Hardware-accelerated data decoding and reconstruction for automotive LiDAR sensors

The automotive industry is facing an unprecedented technological transformation towards fully autonomous vehicles. Optimists predict that, by 2030, cars will be sufficiently reliable, affordable, and common to displace most current human driving tasks. To cope with these trends, autonomous vehicles require reliable perception systems to hear and see all the surroundings, being light detection and ranging (LiDAR) sensors a key instrument for recreating a 3D visualization of the world. However, for a reliable operation, such systems require LiDAR sensors to provide high-resolution 3D representations of the car’s vicinity, which results in millions of data points to be processed in real-time. With this article we propose the ALFA-Pi, a data packet decoder and reconstruction system fully deployed on an embedded reconfigurable hardware platform. By resorting to field-programmable gate array (FPGA) technology, ALFAPi is able to interface different LiDAR sensors at the same time, while providing custom representation outputs to high-level perception systems. By accelerating the LiDAR interface, the proposed system outperforms current software-only approaches, achieving lower latency in the data acquisition and data decoding tasks while reaching high performance ratios

DIOR: a hardware-assisted weather denoising solution for LiDAR Point Clouds

The interest in developing and deploying fully autonomous vehicles on our public roads has come to a full swing. Driverless capabilities, widely spread in modern vehi cles through advanced driver-assistance systems (ADAS), require highly reliable perception features to navigate the environment, being light detection and ranging (LiDAR) sen sors a key instrument in detecting the distance and speed of nearby obstacles and in providing high-resolution 3D rep resentations of the surroundings in real-time. However, and despite being assumed as a game-changer in the autonomous driving paradigm, LiDAR sensors can be very sensitive to adverse weather conditions, which can severely affect the vehicle’s perception system behavior. Aiming at improving the LiDAR operation in challenging weather conditions, which contributes to achieving higher driving automation levels defined by the Society of Automotive Engineers (SAE), this article proposes a weather denoising method called Dynamic light-Intensity Outlier Removal (DIOR). DIOR combines two approaches of the state-of-the-art, the dynamic radius outlier removal (DROR) and the low-intensity outlier removal (LIOR) algorithms, supported by an embedded reconfigurable hardware platform. By resorting to field-programmable gate array (FPGA) technology, DIOR can outperform state-of-the-art outlier removal solutions, achieving better accuracy and performance while guaranteeing the real-time requirements.This work was supported by the Fundacao para a Ciencia e Tecnologia (FCT) within the Research and Development Units Project Scope under Grant UIDB/00319/2020

EcoGreenRoof – EGR: Eco-materials Development for Green Roofs

The project EcoGreenRoofs - EGR aims to develop ecological substrates for application in green roofs, which include in their formulation industrial waste of organic and inorganic base. The substrates are tentatively produced exclusively from industrial waste and / or materials derived from waste treated, and tested at a facility to be studied, developed and built on pilot scale. The substrates produced will be tested under real conditions for their validation and inherent production process. This project aims also to evaluate the commercialization of substrates by analyzing the technical, economic and environmental components. The project is being carried out in co-promotion by two enterprises, one with know-how in the execution of green roofs (Neoturf) and the other with knowledge to implementation of industrial solutions aiming waste management (W2V), and by two SI & I entities with the knowledge and means to develop waste recovery studies (CVR) and roof solutions (Itecons).This work has been co-financed by Compete 2020, Portugal 2020 and the European Union through the European Regional Development Fund – FEDER within the scope of the project EGR - EcoGreenRoof: Desenvolvimento de eco-materiais para coberturas verdes (POCI-01-0247-FEDER- 033728)

Weakly-supervised classification of HER2 expression in breast cancer haematoxylin and eosin stained slides

Human epidermal growth factor receptor 2 (HER2) evaluation commonly requires immunohistochemistry (IHC) tests on breast cancer tissue, in addition to the standard haematoxylin and eosin (H&E) staining tests. Additional costs and time spent on further testing might be avoided if HER2 overexpression could be effectively inferred from H&E stained slides, as a preliminary indication of the IHC result. In this paper, we propose the first method that aims to achieve this goal. The proposed method is based on multiple instance learning (MIL), using a convolutional neural network (CNN) that separately processes H&E stained slide tiles and outputs an IHC label. This CNN is pretrained on IHC stained slide tiles but does not use these data during inference/testing. H&E tiles are extracted from invasive tumour areas segmented with the HASHI algorithm. The individual tile labels are then combined to obtain a single label for the whole slide. The network was trained on slides from the HER2 Scoring Contest dataset (HER2SC) and tested on two disjoint subsets of slides from the HER2SC database and the TCGA-TCIA-BRCA (BRCA) collection. The proposed method attained 83.3% classification accuracy on the HER2SC test set and 53.8% on the BRCA test set. Although further efforts should be devoted to achieving improved performance, the obtained results are promising, suggesting that it is possible to perform HER2 overexpression classification on H&E stained tissue slides.publishersversionpublishe

