Massive localized lymphedema in the morbidly obese: a histologically distinct reactive lesion simulating liposarcoma

We report 14 cases of a soft tissue lesion in the limbs of morbidly obese adults that presents as a large mass and histologically simulates well-differentiated liposarcoma (WDL). Based on its distinctive clinical setting and morphologic identity to diffuse lymphedema we have termed this process massive localized lymphedema (MLL). All cases occurred in morbidly obese adults (mean weight 372 lbs; mean age 47 years). Women predominated (9 women; 5 men). The lesions affected the proximal medial aspect of the extremities (12 thigh; 2 arm) and were unilateral in all but two patients. Etiologically significant antecedent events include ipsilateral axillary lymphadenectomy in both patients with arm lesions, chronic lymphedema resulting from vein-stripping 10 years prior in one patient. inguinal lymphadenectomy for anal carcinoma in another patient, and significant blunt trauma to the inner thigh during a motor vehicle accident in a third patient. The tumors were long standing ( I-IO years) and extremely large (mean size 33.4 cm, 7408 g). Clinically, they were diffuse, ill-defined masses that histologically consisted of lobules of mature fat interrupted by expanded connective tissue septa. The constituents of the septa were fine, fibrillary collagen, edema fluid, and uniformly distributed fibroblasts. Clusters of capillaries were frequently found at the interface between fat and connective tissue. The widened septa simulated the fibrous bands of sclerosing WDL, but MLL lacks the degree of nuclear atypia seen in the former. The consistent clustering of reactive vessels at the interface between the fat and fibrous tissue also contrasted with WDL. Six patients experienced persistent or recurrent lesions within 10 months to 10 years. No aggressive growth or histologic progression was observed during this time, however. Awareness of the features of MLL is important to avoid misclassification of this reactive lesion with WDL.     

Effect of Polyethylene Molecular Architecture on the Dynamic Viscoelastic Behavior of Polyethylene/Polyhexene-1 Blends and Its Correlation with Morphology

In the present work, the rheology, morphology, and interfacial interaction of polyethylene/polyhexane-1 (PE/PH-1) blends with various polyethylene types with different molecular architectures are investigated. The scanning electron microscopy (SEM) images showed a droplet-matrix morphology in all percentage of PH-1 for all blend systems and the size of droplets increased proportionally with PH-1 content. The minimum droplet size is observed for high-density polyethylene (HDPE)/PH-1 blends. The homogeneity of the blends at various compositions is assessed by using viscoelastic parameters determined by dynamic oscillation rheometry in the linear viscoelastic region. A distinct Newtonian plateau at low frequencies is perceived and the variations of complex viscosity (η*) versus angular frequency (ω) for all blend systems are in good agreement with Carreau-Yasuda model. The complex viscosity of samples at various percentages of PH-1 showed the negative deviation from mixing rule in low and high frequencies for all blend systems. The Cole-Cole plots deviated from semi-circular shape at higher percentages of PH-1 than 10wt% in the blends of low-density polyethylene (LDPE)/PH-1 and linear low-density polyethylene (LLDPE)/PH-1. By using emulsion theoretical model, the lowest interfacial tension is found for HDPE/PH-1 blends comparing with its counterparts based on LDPE and LLDPE and the best fitting with experimental data was observed for this blends system.     

A patient network-based machine learning model for disease prediction: The case of type 2 diabetes mellitus

Applied Intelligence - In recent years, the prevalence of chronic diseases such as type 2 diabetes mellitus (T2DM) has increased, bringing a heavy burden to healthcare systems. While regular...     

Thermal buckling analysis of temperature-dependent FG-CNTRC quadrilateral plates

The main objective of the present study is to analyze the thermal buckling of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) quadrilateral plates. Functionally graded patterns are introduced for the distribution of the carbon nanotubes (CNTs) through the thickness direction of the plate. The effective material properties of nanocomposite plate reinforced by CNTs are considered to be temperature-dependent (TD) and estimated using the micromechanical model. By the use of minimum total potential energy principle and based on the first-order shear deformation theory of plates, the stability equations are obtained. In order to use the generalized differential quadrature (GDQ) method and solve the stability equations, the irregular domain of quadrilateral plate is transformed into regular computational domain employing the mapping technique. The efficiency and accuracy of the proposed approach are first validated. Then, a comprehensive parametric study is presented to examine the effects of model parameters on the thermal buckling of FG-CNTRC quadrilateral plates. The results indicate that considering temperature dependency of the material properties plays an important role in the stability of the FG-CNTRC quadrilateral plates subjected to thermal loading.     

