Accelerated repetitive transcranial magnetic stimulation (rTMS) protocols are being increasingly studied because of their potential to provide quicker and enhanced treatment efficacy. However, there ...is a lack of accelerated deep TMS with H1-coil (adTMS) treatment research. This randomized pilot study investigated the efficacy and safety of adTMS protocols. Twenty-eight TRD patients received 20-min sessions twice daily for 10 or 15 days. Primary outcomes were changes in Hamilton Depression Rating Scale (HDRS) scores and discontinuation because of adverse events (AE). Secondary outcomes were response, remission, daily changes in Beck Depression Inventory-II (BDI-II) scores, and AE incidence. HDRS scores decreased by 13 (95% CI 11–17; 59%, 95% CI 45–73%) and 13 (95% CI 11–14; 62%, 95% CI 54–69%) points in the 10- and 15-day protocols, respectively. The adjusted difference between the two protocols was not significant or clinically relevant. Remission was achieved by 38% and 42% after 10-day and 15-day protocols, respectively. The intervention was discontinued because of AEs in 3/33 (9%) patients. The BDI-II decreases were significant and clinically relevant during the first 8 days. Twice-daily adTMS for 10 days seems to be safe and effective, with rapid clinical benefits during the first week of treatment. These promising results warrant further investigation in larger randomized clinical trials comparing adTMS with the standard dTMS protocol.
The implementation of renewable energy sources and heat pumps with natural refrigerants in the existing 3rd-generation district heating (DH) systems is a promising technology for the conversion to a ...4th-generation DH system. This paper aims to investigate this transition through a case study for the existing DH system in Croatia. The district of Rijeka, which is considered in the case study, has an existing 3rd-generation DH system with a capacity of 9.2 MW, which was originally designed for a temperature regime of 130/70 °C and produces thermal energy from natural gas. In order to use heat pumps efficiently in such a system, the temperature of the distribution system and the energy consumption should be reduced. Trnsys software was used to perform complete dynamic simulations of the DH system. Used baseline models were validated according to the actual energy consumption reported by the heat supplier. The application of heat pumps with natural refrigerants in combination with on-site electricity production (PV system) can almost eliminate system CO2 emissions, reduce primary energy consumption and lower operation costs. Simulations were performed for 18 different scenarios that included 2 different building envelope variants. The results were compared, then discussed and conclusions were drawn.
The traveling salesman problem is one of the most well-known combinatorial optimization problems that has been studied for decades due to its importance in theory and practice. Traditional approaches ...to solving this problem include exact and heuristic algorithms, and recently, due to the significant development and excellent results of machine learning in various fields, more and more attention is paid to machine learning approaches. The main motivation for introducing machine learning into solving combinatorial optimization problems was that the development of classical hand-crafted heuristics requires theoretical and empirical expertise, which in the case of machine learning can be replaced by data. Also, the advantage of learned heuristics is that they can be trained on a set of instances of a specific problem that we want to solve in practice, which classical heuristics do not take into account because they are usually developed for the general case. In this paper, we give a detailed overview of machine learning approaches for solving the traveling salesman problem developed so far.
