Proactive Integrated Link Selection for Network Robustness (PILSNER)

This work provides an overview of three prototype augmented reality (AR) applications developed for the Microsoft HoloLens with the intention of exploring the strengths and weaknesses of AR for supporting planning and decision making–specifically, within the domain of US Army Mission Command and Battle Management Command and Control (BMC2) execution. We present each prototype application accompanied by the target audience from whom we sought feedback, key features of the application, and technical goals we hoped to achieve, demonstrate, and evaluate. Findings with respect to AR strengths and weaknesses, framed around the technical goals of each of the AR applications, are then presented to begin to shed light on limitations and opportunities of the state-of-the-art in AR hardware, and the potential to support Mission Command and BMC2 stakeholders. This material is based upon work supported by the Communications-Electronics Research, Development and Engineering Center (CERDEC) under Contract No. W56KGU-18-C-0002. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of CERDEC.

WATT Fuel Cell wins CERDEC contract, expands production

The U.S. Army Communications-Electronics Research, Development and Engineering Center (CERDEC), with a consortium of industry partners, is developing the Distributed Satellite Communications (SATCOM) On-The-Move (SOTM) Terminal (DST) Open Standard Architecture (OSA). The DST OSA is a nonproprietary, open architecture for the engineering design of a SOTM terminal with distributed antennas integrated on a tactical ground vehicle. The open standardized interfaces between system components are intended to increase market competition and reduce acquisition and life-cycle costs for DST components. Furthermore, the modular architecture defined in the DST OSA will enable research and development efforts to be more efficient and lower risk by focusing on the component level. Modular component development will in turn increase the speed and frequency of system technology refresh and new deployment. Current developments in system architecture are described in this paper.

This paper investigates the influence of forwarding scheme on multi-hop connectivity in cognitive radio ad-hoc networks (CRAHNs). We study three different forwarding schemes, i.e. a full flooding scheme and two limited flooding schemes with forwarding angles α = 60° and 90°. The multi-hop connectivity of cognitive radio ad-hoc networks under each forwarding scheme is examined and compared to each other. Simulation results in this paper show that full flooding only outperforms other schemes under certain circumstances of secondary user's density and operating frequency. However, it is a well-known fact that full flooding results in more network resource usage than limited flooding. Therefore, this paper provides an efficient guidance for system designers to characterize and optimize the multi-hop connectivity of CRAHNs under certain packet forwarding schemes of routing protocols so that maximum connectivity can be achieved with lowest network resource usage.

Cooperative caching in MANETS and forwarding data items through mobile nodes in Delay Tolerant Networks are two important methods for improving performance and providing connectivity in mobile tactical networks. In this paper we present the challenges of securing cooperative caching the DTN systems. Our security solution is based on MML-IPSec. The main challenge of this system is key distribution and its impact on performance. We propose leveraging military structure, knowledge of missions, and the roles of personnel to enable secure systems to maintain high performance.

The sizes of datasets available as RDF (e.g., as part of the Linked Data cloud) are increasing continuously. For instance, the recent DBpedia version consists of nearly 500 millions triples. A common strategy to avoid problems that arise e.g., from limited network connectivity or lack of bandwidth is to replicate data locally, therefore making them accessible for applications without depending on a network connection. For mobile devices with limited capabilities, however, the replication and synchronization of billions of triples is not feasible. To overcome this problem, we propose an approach to replicate parts of an RDF graph to a client. Applications may then apply changes to this partial replica while being offline; these changes are written back to the original data source upon reconnection. Our approach does not require any kind of additional logic (e.g., change logging) or data structures on the client side, and hence is suitable to be applied on devices with limited computing power and storage capacity.

Ocean circulation is the engine of dispersal and population connectivity in marine ecosystems, knowledge of which is essential for conservation planning. Understanding connectivity patterns at a large scale can help define the spatial extent of metapopulations. In this study, we built connectivity networks from Lagrangian transport simulations of neutrally buoyant particles released along the Indian coastline, a significant region in the Indian Ocean. We assessed the variation in connectivity networks across release periods for the major drivers of oceanography including the two monsoonal seasons, El Niño–Southern Oscillation (ENSO) years and for the entire range of region‐specific pelagic larval durations (PLDs) for marine invertebrates. We detected well‐connected communities, mapped frequent connectivity breaks, and assessed the functional role of coastal areas within the connectivity network using node metrics. Network characteristics did not differ based on the ENSO year, but varied with season and PLD. Connectance for the Indian coastline was relatively low, ranging from 0.5% to 3.4%, and increased significantly for PLD larger than 20 d. The number of cohesive coastal communities decreased gradually from 60 (PLD < 4 d) to 30 (PLD > 20 d) with increasing PLD. Despite variation in the location of connectivity breaks with the time of particle release within a monsoonal season, four disconnected provinces were consistently identified across the entire PLD range, which partially overlapped with observed genetic and biogeographic breaks reported along the Indian coastline. Our results support the adoption of a coordinated management framework within each of the four provinces delineated in the present study.

