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The Arctic marine ecosystem is changing fast due to climate change, emphasizing the need for solid ecological baselines and monitoring. The polar cod Boreogadus saida functions as a key species in the Arctic marine food web. We investigated the stomach contents of polar cod from the northern Barents Sea using DNA metabarcoding with the mitochondrial cytochrome c oxidase I gene in parallel with classical visual analysis. Arctic amphipods and krill dominated the diet in both methods. Yet, metabarcoding allowed for the identification of digested and unidentifiable prey and provided higher taxonomic resolution, revealing new and undiscovered prey items of polar cod in the area. Furthermore, molecular results suggest a higher importance of barnacles and fish (presumably eggs and pelagic larvae) in the diet than previously recorded. Parasites and, in 6 cases, other prey items were only visually identified, demonstrating the complementary nature of both approaches. The presence of temperate and boreal prey species such as northern krill and (early life stages of) European flounder and European plaice illustrates the advection of boreal taxa into the polar region or may be indicative of ongoing borealisation in the Barents Sea. We show that a combination of visual analysis and metabarcoding provides complementary and semi-quantitative dietary information and integrative insights to monitor changing marine food webs.

OSE-127 is a humanized mAb targeting the IL-7Rα-chain (CD127), under development for inflammatory and autoimmune disease treatment. It is a strict antagonist of the IL-7R pathway, is not internalized by target cells, and is noncytotoxic. In this work, a first-in-human, phase I, randomized, double-blind, placebo-controlled, single-center study was carried out to determine the safety, pharmacokinetics, pharmacodynamics, and immunogenicity of OSE-127 administration. Sixty-three healthy subjects were randomly assigned to nine groups: six single ascending dose groups with i.v. administration (0.002–10 mg/kg), a single s.c. treatment group (1 mg/kg), and two double i.v. injection groups (6 or 10 mg/kg). Subjects were followed during 100 d after two i.v. infusions at 10 mg/kg. IL-7 consumption was inhibited by OSE-127 administration, as demonstrated by a decreased IL-7 pathway gene signature in peripheral blood cells and by ex vivo T lymphocyte restimulation experiments. OSE-127 was well tolerated, with no evidence of cytokine-release syndrome and no significant alteration of blood lymphocyte counts or subset populations. Altogether, the observed lack of significant lymphopenia or serious adverse events, concomitant with the dose-dependent inhibition of IL-7 consumption by target cells, highlights that OSE-127 may show clinical activity in IL-7R pathway–involved diseases.

The SARS-CoV-2 pandemic has highlighted the need for vaccines that are effective, but quickly produced. Of note, vaccines with plug-and-play capabilities that co-deliver antigen and adjuvant to the same cell have shown remarkable success. Our approach of utilizing a nitrilotriacetic acid (NTA) histidine (His)-tag chemistry with viral adjuvants incorporates both of these characteristics: plug-and-play and co-delivery. We specifically utilize the cowpea mosaic virus (CPMV) and the virus-like particles from bacteriophage Qβ as adjuvants and bind the model antigen ovalbumin (OVA). Successful binding of the antigen to the adjuvant/carrier was verified by SDS-PAGE, western blot, and ELISA. Immunization in C57BL/6J mice demonstrates that with Qβ - but not CPMV - there is an improved antibody response against the target antigen using the Qβ-NiNTA:His-OVA versus a simple admixture of antigen and adjuvant. Antibody isotyping also shows that formulation of the vaccines can alter T helper biases; while the Qβ-NiNTA:His-OVA particle produces a balanced Th1/Th2 bias the admixture was strongly Th2. In a mouse model of B16F10-OVA, we further demonstrate improved survival and slower tumor growth in the vaccine groups compared to controls. The NiNTA:His chemistry demonstrates potential for rapid development of future generation vaccines enabling plug-and-play capabilities with effectiveness boosted by co-delivery to the same cell.

In recent years, containers have gained popularity as a lightweight virtualization technology. This rise in popularity has gone hand in hand with the adoption of microservice architectures, mostly thanks to the scalable, ethereal, and isolated nature of containers. More recently, edge devices have become powerful enough to be able to run containerized microservices, while remaining flexible enough in terms of size and power to be deployed almost anywhere. This has triggered research into several container placement strategies involving edge networks, leading to concepts such as osmotic computing. While these container placement strategies are optimal in terms of workload placement, current container orchestrators are often not suitable for running on edge devices due to their high resource requirements. In this article, FLEDGE is presented as a Kubernetes-compatible container orchestrator based on Virtual Kubelets, aimed primarily at container orchestration on low-resource edge devices. Several aspects of low-resource container orchestration are examined, such as the choice of container runtime and how to realize container networking. A number of evaluations are performed to determine how FLEDGE compares to Kubernetes and K3S in terms of resource requirements, showing that it needs around 60MiB memory and 78MiB storage to run on a Raspberry Pi 3, including all dependencies, which is significantly less than both studied alternatives.

