Development of c-means Clustering Based Adaptive Fuzzy Controller for A Flapping Wing Micro Air Vehicle

Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous Unmanned Aerial Vehicles (UAVs). In this work, a four wing Natureinspired (NI) FW MAV is modeled and controlled inspiring by its advanced features like quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability when contrasted with comparable-sized fixed and rotary wing UAVs. The Fuzzy C-Means (FCM) clustering algorithm is utilized to demonstrate the NIFW MAV model, which has points of interest over first principle based modelling since it does not depend on the system dynamics, rather based on data and can incorporate various uncertainties like sensor error. The same clustering strategy is used to develop an adaptive fuzzy controller. The controller is then utilized to control the altitude of the NIFW MAV, that can adapt with environmental disturbances by tuning the antecedent and consequent parameters of the fuzzy system.Comment: this paper is currently under review in Journal of Artificial Intelligence and Soft Computing Researc

PAC: A Novel Self-Adaptive Neuro-Fuzzy Controller for Micro Aerial Vehicles

There exists an increasing demand for a flexible and computationally efficient controller for micro aerial vehicles (MAVs) due to a high degree of environmental perturbations. In this work, an evolving neuro-fuzzy controller, namely Parsimonious Controller (PAC) is proposed. It features fewer network parameters than conventional approaches due to the absence of rule premise parameters. PAC is built upon a recently developed evolving neuro-fuzzy system known as parsimonious learning machine (PALM) and adopts new rule growing and pruning modules derived from the approximation of bias and variance. These rule adaptation methods have no reliance on user-defined thresholds, thereby increasing the PAC's autonomy for real-time deployment. PAC adapts the consequent parameters with the sliding mode control (SMC) theory in the single-pass fashion. The boundedness and convergence of the closed-loop control system's tracking error and the controller's consequent parameters are confirmed by utilizing the LaSalle-Yoshizawa theorem. Lastly, the controller's efficacy is evaluated by observing various trajectory tracking performance from a bio-inspired flapping-wing micro aerial vehicle (BI-FWMAV) and a rotary wing micro aerial vehicle called hexacopter. Furthermore, it is compared to three distinctive controllers. Our PAC outperforms the linear PID controller and feed-forward neural network (FFNN) based nonlinear adaptive controller. Compared to its predecessor, G-controller, the tracking accuracy is comparable, but the PAC incurs significantly fewer parameters to attain similar or better performance than the G-controller.Comment: This paper has been accepted for publication in Information Science Journal 201

Oral Microbiome and Gingival Gene Expression of Inflammatory Biomolecules with Aging and Periodontitis

Although data describe the presence and increase of inflammatory mediators in the local environment in periodontitis vs. health in humans, details regarding how these responses evolve in the transition from health to disease, changes during disease progression, and features of a resolved lesion remain unknown. This study used a nonhuman primate model of ligature-induced periodontitis in young, adolescent, adult, and aged animals to document features of inflammatory response affected by age. Rhesus monkeys had ligatures tied and provided gingival tissue biopsy specimens at baseline, 0.5, 1, and 3 months of disease and at 5 months of the study, which was 2 months post-ligature removal for clinically resolved tissues. The transcriptome was assessed using microarrays for chemokine (n = 41), cytokine (n = 45), chemokine receptor (n = 21), cytokine receptor (n = 37), and lipid mediator (n = 31) genes. Limited differences were noted in healthy tissues for chemokine expression with age; however, chemokine receptor genes were decreased in young but elevated in aged samples. IL1A, IL36A, and IL36G cytokines were decreased in the younger groups, with IL36A elevated in aged animals. IL10RA/IL10RB cytokine receptors were altered with age. Striking variation in the lipid mediator genes in health was observed with nearly 60% of these genes altered with age. A specific repertoire of chemokine and chemokine receptor genes was affected by the disease process, predominated by changes during disease initiation. Cytokine/cytokine receptor genes were also elevated with disease initiation, albeit IL36B, IL36G, and IL36RN were all significantly decreased throughout disease and resolution. Significant changes were observed in similar lipid mediator genes with disease and resolution across the age groups. Examination of the microbiome links to the inflammatory genes demonstrated that specific microbes, including Fusobacterium, P. gingivalis, F. alocis, Pasteurellaceae, and Prevotella are most frequently significantly correlated. These correlations were generally positive in older animals and negative in younger specimens. Gene expression and microbiome patterns from baseline were distinctly different from disease and resolution. These results demonstrate patterns of inflammatory gene expression throughout the phases of the induction of a periodontal disease lesion. The patterns show a very different relationship to specific members of the oral microbiome in younger compared with older animals

