making decisions on pest and disease management? Using pest and disease management in wine grapes (Vitis vinifera) as a case study, three surveys were conducted among grape producers in the western United States to qualitatively explore resource options (n = 15), examine the relative importance of the 23 different information resources identified (n = 63), and investigate the social networks where information is passed within and between regions (n = 65). Five different informational archetypes emerged, demonstrating different preferences for information resource use, which explained 66% of the variance in survey responses. Personal connections (e.g., discussion with professional network, with field foreman and supervisors, and with an Extension agent) were extremely important to the participants. In the communication network analysis, 65 participants were used to form a 324-actor network with 448 links, which were then subdivided into intra-state networks. The networks show evidence of structures that facilitate information diffusion and cooperation between independent producers. Additionally, even with networks much smaller than the grape producer populations in these states, influential individuals could be identified. These individuals, when targeted by outreach professionals, could assist with information dissemination and facilitate changes in opinion or behaviors in the region. [Figure: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2024.

Smart city networks are critical for delivering essential services such as healthcare, education, and business operations. However, these networks are highly susceptible to a range of threats, including natural disasters and intentional cyberattacks, which can severely disrupt their functionality. To address these vulnerabilities, we present the resilient smart city (ResiSC) system, designed to enhance the resilience of smart city communication networks through a topological design approach. Our system employs a graph‐theoretic algorithm to determine the optimal network topology for a given set of nodes, aiming to maximize connectivity while minimizing link provisioning costs. We introduce two novel connectivity measurements, All Nodes Reachability (ANR) and Sum of All Nodes Reachability (SANR), to evaluate network resilience. We applied our approach to data from two public universities of different sizes, simulating various attack scenarios to assess the robustness of the resulting network topologies. Evaluation results indicate that our solution improves network resilience against targeted attacks by 38% compared to baseline methods such as k‐nearest neighbours (k‐NN) graphs, while also reducing the number of additional links and their associated costs. Results also indicate that our proposed solution outperforms baseline methods like k‐NN in terms of network resilience against targeted attacks by 41%. This work provides a practical framework for developing robust smart city networks capable of withstanding diverse threats. [ABSTRACT FROM AUTHOR]

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events, causing surveillance and energy loss. This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters. Initially, the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes. Subsequently, it delves into communication and data processing mechanisms, specifically focusing on central data processing (CDP), communication routers (CRs), and phasor measurement units (PMUs), to re-establish an equipment recovery model based on these data transmission methodologies. Furthermore, it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution. The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system. The findings suggest that the proposed branch- and-bound algorithm significantly augments the observational capabilities of a power system with limited resources, thereby bolstering its stability and emergency response mechanisms.

For chorusing males, optimally timing their calls relative to nearby rivals' calls and fluctuations in background chorus noise is crucial for reproductive success. A caller's acoustic environment will vary by chorus density and the properties of his chorus-mates' calls and will fluctuate unpredictably due to chorusing dynamics emerging among his chorus-mates. Thus, callers must continuously monitor moment-to-moment fluctuations in the acoustic scene they perceive at the chorus for advantageous times to call. In live experimental choruses, we investigated the factors influencing túngara frog call-timing responses to chorus-mates' calls on an interaction-by-interaction basis, revealing that intrinsic and extrinsic factors influenced call-timing decisions. Callers were more likely to overlap calls from smaller chorus-mates and chorus-mates at intermediate distances, as well as calls containing lower frequencies and exhibiting lower final amplitude minima. Consequently, variation among males in call properties led to variation in levels of call-interference received when calling in the same social environment. Additionally, callers were more likely to overlap chorus-mates' calls after experiencing extended periods of inhibition and were less likely to overlap synchronized chorus-mates' calls relative to single calls. In chorusing species, female choice is influenced by inter-caller dynamics, selecting for male call-timing strategies which, in turn, constitute the selective environment further refining these same strategies. Thus, understanding the specific factors driving call-timing decisions is essential for understanding how sexual selection operates in chorusing taxa. [ABSTRACT FROM AUTHOR]