Andrenosoma lottae Mortelmans sp. nov. is described based on males and females from Fars province, Iran. Pictures of the habitus are provided, together with details of the male terminalia to facilitate species identification. The status of Andrenosoma violacea is discussed and hereby put forward as a species inquirenda. http://www.zoobank.org/urn:lsid:zoobank.org:pub:2E6AB0F2-7227-4BDA-BA1C-3BA032B7A84D

Modification of the electronic structure of quantum matter by ad atom deposition allows for directed fundamental design of electronic and magnetic properties. This concept is utilized in the present work in order to tune the surface electronic structure of magnetic topological insulators based on MnBi2Te4. The topological bands of these systems are typically strongly electron-doped and hybridized with a manifold of surface states that places the salient topological states out of reach of electron transport and practical applications. In this work, micro-focused angle-resolved photoemission spectroscopy (microARPES) provides direct access to the termination-dependent dispersion of MnBi2Te4and MnBi4Te7during in situ deposition of rubidium atoms. The resulting band structure changes are found to be highly complex, encompassing coverage-dependent am-bipolar doping effects, removal of surface state hybridization and the collapse of a surface state band gap. In addition, a doping-dependent band bending is found to give rise to tunable quantum well states. This wide range of observed electronic structure modifications could provide new ways to exploit the topological states and the rich surface electronic structures of manganese bismuthtellurides.

Background: Inhibition of PCSK9 (proprotein convertase subtilisin/kexin type 9)-low density lipoprotein receptor interaction with injectable monoclonal antibodies or small interfering RNA lowers plasma low density lipoprotein-cholesterol, but despite nearly 2 decades of effort, an oral inhibitor of PCSK9 is not available. Macrocyclic peptides represent a novel approach to target proteins traditionally considered intractable to small-molecule drug design. Methods: Novel mRNA display screening technology was used to identify lead chemical matter, which was then optimized by applying structure-based drug design enabled by novel synthetic chemistry to identify macrocyclic peptide (MK-0616) with exquisite potency and selectivity for PCSK9. Following completion of nonclinical safety studies, MK-0616 was administered to healthy adult participants in a single rising-dose Phase 1 clinical trial designed to evaluate its safety, pharmacokinetics, and pharmacodynamics. In a multiple-dose trial in participants taking statins, MK-0616 was administered once daily for 14 days to characterize the safety, pharmacokinetics, and pharmacodynamics (low density lipoprotein cholesterol). Results: MK-0616 displayed high affinity ( K i = 5pM) for PCSK9 in vitro and sufficient safety and oral bioavailability preclinically to enable advancement into the clinic. In Phase 1 clinical studies in healthy adults, single oral doses of MK-0616 were associated with >93% geometric mean reduction (95% CI, 84–103) of free, unbound plasma PCSK9; in participants on statin therapy, multiple–oral-dose regimens provided a maximum 61% geometric mean reduction (95% CI, 43–85) in low density lipoprotein cholesterol from baseline after 14 days of once-daily dosing of 20 mg MK-0616. Conclusions: This work validates the use of mRNA display technology for identification of novel oral therapeutic agents, exemplified by the identification of an oral PCSK9 inhibitor, which has the potential to be a highly effective cholesterol lowering therapy for patients in need.

Publisher: Pensoft Publishers; International audience; Truly sustainable development in a human-altered, fragmented marine environment subject to unprecedented climate change, demands informed planning strategies in order to be successful. Beyond a simple understanding of the distribution of marine species, data describing how variations in spatio-temporal dynamics impact ecosystem functioning and the evolution of species are required. Marine Functional Connectivity (MFC) characterizes the flows of matter, genes and energy produced by organism movements and migrations across the seascape. As such, MFC determines the ecological and evolutionary interdependency of populations, and ultimately the fate of species and ecosystems. Gathering effective MFC knowledge can therefore improve predictions of the impacts of environmental change and help to refine management and conservation strategies for the seas and oceans. Gathering these data are challenging however, as access to, and survey of marine ecosystems still presents significant challenge. Over 50 European institutions currently investigate aspects of MFC using complementary methods across multiple research fields, to understand the ecology and evolution of marine species. The aim of SEA-UNICORN, a COST Action within the European Union Horizon 2020 framework programme, is to bring together this research effort, unite the multiple approaches to MFC, and to integrate these under a common conceptual and analytical framework. The consortium brings together a diverse group of scientists to collate existing MFC data, to identify knowledge gaps, to enhance complementarity among disciplines, and to devise common approaches to MFC. SEA-UNICORN will promote co-working between connectivity practitioners and ecosystem modelers to facilitate the incorporation of MFC data into the predictive models used to identify marine conservation priorities. Ultimately, SEA-UNICORN will forge strong forward-working links between scientists, policy-makers and stakeholders to facilitate the integration of MFC knowledge into decision support tools for marine management and environmental policies.

