Complex Communication Networks Research Articles

Industrial Internet of Things for Safety Management Applications: A Survey

Industrial Internet of Things (IIoT) aims to achieve higher operational and management efficiencies by bridging machinery, equipment, human resources, and all other actors involved in an industrial environment. This bridging enables data flow over an often complex and heterogeneous communication network. It enables timely decision-making, which affects various aspects of the organization such as business, operations, maintenance, safety, stock, and logistics. Despite the plethora of works in the domain of IIoT dealing with the above aspects, very few works deal with safety in industries. Industrial safety, especially whenever it is intertwined with the safety of humans, is a critical domain and holds much scope for improvement in the context of IIoT-based solutions for industrial safety management. Through this survey, we provide a comprehensive overview of the safety issues prevalent in the industries. Subsequently, we classify and provide an in-depth analysis of the safety aspects in various application areas of IIoT such as healthcare, transportation, manufacturing, and mining. Finally, we examine the research gaps in various domains and recommend future research directions. We discuss diverse forms of technologies, prototypes, systems, models, methods, and applications to ensure the safety of individuals and the risks associated with them. The primary aim of this work is to analyze and synthesize the existing researches and acknowledge the applicability of these research works towards safety management using IIoT.

Future OFDM-based Communication Systems Towards 6G and Beyond: Machine Learning Approaches

The vision towards 6G and beyond communication systems demands higher rate transmission, massive amount of data processing, and low latency communication. Orthogonal Frequency Division Modulation (OFDM) has been adopted in the current 5G networks and has become one of the potential candidates for the future communication systems. Although OFDM offers many benefits including high spectrum efficiency and high robustness against the multipath fading channels, it has major challenges such as frequency offset and high Peak to Power Ratio (PAPR). In 5G communication network, there is a significant increase in the number of sensors and other low-power devices where users or devices may create large amount of connection and dynamic data processing. In order to deal with the increasingly complex communication network, Machine Learning (ML) has been increasingly utilised to create intelligent and more efficient communication network. This paper discusses challenges and the impacts of embedding ML in OFDM-based communication systems.

Mitochondrial genome-wide analysis of nuclear DNA methylation quantitative trait loci.

Mitochondria have a complex communication network with the surrounding cell and can alter nuclear DNA methylation (DNAm). Variation in the mitochondrial DNA (mtDNA) has also been linked to differential DNAm. Genome-wide association studies have identified numerous DNAm quantitative trait loci, but these studies have not examined the mitochondrial genome. Herein, we quantified nuclear DNAm from blood and conducted a mitochondrial genome-wide association study of DNAm, with an additional emphasis on sex- and prediabetes-specific heterogeneity. We used the Young Finns Study (n = 926) with sequenced mtDNA genotypes as a discovery sample and sought replication in the Ludwigshafen Risk and Cardiovascular Health study (n = 2317). We identified numerous significant associations in the discovery phase (P < 10−9), but they were not replicated when accounting for multiple testing. In total, 27 associations were nominally replicated with a P < 0.05. The replication analysis presented no evidence of sex- or prediabetes-specific heterogeneity. The 27 associations were included in a joint meta-analysis of the two cohorts, and 19 DNAm sites associated with mtDNA variants, while four other sites showed haplogroup associations. An expression quantitative trait methylation analysis was performed for the identified DNAm sites, pinpointing two statistically significant associations. This study provides evidence of a mitochondrial genetic control of nuclear DNAm with little evidence found for sex- and prediabetes-specific effects. The lack of a comparable mtDNA data set for replication is a limitation in our study and further studies are needed to validate our results.

Dynamic event-triggered protocol-based distributed secondary control for islanded microgrids

This paper proposes a distributed secondary control scheme with dynamic event-triggered protocol for multiple distributed generators (DGs) in an islanded microgrid. First of all, a dynamic event-triggered (DET) protocol is introduced for each DG unit to orchestrate the information transmission, which aims to save communication resources in the microgrid. The proposed event-triggered condition involves an internal dynamic variable, which is employed to dynamically adjust the event-triggered threshold. Then, under the schedule of the DET protocol, the distributed secondary controllers of the DGs are designed on the basis of the available information. The proposed secondary control scheme is completely distributed, which means that each DG only needs the information from itself and its neighbors, which reduces the requirements for the central controller and complex communication networks, and improves the reliability of the system. Meanwhile, it is proved that there is no Zeno behavior in the closed-loop system and the lower bound of the interevent time is enlarged due to the introduction of the dynamic event-triggered protocol. Subsequently, the similar idea is employed to deal with the distributed secondary frequency and load sharing problems. Finally, an illustrative example is utilized to verify the effectiveness of the proposed control scheme by using the MATLAB/SimPowerSystems toolbox.

