Abstract-This paper presents an overview of a Wireless Sensor and Actuator Network (WSAN) used to monitor an electrical power grid distribution infrastructure. The WSAN employs appropriate sensors to monitor key grid components, integrating both safety and security services, which improve the grid distribution dependability. The supported applications include, among others, video surveillance of remote secondary substations, which imposes special requirements from the point of view of quality of service and reliability. The paper presents the hardware and software architecture of the system together with performance results.

Platinum metal complexes are the most common chemotherapeutics currently used in cancer treatment. However, the frequent adverse effects, as well as acquired resistance by tumor cells, urge the development of effective alternatives. In the recent past, copper complexes with Schiff base ligands have emerged as good alternatives, showing interesting results. Accordingly, and in continuation of previous studies in this area, three new camphoric acid‐derived halogenated salen ligands and their corresponding Cu (II) complexes were synthesized and their antitumor activity was evaluated in order to determine the influence of the type and number of halogens present (Br, Cl). The in vitro cytotoxic activity was screened against colorectal WiDr and LS1034 and against breast MCF‐7 and HCC1806 cancer cell lines. The results proved the halogenated complexes to be very efficient, the tetrachlorinated Cu (II) complex being the most promising, presenting IC50 of 0.63–1.09 μM for the cell lines studied. The complex also shows selectivity to colorectal cancer cells compared to non‐tumor colon cells. It is worth highlighting that the tetrachlorinated Cu (II) complex, our most efficient complex, shows a significantly more powerful antitumor effect than the reference drugs currently used in conventional chemotherapy. The halogenated salen and corresponding complexes were also screened for their antimicrobial activity against four bacterial species‐Staphylococcus aureus, Enterococcus faecalis, Escherichia coli and Pseudomonas aeruginosa‐and four fungal species‐Candida albicans, Candida glabrata, Aspergillus fumigatus and Alternaria alternata. The compounds were found to exhibit moderate to strong antibacterial activity against the bacterial strains studied. NMR studies and theoretical calculations provided some insight into the structure of the ligands and copper complexes. Considering the results presented herein, our work validates the potential use of copper‐based chemotherapeutics as alternatives for cancer treatment.

This paper presents a methodology to provide a decision maker, e.g. the distribution system operator, information on the associated impacts of the operation of distributed electric energy storage systems (ESS 1) in an urban environment, in order to support the choice of the best locations of storage units. The developed methodology uses three types of profile prototypes based on actual data, obtained through clustering techniques. These profiles, which include electricity demand, electricity prices and renewable electricity production, are used to optimize the placement of electric energy storage units. The paper considers expected attitudes of the main stakeholders towards distributed electric ESS implementation, and discusses possible regulatory framework options to define the distributed electric ESS business model. The model was applied to a case study using the nanophosphate lithium-ion battery technology as an example. Results show a significant influence of the charge/discharge profile of batteries on the choice of their best locations.

a b s t r a c tThe objective of this work is to obtain characteristic daily profiles of consumption, wind generation and electricity spot prices, needed to develop assessments of two different options commonly regarded under the smart grid paradigm: residential demand response, and small scale distributed electric energy storage. The approach consists of applying clustering algorithms to historical data, namely using a hierarchical method and a self-organizing neural network, in order to obtain clusters of diagrams representing characteristic daily diagrams of load, wind generation or electricity price. These diagrams are useful not only to analyze different scenarios of combined existence, but also to understand their individual relative importance. This study enabled also the identification of a probable range of variation around an average profile, by defining boundary profiles with the maximum and minimum values of any cluster prototypes.