Abstract
Background: In peripheral arterial disease (PAD) patients with intermittent claudication (IC), the combination of aerobic and resistance exercises could counteract muscle loss and attenuate disease progression. This study analyzed the effects of six months of a combined exercise program on walking ability, lower limb body composition, cardiovascular risk factors, and Ankle-Brachial Index (ABI). Methods: Twenty-three patients (age 63.2 +/- 1.5 years and ABI 0.58 +/- 0.07) with PAD and IC were allocated to a control group (CG) or a supervised exercise group (SUP). Ten patients underwent six months of treadmill walking combined with resistance exercises, three times a week. The CG (N.=13) received a recommendation for walking. All patients were measured at baseline (M0), after three months (M3), and six months (M6). Results: During constant treadmill protocol, the claudication onset time/distance (COT/COD), absolute claudication time/distance (ACT/ACD), and number of pauses of overall patients significantly improved at M3 and M6. Between groups were found significant differences in COT and COD at M6 (P=0.005 and P=0.007, respectively); and in ACT and ACD at M3 (P=0.003 for both) and at M6 (P=0.005 and P=0.005, respectively), with major improvements in the SUP. Over the six months, a significant group effect was found in fat-free mass (P=0.041) and predicted muscle mass (P=0.039) of the lower ABI leg, with greater improvements in the SUP. Conclusions: A supervised exercise program that combines aerobic and resistance training improves PAD symptoms and has additional benefits for patients. Patients in the program showed improvements in walking ability, lower-limb body composition, perceived exertion, and heart rate during treadmill walking.

Abstract
Malnutrition is widespread among older adults, and its determinants may differ between countries. We compared Portuguese and Turkish non-institutionalized older adults regarding nutritional status, sociodemographic, health and anthropometric characteristics and studied the relationships between nutritional status and those characteristics. This cross-sectional study analyzed data from 430 Portuguese and 162 Turkish non-institutionalized older adults regarding sociodemographics, health conditions, the Mini-Nutritional Assessment (MNA-FF) and anthropometry. Turkish older adults were more likely to be malnourished or at risk of malnutrition and had lower average BMI but a higher calf circumference. A higher proportion of the Portuguese sample had tooth loss, diabetes, hypertension, oncologic diseases, kidney diseases, osteoarticular problems or eye problems, while less had anemia. A better nutritional status (higher MNA-FF score) was found among the Portuguese, males, people using dentures, those without tooth loss, hypertension, cardiovascular diseases, anemia or oncological diseases and was related to younger age, higher BMI and a higher calf circumference. Malnutrition and its risk were higher among older adults from Turkey, despite Portuguese older adults presenting a higher prevalence of chronic diseases. Being female, older age, tooth loss, hypertension, anemia, CVD or oncological disorders and having a lower BMI or CC were associated with higher rates of malnutrition among older adults from Portugal and Turkey.

Abstract
Answering a query through a peer-to-peer database presents one of the greatest challenges due to the high cost and time required to obtain a comprehensive response. Consequently, these systems were primarily designed to handle approximation queries. In our research, the primary objective was to develop an intelligent system capable of responding to approximate set-value inquiries. This paper explores the use of particle optimization to enhance the system's intelligence. In contrast to previous studies, our proposed method avoids the use of sampling. Despite the utilization of the best sampling methods, there remains a possibility of error, making it difficult to guarantee accuracy. Nonetheless, achieving a certain degree of accuracy is crucial in handling approximate queries. Various factors influence the accuracy of sampling procedures. The results of our studies indicate that the suggested method has demonstrated improvements in terms of the number of queries issued, the number of peers examined, and its execution time, which is significantly faster than the flood approach. Answering queries poses one of the most arduous challenges in peer-to-peer databases, as obtaining a complete answer is both costly and time-consuming. Consequently, approximation queries have been adopted as a solution in these systems. Our research evaluated several methods, including flood algorithms, parallel diffusion algorithms, and ISM algorithms. When it comes to query transmission, the proposed method exhibits superior cost-effectiveness and execution times.

Abstract
Software-Defined Networking (SDN) is one of the promising and effective approaches to establishing network virtualization by providing a central controller to monitor network bandwidth and transmission devices. This paper studies resource allocation in SDN by mapping virtual networks on the infrastructure network. Considering mapping as a way to distribute tasks through the network, proper mapping methodologies will directly influence the efficiency of infrastructure resource management. Our proposed method is called Effective Initial Mapping in SDN (EIMSDN), and it suggests writing a module in the controller to initialize mapping by arriving at a new request if a sufficient number of resources are available. This would prevent rewriting the rules on the switches when remapping is necessary for an n-time window. We have also considered optimizing resource allocation in network virtualization with dynamic infrastructure resources management. We have done it by writing a module in OpenFlow controller to initialize mapping when there are sufficient resources. EIMSDN is compared with SDN-nR, SSPSM, and SDN-VN in criteria such as acceptance rates, cost, average switches resource utilization, and average link resource utilization.

Abstract

Abstract
This paper presents a new strategy for recharging electric vehicles in residential buildings. The proposed approach minimizes the difference between desired and final state of charge (SOC) by the end of the charging period, by adjusting the charging power for each vehicle in real-time. A non-linear optimization problem is formulated, considering the initial and final SOC, as well as available charging time, and total available power. Results were compared to a baseline and show that the proposed solution outperforms the currently most used nonoptimized method, particularly in high demand scenarios, where we achieve values of 9.3% of curtailed range when compared with the non-optimized methodology.