The maximum tree of a random forest in the configuration graph

Galton-Watson random forests with a given number of root trees and a known number of nonroot vertices are investigated. The distribution of the number of direct offspring of each particle in the forest- generating process is assumed to have infinite variance. Branching processes of this kind are used successfully to study configuration graphs aimed at simulating the structure and development dynamics of complex communication networks, in particular the internet. The known relationship between configuration graphs and random forests reflects the local tree structure of simulated networks. Limit theorems are proved for the maximum size of a tree in a random forest in all basic zones where the number of trees and the number of vertices tend to infinity. Bibliography: 14 titles.

Organ Crosstalk and the Modulation of Insulin Signaling.

A highly complex network of organ communication plays a key role in regulating metabolic homeostasis, specifically due to the modulation of the insulin signaling machinery. As a paradigm, the role of adipose tissue in organ crosstalk has been extensively investigated, but tissues such as muscles and the liver are equally important players in this scenario. Perturbation of organ crosstalk is a hallmark of insulin resistance, emphasizing the importance of crosstalk molecules in the modulation of insulin signaling, potentially leading to defects in insulin action. Classically secreted proteins are major crosstalk molecules and are able to affect insulin signaling in both directions. In this review, we aim to focus on some crosstalk mediators with an impact on the early steps of insulin signaling. In addition, we also summarize the current knowledge on the role of extracellular vesicles in relation to insulin signaling, a more recently discovered additional component of organ crosstalk. Finally, an attempt will be made to identify inter-connections between these two pathways of organ crosstalk and the potential impact on the insulin signaling network.

Modulation of Quorum Sensing and Biofilms in Less Investigated Gram-Negative ESKAPE Pathogens.

Pathogenic bacteria have the ability to sense their versatile environment and adapt by behavioral changes both to the external reservoirs and the infected host, which, in response to microbial colonization, mobilizes equally sophisticated anti-infectious strategies. One of the most important adaptive processes is the ability of pathogenic bacteria to turn from the free, floating, or planktonic state to the adherent one and to develop biofilms on alive and inert substrata; this social lifestyle, based on very complex communication networks, namely, the quorum sensing (QS) and response system, confers them an increased phenotypic or behavioral resistance to different stress factors, including host defense mechanisms and antibiotics. As a consequence, biofilm infections can be difficult to diagnose and treat, requiring complex multidrug therapeutic regimens, which often fail to resolve the infection. One of the most promising avenues for discovering novel and efficient antibiofilm strategies is targeting individual cells and their QS mechanisms. A huge amount of data related to the inhibition of QS and biofilm formation in pathogenic bacteria have been obtained using the well-established gram-positive Staphylococcus aureus and gram-negative Pseudomonas aeruginosa models. The purpose of this paper was to revise the progress on the development of antibiofilm and anti-QS strategies in the less investigated gram-negative ESKAPE pathogens Klebsiella pneumoniae, Acinetobacter baumannii, and Enterobacter sp. and identify promising leads for the therapeutic management of these clinically significant and highly resistant opportunistic pathogens.

Interleukin-33-Enhanced CXCR4 Signaling Circuit Mediated by Carcinoma-Associated Fibroblasts Promotes Invasiveness of Head and Neck Cancer.