A major area of application of multiobjective path problems and resolution algorithms is telecommunication network routing design, taking into account the extremely rapid technological and service evolutions. The need for explicit consideration of heterogeneous Quality of Service metrics makes it advantageous for the development of routing models where various technical–economic aspects, often conflicting, should be tackled. Our work is focused on multiobjective path problem formulations and resolution methods and their applications to routing methods. We review basic concepts and present main formulations of multiobjective path problems, considering different types of objective functions. We outline the different types of resolution methods for these problems, including a classification and overview of relevant algorithms concerning different types of problems. Afterwards, we outline background concepts on routing models and present an overview of selected papers considered as representative of different types of applications of multiobjective path problem formulations and algorithms. A broad characterization of major types of path problems relevant in this context is shown regarding the overview of contributions in different technological and architectural network environments. Finally, we outline research trends in this area, in relation to recent technological evolutions in communication networks. [ABSTRACT FROM AUTHOR]

Research by Cynthia Irwin-Williams and the San Juan Valley Archaeological Project during the 1970s included investigations at Salmon Pueblo, near modern Bloomfield, NM. Interest focused on the construction and early occupation by immigrants from Chaco Canyon. Research also included the 80 km Great North Road, which joined Pueblo Alto at the southern end with Salmon Pueblo at the northern terminus. In order to investigate the North Road, Pierre Morenon conducted an intensive foot survey of the road trajectory and associated features. A large ceramic collection from the road and nearby sites was analyzed by Hayward Franklin. Pottery types dated mostly from 1050 to 1130 CE. A typical assemblage of decorated and utility pottery came northward from Chaco Canyon centers. Smaller amounts of northern San Juan pottery also occurred, signifying transport of ceramics and other goods southward from outliers at Salmon and Aztec Pueblos. [ABSTRACT FROM AUTHOR]

To better understand how vocalisations are used during interactions of multiple individuals, studies are increasingly deploying on‐board devices with a microphone on each animal. The resulting recordings are extremely challenging to analyse, since microphone clocks drift non‐linearly and record the vocalisations of non‐focal individuals as well as noise. Here we address this issue with callsync, an R package designed to align recordings, detect and assign vocalisations to the caller, trace the fundamental frequency, filter out noise and perform basic analysis on the resulting clips. We present a case study where the pipeline is used on a dataset of six captive cockatiels (Nymphicus hollandicus) wearing backpack microphones. Recordings initially had a drift of ~2 min, but were aligned to within ~2 s with our package. Using callsync, we detected and assigned 2101 calls across three multi‐hour recording sessions. Two had loud beep markers in the background designed to help the manual alignment process. One contained no obvious markers, in order to demonstrate that markers were not necessary to obtain optimal alignment. We then used a function that traces the fundamental frequency and applied spectrographic cross correlation to show a possible analytical pipeline where vocal similarity is visually assessed. The callsync package can be used to go from raw recordings to a clean dataset of features. The package is designed to be modular and allows users to replace functions as they wish. We also discuss the challenges that might be faced in each step and how the available literature can provide alternatives for each step. [ABSTRACT FROM AUTHOR]

The fundamental problem of finding transmission schedules for achieving optimal throughput in time division multiple access (tdma) communication networks is known to be np-hard. Let N be a scheduled k-time slot tdma network with n stations and m links. We showed that an optimal link schedule for N can be computed recursively with a recursion tree of logarithmic depth O(lnm) in expectation. Additionally, we showed that optimal link schedules for those tdma networks, with recursion trees of depth meeting the expectation, can be found in time O(m2+ln k). Likewise, we discuss analogous results for computing optimal station schedules of tdma networks. [ABSTRACT FROM AUTHOR]

The fundamental problem of finding transmission schedules for achieving optimal throughput in time division multiple access (TDMA) communication networks is known to be NP-hard. Let $ \mathcal{N} $ be a scheduled $ k $-time slot TDMA network with $ n $ stations and $ m $ links. We showed that an optimal link schedule for $ \mathcal{N} $ can be computed recursively with a recursion tree of logarithmic depth $ \mathcal{O}(\ln m) $ in expectation. Additionally, we showed that optimal link schedules for those TDMA networks, with recursion trees of depth meeting the expectation, can be found in time $ \mathcal{O}(m^{2+\ln k}) $. Likewise, we discuss analogous results for computing optimal station schedules of TDMA networks.

