Abstract
Quarmic is a web framework for rapid prototyping of web applications. Its main goal is to facilitate the development of web applications by providing a high level of abstraction that hides Web communication complexities. This framework allows developers to build scalable applications capable of handling data communication in different models, data persistence and authentication, requiring them just to use simple annotations. Quarmic’s approach consists of the replication of the shared object among clients and server in order to communicate through its methods execution. Where the annotations, namely decorators, are used to indicate the concern (model or view) that each method addresses and to implement the framework’s inversion of control. By indicating the method concern, it enables the separation of its execution across the clients (responsible for the view) and the server (responsible for the model) which facilitates the state management and code maintenance.

Abstract
The analysis of heart sounds is a challenging task, due to the quick temporal onset between successive events and the fact that an important fraction of the information carried by phonocardiogram (PCG) signals lies in the inaudible part of the human spectrum. For these reasons, computer-aided analysis of the PCG can dramatically improve the quantity of information recovered from such signals. In this paper, a hidden semi-Markov model (HSMM) is used to automatically segment PCG signals. In the proposed models, the emission probability distributions are approximated via Gaussian mixture model (GMM) priors. The choice of GMM emission probability distributions allow to apply re-estimation routines to automatically adjust the HSMM emission probability distributions to each subject. Building on the proposed method for fine tuning emission distributions, a novel subject-driven unsupervised heart sound segmentation algorithm is proposed and validated over the publicly available PhysioNet dataset. Perhaps surprisingly, the proposed unsupervised method achieved results in line with state-of-the-art supervised approaches, when applied to long heart sounds.

Abstract
Switched reluctance machines (SRM) are simple, robust and fault tolerant machines, usually operating under strong nonlinear characteristics. Most SRM models address magnetic saturation, but hysteresis effect is usually disregarded. This paper is based on a developed four-quadrant SRM drive simulation model, where magnetization characteristics are generated through the original Jiles-Atherton (J-A) hysteresis model. The main goal is to investigate the hysteresis impact on the SRM drive controller performance. Steady-state operation scenarios are simulated and compared. For the adopted current control strategy (PWM), the results show a significant impact in all drive components, particularly for low speed with high load operation.

Abstract
The volatile organic compounds benzene, toluene, ethylbenzene, and xylene (BTEX) are emitted into the atmosphere at gas stations (GS) leading to chronic exposure of nearby residents, which raises public health concerns. This study aimes at determining the contribution of GS emissions to BTEX exposure in nearby residents. Three Control and Exposed areas to BTEX emissions from GS were defined in a medium-sized European city (Porto, Portugal). BTEX atmospheric levels were determined in Control and Exposed areas using passive samplers deployed outdoors (n = 48) and indoors (n = 36), and human exposure was estimated for 119 non-smoking residents using the first urine of the day. Results showed that median BTEX outdoor and indoor concentrations were significantly higher for Exposed than Control areas, with exception of ethylbenzene and xylene indoor concentrations, where no marked differences were found. Comparison of urinary concentrations between Exposed and Control residents demonstrated no significant differences for benzene and ethylbenzene, whereas levels of toluene and xylene were significantly higher in Exposed residents. No marked correlation was obtained between atmospheric BTEX concentrations and urinary concentrations. Data indicate the potential impact on air quality of BTEX emissions from GS, which confirms the importance of these findings in urban planning in order to minimize the impact on health and well-being of surrounding populations.

Abstract
The integration of micro-generation (µG) in distribution networks faces new challenges concerning the technical as well as commercial management. The µG integration in the Low and medium voltage distribution networks has many advantages for the grid operation, such as voltage profiles improvement, power losses reduction, and branches congestion levels reduction. This paper presents a method for guiding continuation power flow simulation of integrating µG on distribution feeders. A base model is designed with variable capacitor bank, µG unit such as PV and Wind generation are integrated. A control method is used to improve the voltage level of each node as well as improving power factor of the systems. The electricity consumption of a university's substation area where commercial, residential and municipal load are presented are modeled using actual data collected from each single residential hall and commercial buildings. This model allows analyzing the power flow and voltage profile along each distribution feeders on continuing fashion for a 24- hour period at hour-by-hour formulation. By dividing the feeder into load zones based on distance from each load node to distribution feeder head, the impact of integration of different µG operation in different condition has been discussed. © 2019 IEEE.

Abstract
Industrial and commercial electricity customers have significant potential in providing flexibility for power systems through diverse demand response (DR) programs. However, the industrial and commercial potential of DR is not yet completely understood, especially regarding the emerging and advanced technologies associated with the smart grid. Advances in smart meter technology that allow monitoring and controlling responsive loads in real time will also be key enablers of DR potential. It can be more complex to implement DR for industrial loads if compared to residential loads mainly due to the reliability management that is more vital for industrial plants. Hence, this paper aims at providing a comprehensive review of the most recent advances on industrial and commercial DR. On this basis, this survey first presents the potential and technologies of DR in industrial and commercial sectors. Then, the existing models of DR in the mentioned sectors are presented. The presence of industrial and commercial DR in electricity markets is also investigated. Finally, the main positive and beneficial aspects, as well as challenges and barriers of industrial and commercial DR, are investigated.