Despite recent advances, treatment for head and neck squamous cell carcinoma (HNSCC) has limited efficacy in preventing tumor progression. We confirmed previously that carcinoma-associated fibroblasts (CAF)-induced interleukin-33 (IL-33) contributed to cancer progression. However, the molecular mechanisms underlying the complex communication network of the tumor microenvironment merited further evaluation. To simulate the IL-33-induced autocrine signaling, stable clones of IL-33-overexpressing HNSCC cells were established. Besides well-established IL-33/ST2 and SDF1/CXCR4 (stromal-derived factor 1/C-X-C motif chemokine receptor 4) signaling, the CAF-induced IL-33 upregulated CXCR4 via cancer cell induction of IL-33 self-production. The IL-33-enhanced-CXCR4 regulatory circuit involves SDF1/CXCR4 signaling activation and modulates tumor behavior. An in vivo study confirmed the functional role of IL-33/CXCR4 in tumor initiation and metastasis. The CXCR4 and/or IL-33 blockade reduced HNSCC cell aggressiveness, with attenuated invasions and metastases. Immunohistochemistry confirmed that IL-33 and CXCR4 expression correlated significantly with disease-free survival and IL-33-CXCR4 co-expression predicted a poor outcome. Besides paracrine signaling, the CAF-induced IL-33 reciprocally enhanced the autocrine cancer-cell self-production of IL-33 and the corresponding CXCR4 upregulation, leading to the activation of SDF1/CXCR4 signaling subsequent to cancer progression. Thus, targeting the IL-33-enhanced-CXCR4 regulatory circuit attenuates tumor aggressiveness and provides a potential therapeutic option for improving the prognosis in HNSCC patients.

Intrasexual Vibrational Behavior of Philaenus spumarius in Semi-Field Conditions.

Simple SummaryVibrational communication is widespread in insects. Since most studies of intrasexual behavior on insects have targeted few individuals, the behaviors occurring within groups have been left unexplored. Including multiple individuals in behavioral studies on vibrational communication would provide more reliable information about their intrasexual behavior. In semi-field conditions, the intrasexual behavior of the meadow spittlebug, Philaenus spumarius, was studied. Using a laser vibrometer, we recorded vibrational signals exchanged among individuals of the same sex, throughout their adult stage and during the day, from the morning to the evening. The results showed that males were less active than females and the interactions among males were less frequent than among females. Intrasexual interactions were characterized by signal overlapping in both unisex groups, in addition to signal alternating only in the case of males. This study provided a better understanding of the social behavior of P. spumarius based on vibrational signals.Insects that communicate by vibrational signals live in a complex interactive network of communication. Most studies on insect intrasexual behavior, based on plant-borne vibrational signals, have targeted few individuals. Despite their importance, behaviors that occur within groups were often overlooked. The study of multiple individuals, when insects occur in high density could simulate the environment in which they live and provide more reliable information on their behavior. In semi-field conditions, we investigated the intrasexual behavior of the meadow spittlebug, Philaenus spumarius. Vibrational signals exchanged among individuals of the same sex were recorded throughout their adult stage, from late spring to early autumn, and during the day, from the morning to the evening using a laser vibrometer. Males were less active than females throughout the season and their interactions were less frequent compared to females. Intrasexual interactions were characterized by signal overlapping in both unisex groups, in addition to signal alternating only in the case of males. In conclusion, the study of signaling behavior in intrasexual groups contributed to a better understanding of P. spumarius social behavior. We discuss the hypothesis of a possible competitive behavior between males and cooperative behavior between females.

Successive High-Resolution (H2O)n-GCIB and C60-SIMS Imaging Integrates Multi-Omics in Different Cell Types in Breast Cancer Tissue.

The temporo-spatial organization of different cells in the tumor microenvironment (TME) is the key to understanding their complex communication networks and the immune landscape that exists within compromised tissues. Multi-omics profiling of single-interacting cells in the native TME is critical for providing further information regarding the reprograming mechanisms leading to immunosuppression and tumor progression. This requires new technologies for biomolecular profiling of phenotypically heterogeneous cells on the same tissue sample. Here, we developed a new methodology for comprehensive lipidomic and metabolomic profiling of individual cells on frozen-hydrated tissue sections using water gas cluster ion beam secondary ion mass spectrometry ((H2O)n-GCIB-SIMS) (at 1.6 μm beam spot size), followed by profiling cell-type specific lanthanide antibodies on the same tissue section using C60-SIMS (at 1.1 μm beam spot size). We revealed distinct variations of distribution and intensities of >150 key ions (e.g., lipids and important metabolites) in different types of the TME individual cells, such as actively proliferating tumor cells as well as infiltrating immune cells. The demonstrated feasibility of SIMS imaging to integrate the multi-omics profiling in the same tissue section at the single-cell level will lead to new insights into the role of lipid reprogramming and metabolic response in normal regulation or pathogenic discoordination of cell–cell interactions in a variety of tissue microenvironments.