V2G (Vehicle-to-Grid) is a system that allows an electric vehicle to connect and exchange energy with the electricity grid. This system is part of the smart-grid, which is an intelligent electricity network offering bidirectional communication and contributes to the environmental protection. Different actors are involved in communication in a V2G network, such as electric vehicles, charging stations, energy suppliers, and network operators, etc. Therefore, the V2G network faces several security challenges, such as data integrity, power system security, physical security of charging systems, data confidentiality and system interoperability. In this paper, an intrusion detection system (IDS) is proposed with the aim of predicting attacks in the V2G network. The study started with the generation of a dataset and the implementation of the Cockroach Behavior-Based Machine Learning Classifier with the objective of enhancing security of V2G networks by addressing Men-in-the-Middle (MitM) and Denial of Service (DoS) attacks. The simulation results, through the MiniV2G simulator, show that the proposed system achieved a detection accuracy of 98.93 %. This improves the reliability of the V2G network for users and better protects Electric Vehicle Charging Stations (EVCS) against DoS and MitM. [ABSTRACT FROM AUTHOR]

This article uncovers the pre-1991 origins of Baltic neoliberal regimes. It highlights the role of the communication networks between reformist economists in the Baltic National Fronts and social forces advocating neoliberalism in Scandinavia and the United States. We assert that those networks functioned as the early carriers of ideational and policy change, even if reform contents were authored by domestic rather than transnational agencies. Firstly, the article previews the structural factors conducive to network formation. Secondly, it examines the networks by highlighting cross-national differences. Finally, it chronicles the idiosyncratic paths of neoliberal reformers' ascendance to the positions of influence. [ABSTRACT FROM AUTHOR]

The integration of communication infrastructures into traditional power systems, transforming them into cyber-physical power systems (CPPS), accentuates the significance of communication in influencing system performance and sustainability. This paper presents a versatile, innovative cyber-physical co-simulation framework that integrates the physical power system and communication networks, uniting OPAL-RT, a network simulator (ns3), and Docker containers into a sophisticated platform, facilitating intensive studies into CPPS dynamics. The proposed experimental study provides an innovative way to assess the frequency control response of a cyber-physical inverter-based microgrid (MG), addressing the MG sustainability challenges. We consider diverse real-world scenarios, focusing on communication delays and distributed denial of service (DDoS) attacks within the communication channels. We propose a precise ns3-based communication model that bridges the MG's primary and secondary control layers, an aspect often overlooked in previous studies; this is a noteworthy contribution to elucidating the adverse impacts of communication latency on MG frequency performance. The experimental results demonstrate the effectiveness of the centralized secondary controller in eliminating the frequency deviations. Furthermore, the findings offer insights into stable and unstable regions, revealing how the communication delay value affects the frequency stability under different operating conditions. In addition, the developed real-time DDoS attacks model within the proposed communication surface unveils crucial insights into the MG's resilience to cyber threats. This work's revelations offer a foundational awareness of MG vulnerabilities, paving the way for designing robust and resilient communication networks and control strategies within the cyber-physical inverter-based microgrids. [ABSTRACT FROM AUTHOR]