The collaboration between HADES and the Mont Terri rock laboratory started in 1995, when granite was considered the most suitable host rock for radioactive waste disposal in Switzerland. When an alternative host formation was looked for by NAGRA, the choice of clay as host rock became rapidly clear. It was then decided to build an underground research laboratory in the Opalinus Clay taking advantage of the excavation of a motorway tunnel crossing the Mont Terri anticline. Exchanges of knowledge and experience on the behaviour of argillaceous formations were focused on the feasibility of constructing a safe geological repository for high-level radioactive waste: from excavation and gallery lining techniques to geochemistry, diffusion of radionuclides and coupled thermo-hydro-mechanical processes. The research programme at Mont Terri and the growing numbers of partners from four up to nine countries worldwide led to successive extensions of the galleries. The scientific and technical advances made possible by the collaboration between both laboratories dealt with the development of common methods and joint experimental and modelling efforts. This review article summarizes the main scientific lessons learned during these exchanges, stressing the added values of the knowledge transfer between partners and the overall cross-fertilization between HADES and Mont Terri.

In order to fulfil its mission, the Belgian Regulatory Body (constituted in Belgium by FANC and Bel V) has set up its own Research & Development programme, independent from the Waste Management Organisation's one. The Regulatory Body's Research & Development programme is mostly intended to investigate safety issues with the objective to be able to assess if the safety concept developed by the Waste Management Organisation fulfils the defined safety requirements. It includes the development and the follow-up of in situ experiments in underground research laboratories (e.g. in the Mont Terri project in Switzerland and at Tournemire in France). Such activities are essential to maintain and improve the scientific and technical skills, to strengthen the independence from the Waste Management Organisation and to build public confidence in the regulatory function. More generally, Research & Development in underground research laboratories is important to the Regulatory Body as it allows investigating processes, technologies and activities important to safety under in situ conditions. In particular, it is essential to accurately identify and characterize the processes upon which the safety functions of a disposal system rely, as well as processes that may affect the system performance. It is also necessary to demonstrate that construction and operational methods and technologies are technically feasible and can be implemented as assumed in the safety case. Such research and development activities are of great importance to properly manage some of the key uncertainties associated with a disposal programme and in particular to identify, characterize and reduce them where needed.

Despite their maturity and robustness, container orchestration platforms still suffer from some limitations. One of those concerns the lack of runtime adaptability of the scheduler to the overall cluster status as i) it instantiates containers with local optimization in mind i.e. it only considers the container-specific predefined requirements which may lead to a sub-optimal overall cluster state and ii) it does not reshuffle the deployed containers at runtime based on container observed behavior and interdependencies. These limitations become even more apparent within volatile load contexts. This work proposes an autonomous and dynamic rescheduling system that aims at improving application service time by co-locating highly interdependent containers for network delay reduction. To this extend, two distinct combinatorial optimization heuristics, Simulated Annealing and Particle Swarm Optimization, are evaluated and compared on their respective effectiveness and efficiency as well as their relative performance towards the optimal solution obtained by Integer Linear Programming. Additionally, the impact of the proposed system on application service time is validated by means of two complementary use-cases, an event-based IoT data-hub platform and a web-based e-commerce app, with an average improvement of the end-to-end service time of 21.6% and 13.1% respectively.

Understanding why certain host species harbor more parasites is an important question in parasite and fish ecology. Parasite infection among sympatric species may integrate various processes affecting parasite assembly, including the species-specific ecology and the success of invaders. We focused on spatial, environmental, and host-related determinants of parasite assembly in three riverine fish species: the native three-spined stickleback and stone loach, and the invasive topmouth gudgeon. Parasite community structure differed significantly between the three host species. Three-spined stickleback harbored the most ectoparasites. Host density and nutrients were the strongest predictors of its parasite communities. Topmouth gudgeon harbored the lowest number of parasites, both in terms of abundance and species richness. None of the parasites identified originated from its expanded range, suggesting that enemy release occurred during invasion. Temperature and host density predicted parasite assemblages of topmouth gudgeon. Stone loach hosted the most endoparasites, likely resulting from its varied diet, benthic lifestyle, and larger size. Additionally, host size and condition were positively correlated with parasite infection, which was similar among the three host species. The results suggest that host-related factors have a similar effect among host species, while the importance of environmental and spatial factors differs according to host ecology.