Caregiver Perceptions of Mental Health and Barriers to and Facilitators of Their Child's Treatment.

Nearly 1 million children visit emergency departments (EDs) annually for mental health crises. Caregivers play a critical role in the outcome of mental illness in their children, yet there is limited research on effective means to engage caregivers in the ED and provide the support they need. Our aim was to determine caregivers' perceptions about mental illness in their children, specifically regarding suicidality and depression, the impact of the children's mental health on the caregiver, and barriers to and facilitators of treatment. Guided by qualitative descriptive methodology, we conducted semistructured, open-ended interviews with a purposive sample of English-speaking primary caregivers of children 6 to 17 years old who presented with suicidal ideations or behaviors to 1 urban pediatric ED. Interviews were recorded and transcribed verbatim, and conventional content analysis was performed. The participants (n = 20) were largely single ethnic-racial minority mothers. Content analysis identified 6 categories: caregivers' definitions of mental health, depression, and suicidality; perceived causes of mental illness; difficulty in identification of mental illness; the influence of the mental illness on caregivers; a complex network of communication among involved parties that resulted in the child's ED visit, as well as barriers to and facilitators of treatment. We identified several categories that encapsulate caregivers' perceptions of mental health and mental illness in their children and its effect on them. Future research should explore how inner-city EDs might partner with schools and trusted community-based organizations to enhance caregiver knowledge, reduce obstacles to care, increase screening for at-risk youth and implement strategies to optimize outcomes for children with depression and suicidal ideations.

The Notch Signaling Pathway and Breast Cancer: The Importance of Balance and Cellular Self-Control

Background:Notch is a cell signaling pathway that is highly conserved in all metazoans and is the master responsible for cell differentiation and cross communication with other signaling pathways such as Wingless and Hedgehog. In most cancers, the Notch signaling pathway is altered, causing normal controls of vital processes such as cell cycle, differentiation and apoptosis to be compromised, leading the cell to a carcinogenic state. However, the inherent nature of the Notch signaling pathway of regulating the activation or repression of other signaling pathways related to differentiation and cell cycle has caused the strategies against breast cancer to be even more specialized and to know more efficiently the suitable method againts the disease.Methods:Different bibliographies and articles related to the Notch pathway and the biology of cancer were reviewed, especially with breast cancer, as well as the participation of other signaling pathways directly and indirectly related to the constitutive activation of the Notch pathway and relating the threads loose to create a general conceptual map of the wide effects of the malfunction of the Notch pathway in this disease so that we can understand from another point of view how this flow of information can be controlled.Results:The study of Notch signaling during more than a decade has gave us new clues to elucidate the mechanisms of their finely orchestrated molecular functioning and how this signaling path interacts with another signaling pathways in differentiation, survival, cell cycle and apoptosis. Notch Signaling is a professional in the process of differentiation and cross-talk communication with another signaling pathways, especially with the WNT and Hh pathways. The responsibility of WNT pathway is to maintain the survival and growth controls, having direct effects on the cell cycle and the Hh pathway is to maintain a state of diferentiation trought the life of the cell and the cell migration instead, cell cycle and the response to growth stimuli of angiogenesis, exacerbated characteristics of many breast cancer.Conclusion:This review highlights the complex communication network between the WNT, Hh and Notch Signaling and the therapies in the field of cancer that are not entirely effective, however, most of the therapies that are currently being developed are including the Notch Signaling as a target quite promising and is for its regulatory effect with other signaling pathways.

