Prevalence of cardiovascular risk factors in the urban population of Soussa in Tunisia

BACKGROUND: With the epidemiological transition phenomenon, Tunisia is now facing the growing prevalence of chronic diseases. Environmental and behavioural changes such as the adoption of new dietary habits and a sedentary lifestyle, and the stress of urbanization and of working conditions all lead to the rise in cardiovascular disease (CVD) risk factors. METHODS: The aim of this study is to estimate the prevalence of the main CVD risk factors in an urban context. For this, we have undertaken a household epidemiological survey of a representative sample of the adult urban population of Soussa, Tunisia (n = 957). RESULTS: This study shows high prevalences of hypertension (blood pressure >160/95 mmHg) of 18.8 per cent with an adjusted rate of 15.6 per cent, history of diabetes of 10.2 per cent, and obesity (body mass index > 30) of 27.7 per cent [significantly higher in women (34.4 per cent)], android obesity 36 per cent, smoking habits 21.5 per cent [significantly higher in men (61.4 per cent)]. CONCLUSION: With this profile of CVD risk factors, Tunisia must implement a national strategy of primary prevention and heart health promotion in addition to the efforts recently made in secondary prevention of some chronic diseases such as hypertension and diabetes.     

Fracture mechanics global approach concepts applied to creep slow crack growth in a medium density polyethylene (MDPE)

Creep fracture by slow crack growth is studied in a medium density polyethylene at 60 °C and 80 °C. Whereas elastic-plastic fracture mechanics load parameters fail to provide a unique temperature-independent correlation, that of the fracture mechanics for creeping solids C^∗ is proved to be relevant since this parameter correlates very well with the time to failure. Correlation established on both full notched creep tensile and double edge notched tensile tests was validated on cracked gas-pipe samples tested under hydrostatic pressure, extending the use of time to failure versus C^∗ diagram to predict lifetime of engineering components.     

Catalyst surface at a fractal of cost—a quest for optimal catalyst loading

Intuition tells us that any decrease in the catalytically active surface area should result in an equivalent decrease in the reaction yield and efficiency. Our findings counter this by showing that the active surface and hence the catalyst loading can be reduced drastically in the diffusion-limited heterogeneous reaction systems, while the conversion rate remains essentially unchanged by using fractals for spatial distribution of the catalyst load. The results of this study provide an unusual circumstance for optimal design of chemically active surfaces and can be used to drastically reduce cost of heterogeneous chemical and biological reactors, sensors, and electrodes of fuel cells. The proposed approach can be exploited to its fullest extent in chemical microsystems by utilizing the latest advances in our abilities to manipulate matter on the micro/nano scale.     

Schedule-Based Cooperative Multi-agent Reinforcement Learning for Multi-channel Communication in Wireless Sensor Networks

Wireless sensor networks (WSNs) have become an important component in the Internet of things (IoT) field. In WSNs, multi-channel protocols have been developed to overcome some limitations related to the throughput and delivery rate which have become necessary for many IoT applications that require sufficient bandwidth to transmit a large amount of data. However, the requirement of frequent negotiation for channel assignment in distributed multi-channel protocols incurs an extra-large communication overhead which results in a reduction of the network lifetime. To deal with this requirement in an energy-efficient way is a challenging task. Hence, the Reinforcement Learning (RL) approach for channel assignment is used to overcome this problem. Nevertheless, the use of the RL approach requires a number of iterations to obtain the best solution which in turn creates a communication overhead and time-wasting. In this paper, a Self-schedule based Cooperative multi-agent Reinforcement Learning for Channel Assignment (SCRL CA) approach is proposed to improve the network lifetime and performance. The proposal addresses both regular traffic scheduling and assignment of the available orthogonal channels in an energy-efficient way. We solve the cooperation between the RL agents problem by using the self-schedule method to accelerate the RL iterations, reduce the communication overhead and balance the energy consumption in the route selection process. Therefore, two algorithms are proposed, the first one is for the Static channel assignment (SSCRL CA) while the second one is for the Dynamic channel assignment (DSCRL CA). The results of extensive simulation experiments show the effectiveness of our approach in improving the network lifetime and performance through the two algorithms.

     

Photothermoelectric (PTE) Versus Photopyroelectric (PPE) Detection of Phase Transitions

The photopyroelectric (PPE) technique is one of the photothermal (PT) methods mostly used for phase transitions investigations. In this paper, we want to compare the PPE results with those obtained using another, recently developed PT method [the photothermoelectric (PTE) calorimetry] for the same purpose of detecting phase transitions. The well-known ferro-paraelectric phase transition of TGS, taking place at a convenient temperature (about \(49\, {}^{\circ }\hbox {C}\)), has been selected for demonstration. A comparison of the two PPE and PTE methods, both in the back detection configuration (in the special case of optically opaque sample and thermally thick regime for both sensors and sample) shows that they are equally suitable for phase transitions detection. Performing a proper calibration, the amplitude and phase of the signals can be used in order to obtain the critical behaviour of all sample’s static and dynamic thermal parameters.     

On the accurate determination of thermal diffusivity of liquids by using the photopyroelectric thickness scanning method

An enhanced accurate method of measuring the thermal diffusivity of liquids by the sample's thickness scan of the phase of the photopyroelectric signal is presented. The method, making use of the absolute values of the phase and sample thickness, leads to very accurate results for the room temperature values of thermal diffusivity (about +/-0.3%). The high accuracy of the method is due to a very precise control of the sample's thickness variation (0.1 microm step), to a proper localization of the thickness scan range, and to a new procedure of data analysis. The high accuracy of the method recommends it for the study of processes associated with small changes of the thermal parameters.     

Predictive control of Timed Event Graphs with specifications defined by P-time Event Graphs

The aim of this paper is the predictive control of Timed Event Graphs with specifications defined by P-time Event Graphs. We propose a fixed-point approach which leads to a pseudo-polynomial algorithm. As the performance of the algorithm is crucial in on-line control, we highlight an important case where the resolution of this first algorithm is efficient. The second technique is a space controller on a horizon leading to a strongly polynomial algorithm.