Deploying low-altitude unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) is a promising approach to enhance cellular network coverage in dynamic and infrastructure-constrained environments. However, real-world UAV deployment involves complex challenges, including managing partially observable and mobile users, maintaining multi-hop backhaul connectivity to a fixed ground base station, mitigating co-channel interference via minimum UAV separation, and optimizing coverage efficiency, fairness, and energy consumption. This paper proposes a multi-agent deep reinforcement learning (MARL) framework that formulates the dynamic UAV deployment task as a centralized multi-input multi-output policy. Our method employs sequential action masking to guarantee multi-hop connectivity and enforce minimum distance constraints during UAV placement. The policy network integrates graph neural networks, residual convolutional layers, and feature-wise linear modulation to effectively capture spatial relations, inter-UAV interactions, and global and local network states. We validate our approach through extensive simulations across various user density scenarios, demonstrating significant improvements in coverage efficiency, fairness of coverage distribution, and flight energy reduction compared to strong baseline algorithms. Our proposed framework provides a comprehensive solution that simultaneously addresses dynamic user mobility, multi-hop connectivity, interference mitigation, and energy efficiency in UAV-assisted cellular networks.

The study aimed to investigate the spatial correlation network of carbon emissions from cultivated land use in the Yellow River Basin(YRB) and its driving factors, which is conducive to promoting collaborative carbon emission reduction in cultivated land use across the region. The study utilized the carbon emission coefficient method to calculate carbon emissions from cultivated land use in the YRB between 2008 and 2022. A modified gravity model and social network analysis method were then employed to analyze the characteristics of the spatial correlation network of carbon emissions from cultivated land use in the YRB. Additionally, the Quadratic Assignment Procedure (QAP) method was utilized to identify driving factors. The research findings indicate that: (1) Between 2008 and 2022, the overall carbon emissions from cultivated land use in the YRB increased by 27.6%. The proportion of carbon emissions from different sources, from largest to smallest, was as follows: straw burning (over 60%), agricultural inputs (over 20%), and crop cultivation (around 13%). (2) According to the overall network characteristics, the spatial correlation network underwent an evolution from dispersion to concentration and then to adjustment. The network connectivity was good, efficiency fluctuated and rose to stability, centrality showed an inverted "U" shaped change, with Shandong and Henan remaining at the core of the network throughout. (3)Based on individual network characteristics, the network structure showed a core-periphery hierarchy, with Gansu and Inner Mongolia identified as the core provinces. (4) QAP analysis indicated that factors such as geographical proximity, urbanization levels, and agricultural machinery input intensity positively influenced the spatial correlation network, while factors like agricultural economic levels, farmer income levels, and environmental regulations had negative effects. Based on the findings of this study, feasible pathways are proposed from aspects including the three sources of carbon emissions, regional cooperation within the YRB, and policy optimization.

To allow the number of simultaneous participants and applications to grow, many Collaborative Virtual Environment (CVE) platforms are combining ideas such as loose consistency, absence of central servers and world sub-partitioning with IP multicasting. For long distance connections, most of these systems rely on the existence of the Internet multicast backbone - the MBone. However, its generality and complexity is often an obstacle to the establishment and testing of large-scale CVEs. This paper presents the DIVEBONE, an application-level network architecture built as a stand-alone part of the DIVE toolkit [5]. The DIVEBONE is an application-level backbone that can interconnect sub-islands with multicast connectivity and/or single local networks. Furthermore, the DIVEBONE allows for visual analysis of the connection architecture and network traffic and for remote maintenance operations. The DIVEBONE capabilities have been demonstrated and successfully used in a series of large-scale pan-European tests over the Internet, as well as in various experiments involving IP over ISDN and ATM. All trials have proven the qualitative and quantitative adequacy of the DIVEBONE in heterogeneous settings where multicast connectivity in other ways is limited.