Discovery of Cell Aggregate-Inducing Peptides

Most cells within the human body interact with neighboring cells and extracellular matrix (ECM) components to establish a unique 3D organization. These cell–cell and cell–ECM interactions form a complex communication network of biochemical and mechanical signals critical for normal cell physiology. The behavior of cells in a 3D environment is fundamentally different from that of cells in monolayer culture. Aggregation can affect cell–cell interactions, being more representative of the normal tissue microenvironment. Therefore, 3D cell culture technologies have been developed. The general method for cell aggregate is a physical method; it is difficult to control the size and number of cell aggregates. In any case, no chemical method has been discovered yet, so a new method to solve these problems is needed. In this paper, we describe the induction of a cell aggregate of the newly discovered (Lys-Pro)12(KP24) peptide. Since it was revealed that KP24 had cell aggregate-inducing activity, its derivatives were molecularly designed to clarify the importance of the KP24 sequence. We report that cell aggregations were induced by KP24 to form aggregates of fibroblast cells. We evaluated KP24 derivative periodic peptides such as (Lys-Pro-Pro)8(KPP24) and (Lys-Lys-Pro)8(KKP24). The relationship between the structure of the peptide chain and the activity induced by the cell aggregations was investigated from the viewpoint of basic research and the biomedical engineering field.

NO Network for Plant-Microbe Communication Underground: A Review.

Mechanisms governing plant–microbe interaction in the rhizosphere attracted a lot of investigative attention in the last decade. The rhizosphere is not simply a source of nutrients and support for the plants; it is rather an ecosystem teeming with diverse flora and fauna including different groups of microbes that are useful as well as harmful for the plants. Plant–microbe interaction occurs via a highly complex communication network that involves sophisticated machinery for the recognition of friend and foe at both sides. On the other hand, nitric oxide (NO) is a key, signaling molecule involved in plant development and defense. Studies on legume–rhizobia symbiosis suggest the involvement of NO during recognition, root hair curling, development of infection threads, nodule development, and nodule senescence. A similar role of NO is also suggested in the case of plant interaction with the mycorrhizal fungi. Another, insight into the plant–microbe interaction in the rhizosphere comes from the recognition of pathogen-associated molecular patterns (PAMPs)/microbe-associated molecular patterns (MAMPs) by the host plant and thereby NO-mediated activation of the defense signaling cascade. Thus, NO plays a major role in mediating the communication between plants and microbes in the rhizosphere. Interestingly, reports suggesting the role of silicon in increasing the number of nodules, enhancing nitrogen fixation, and also the combined effect of silicon and NO may indicate a possibility of their interaction in mediating microbial communication underground. However, the exact role of NO in mediating plant–microbe interaction remains elusive. Therefore, understanding the role of NO in underground plant physiology is very important, especially in relation to the plant’s interaction with the rhizospheric microbiome. This will help devise new strategies for protection against phytopathogens and enhancing plant productivity by promoting symbiotic interaction. This review focuses on the role of NO in plant–microbe communication underground.

CNN and MLP neural network ensembles for packet classification and adversary defense

Machine learning techniques such as artificial neural networks are seeing increased use in the examination of communication network research questions. Central to many of these research questions is the need to classify packets and improve visibility. Multi-Layer Perceptron (MLP) neural networks and Convolutional Neural Networks(CNNs) have been used to successfully identify individual packets. However, some datasets create instability in neural network models. Machine learning can also be subject to data injection and misclassification problems. In addition, when attempting to address complex communication network challenges, extremely high classification accuracy is required. Neural network ensembles can work towards minimizing or even eliminating some of these problems by comparing results from multiple models. After ensembles tuning, training time can be reduced, and a viable and effective architecture can be obtained. Because of their effectiveness, ensembles can be utilized to defend against data poisoning attacks attempting to create classification errors. In this work, ensemble tuning and several voting strategies are explored that consistently result in classification accuracy above 99%. In addition, ensembles are shown to be effective against these types of attack by maintaining accuracy above 98%.

High-purity pulsed squeezing generation with integrated photonics

Squeezed light has evolved into a powerful tool for quantum technology, ranging from quantum enhanced sensing and quantum state engineering based on partial post-selection techniques. The pulsed generation of squeezed light is of particular interest, as it can provide accurate time stamp and physically defined temporal mode, which are highly preferred in complex communication networks and large-scale information processing. However, the multimode feature of pulsed squeezing in conventional single-pass configuration limits the purity of the output state, negatively impacting its application in quantum technology. In this Letter, we propose a new approach to generate pulsed squeezing with high temporal purity. Pulsed squeezing based on parametric down-conversion in photonic cavities is analyzed. We show that the effective mode number of the output squeezed light approaches unity. Such a high-purity squeezed light can be realized with broad parameters and low pump power, providing a robust approach to generate large-scale quantum resource.