Abstract To better understand how vocalisations are used during interactions of multiple individuals, studies are increasingly deploying on‐board devices with a microphone on each animal. The resulting recordings are extremely challenging to analyse, since microphone clocks drift non‐linearly and record the vocalisations of non‐focal individuals as well as noise. Here we address this issue with callsync, an R package designed to align recordings, detect and assign vocalisations to the caller, trace the fundamental frequency, filter out noise and perform basic analysis on the resulting clips. We present a case study where the pipeline is used on a dataset of six captive cockatiels (Nymphicus hollandicus) wearing backpack microphones. Recordings initially had a drift of ~2 min, but were aligned to within ~2 s with our package. Using callsync, we detected and assigned 2101 calls across three multi‐hour recording sessions. Two had loud beep markers in the background designed to help the manual alignment process. One contained no obvious markers, in order to demonstrate that markers were not necessary to obtain optimal alignment. We then used a function that traces the fundamental frequency and applied spectrographic cross correlation to show a possible analytical pipeline where vocal similarity is visually assessed. The callsync package can be used to go from raw recordings to a clean dataset of features. The package is designed to be modular and allows users to replace functions as they wish. We also discuss the challenges that might be faced in each step and how the available literature can provide alternatives for each step.

Resilience assessment is crucial for maintaining high availability, security, and quality of service in power grids. However, most current grid research lacks hardware testbed capabilities. Moreover, the integration of distributed energy resources expands the grid’s attack surface, necessitating reliable and realistic modeling techniques to be accessible to the broader research community. Consequently, simulation testbeds have emerged to model real-world power grid topologies and evaluate the impact of various disruptions. Existing co-simulation platforms for power grids focus on limited components, such as focusing only on the dynamics of the physical layer. Additionally, many platforms require specialized hardware that may be too expensive for most researchers. Furthermore, not many platforms support realistic modeling of the communication layer, which demands the use of Supervisory Control and Data Acquisition (SCADA) communication protocols like DNP3 for cybersecurity scenario modeling. We introduce Network Attack Testbed in [Power] Grid (NATI[P]G) (pronounced “natig”), a stand-alone, containerized, and reusable environment that enables cyber analysts and researchers to execute various cybersecurity and performance scenarios on power grids. NATIG integrates GridLAB-D, a grid simulator, HELICS, a co-simulation framework, and NS3, a network simulator, to create an end-to-end simulation environment for the power grid. We demonstrate use cases by generating a library of datasets for several scenarios. These datasets can be utilized to detect cyberattacks at the cyber layer and develop countermeasures against these adverse scenarios.

Energy intensity is the ratio between energy consumed and data volume over a certain time frame. It is frequently used as a metric to indicate the energy efficiency of communication networks and data centres for the provision of digital services, and as a coefficient to apportion the total energy consumption of a network to a specific service. As energy efficiency becomes more important, energy intensity metrics are increasingly used to estimate the energy costs and benefits of changes in data volumes across networks and data centres. Typically, energy intensity integrates annual accounts of energy consumption and data transmitted. At shorter time scales, this metric is affected by the lack of correlation between transmitted data and energy consumption, which leads in some cases to inappropriate conclusions. In this work, we first review the use of energy efficiency metrics in the literature. Then, we define generic measures for energy efficiency as well as energy intensity. The relationships of those measures are analysed, and we show under which conditions they lead to the same or different results. Practical applications of the measures and their insights are demonstrated when benchmarking systems and when considering the value of the system’s output. Furthermore, the limits and pitfalls of the metrics are analysed, especially considering the energy intensity metric for communication networks.