As an important part of the city, the positive interaction between the road network and its built environment is conducive to promoting the formation of a safe, convenient, sustainable and livable spatial environment. Taking Futian District of Shenzhen as an example, this paper explores the structural characteristics of the road network by calculating the four types of centrality indicators of the global road network and the density of the local Community network, and analyzes the spatial distribution characteristics of the built road environment from the perspective of street view, and then uses multiple regression analysis and Pearson correlation method to measure the relationship between the two. The results show that the overall road structure in Futian District has high Degree centrality, low Betweenness centrality, relatively complete road network structure, high Network density of local community network, compact roads and good connectivity. The environmental factors of road construction in community scale have geographical and spatial distribution differences and diversity. The results of correlation characteristics show that there is a significant correlation between the structural characteristics of the global road network and the built environment, while there is a strong positive correlation between the Network density of local communities and PSTSR.

Computational identification of key genes and regulatory miRNAs responsible for differential regulation of host-pathogen response during early and late blight diseases in tomato

Whereas sexual relationships among low-risk individuals account for the majority of HIV infections in sub-Saharan Africa, limited knowledge exists about the structure and characteristics of sexual networks among the general population in sub-Saharan Africa. To investigate the population-level structure of sexual networks connecting the young adult population of several villages on Likoma Island (Malawi), and analyse the structural position of HIV-positive individuals within the sexual network. A cross-sectional sociocentric survey of sexual partnerships and biomarkers of prevalent HIV infections. The study documents the existence of a large and robust sexual network linking a substantial fraction of the island's young adult population: half of all sexually active respondents were connected in a giant network component, and more than a quarter were linked through multiple independent chains of sexual relationships. This high network connectivity emerges within short time frames. The prevalence of HIV also varied significantly across the network, with sparser regions having a higher HIV prevalence than densely connected components. Several risk factors related to sexual mixing patterns help explain differentials in HIV prevalence across network locations. Contrary to claims that sexual networks in rural sub-Saharan Africa are too sparse to sustain generalized HIV epidemics, the structure of the networks observed in Likoma appears compatible with a broad diffusion of HIV among lower-risk groups. The non-homogeneous distribution of HIV infection within the network suggests that network characteristics are an important determinant of the dynamics of HIV spread within a population.

Rhizosphere microorganisms mediate the material exchange and chemical cycling between plant roots and soil. However, the response mechanisms of the rhizosphere microbial community, especially its co-occurrence patterns, to thinning remain poorly understood. We investigated the rhizosphere microbial communities of Pinus massoniana under different thinning intensities, including control (CK, 0%), light-intensity thinning (LIT, 10%), moderate-intensity thinning (MIT, 30%), and high-intensity thinning (HIT, 50%). Basic taxonomic information was obtained through high-throughput sequencing, while R software was utilized to identify thinning-sensitive operational taxonomic units (tsOTUs), construct co-occurrence networks, and perform other statistical analyses. Although no discernible patterns were observed in α-diversity changes, the Kruskal–Wallis test indicated that season was the primary factor driving α-diversity variation. Meanwhile, thinning intensity significantly shaped the rhizosphere microbial community structures, with each intensity harboring a specific tsOTUs subset. Although the top three modules of the meta-co-occurrence networks in summer and winter exhibited consistent tsOTU composition, winter triggered changes in network connectivity. Regardless of summer or winter, the number of network nodes under MIT was the highest. Additionally, after thinning, the relative abundances of most keystone taxa declined; however, MIT facilitated the enrichment of certain keystone taxa. Collectively, thinning profoundly shapes microbial community composition and network characteristics. Moderate thinning intensity may represent the optimal thinning intensity for the studied P. massoniana plantations.

A growing body of evidence highlights the role of life stress as a risk factor for the development and relapse of substance use disorders (SUDs), but the relationship of life stress with the interactions among SUD symptoms is overlooked. The current study investigated the role of life stress in symptom networks of 3 different SUDs-alcohol, tobacco, and drug use-using the U.S. representative data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) I and II (N = 34,653). The symptom networks were estimated using the Ising model and l1-regularziation with model selection based on the Extended Bayesian Information Criterion. We examined the association of stress with 2 network characteristics: the network connectivity and the network structure. In addition, we applied bootstrap routines to examine the stability of our results and tested whether our findings of Wave 1 replicated in Wave II of the NESARC. For alcohol and drug use symptoms, but not for tobacco use symptoms, greater network connectivity (which is related to psychiatric severity and prognosis) was associated with the number of stressors. In contrast, the structure of SUD symptom networks remained stable regardless of the level of stress, which indicated that the order of central nodes in the symptom networks was not significantly associated with stress. Altogether, our findings suggest that there is a quantitative (i.e., greater connectivity), but not qualitative (i.e., structure), difference in alcohol and drug use symptom relationships associated with life stress. (PsycINFO Database Record (c) 2020 APA, all rights reserved).