Level monitoring system for waste oil containers: an EPS@ISEP project

Waste oil recycling companies play a very important role in our society. Competition among companies is tough and process optimization is essential for survival. By equipping oil containers with a level monitoring system that periodically reports the level and alerts when it reaches the preset threshold, the oil recycling companies are able to streamline the oil collection process and, thus, reduce the operation costs while maintaining the quality of service. This paper describes the development of this level monitoring system by a team of four students from different engineering backgrounds and nationalities. The team conducted a study of the state of the art, draw marketing and sustainable development plans and, finally, designed and implemented a prototype that continuously measures the container content level and sends an alert message as soon as it reaches the preset capacity

Software-Defined NB-IoT Uplink Framework—The Design, Implementation and Use Cases

In the radiocommunication area, we may observe a rapid growth of new technology, such as 5G. Moreover, all the newly introduced radio interfaces, e.g., narrowband Internet of Things (NB-IoT), are strongly dependent on the software. Hence, the radiocommunication software development and optimization, as well as the 3GPP technical specification, should be introduced at the academic level of education. In this paper, a software-defined NB-IoT uplink framework in the field of design is presented, as well as its realization and potential use cases. The framework may be used as an academic tool for developing, investigating, and optimizing the digital transmitter paths. The proposed realization is focused on the key elements in the physical layer of the NB-IoT interface used in the sensor devices. Furthermore, the paper also highlights the need of the data processing optimization to minimize the power consumption and usage of the resources of the NB-IoT node during transmitting gathered telemetric data

Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning

Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides a significant gain (almost 40%) with 10.7% compared to the linear model with the lowest RMSE (Root Mean Squared Error) 17.01%. The solution can be adopted as a part of the data allocation algorithm implemented in the telemetry devices equipped with the 4G radio interface, or, after the adjustment, the NB-IoT (Narrowband Internet of Things), to maximize the reliability of the services in harsh indoor or urban environments. Presented results also prove the existence of the inverse proportional dependence between the number of hidden layers and the number of historical samples in terms of the obtained RMSE. The increase of the historical data memory allows using models with fewer hidden layers while maintaining a comparable RMSE value for each scenario, which reduces the total computational cost

Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks

In this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on the basis of the measurement data for dynamic scenarios in an indoor environment. The obtained results clearly prove the validity of the proposed DL approach in the UWB WBANs and high (over 98.6% for most cases) efficiency for LOS and NLOS conditions classification

Minimum Technical Requirements for Performing Ambulatory EEG

Ambulatory EEG (AEEG) devices offer portable, multichannel, digital EEG recording with or without video in the patient\u27s natural environment. The technology applied for AEEG recording is like the technology for routine EEG and inpatient long-term video-EEG monitoring but designed to be compact and wearable. Computer-based AEEG technology is well-suited to digital recording, signal processing, and visual display. However, acquiring interpretable EEG outside of the hospital setting presents its own technical challenges. Published guidelines have established technical standards for performing routine EEG and inpatient video-EEG monitoring, but technical standards for AEEG are lacking. Therefore, this guideline provides minimal technical standards for the performance of AEEG which are essential to ensure the quality of studies for clinical and research practice. We expect these minimum standards to evolve over time with improved performance and advances in the technology

Identification of MYOM2 as a candidate gene in hypertrophic cardiomyopathy and tetralogy of fallot, and its functional evaluation in the Drosophila heart

The causal genetic underpinnings of congenital heart diseases, which are often complex and multigenic, are still far from understood. Moreover, there are also predominantly monogenic heart defects, such as cardiomyopathies, with known disease genes for the majority of cases. In this study, we identified mutations in myomesin 2 (MYOM2) in patients with Tetralogy of Fallot (TOF), the most common cyanotic heart malformation, as well as in patients with hypertrophic cardiomyopathy (HCM), who do not exhibit any mutations in the known disease genes. MYOM2 is a major component of the myofibrillar Moand of the sarcomere, and a hub gene within interactions of sarcomere genes. We show that patient-derived cardiomyocytes exhibit myofibrillar disarray and reduced passive force with increasing sarcomere lengths. Moreover, our comprehensive functional analyses in the Drosophila animal model reveal that the so far uncharacterized fly gene CG14964 [herein referred to as Drosophila myomesin and myosin binding protein (dMnM)] may be an ortholog of MYOM2, as well as other myosin binding proteins . Its partial loss of function or moderate cardiac knockdown results in cardiac dilation, whereas more severely reduced function causes a constricted phenotype and an increase in sarcomere myosin protein. Moreover, compound heterozygous combinations of CG14964 and the sarcomere gene Mhc (MYH6/7) exhibited synergistic genetic interactions. In summary, our results suggest that MYOM2 not only plays a critical role in maintaining robust heart function but may also be a candidate gene for heart diseases such as HCM and TOF, as it is clearly involved in the development of the heart

Composite Films of HDPE with SiO2 and ZrO2 Nanoparticles: The Structure and Interfacial Effects

Herein, we investigated the influence of two types of nanoparticle fillers, i.e., amorphous SiO2 and crystalline ZrO2, on the structural properties of their nanocomposites with high-density polyethylene (HDPE). The composite films were prepared by melt-blending with a filler content that varied from 1% to 20% v/v. The composites were characterized by small- and wide-angle x-ray scattering (SAXS and WAXS), small-angle neutron scattering (SANS), Raman spectroscopy, differential scanning calorimetry (DSC), and scanning electron microscopy (SEM). For both fillers, the nanoaggregates were evenly distributed in the polymer matrix and their initial state in the powders determined their surface roughness and fractal character. In the case of the nano-ZrO2 filler, the lamellar thickness and crystallinity degree remain unchanged over a broad range of filler concentrations. SANS and SEM investigation showed poor interfacial adhesion and the presence of voids in the interfacial region. Temperature-programmed SANS investigations showed that at elevated temperatures, these voids become filled due to the flipping motions of polymer chains. The effect was accompanied by a partial aggregation of the filler. For nano-SiO2 filler, the lamellar thickness and the degree of crystallinity increased with increasing the filler loading. SAXS measurements show that the ordering of the lamellae is disrupted even at a filler content of only a few percent. SEM images confirmed good interfacial adhesion and integrity of the SiO2/HDPE composite. This markedly different impact of both fillers on the composite structure is discussed in terms of nanoparticle surface properties and their affinity to the HDPE matrix

Selected aspects of allergy nursing

Introduction. Due to their dynamic character, allergic conditions pose challenges for modern medicine and constitute a public health problem. Nearly 40% of the general Polish population is estimated to suffer from an allergy. We would like to emphasize that allergies are not some extraordinary ailments; instead, they commonly coincide with or are complications of other systemic conditions. Hence, national health policies should prioritize the development and implementation of ready-to-use protocols that focus mainly on prevention rather than treatment