Flanders (Belgium) is aging at high speed. In 2060, almost one in three (32 percent) will be older than 60. The number of people aged 80 and over will increase from more than 400,000 today to nearly 800,000 in 2060. This demographic change can be witnessed throughout the entire region, yet older people are overrepresented in rural areas. A large majority of older people is ‘aging in place’. This often occurs in places that witness a severe decline in basic facilities and that suffer from a loss of its young(er) population. Nevertheless, policies in Flanders strongly support aging in place, while emphasizing the role of informal caregivers. This paper explores older people's perceptions of and experiences with informal care in rural Flanders. Based on qualitative in-depth interviews, we focus on the role of family members and neighbors in providing informal care for older people living at home in two different rural areas in Flanders (‘Westhoek’ and ‘Kempen’). The analysis shows how, in both regions, receiving care from children and neighbors is simply not always perceived as a valid and realistic option by our respondents, and this for different reasons. It concludes that the current focus of elderly policy in Flanders on aging in place and the strong emphasis on the role of informal caregivers work only for those older people whose informal caregivers (in practice mostly children) live nearby. This depends strongly, of course, on spatial and economic factors. Also, neighbors are not the cohesive group they are presumed to be. We thus have to move beyond the nostalgic idea that neighbors and close family members can or will actively engage in informal care.

Een lift die pas toegankelijk is, nadat je zes treden opgaat. Wonen in een dorpwaar geen slager, bakker of bankautomaat meer is. En beroep moeten doen opje dochter die 60 kilometer verder woont om te helpen met boodschappen enklusjes in huis. Wie denkt dat thuis ouder worden geen ruimtelijke dimensieheeft, komt van een kale reis thuis.

Physical review / B 106(20), L201409 (2022). doi:10.1103/PhysRevB.106.L201409, X-ray photoelectron diffraction is a powerful tool for determining the structure of clean and adsorbate-covered surfaces. Extending the technique into the ultrafast time domain will open the door to studies as diverse as the direct determination of the electron-phonon coupling strength in solids and the mapping of atomic motion in surface chemical reactions. Here we demonstrate time-resolved photoelectron diffraction using ultrashort soft x-ray pulses from the free electron laser FLASH. We collect Se $3d$ photoelectron diffraction patterns over a wide angular range from optically excited Bi$_2$Se$_3$ with a time resolution of 140 fs. Combining these with multiple scattering simulations allows us to track the motion of near-surface atoms within the first 3 ps after triggering a coherent vibration of the $A_{1g}$ optical phonons. Using a fluence of $4.2mJ/cm^2$ from a 1.55 eV pump laser, we find the resulting coherent vibrational amplitude in the first two interlayer spacings to be on the order of 0.01 Å., Published by Inst., Woodbury, NY

Fitness tracking social networks such as Strava allow users to record sports activities and share them publicly. Sharing encourages peer interaction but also constitutes a risk, because an activity's start or finish may inadvertently reveal privacy-sensitive locations such as a home or workplace. To mitigate this risk, networks introduced endpoint privacy zones (EPZs), which hide track portions around protected locations. In this paper, we show that EPZ implementations of major services remain vulnerable to inference attacks that significantly reduce the effective anonymity provided by the EPZ, and even reveal the protected location. Our attack leverages distance information leaked in activity metadata, street grid data, and the locations of the entry points into the EPZ. This yields a constrained search space where we use regression analysis to predict protected locations. Our evaluation on 1.4 million Strava activities shows that our attack discovers the protected location for up to 85% of EPZs. Larger EPZs reduce the performance of our attack, while geographically dispersed activities in sparser street grids yield better performance. We propose six countermeasures, that, however, come with a usability trade-off, and responsibly disclosed our findings and countermeasures to the major networks. ispartof: pages:801-814 ispartof: Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security pages:801-814 ispartof: 2022 ACM SIGSAC Conference on Computer and Communications Security location:Los Angeles, CA, USA date:7 Nov - 11 Nov 2022 status: published

Data visualization recommendation aims to assist the user in creating visualizations from a given dataset. The process of creating appropriate visualizations requires expert knowledge of the available data model as well as the dashboard application that is used. To relieve the user from requiring this knowledge and from the manual process needed to create numerous visualizations or dashboards, we present a context-aware visualization recommender system that automatically recommends a personalized dashboard to the user, based on the system they are monitoring and the task they are trying to achieve. Through a knowledge graph-based approach, expert knowledge about the data and the application is included to improve the recommendation process. Preliminary results show a promising performance of the presented recommender system, validating its ability to assist the end-user in visualizing the most relevant information and reduce the time required to manually create dashboards.