An increasing number of satellite constellations being deployed in orbit fosters the introduction of a more efficient paradigm of distributed, interconnected orbital assets to ensure better resource exploitation in orbit. This paper aims to illustrate through quantitative modeling the effects of satellites on board available resources and inter-satellite telecommunication hypotheses on the overall operations of a federated satellite system network. Key research questions addressed by this work include the performance quantification of a one hundred CubeSats federated satellite system network in terms of network response and data volume exchanged under several onboard resource constraints. The applicability of a federated satellite system to a time-critical disaster response monitoring scenario has also been verified to assess the practical implementation of such a paradigm in reduced inter-satellite communicability conditions. A distributed simulator based on the IEEE 1516–2010 standard is employed to obtain the federated satellite system network topology according to the individual satellite operations to analyze the network performances, exploiting an approach based on the network’s adjacency matrix. Despite reduced communicability, which limits the average inter-satellite link to an 8 bps time-averaged goodput due to poor onboard resources availability, the federated satellite system proves to be an auto-sufficient and decentralized paradigm, capable of responding to a time-critical scenario such as a rapid mapping request after a natural disaster in under 6 hours. As a result, this work provides the foundation for more detailed development of a federate satellite network, compliant with current radiofrequency regulations.

Network intrusion detection systems work on huge data sets, with large feature sets dominated by noisy data and irrelevant features, resulting in steep degradation in detection accuracy and a steep proliferation in model training and computation time. This work presents a novel method to optimize the feature selection process in machine learning algorithms for accurate detection of intrusion attacks in communication networks. The proposed method targets features with a high impact on the target variable to optimize feature selection and reduction. The CICIDS-2017 data set is used to test the performance of the proposed approach. Results prove the dexterity of the proposed method as it is able to achieve an almost 51% reduction in irrelevant features and increases the detection accuracy of the tuned random forest classifier to 99.9% with an almost 50% reduced model computation time.

In chorusing species, conspecific interference exerts strong selection on signal form and timing to maximize conspicuousness and attractiveness within the signaling milieu. We investigated how túngara frog calling strategies were influenced by varied social environments and male phenotypes and how calling interactions influenced female preferences. When chorusing, túngara frog calls consist of a whine typically followed by one to three chucks. In experimental choruses we saw that as chorus size increased, calls increasingly had their chucks overlapped by the high-amplitude beginning section of other callers' whines. Playback experiments revealed that such overlap reduced the attractiveness of calls to females but that appending additional chucks mitigated this effect. Thus, more elaborate calls were preferred when calls suffered overlap, although they were not preferred when overlap was absent. In response to increasing risk of overlap in larger choruses, males increased call elaboration. However, males overwhelmingly produced two-chuck calls in even the largest choruses, despite our results suggesting that additional chucks would more effectively safeguard calls. Furthermore, aspects of male phenotypes predicted to limit call elaboration had negligible or uncertain effects, suggesting that other constraints are operating. These results highlight how complex interrelations among signal form, signaling interactions, and the social environment shape the evolution of communication in social species. [ABSTRACT FROM AUTHOR]

Network creation games are a well-known approach for explaining and analyzing the structure, quality, and dynamics of real-world networks that evolved via the interaction of selfish agents without a central authority. In these games selfish agents corresponding to nodes in a network strategically buy incident edges to improve their centrality. However, past research on these games only considered the creation of networks with unit-weight edges. In practice, e.g., when constructing a fiber-optic network, the choice of which nodes to connect and also the induced price for a link crucially depend on the distance between the involved nodes, and such settings can be modeled via edge-weighted graphs. We incorporate arbitrary edge weights by generalizing the well-known model by Fabrikant et al. [Proceedings of PODC'03, ACM, 2003, pp. 347--351] to edge-weighted host graphs and focus on the geometric setting where the weights are induced by the distances in some metric space. In stark contrast to the state of the art for the unit-weight version, where the price of anarchy is conjectured to be constant and where resolving this is a major open problem, we prove a tight nonconstant bound on the price of anarchy for the metric version and a slightly weaker upper bound for the nonmetric case. Moreover, we analyze the existence of equilibria, the computational hardness, and the game dynamics for several natural metrics. The model we propose can be seen as the game-theoretic analogue of the classical network design problem. Thus, low-cost equilibria of our game correspond to decentralized and stable approximations of the optimum network design. [ABSTRACT FROM AUTHOR]