An anisotropic damage model for tensile fatigue

Fatigue damage in materials is considered to be the effect of material degradation, and the dispersion in fatigue life is attributed to variability in microstructure. This paper presents a numerical model to simulate fatigue damage evolution using continuum damage mechanics to characterize material degradation. An explicit microstructure topology representation is achieved using Voronoi tessellations. Unlike conventional models which use a scalar approximation for damage, this model treats the damage variable as an anisotropic tensor. The model is used to simulate tensile fatigue failure in thin steel specimen. The fatigue life estimations from the model compares well with published experimental results. The results predict a high variability in fatigue life that is characteristic of metals and alloys, as compared with the existing isotropic damage models available in the literature. The model was also used to study the influence of material inhomogeneity on fatigue life dispersion.     

Dynamic buckling of functionally graded multilayer graphene nanocomposite annular plate under different boundary conditions in thermal environment

This paper deals with dynamic stability of functionally graded (FG) nanocomposite annular plate reinforced with graphene platelets (GPLs) subjected to a periodic radial compressive load in thermal environment. On the basis of modified Halpin–Tsai micromechanics model, the effective elastic modulus of structure is estimated. Taking into consideration of the first-order shear deformation theory, the governing motion equations are obtained via the Hamilton’s principle. Afterward, the partial differential motion equations are discretized into a system of Mathieu–Hill equations by utilizing generalized differential quadrature method. Furthermore, the Bolotin’s technique is applied to determine the principle unstable zone of functionally graded graphene platelet reinforced composite (FG-GPLRC) annular plate. The accuracy and validity of current study are examined by comparing the fundamental natural frequencies of structure with those published in available literature. Eventually, to investigate the influences of number of layers, GPLs patterns and their geometric, boundary conditions, geometrical parameters of structure, static load factor, and temperature change on the DIRs of FG-GPLRC multilayer annular plate, different parametric studies are performed.

     

A dynamic task scheduling framework based on chicken swarm and improved raven roosting optimization methods in cloud computing

Scheduling means devoting tasks among computational resources, considering specific goals. Cloud computing is facing a dynamic and rapidly evolving situation. Devoting tasks to the computational resources could be done in numerous different ways. As a consequence, scheduling of tasks in cloud computing is considered as a NP-hard problem. Meta-heuristic algorithms are a proper choice for improving scheduling in cloud computing, but they should, of course, be consistent with the dynamic situation in the field of cloud computing. One of the newest bio-inspired meta-heuristic algorithms is the chicken swarm optimization (CSO) algorithm. This algorithm is inspired by the hierarchical behavior of chickens in a swarm for finding food. The diverse movements of the chickens create a balance between the local and the global search for finding the optimal solution. Raven roosting optimization (RRO) algorithm is inspired by the social behavior of raven and the information flow between the members of the population with the goal of finding food. The advantage of this algorithm lies in using the individual perception mechanism in the process of searching the problem space. In the current work, an ICDSF scheduling framework is proposed. It is a hybrid (IRRO-CSO) meta-heuristic approach based on the improved raven roosting optimization algorithm (IRRO) and the CSO algorithm. The CSO algorithm is used for its efficiency in satisfying the balance between the local and the global search, and IRRO algorithm is chosen for solving the problem of premature convergence and its better performance in bigger search spaces. First, the performance of the proposed hybrid IRRO-CSO algorithm is compared with other imitation-based swarm intelligence methods using benchmark functions (CEC 2017). Then, the capabilities of the proposed scheduling hybrid algorithm (IRRO-CSO) are tested using the NASA-iPSC parallel workload and are compared with the other available algorithms. The obtained results from the implementation of the hybrid IRRO-CSO algorithm in MATLAB show an improvement in the average best fitness compared with the following algorithms: IRRO, RRO, CSO, BAT and PSO. Finally, simulation tests performed in cloud computing environment show improvements in terms of reduction of execution time, reduction of response time and the increase in throughput by using the proposed hybrid IRRO-CSO approach for dynamic scheduling.     

Improving Daily and Monthly River Discharge Forecasts using Geostatistical Ensemble Modeling

Water Resources Management - In this paper, daily and monthly runoff discharge forecasts are improved by developing an ensemble model based on the Bayesian maximum entropy (BME), which integrates...