Machine learning is finding its way into more and more application domains, often reaching outstanding results. However, most of its premier results have been achieved in vision and language tasks. The new methods which power those results are then eagerly adopted in a broader set of research fields to solve other tasks, typically with other types of data. This demonstration will show that the blind adoption of computationally expensive methods has caused more harm than good in my research field, (network / host) intrusion detection and in the application of data science in cybersecurity tasks more broadly. Foregoing establishing proper baselines with simple methods has deluded many researchers into hailing their methods as improvements over the state-of-the-art, when in fact they are not. This demo is targeted at researchers who are applying ML to any task with structured input data.

An intrusion detection system (IDS) is a security monitoring system capable of detecting potential attacks exceeding the firewall. Traditionally, these systems rely on pattern matching and signatures of known attacks, but in the last decades, security researchers have shifted their interest to machine learning (ML) techniques with varying degrees of success. While the published literature reports outstanding results, we are still waiting for the breakthrough of operational ML-IDS in the real world. To address this issue, we investigate the source of the problem, the datasets themselves, and propose guidelines to work with existing benchmark datasets to improve the generalization power of the ML models. This study evaluates the generalization strength of a ML model using the novel inter-dataset evaluation strategy compared to the traditional intra-dataset strategy. The results show high classification performance on the training dataset but fail to transfer this to a second related but unseen dataset with an average drop in accuracy of 25%. The proposed inter-dataset evaluation strategy empowers future research to estimate the generalization strength of ML solutions closer to a real-world setting.

A recent trend observed in the Kubernetes world is trying to deploy a Kubernetes cluster entirely or partially to the edge. When further looking into these edge environments, it is often noted that wireless technologies are used. Kubernetes is not designed to support these wireless network setups and will have to be extended to run smoothly on these networks. One of the most used network setups in edge environments is a wireless mesh network. Therefore the main focus will be on running Kubernetes on top of a wireless mesh network. Other mesh networks will also be supported with a minimal set of changes needed. The main goal of this paper is to list all the problems encountered when running Kubernetes on top of a mesh network and provide a framework of components and extensions to solve these problems. The majority of these components will be implemented, and demonstrations show that these components are able to solve most of the listed problems when used in a setup with some predefined restrictions. When deploying a demo application with the proposed solution, the required bitrate is observed 97 percent of the time compared to 42 percent with the native Kubernetes scheduler.

Lake Tanganyika, East Africa, is the oldest and deepest African Great Lake and harbours one of the most diverse fish assemblages on earth. Two clupeid fishes, Limnothrissa miodon and Stolothrissa tanganicae, constitute a major part of the total fish catch, making them indispensable for local food security. Parasites have been proposed as indicators of stock structure in highly mobile pelagic hosts. We examined the monogeneans Kapentagyrus limnotrissae and Kapentagyrus tanganicanus (Dactylogyridae) infecting these clupeids to explore the parasites' lake-wide population structure and patterns of demographic history. Samples were collected at seven sites distributed across three sub-basins of the lake. Intraspecific morphological variation of the monogeneans (n = 380) was analysed using morphometrics and geomorphometrics of sclerotised structures. Genetic population structure of both parasite species (n = 246) was assessed based on a 415 bp fragment of the mitochondrial cytochrome c oxidase subunit I (COI) gene. Overall, we observed a lack of clear geographical morphological differentiation in both parasites along a north-south axis. This lack of geographical population structure was also reflected by a large proportion of shared haplotypes, and a pattern of seemingly unrestricted gene flow between populations. Significant morphological and genetic differentiation between some populations might reflect temporal differentiation rather than geographical isolation. Overall, the shallow population structure of both species of Kapentagyrus reflects the near-panmictic population structure of both host species as previously reported. Morphological differences related to host species identity of K. tanganicanus were consistent with incipient speciation at the genetic level. Both parasite species experienced a recent demographic expansion, which might be linked to paleohydrological events. Finally, interspecific hybridisation was found in Kapentagyrus, representing the first case in dactylogyrid monogeneans. (C) 2020 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved. The authors would like to thank L. Raisingerová, C. Rahmouni, H. Zimmermann, A. P. H. Bose and W. Salzburger for help with collecting host samples. M. Jorissen is gratefully acknowledged for fruitful discussions about monogenean morphological variability and help in the laboratory. Special thanks to the staff of the parasitological group at Masaryk University, Brno (Czech Republic), the Research Group Zoology at Hasselt University (Belgium), Research Centre of Hydrobiology in Uvira (DR Congo) and Fisheries Research Unit in Mpulungu (Zambia) for their hospitality. Research was supported by the Czech Science Foundation (P505/12/G112 (ECIP) and GA19-13573S), EMBRC Belgium – FWO project GOH3817N as well as by a joint program between the Austrian Agency for International Cooperation in Education and Research (OEAD; project number CZ 08/2018; to SK) and the Ministry of Education, Youth and Sports (project number 8J18AT007). MPMV was co-financed by institutional funding of the Finnish Museum of Natural History and the Belgian Directorate-General for Development Cooperation and Humanitarian Aid (CEBioS program). ELRDK was supported by the Belgian Development Cooperation through VLIR-UOS (VLADOC scholarship NDOC2016PR006 to ELRDK and South Initiative project CD2018SIN218A101). Fieldwork was carried out with the approval of the competent local authorities under mission statement 031/MINRST/CRH-U/2016 and the permission of the Fisheries Department of Zambia and under a study permit issued by the government of Zambia (SP 008732).