Gingival Transcriptome of Innate Antimicrobial Factors and the Oral Microbiome with Aging and Periodontitis

The epithelial barrier at mucosal sites comprises an important mechanical protective feature of innate immunity, and is intimately involved in communicating signals of infection/tissue damage to inflammatory and immune cells in these local environments. A wide array of antimicrobial factors (AMF) exist at mucosal sites and in secretions that contribute to this innate immunity. A non-human primate model of ligature-induced periodontitis was used to explore characteristics of the antimicrobial factor transcriptome (n = 114 genes) of gingival biopsies in health, initiation and progression of periodontal lesions, and in samples with clinical resolution. Age effects and relationship of AMF to the dominant members of the oral microbiome were also evaluated. AMF could be stratified into 4 groups with high (n = 22), intermediate (n = 29), low (n = 18) and very low (n = 45) expression in healthy adult tissues. A subset of AMF were altered in healthy young, adolescent and aged samples compared with adults (e.g., APP, CCL28, DEFB113, DEFB126, FLG2, PRH1) and were affected across multiple age groups. With disease, a greater number of the AMF genes were affected in the adult and aged samples with skewing toward decreased expression, for example WDC12, PGLYRP3, FLG2, DEFB128, and DEF4A/B, with multiple age groups. Few of the AMF genes showed a \u3e2-fold increase with disease in any age group. Selected AMF exhibited significant positive correlations across the array of AMF that varied in health and disease. In contrast, a rather limited number of the AMF significantly correlated with members of the microbiome; most prominent in healthy samples. These correlated microbes were different in younger and older samples and differed in health, disease and resolution samples. The findings supported effects of age on the expression of AMF genes in healthy gingival tissues showing a relationship to members of the oral microbiome. Furthermore, a dynamic expression of AMF genes was related to the disease process and showed similarities across the age groups, except for low/very low expressed genes that were unaffected in young samples. Targeted assessment of AMF members from this large array may provide insight into differences in disease risk and biomolecules that provide some discernment of early transition to disease

Gingival transcriptomic patterns of macrophage polarization during initiation, progression, and resolution of periodontitis.

Phenotypic and functional heterogeneity of macrophages is clearly a critical component of their effective functions in innate and adaptive immunity. This investigation hypothesized that altered profiles of gene expression in gingival tissues in health, disease, and resolution would reflect changes in macrophage phenotypes occurring in these tissues. The study used a nonhuman primate model to evaluate gene expression profiles as footprints of macrophage variation using a longitudinal experimental model of ligature-induced periodontitis in animals from 3 to 23 years of age to identify aging effects on the gingival environment. Significant differences were observed in distribution of expressed gene levels for M0, M1, and M2 macrophages in healthy tissues with the younger animals showing the least expression. M0 gene expression increased with disease in all but the aged group, while M1 was increased in adult and young animals, and M2 in all age groups, as early as disease initiation (within 0.5 months). Numerous histocompatibility genes were increased with disease, except in the aged samples. An array of cytokines/chemokines representing both M1 and M2 cells were increased with disease showing substantial increases with disease initiation (e.g. IL1A, CXCL8, CCL19, CCL2, CCL18), although the aged tissues showed a more limited magnitude of change across these macrophage genes. The analytics of macrophage genes at sites of gingival health, disease, and resolution demonstrated distinct profiles of host response interactions that may help model the disease mechanisms occurring with the formation of a periodontal lesion

Comparative Analysis of Microbial Sensing Molecules in Mucosal Tissues with Aging

Host-bacterial interactions at mucosal surfaces require recognition of the bacteria by host cells enabling targeted responses to maintain tissue homeostasis. It is now well recognized that an array of host-derived pattern recognition receptors (PRRs), both cell-bound and soluble, are critical to innate immune engagement of microbes via microbial-associated molecular patterns (MAMP). This report describes the use of a nonhuman primate model to evaluate changes in the expression of these sensing molecules related to aging in healthy gingival tissues. Macaca mulatta aged 3-24 years were evaluated clinically and gingival tissues obtained, RNA isolated and microarray analysis conducted for gene expression of the sensing pattern recognition receptors (PRRs). The results demonstrated increased expression of various PRRs in healthy aging gingiva including extracellular (CD14, CD209, CLEC4E, TLR4), intracellular (NAIP, IFIH1, DAI) and soluble (PTX4, SAA1) PRRs. Selected PRRs were also correlated with both bleeding on probing (BOP) and pocket depth (PD) in the animals. These findings suggest that aged animals express altered levels of various PRRs that could affect the ability of the tissues to interact effectively with the juxtaposed microbial ecology, presumably contributing to an enhanced risk of periodontitis even in clinically healthy oral mucosal tissues with aging