The coronavirus pandemic has been accompanied by the spread of misinformation on social media. The Plandemic conspiracy theory holds that the pandemic outbreak was planned to create a new social order. This study examines the evolution of this popular conspiracy theory from a dynamic network perspective. Guided by the analytical framework of network evolution, the current study explores drivers of tie changes in the Plandemic communication network among serial participants over a 4-month period. Results show that tie changes are explained by degree-based and closure-based structural features (i.e. tendencies toward transitive closure and shared popularity and tendencies against in-degree activity and transitive reciprocated triplet) and nodal attributes (i.e. bot probability and political preference). However, a participant's level of anger expression does not predict the evolution of the observed network. [ABSTRACT FROM AUTHOR]

The study of coordination practices in health policy is a central aspect. The need for further research has been recently highlighted because of COVID-19. In this sense, dialogic practices (DP) have been identified but not validated yet. The purpose of this study is to develop and validate a DP questionnaire for healthcare teams. Items were identified based on a literature review, and the content validation was carried out by means of a Delphi study. A total of 10 experts assessed the clarity and appropriateness of the items and their corresponding measurement scales. After two rounds, a high level of consensus was reached, with agreement of 90% or higher on all items, and a high degree of stability and concordance in the results. This study resulted in a questionnaire consisting of four items, one for each identified DP initially proposed to the experts, as no other practices were revealed. From a practical perspective, the validation of these items constitutes a methodological innovation that responds to the call in the literature to open new avenues for comparative studies, and the possibility of generalising the findings and bringing together different approaches to the problem of coordination, which is key in health policy where unforeseen situations emerge. [ABSTRACT FROM AUTHOR]

The standard communication protocols transfer big data over the internet. However, the challenge lies while sharing the massive amount of genomics data quickly over limited bandwidth networks. Managed File Transfer (MFT) that uses File Transfer Protocol Secure (FTPS) or Secure Shell File Transfer Protocol (SFTP) is a scalable and secure alternative for the purpose. This paper proposes a framework consisting of a Variable-length Genomic Binary Encoding (VGBE) scheme and a hybrid Gated Recurrent Unit-Convolutional Neural Network model (GRU-CNN). The Method exploits Managed File Transfer to reduce the bit size before transmission and increases the bit rate during the transmission of genomics data. Consequently, the method ensures a minimum number of bits per word and less latency. The methodology is tested on various communication protocols. It is validated in terms of performance metrics viz. transfer rate and the size of transferred data using diverse benchmark datasets such as protein sequences and human reference genome taken from the University of California Santa Cruz (UCSC) and National Center for Biotechnology Information (NCBI), respectively. Furthermore, simulation and implementation results show that the model is 98% faster, has 96% less data size, and is more secure than standard communication protocols. Thus, the proposed method is an efficient and secure genomics data transfer method using deep learning techniques. [ABSTRACT FROM AUTHOR]

We study the connection between communication network structure and an organization's collective adaptability to a shifting environment. Research has shown that network centralization—the degree to which communication flows disproportionately through one or more members of the organization rather than being more equally distributed—interferes with collective problem-solving by obstructing the integration of existing ideas, information, and solutions in the network. We hypothesize that the mechanisms responsible for that poor integration of ideas, information, and solutions would nevertheless prove beneficial for problems requiring adaptation to a shifting environment. We conducted a 1,620-subject randomized online laboratory experiment, testing the effect of seven network structures on problem-solving success. To simulate a shifting environment, we designed a murder mystery task and manipulated when each piece of information could be found: early information encouraged an inferior consensus, requiring a collective shift of solution after more information emerged. We find that when the communication network within an organization is more centralized, it achieves the benefits of connectivity (spread of novel better solutions) without the costs (getting stuck on an existing inferior solution). We also find, however, that these benefits of centralization only materialize in networks with two-way flow of information and not when information only flows from the center of the network outward (as can occur in hierarchical structures or digitally mediated communication). We draw on these findings to reconceptualize theory on the impact of centralization—and how it affects conformity pressure (lock-in) and awareness of diverse ideas (learning)—on collective problem-solving that demands adaptation. History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory. Funding: The authors acknowledge financial support from the Division of Research at the Harvard Business School for making this research possible. [ABSTRACT FROM AUTHOR]