Формирование коммуникативной компетентности старшеклассников в системе дополнительного образования

We describe communicative competence as one of the key competencies of modern high school students, which is a resource for effective future professional realization. The research revealed the content of communicative competence, which is determined by more complex com-munication processes and network interactions. The stages, components and conditions for the development of communicative competence are identified, the levels of development are determined, psychological and pedagogical techniques and technologies for the development of communicative competence are proposed, and a supplementary general educational and developmental program of a socio-pedagogical direction “School of Successful Communication” is developed. The results of the research can be used to organize the development of communicative competence in the system of supplementary education. The main feature of the program is its variability and possibility of realization in both full-time and distance format.

Reconstruction of Intercellular Signaling Network by Cytokine-Receptor Interactions.

Background: The immune system function depends on the coordination activity of the components of system and communications between them which leads to the formation of a complex communication network between immune cells. In this network, cytokines have an important role in the communication between immune cells through the interaction to their specific receptors. These molecules cause to cellular communications and normal function of a tissue. Reconstruction of such a complex network can be a way to provide a better understanding of cytokines’ function.Objective: Our main goal from reconstructing such a network was investigation of expressed cytokines and cytokines receptors in various lineage and tissues of immune cells and identifying the lineage and tissue with the highest expression of cytokines and their receptors.Materials and Methods: In this study, gene expression data related to part of the Immunological Genome Project (ImmGen) and receptor-ligand interactions dataset were used to reconstruct the immune network in mouse. In next step, the topological properties of reconstructed network, expression specificity of cytokines and their receptors and interactions specificity were analyzed.Results: The results of the network analysis were indicated that non- hematopoietic stromal cells have the highest expression of cytokines and cytokine receptors and interactions specificity is very high. Our results show that chemokine receptor of Ccr1 receives the largest number of signals between receptors and only expressed in three hematopoietic lineages.Conclusions: The most of the network communications belonged to non-hematopoietic stromal and macrophage cells. The relationships between stromal cells and macrophages are necessary to create an appropriate environment for differentiation of immune cells. Studying the cellular expression specificity of receptor and ligand genes reveal the high degree of specificity of these genes that indicate non-random transfer of information between cells in multicellular organisms.

Applications of Machine Learning in Networking: A Survey of Current Issues and Future Challenges

Communication networks are expanding rapidly and becoming increasingly complex. As a consequence, the conventional rule-based algorithms or protocols may no longer perform at their best efficiencies in these networks. Machine learning (ML) has recently been applied to solve complex problems in many fields, including finance, health care, and business. ML algorithms can offer computational models that can solve complex communication network problems and consequently improve performance. This paper reviews the recent trends in the application of ML models in communication networks for prediction, intrusion detection, route and path assignment, Quality of Service improvement, and resource management. A review of the recent literature reveals extensive opportunities for researchers to exploit the advantages of ML in solving complex performance issues in a network, especially with the advancement of software-defined networks and 5G.

Multilingual Genre Practices in International Relations

Globalisation has produced not only denser, but also linguistically more complex communication networks. Multilingual practices have transformed the academic and professional lives of language learners, and imposed new requirements on LSP teaching. This article foregrounds genres in multilingual globalised contexts. Genres have been recognised as one of the key focuses of LSP. Although previous research highlighted the importance of developing relevant field-specific genre practices, little attention has been paid to the nature of genre repertoires in the field of International Relations (IR). We report on the findings of a qualitative study into genre practices of the IR community. We set out to examine the typical genres of IR in academic and in professional settings. We focus on the languages in which these genres are enacted, and on the transformation of genre practices that occurs as a result of the community members’ trajectories through different academic and professional or institutional contexts. The analysis of genre collections and of the data collected through semi-structured interviews with IR students, professors, and graduates, reveals the rich, diverse, and asymmetrical patterns of genre use in three languages: French, Slovene, and English. The study suggests that the informants’ disciplinary communication has changed considerably over the past twenty years, and that the changes in the genre ecologies require new approaches to teaching about genres. Based on the findings of the study, the paper discusses the challenges of multilingual realities for LSP teachers and genre analysts.&#x0D;