PROGNOSTIC IMPACT OF PREOPERATIVE INFLAMMATORY BIOMARKERS IN ACUTE LIMB ISCHEMIA PATIENTS: A SYSTEMATIC REVIEW

Introduction: In many areas of Medicine, biomarkers have been proving their value in disease management. The inclusion of inflammatory biomarkers in acute limb ischemia (ALI) decision-making remains debatable due to the scarce literature evidence. Nevertheless, much attention has been held towards the prognostic value of these simple, readily available and low-cost biomarkers might have. Therefore, this review aimed to identify studies that support the utility of preoperative inflammatory markers, such as the neutrophil-lymphocyte ratio (NLR) and the platelet-lymphocyte ratio (PLR), for predicting ALI outcome. Methods: A comprehensive systematic search was applied to Medline database to identify all the cohort studies that specifically investigated and compared the outcomes of ALI patients in relation to their preoperative inflammatory biomarkers. Results: Four cohort studies were included in the review: two published citations, one research letter and one unpublished paper from the same authors of this review. In all studies, the primary outcomes were amputation and/or survival. All studies reported that higher NLR values were independently associated with adverse outcomes after treatment. One study stated that NLR ≥ 5.2 was found to have an 83% sensitivity and 63% specificity for predicting amputation within 30 days (Area Under Curve (AUC) 0.8) while other found that NLR ≥ 5.4 demonstrated to have a 90.5% sensitivity and 73.6% specificity for predicting 30-day amputation or death (AUC 0.86). Higher preoperative RDW, MPV, PLR and C-reactive protein were also reported as predictors of amputation in acute arterial thromboembolism patients in another study. Conclusion: This review demonstrates that although limited literature exists, inflammatory biomarkers like NLR and PLR appear to have a role in ALI preoperative risk stratification. Definition of levels and trends of inflammatory biomarkers and their relationship with treatment outcome could be established through multicentric studies, influencing timing and intervention selection and leading to potential improvements in ALI morbimortality

Microphone array for speaker localization and identification in shared autonomous vehicles

With the current technological transformation in the automotive industry, autonomous vehicles are getting closer to the Society of Automative Engineers (SAE) automation level 5. This level corresponds to the full vehicle automation, where the driving system autonomously monitors and navigates the environment. With SAE-level 5, the concept of a Shared Autonomous Vehicle (SAV) will soon become a reality and mainstream. The main purpose of an SAV is to allow unrelated passengers to share an autonomous vehicle without a driver/moderator inside the shared space. However, to ensure their safety and well-being until they reach their final destination, active monitoring of all passengers is required. In this context, this article presents a microphone-based sensor system that is able to localize sound events inside an SAV. The solution is composed of a Micro-Electro-Mechanical System (MEMS) microphone array with a circular geometry connected to an embedded processing platform that resorts to Field-Programmable Gate Array (FPGA) technology to successfully process in the hardware the sound localization algorithms.This work is supported by: European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039334; Funding Reference: POCI-01-0247-FEDER-039334]

Ganoderma lucidum in an animal model of obesity: preliminary results

Obesity is an emerging health problem worldwide. Hypercaloric or hyperlipidemic diets have been used as models of obesity induction in laboratory animals. Obesity can be influenced by regular consumption of natural bioactive compounds. Mushrooms, such as Ganoderma lucidum (GL), have been used in the human diet since ancient times and include a wide variety of biomolecules with medicinal properties. The main objective of this work was to study the effects of G. lucidum in an animal model of obesity.info:eu-repo/semantics/publishedVersio

Clube Português do Pâncreas Recommendations for Chronic Pancreatitis: Medical, Endoscopic, and Surgical Treatment (Part II)

Chronic pancreatitis (CP) is a complex disease that should be treated by experienced teams of gastroenterologists, radiologists, surgeons, and nutritionists in a multidisciplinary environment. Medical treatment includes lifestyle modification, nutrition, exocrine and endocrine pancreatic insufficiency correction, and pain management. Up to 60% of patients will ultimately require some type of endoscopic or surgical intervention for treatment. However, regardless of the modality, they are often ineffective unless smoking and alcohol cessation is achieved. Surgery retains a major role in the treatment of CP patients with intractable chronic pain or suspected pancreatic mass. For other complications like biliary or gastroduodenal obstruction, pseudocyst drainage can be performed endoscopically. The recommendations for CP were developed by Clube Português do Pâncreas (CPP), based on literature review to answer predefined topics, subsequently discussed and approved by all members of CPP. Recommendations are separated in two parts: "chronic pancreatitis etiology, natural history, and diagnosis," and "chronic pancreatitis medical, endoscopic, and surgical treatment." This abstract pertains to part II.info:eu-repo/semantics/publishedVersio

Composição e abundância de macrófitas num troço do rio Ovelha

As macrófitas fluviais são um grupo relevante para a avaliação ecológica dos rios. Numa amostragem realizada num troço de 100 m do rio Ovelha, localizado a 217 m de altitude, na freguesia de Fornos, Marco de Canaveses, estudou-se a abundância, composição e distribuição das macrófitas. Verificou-se que o troço estudado é pobre em macrófitas, apresentando uma riqueza específica baixa, o que poderá estar relacionado, sobretudo, com o substrato rochoso. Considerando os resultados obtidos é fundamental que, futuramente, sejam estudadas as macrófitas conjuntamente com outros elementos biológicos, no sentido de se proceder a uma correta monitorização do estado ecológico do rio Ovelha.info:eu-repo/semantics/publishedVersio