The Effects of Nitrate Supplementation on Performance as a Function of Habitual Dietary Intake of Nitrates: A Randomized Controlled Trial of Elite Football Players.

Nitrates are an effective ergogenic supplement; however, the effects of nitrate supplements based on habitual dietary nitrate intake through diet alone are not well understood. We aimed to assess this in a group of 15 highly trained football players from Slovenian football's First Division. Participants underwent two separate Cooper performance tests either with nitrate supplementation (400 mg nitrates) or placebo while having their nutrition assessed for nitrate intake, as well as energy and macronutrient intake. Nitrate supplementation had a statistically significant positive effect on performance if baseline dietary nitrate intake was below 300 mg (p = 0.0104) in both the placebo and intervention groups. No effects of nitrate supplementation when baseline dietary nitrate intake was higher than 300 mg in the placebo group could be concluded due to the small sample size. Nitrate supplementation did not have a significant effect on perceived exertion. The daily nitrate intake of the participants was measured at 165 mg, with the majority of nitrates coming from nitrate-rich vegetables.

Optimization of a plastic optical fiber based sensor for dye sensing coupled with an adapted neuro-fuzzy inference system.

In this study, estimation capacities and optimization of a dye concentration sensing model by an adapted neuro-fuzzy inference system (ANFIS) as well as central composite design coupled with response surface methodology using a plastic optical fiber (POF) based sensor were investigated. Various diameters d of POF were used for sensing different concentrations of Remazol Black B (RBB), which acts as a sensing medium of the process. The efficiency of sensing was studied as a function of three independent variables: diameter of POF, concentration of RBB dye, and initial temperature of the solution. First, the independent parameters were fed as inputs to an ANFIS, and the output of the system was the output intensity of dye ratio to output the intensity of distilled water. ANFIS showed that this established model is reliable for a dye concentration sensing process and is mainly influenced by its diameter.

Dietary Intake, Body Composition and Performance of Professional Football Athletes in Slovenia.

This is the first study to examine the nutritional status of professional Slovenian football players. This study aimed to analyze the dietary intake of elite football players during their preparation phase of the season and to investigate whether there is a relationship between energy and macronutrient intake with body composition and physical performance. Twenty-three footballers completed a three-day dietary and physical activity diary and underwent body composition measurements via bioelectrical impedance vector analysis (BIVA). Fifteen participants also took part in the Cooper treadmill test to assess their physical performance in correlation with their nutritional intake. Football players had an energy intake that was significantly too low for their needs, reflecting low energy availability. The average carbohydrate (CHO) intake was below the Union of European Football Associations (UEFA) recommendations, i.e., <4 g CHO/kg body weight (BW). Additionally, players had adequate intakes of protein and fat, and inadequate intakes of saturated fat, fiber, calcium and vitamin D. There was a positive correlation between protein intake and lean body mass. Additionally, a negative correlation was observed between body fat mass and carbohydrate intake as well as between performance with the percentage of energy intake from fat. Results of this study highlight what aspects of nutrition might be improved upon in professional football players to maximize performance, longevity and body composition of athletes, as well as the necessity of a nutritionist role in this process.

A neural networks-based hybrid routing protocol for wireless mesh networks.

The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic-i.e., neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance.