Coarse-graining the dynamics of network evolution: the rise and fall of a networked society

We explore a systematic approach to studying the dynamics of evolving networks at a coarse-grained, system level. We emphasize the importance of finding good observables (network properties) in terms of which coarse grained models can be developed. We illustrate our approach through a particular social network model: the "rise and fall" of a networked society [1]: we implement our low-dimensional description computationally using the equation-free approach and show how it can be used to (a) accelerate simulations and (b) extract system-level stability/bifurcation information from the detailed dynamic model. We discuss other system-level tasks that can be enabled through such a computer-assisted coarse graining approach.Comment: 18 pages, 11 figure

Evaluation of Micromovements and Stresses around Single Wide-Diameter and Double Implants for Replacing Mandibular Molar: A Three-Dimensional FEA

Purpose. The purpose of this finite element study was to compare stresses, strains, and displacements of double versus single implant, in immediate loading for replacing mandibular molar. Materials and Methods. Two 3D FEM models were made to simulate implant designs. The first model used 6 mm wide-diameter implant to support a single molar crown. The second model used 3.75-3.75 double implant design. Each model was analyzed with a single force magnitude of 70 N in oblique axis in three locations. Results. This FEM study suggested that micromotion can be well controlled by both double implants and 6 mm single wide-diameter implant. The Von Mises stress for double implant had 31%–43% stress reduction compared to the 6 mm implant. Conclusion. Within the limitations of the paper, when the mesiodistal space for artificial tooth is more than 12.5 mm, under immediate loading, the double implant support should be considered

Evaluation of design parameters of eight dental implant designs: A two‑dimensional finite element analysis

Aim: Implants could be considered predictable tools for replacing missing teeth or teeth that are irrational to treat. Implant macrodesign includes thread, body shape and thread design. Implant threads should be designed to maximize the delivery of optimal favorable stresses. The aim of this finite element model study was to determine stresses and strains in bone by using various dental implant thread designs.Materials and Methods: A two‑dimensional finite element model of an implant–bone system is developed by using Ansys. An oblique load of 100 N 45° to the vertical axis of implant as well as a vertical load was considered in the analyses. The study evaluated eight types of different thread designs to evaluate stresses and strains around the implants placed in D1 bone quality.Results: Forty‑five‑degree oblique von Mises stresses and strains were the highest for the filleted and rounded square thread with an angulation of 30° (216.70 MPa and 0.0165, respectively) and the lowest for the trapezoidal thread (144.39 MPa and 0.0015, respectively).Conclusions: The findings in this study suggest that the filleted and rounded square thread with an angulation of 30° showed highest stresses and strains at the implant–bone interface. The trapezoidal thread transmitted least amount of stresses and strains to the cortical bone than did other models

Prevalence of plantar ulcer and its risk factors in leprosy:a systematic review and meta-analysis

Background: Plantar ulcers are a leading complication of leprosy that requires frequent visits to hospital and is associated with stigma. The extent of burden of ulcers in leprosy and its risk factors are scant impeding the development of targeted interventions to prevent and promote healing of ulcers. The aim of this review is to generate evidence on the prevalence of plantar ulcer and its risk factors in leprosy. Methods: Databases (Medline, Embase, Web of Science, CINAHL, BVS), conference abstracts and reference lists were searched for eligible studies. Studies were included that reported a point prevalence of plantar ulcer and/or its “risk factors” associated with development of ulcers (either causatively or predictively), including individual level, disease related and bio-mechanical factors. We followed PRISMA guidelines for this review. Random-effects meta-analysis was undertaken to estimate the pooled point prevalence of ulcers. Reported risk factors in included studies were narratively synthesised. This review is registered in PROSPERO: CRD42022316726. Results: Overall, 15 studies (8 for prevalence of ulcer and 7 for risk factors) met the inclusion criteria. The pooled point prevalence of ulcer was 34% (95% CIs: 21%, 46%) and 7% (95% CIs: 4%, 11%) among those with foot anaesthesia and among all people affected by leprosy, respectively. Risk factors for developing ulcers included: unable to feel 10 g of monofilament on sensory testing, pronated/hyper-pronated foot, foot with peak plantar pressure, foot with severe deformities, and those with lower education and the unemployed. Conclusions: The prevalence of plantar ulceration in leprosy is as high as 34% among those with loss of sensation in the feet. However, the incidence and recurrence rates of ulceration are least reported. The inability to feel 10 g of monofilament appears to be a strong predictor of those at risk of developing ulcers. However, there is a paucity of evidence on identifying those at risk of developing plantar ulcers in leprosy. Prospective studies are needed to estimate the incidence of ulcers. Identifying individuals at risk of ulcers will help design targeted interventions to minimize risk factors, prevent ulcers and promote ulcer healing

Analytical Evaluation of the MoM Matrix Elements

Cataloged from PDF version of article.Derivation of the closed-form Green’s functions has eliminated the computationally expensive evaluation of the Sommerfeld integrals to obtain the Green’s functions in the spatial domain. Therefore, using the closed-form Green’s functions in conjunction with the method of moments (MOM) has improved the computational efficiency of the technique significantly. Further improvement can he achieved on the calculation of the matrix elements involved in the MOM, usually double integrals for planar geometries, by eliminating the numerical integration. The contribution of this paper is to present the analytical evaluation of the matrix elements when the closed-form Green’s functions are used, and to demonstrate the amount of improvement in computation time

COVID -19 Predictions using Transfer Learning based Deep Learning Model with Medical Internet of Things

Early detection of COVID-19 may help medical expert for proper treatment plan and infection control. Internet of Things (IoT) has vital improvement in many areas including medical field. Deep learning also provide tremendous improvement in the field of medical. We have proposed a Transfer learning based deep learning model with medical Internet of Things for predicting COVID-19 from X-ray images. In the proposed method, the X ray images of patient are stored in cloud storage using internet for wide access. Then, the images are retrieved from cloud and Transfer learning based deep learning models namely VGG-16, Inception, Alexnet, Googlenet and Convolution neural Network models are applied on the X-rays images for predicting COVID 19, Normal and pneumonia classes. The pre-trained models helps to the effectiveness of deep learning accuracy and reduced the training time. The experimental analysis show that VGG -16 model gives accuracy of 99% for detecting COVID19 than other models

The unusual dynamics of parasite actin result from isodesmic polymerization

Previous reports have indicated that parasite actins are short and inherently unstable, despite being required for motility. Here, we re-examine the polymerization properties of actin in Toxoplasma gondii (TgACTI), unexpectedly finding that it exhibits isodesmic polymerization in contrast to the conventional nucleation-elongation process of all previously studied actins from both eukaryotes and bacteria. TgACTI polymerization kinetics lacks both a lag phase and critical concentration, normally characteristic of actins. Unique among actins, the kinetics of assembly can be fit with a single set of rate constants for all subunit interactions, without need for separate nucleation and elongation rates. This isodesmic model accurately predicts the assembly, disassembly, and the size distribution of TgACTI filaments in vitro, providing a mechanistic explanation for actin dynamics in vivo. Our findings expand the repertoire of mechanisms by which actin polymerization is governed and offer clues about the evolution of self-assembling, stabilized protein polymers