Nowadays, many complex multi-vendor production environments, such as telecom infrastructures in smart cities or on-board passenger information systems in trains, are based on micro-services and deployed in the cloud. From a service integrator viewpoint, building new solutions for these environments, which can host a large number of externally designed and developed micro-services, is often complex and error-prone. This is in part due to undocumented behaviour or undocumented architectural specifications of such systems. Advanced service monitoring can offer a solution to quickly detect anomalies or unexpected service interaction behaviour during on-site integration. However, the monitoring service should not have an impact on the production environment itself. Therefore, this article proposes an agent-based unobtrusive monitoring platform, capable of monitoring both internally developed and externally developed services through the use of sidecar containers. It monitors state, metrics and network traffic at micro-service level and the research was conducted as part of the DynAMo research project, a collaboration with various industry partners. Prototype evaluation proves that our solution has a negligible impact (below 0.02% CPU usage on average) on an existing micro-service environment just as other monitoring systems like Prometheus while offering additional functionality focused on multi-vendor service integration. This makes it suitable to be deployed in complex production domains to further aid on-site integration and quickly find potential new anomalies.

Recently, distributed cloud infrastructures have become a potential business opportunity for most service providers due to the exponential growth of connected devices. The advent of the Internet of Things (IoT) and softwarized networks made centralized cloud systems impractical. In response, Fog Computing (FC) emerged, enabling the deployment of services on computational resources from the cloud up to the edge. However, the adoption of FC concepts is still in its early stages and challenges persist to fully benefit from fog–cloud infrastructures. One of them is known as Service Function Chaining (SFC) where providers benefit from network softwarization to create virtual chains of connected services. Recent research has tackled SFC allocation through theoretical modeling and heuristic algorithms, which often cannot cope with the dynamic behavior of the network. Thus, in this chapter, we explore a subset of machine learning (ML) called Reinforcement Learning (RL) to provide an efficient solution for SFC allocation in FC. The proposed approach learns about the best resource allocation decisions, focused on energy efficiency from a previously presented mixed‐integer linear programming (MILP) formulation. Results showed that RL algorithms perform comparably to state‐of‐the‐art ILP‐based implementations while offering more scalable solutions. Future research directions and open challenges are discussed.

Background Current influenza vaccines are strain specific and demonstrate low vaccine efficacy against H3N2 influenza disease, especially when vaccine is mismatched to circulating virus. The novel influenza vaccine candidate, M2-deficient single replication (M2SR), induces a broad, multi-effector immune response. Methods A phase 2 challenge study was conducted to assess the efficacy of an M2SR vaccine expressing hemagglutinin and neuraminidase from A/Brisbane/10/2007 (Bris2007 M2SR H3N2; clade 1). Four weeks after vaccination, recipients were challenged with antigenically distinct H3N2 virus (A/Belgium/4217/2015, clade 3C.3b) and assessed for infection and clinical symptoms. Results Adverse events after vaccination were mild and similar in frequency for placebo and M2SR recipients. A single dose of Bris2007 M2SR induced neutralizing antibody to the vaccine (48% of recipients) and challenge strain (27% of recipients). Overall, 54% of M2SR recipients were infected after challenge, compared with 71% of placebo recipients. The subset of M2SR recipients with a vaccine-induced microneutralization response against the challenge virus had reduced rates of infection after challenge (38% vs 71% of placebo recipients; P = .050) and reduced illness. Conclusions Study participants with vaccine-induced neutralizing antibodies were protected against infection and illness after challenge with an antigenically distinct virus. This is the first demonstration of vaccine-induced protection against a highly drifted H3N2 challenge virus.

