166 research outputs found
Asynchronous Distributed Averaging on Communication Networks
Distributed algorithms for averaging have attracted interest in the control and sensing literature. However, previous works have not addressed some practical concerns that will arise in actual implementations on packet-switched communication networks such as the Internet. In this paper, we present several implementable algorithms that are robust to asynchronism and dynamic topology changes. The algorithms are completely distributed and do not require any global coordination. In addition, they can be proven to converge under very general asynchronous timing assumptions. Our results are verified by both simulation and experiments on Planetlab, a real-world TCP/IP network. We also present some extensions that are likely to be useful in applications
Optimization flow control with estimation error
We analyze the effects of price estimation error in a dual-gradient optimization flow control scheme, and characterize the performance of the algorithm in this case. By treating estimation error as inexactness of the gradient, we utilize sufficient conditions for convergence subject to bounded error to characterize the long-term dynamics of the link utilization in terms of a region, which the trajectory enters in finite time. We explicitly find bounds for this region under a particular quantization error model, and provide simulation results to verify the predicted behavior of the system. Finally, we analyze the effects of the stepsize on the convergence of the algorithm, and provide analytical and numerical results, which suggest a particular choice for this parameter
Evaluating of Short-Term Electrical Load Forecasting System Using Fuzzy Logic Control: A Study Case in Sudan
Generation, Transmission and Distribution sections of the electric power grid system are a function of electric load forecasting. This is because, many benefits can be obtained by using load forecasting, such as reduction in the generating cost and increasing the reliability of the power system due to improving energy management. The objective of this study is therefore to design a fuzzy logic system for short-term electric load forecasting to reduce power losses particularly in times where the electric power generation is higher than the electric load demand. In this study, the independent variables that were applied to the developed short-term load forecasting Simulink model were time, temperature, and similar previous electric day load demand, and they were collected from the specific area load control center in Sudan. Fuzzy rules were prepared using Mamdani implication. The obtained fuzzy logic results were compared with the actual load demand, and it was found that there was an error that ranged between 12% and 0.09%
Exploiting gelatin nanocarriers in the pulmonary delivery of methotrexate for lung cancer therapy.
Gelatin has many merits that encourage its use in the pulmonary delivery of anticancer drugs. It is a biodegradable denatured protein which possesses several functional groups that could be modified. Additionally, it has balanced hydrophilic and hydrophobic characters, which facilitate the loading of chemotherapeutic agents. Accordingly, the purpose of the current work was to exploit this valuable biomaterial in the efficient pulmonary delivery of methotrexate in case of lung cancer. Gelatin nanoparticles were prepared via a desolvation method and the fabrication process was optimized using Box Behnken design of experiment. A comparative study on uptake of gelatin nanoparticles by lung adenocarcinoma cells and macrophages was implemented using flow cytometry. Investigation of the effect of different methotrexate loading techniques: encapsulation, post loading and chemical conjugation on the nanoparticles characteristics and cellular cytotoxicity was performed. Nano-in-microparticles were prepared by co-spray drying optimized nanoparticles with leucine. Results showed that Box Behnken design was able to optimize preparation parameters to yield uniform nanoparticles with suitable particle size for cancer cells uptake. The prepared nanoparticles demonstrated a preferential uptake by lung cancer cells. Additionally, methotrexate loaded nanoparticles demonstrated up to four fold significant reduction in methotrexate IC50. The spray dried gelatin nano-in microparticles demonstrated good aerosolization properties enabling lung deposition in the respirable airways. Thus, providing a promising platform for lung cancer therapy
The Mechanism Analysis of Underactuated Robotic Finger for Optimum Grasping Using Gradient Descent Method
This study was devoted in investigating the optimum geometric parameters for underactuated linkage three phalanges robotic finger. New kinematic and kinetic equations of grasping were derived in this research taking into account the angle for the ternary solid links of the four-bar linkages. To obtain the target of optimization, a gradient descent method was used which consists of three stages to find the optimal geometric parameters with high accuracy. Five criteria were selected to find the optimal solution by using multi objectives function algorithm, these are percentage of the grasping stability, the grasp forces, squeezing force, Mimic function for grasping task, and transmission angle for grasping operation. Gradient descent method starts by detecting the optimal geometric parameters for each criterion and choosing the best geometric parameters from the five criteria functions. At the optimum solution, the underactuated robotic finger prototype was built from hard Polylactic acid (PLA) plastic using rapid prototyping and was tested performance by grasping objects. Finally, the results have been shown that the robotic finger adapts to the wanted configurations
Promoting and supporting children's health and healthcare during COVID-19-International Paediatric Association Position Statement
Egyptian consensus on treat-to-target approach for osteoporosis: a clinical practice guideline from the Egyptian Academy of bone health and metabolic bone diseases
Background: This study was carried out to achieve an Egyptian expert consensus on a treat-to-target managementstrategy for osteoporosis using Delphi technique. A scientific committee identified researchers and clinicians with expertise in osteoporosis in Egypt. Delphi process was implemented (2 rounds) to establish a consensus on 15
clinical standards: (1) concept, (2) diagnosis, (3) case identification, (4) whom to treat, (5) who should treat?, (6) case stratification and intervention thresholds, (7) falls risk, (8) investigations, (9) treatment target, (10) management, (11) optimum treatment duration, (12) monitoring, (13) drug holiday, (14) osteoporosis in men, and (15) post-fracture care and fracture liaison service.
Results: The surveys were sent to an expert panel (n = 25), of whom 24 participated in the two rounds. Respondents were drawn from different governorates and health centres across Egypt including the Ministry of Health. Most of the participants were rheumatologists (76%), followed by internists (8%), orthopaedic doctors (4%), rehabilitation doctors (4%), primary care (4%), and ortho-geriatrics (4%) physicians. Seventy-two recommendations, categorised into 15 sections, were obtained. Agreement with the recommendations (rank 7–9) ranged from 83.4 to 100%. Consensus was reached (i.e. ≥ 75% of respondents strongly agreed or agreed) on the wording of all 15 clinical standards identified by the scientific committee. An algorithm for the management of postmenopausal osteoporosis has been suggested.
Conclusion: A wide and representative panel of experts established a consensus regarding the management of
osteoporosis in Egypt. The developed guidelines provide a comprehensive approach to the assessment and management of osteoporosis for all Egyptian healthcare professionals who are involved in its management
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