Correlation Analysis of In-Vehicle Sensors Data and Driver Signals in Identifying Driving and Driver Behaviors.

Today's cars have dozens of sensors to monitor vehicle performance through different systems, most of which communicate via vehicular networks (CAN). Many of these sensors can be used for applications other than the original ones, such as improving the driver experience or creating new safety tools. An example is monitoring variables that describe the driver's behavior. Interactions with the pedals, speed, and steering wheel, among other signals, carry driving characteristics. However, not always all variables related to these interactions are available in all vehicles; for example, the excursion of the brake pedal. Using an acquisition module, data from the in-vehicle sensors were obtained from the CAN bus, the brake pedal (externally instrumented), and the driver's signals (instrumented with an inertial sensor and electromyography of their leg), to observe the driver and car information and evaluate the correlation hypothesis between these data, as well as the importance of the brake pedal signal not usually available in all car models. Different sets of sensors were evaluated to analyze the performance of three classifiers when analyzing the driver's driving mode. It was found that there are superior results in classifying identity or behavior when driver signals are included. When the vehicle and driver attributes were used, hits above 0.93 were obtained in the identification of behavior and 0.96 in the identification of the driver; without driver signals, accuracy was more significant than 0.80 in identifying behavior. The results show a good correlation between vehicle data and data obtained from the driver, suggesting that further studies may be promising to improve the accuracy of rates based exclusively on vehicle characteristics, both for behavior identification and driver identification, thus allowing practical applications in embedded systems for local signaling and/or storing information about the driving mode, which is important for logistics companies.

Analysis of Influence of Segmentation, Features, and Classification in sEMG Processing: A Case Study of Recognition of Brazilian Sign Language Alphabet.

Sign Language recognition systems aid communication among deaf people, hearing impaired people, and speakers. One of the types of signals that has seen increased studies and that can be used as input for these systems is surface electromyography (sEMG). This work presents the recognition of a set of alphabet gestures from Brazilian Sign Language (Libras) using sEMG acquired from an armband. Only sEMG signals were used as input. Signals from 12 subjects were acquired using a MyoTM armband for the 26 signs of the Libras alphabet. Additionally, as the sEMG has several signal processing parameters, the influence of segmentation, feature extraction, and classification was considered at each step of the pattern recognition. In segmentation, window length and the presence of four levels of overlap rates were analyzed, as well as the contribution of each feature, the literature feature sets, and new feature sets proposed for different classifiers. We found that the overlap rate had a high influence on this task. Accuracies in the order of 99% were achieved for the following factors: segments of 1.75 s with a 12.5% overlap rate; the proposed set of four features; and random forest (RF) classifiers.

Bacteria from tropical semiarid temporary ponds promote maize growth under hydric stress.

World climate change has triggered soil water stress and imposed limitations on agricultural production. Plant growth-promoting bacteria (PGPBs) have been an efficient strategy to improve the biological supply and growth of plants under distinct abiotic stress conditions. We hypothesized that the soils from a temporary pond may harbor PGPBs with potential strains which increase maize tolerance to water deficit. We studied rhizosphere and bulk soil of Mimosa bimucronata in a temporary pond from semiarid Northeast Brazil to access strains with characteristics to promote plant growth and mitigate abiotic stress for maize crop. We isolated 355 bacterial isolates, from which 96 were selected based on the morphophysiological characterization to assess IAA production (42 % produced over 50 µg mL-1 of IAA), calcium phosphate solubilization (with one isolate achieving medium IS), biofilm and exopolysaccharides production (66 % and 98 % of isolates, respectively). Based on these mechanisms, the 30 most promising bacterial isolates were selected to assess biological nitrogen fixation (74 % of the isolates showed nitrogenase activity greater than 20 C2H4.h-1.mg-1), ACC deaminase activity (80 % of isolates) and growth in medium with reduced water activity (8 % of isolates grew in medium with water activity (Aw) of 0.844). We sequenced the 16S rRNA gene from the seven most promising isolates in in vitro and in vivo assays, which were identified as Staphylococcus edaphicus, Bacillus wiedmannii, Micrococcus yunnanensis, Streptomyces alboflavus, Streptomyces alboflavus, Bacillus wiedmanni and Bacillus cereus. In vivo, eleven isolates and three bacterial consortia did not differ from the control with nutrient solution, for total leaf area and root dry mass of maize. S. alboflavus (BS43) had the best in vivo results, not differing from the control with nutrient solution. We highlight the unpublished potential of Staphylococcus edaphicus and Streptomyces alboflavus in promoting the growth of plants under water stress. In addition, it is the first report of bacteria isolated from a temporary pond in the Brazilian semiarid which promoting plant growth attributes and development.

Sensors and Systems for Physical Rehabilitation and Health Monitoring-A Review.

The use of wearable equipment and sensing devices to monitor physical activities, whether for well-being, sports monitoring, or medical rehabilitation, has expanded rapidly due to the evolution of sensing techniques, cheaper integrated circuits, and the development of connectivity technologies. In this scenario, this paper presents a state-of-the-art review of sensors and systems for rehabilitation and health monitoring. Although we know the increasing importance of data processing techniques, our focus was on analyzing the implementation of sensors and biomedical applications. Although many themes overlap, we organized this review based on three groups: Sensors in Healthcare, Home Medical Assistance, and Continuous Health Monitoring; Systems and Sensors in Physical Rehabilitation; and Assistive Systems.

A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose.

Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be the most suitable equipment for this situation. In this work, a prototype was developed to detect the concentration of ethanol in a high spectrum of beers presents in the market. It was used cheap and easy-to-acquire 13 gas sensors made with a metal oxide semiconductor (MOS). Samples with 15 predetermined alcohol contents were used for the training and construction of the models. For validation, seven different commercial beverages were used. The correlation (R2) of 0.888 for the MLR (RMSE = 0.45) and the error of 5.47% for the ELM (RMSE = 0.33) demonstrate that the equipment can be an effective tool for detecting the levels of alcohol contained in beverages.

Pielonefrite enfisematosa em enxerto renal: relato de caso / Emphysematous pyelonephritis in renal: allograft-case report

Pielonefrite enfisematosa é uma rara complicação após o transplante renal. Este é um relato de caso de uma paciente diabética de 42 anos de idade, do sexo feminino, que se apresentou após uma semana de tratamento de infecção do trato urinário causada por Escherichia coli, referindo uma massa palpável sobre o enxerto. A tomografia computadorizada de abdome mostrou coleção perirrenal contendo ar. Tratada com antibióticos e drenagem percutânea. Após 20 dias de drenagem, recebeu alta hospitalar com função renal estável.

Emphysematous pyelonephritis is a rare post renal transplant complication. This is a case report of a 42 year-old diabetic female, who presented a urinary tract infection caused by Escherichia coli and a palpable mass above the graft approximately 1 week after treatmtent, A computer tomography scan of the abdomen showed peri-renal collection containing air. The patient was treated with antibiotics and a percutaneous nephrostomy was performed. After 20 days of drainage, renal function was considered stable and she was discharged from the hospital.

Fístula congênita do lábio inferior / Congenital fistula of the lower lip

Os autores apresentam dois casos de fístula congênita do lábio inferior. Estudam a hereditariedade, associaçäo com a fissura labiopalatina, aspectos histológicos e tratamento