Most newly proposed detection methods in intrusion detection incorporate machine learning models to distinguish between benign and malicious traffic. The models are validated on a handful of academic datasets and ranked based on their classification performance. This article aims to demonstrate that unbeknownst to the new models' authors, there are features in these datasets which heavily bias the results and obscure a realistic, reliable estimate of the separability of the datasets. This paper proposes a methodology to estimate the contaminating influence of a dataset's features based on the concept of blind generalization. The novel methodology is subsequently used to assess the features of six widely adopted intrusion detection datasets. In each dataset, several features show a pattern where regardless of training attack class, the models blindly generalize towards all available attack classes with nearly identical classification metrics. These features provide undeserved boosts in the baseline classification scores for each dataset. By themselves, some contaminant features even push these baselines upwards of 90% accuracy (balanced).

Background: The striped catfish,Pangasionodon hypophthalmus, is one of the most important cultured fish species worldwide. Although genetic management and improvement based on molecular approaches have a high potential, few applications are available due to the lack of genomic resources.Methods and results: We used a draft genome of striped catfish to develop 26 polymorphic DNA microsatellite markers. Markers were validated on 62 individuals from three wild populations. The 26 loci were highly polymorphic, with 7 to 21 alleles per locus for a total of 342 alleles. Null alleles were observed at 6 of the 26 loci. Polymorphism Information Content (PIC) values pointed to a high level of polymorphism (PIC>0.5) at all tested loci. Observed and expected heterozygosity ranged from 0.532 to 0.919 and 0.584 to 0.891, respectively. The Tonlé Sap and Lower Mekong samples were similar and differed from the Kratié sample.Conclusions:The 26 microsatellite markers represent an additional and valuable source for population genetic studies, parentage assignment, the estimation of genetic parameters for broodstock management and marker assisted selection in striped catfish.

The recent rise of edge computing and FaaS triggered a revolution in the field of software virtualization, improving performance and security. This paper benchmarks various lightweight virtualization platforms, such as microVMs and containers, in the context of edge microservices. Factors taken into account include toolchain maturity, networking capabilities, boot time, resource use, microservice performance, and ARM architecture readiness. We present a functional comparison and benchmarks on both a Raspberry Pi 4 and an x86-64 platform. The results indicate standard Docker containers offer reliable performance and low memory use, while microVM-based solutions such as Firecracker are more isolated. Moreover, OSv unikernels have extremely low boot times and significantly better performance than Docker containers. Finally, while gVisor offers improved security and excellent compatibility, its performance is only 10% of default Docker performance.

This study investigates the use of an immunotherapeutic plant virus, namely the cowpea mosaic virus (CPMV), that when used prophylactically and therapeutically can protect against metastatic cancer in multiple tumor mouse models. Metastatic cancer continues to be the main cause of death of most cancer patients, and new treatment modalities must be engineered to protect patients from metastatic disease. For instance, peritoneal metastases (PMs) are oftentimes fatal, and patients survive for a median 6 months following diagnosis. PMs are common for colon, ovarian, gastric, appendiceal, and pancreatic cancers. Previously, it was demonstrated that CPMV is a potent in situ vaccine causing tumor shrinkage with abscopal effect and long-term protection observed in tumor mouse models and canine cancer patients. CPMV functions as a toll like receptor (TLR) agonist and acts on innate immune cells to induce tumor cell killing and antigen processing to eventually prime adaptative and tumor-specific immunity. However, metastatic cancers such as PMs are not easily and directly injectable and therefore, we have expanded the ability of CPMV to protect against PMs by engineering targeted CPMV nanoparticles. Data indicates that CPMV can improve survival and slow tumor growth in a murine colon PM model compared to controls and that long-term survivors are further protected from re-challenge indicating tumor specificity. Analysis from current and past studies indicate that CPMV injection into the intraperitoneal space leads to distinct upregulation of immunostimulatory cytokines and recruitment of innate immune cell populations. PMs lead to extreme declines in quality of life of patients, and current treatments can be ineffective in slowing down or reducing tumor development and death - in tackling this problem, the data clearly points to the strong potential for CPMV-mediated therapeutics in the treatment and prophylaxis of PMs. Dr. Steinmetz is a co-founder of and has a financial interest in Mosaic ImmunoEngineering Inc. The other authors have no conflict of interest to declare. Acknowledgments: This work is supported in part through NIH grants R01 CA274640, R01 CA224605, R01 CA253615, CDMRP W81XWH2010742, and the Shaughnessy Family Fund for Nano-ImmunoEngineering (nanoIE at UC San Diego). Citation Format: Young Hun Chung, Britney A. Volckaert, Nicole F. Steinmetz. Treatment of metastatic cancers using immunotherapeutic cowpea mosaic virus nanoparticles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 812.