A major area of application of multiobjective path problems and resolution algorithms is telecommunication network routing design, taking into account the extremely rapid technological and service evolutions. The need for explicit consideration of heterogeneous Quality of Service metrics makes it advantageous for the development of routing models where various technical–economic aspects, often conflicting, should be tackled. Our work is focused on multiobjective path problem formulations and resolution methods and their applications to routing methods. We review basic concepts and present main formulations of multiobjective path problems, considering different types of objective functions. We outline the different types of resolution methods for these problems, including a classification and overview of relevant algorithms concerning different types of problems. Afterwards, we outline background concepts on routing models and present an overview of selected papers considered as representative of different types of applications of multiobjective path problem formulations and algorithms. A broad characterization of major types of path problems relevant in this context is shown regarding the overview of contributions in different technological and architectural network environments. Finally, we outline research trends in this area, in relation to recent technological evolutions in communication networks.

Under Metaverse, security management of communication networks in digital cultural consumption has attracted more and more attention. As we know, security risks of communication networks caused by non-human factors are becoming weaker and weaker due to technology optimization. Meanwhile, players play significant and increasing role in communication networks. Taking mobile games as an example, this paper designed and applied the security management model to improve security management of communication networks in digital cultural consumption under Metaverse. The results show that: (1) The physiological, psychological, pathological, pharmacological, physical and psychosocial factors exert tremendous influence on communication networks. The psychosocial factors are more prominent. (2) There is security threshold in communication networks. It means that the security state can be entered if security threshold is crossed. This paper designs security threshold as the III level (5.5 ≤ P G1 = 5.01. This confirms the effectiveness of the security management model.

AbstractSmallholder farmers have for a long time preferred to sell at the farm gate, where the prices have been very low compared to market places. This has been fueled by several challenges related to market participation. The purpose of this study is therefore aiming at developing an empirical understanding that uncovers whether digital technology can mediate the relationship between entrepreneurial networks and market participation. Entrepreneurship and digital technology are novel concepts in agriculture, especially for smallholder farmers. Therefore, this study presents new insights on how the challenges of market participation can be solved through entrepreneurial networks and digital technology. The study used validated items adopted from previous studies, from which the structured questionnaires were distributed to 298 smallholder farmers. In addition, structural equation modelling (SEM) was used to analyse relationships in which digital technology was found to be a mediator of the relationship between entrepreneurial networks and market participation among smallholder farmers. Further, the study suggests that smallholder farmers can overcome challenges and increase market participation if they change their attitudes through training conducted by rural extension officers and embrace digital technologies by designing new or joining existing entrepreneurial networks.

The frequency and severity of natural disasters is surging, posing an urgent need for robust communication network infrastructure that is capable of withstanding these events. In this paper, we present a groundbreaking graph-theoretic system designed to evaluate and enhance network resilience in the face of natural disasters. Our solution harnesses the power of topological robustness metrics, integrating real-time weather data, geographic information, detailed network topology data, advanced resilience algorithms, and continuous network monitoring. The proposed scheme considers four major real-world U.S.-based network providers and evaluates their physical topologies against two major hurricanes. Our novel framework quantifies the important characteristics of network infrastructure; for instance, AT&T is identified to have fared better against Hurricane Ivan (57.98 points) than Hurricane Katrina (39.17 points). We not only provide current insights into network infrastructure resilience, but also uncover valuable findings that shed light on the performance of backbone U.S. networks during hurricanes. Furthermore, our findings provide actionable insights to enrich the overall survivability and functionality of communication networks, mitigating the adverse impacts of natural disasters on communication systems and critical services in terms of improving network resiliency via adding additional nodes and link or rewiring. [ABSTRACT FROM AUTHOR]