The current and projected environmental change of the Arctic Ocean contrasts sharply with the limited knowledge of its genetic biodiversity. Polar cod Boreogadus saida (Lepechin, 1774) is an abundant circumpolar marine fish and ecological key species. The central role of polar cod in the Arctic marine food web warrants a better understanding of its population structure and connectivity. In this study, the genetic population structure of 171 juveniles, collected from several fjords off West-Svalbard (Billefjorden, Hornsund and Kongsfjorden), the northern Sophia Basin and the Eurasian Basin of the Arctic Ocean, was analysed using nine DNA microsatellite loci. Genetic analyses indicated moderate to high genetic diversity, but absence of spatial population structure and isolation-by-distance, suggesting ongoing gene flow between the studied sampling regions. High levels of connectivity may be key for polar cod to maintain populations across wide spatial scales. The adaptive capacity of the species will be increasingly important to face challenges such as habitat fragmentation, ocean warming and changes in prey composition. In view of a limited understanding of the population dynamics and evolution of polar cod, a valuable next step to predict future developments should be an integrated biological evaluation, including population genomics, a life-history approach, and habitat and biophysical dispersal modelling. ispartof: JOURNAL OF FISH BIOLOGY vol:99 issue:1 pages:49-60 ispartof: location:England status: published

Freshwater snails act as intermediate hosts (IH) for schistosomiasis, a tropical disease affecting over 200 million people worldwide. Despite their medical importance, an extensive understanding of IH snail ecology remains absent. Especially data on the tolerance limits to different abiotic factors are fragmented and incomplete. Consequently, the construction of accurate species distribution models to identify snail habitats and guide targeted snail control efforts remains difficult. Here, we compiled a summary on the tolerance limits to abiotic factors of African IH snails of human schistosomiasis. A systematic search on Web of Science, PubMed, and Embase identified 45 relevant studies. Synthesis of these studies indicates that research efforts differ greatly between IH snail species, life stages, and abiotic factors. The importance of each abiotic factor in determining snail presence and abundance is discussed. Furthermore, attention was drawn to knowledge gaps and the lack of standardised experimental designs, which impedes comparisons between studies. This in turn prevents us from making firm conclusions and calls for best practices adopted by all malacologists. In doing so, IH snail ecological data could serve as a basis to assess schistosomiasis risk and guide snail control efforts in order to support schistosomiasis control. ispartof: Hydrobiologia vol:848 issue:8 pages:1773-1793 status: Published online

The advent of softwarized networks has enabled the deployment of chains of virtual network and service components on computational resources from the cloud up to the edge, creating a continuum of virtual resources. The next generation of low latency applications (e.g., Virtual Reality (VR), autonomous cars) adds even more stringent requirements to the infrastructure, calling for considerable advancements towards cloud-native micro-service-based architectures. This article presents a comprehensive survey on ongoing research aiming to effectively support low latency services throughout their execution lifetime in next-generation networks. The current state-of-the-art is critically reviewed to identify the most promising trends that will strongly impact the full applicability and high performance of low latency services. This article proposes a taxonomy as well as specific evaluation criteria to classify research across different domains addressing low latency service delivery. Current architectural paradigms such as Multi-access Edge Computing (MEC) and Fog Computing (FC) alongside novel trends on communication networks are discussed. Among these, the integration of Machine Learning (ML) and Artificial intelligence (AI) is introduced as a key research field in current literature towards autonomous network management. A discussion on open challenges and future research directions on low-latency service delivery leads to the conclusion, offering lessons learned and prospects on emerging use cases such as Extended Reality (XR), in which novel trends will play a major role.

ispartof: STORE- status: published

ispartof: STORE- status: published

ispartof: STORE- status: published

ispartof: STORE- status: published

ispartof: STORE- status: published