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In recent years, the Internet of Things (IoT) paradigm has been widely applied across a variety of industrial and consumer areas to facilitate greater automation and increase productivity. Higher dependability on connected devices led to a growing range of cyber security threats targeting IoT-enabled platforms, specifically device firmware vulnerabilities, often overlooked during development and deployment. A comprehensive security strategy aiming to mitigate IoT firmware vulnerabilities would entail auditing the IoT device firmware environment, from software components, storage, and configuration, to delivery, maintenance, and updating, as well as understanding the efficacy of tools and techniques available for this purpose. To this effect, this paper reviews the state-of-the-art technology in IoT firmware vulnerability assessment from a holistic perspective. To help with the process, the IoT ecosystem is divided into eight categories: system properties, access controls, hardware and software re-use, network interfacing, image management, user awareness, regulatory compliance, and adversarial vectors. Following the review of individual areas, the paper further investigates the efficiency and scalability of auditing techniques for detecting firmware vulnerabilities. Beyond the technical aspects, state-of-the-art IoT firmware architectures and respective evaluation platforms are also reviewed according to their technical, regulatory, and standardization challenges. The discussion is accompanied also by a review of the existing auditing tools, the vulnerabilities addressed, the analysis method used, and their abilities to scale and detect unknown attacks. The review also proposes a taxonomy of vulnerabilities and maps them with their exploitation vectors and with the auditing tools that could help in identifying them. Given the current interest in analysis automation, the paper explores the feasibility and impact of evolving machine learning and blockchain applications in securing IoT firmware. The paper concludes with a summary of ongoing and future research challenges in IoT firmware to facilitate and support secure IoT development.
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Despite the substantial decrease in mortality rates following a pancreaticoduodenectomy to less than 5%, morbidity rates remain significant, reaching even 73%. Postoperative pancreatic fistula is one of the most frequent major complications and is significantly associated with other complications, including patient death. Currently, there is no consensus regarding the ideal type of pancreatic anastomosis, as the question of the choice between a pancreaticogastrostomy and pancreaticojejunostomy is still open. Furthermore, worldwide implementation of an ideal pancreatic fistula risk prediction score is missing. Our study found several significant predictive factors for the postoperative occurrence of fistulas, such as the soft consistency of the pancreas, non-dilated Wirsung duct, important intraoperative blood loss, other perioperative complications, preoperative patient hypoalbuminemia, and patient weight loss. Our study also revealed that for patients who exhibit fistula risk factors, pancreaticogastrostomy demonstrates a significantly lower pancreatic fistula rate than pancreaticojejunostomy. The occurrence of pancreatic fistulas has been significantly associated with the development of other postoperative major complications, and patient death. As the current pancreatic fistula risk scores proposed by various authors have not been consensually validated, we propose a simple, easy-to-use, and sensitive score for the risk prediction of postoperative pancreatic fistula occurrence based on important predictors from statistical analyses that have also been found to be significant by most of the reported studies. The new pancreatic fistula risk score proposed by us could be extremely useful for improved therapeutic management of cephalic pancreaticoduodenectomy patients.
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Counterfeiting drugs has been a global concern for years. Considering the lack of transparency within the current pharmaceutical distribution system, research has shown that blockchain technology is a promising solution for an improved supply chain system. This study aims to explore the current solution proposals for distribution systems using blockchain technology. Based on a literature review on currently proposed solutions, it is identified that the secrecy of the data within the system and nodes' reputation in decision making has not been considered. The proposed prototype uses a zero-knowledge proof protocol to ensure the integrity of the distributed data. It uses the Markov model to track each node's 'reputation score' based on their interactions to predict the reliability of the nodes in consensus decision making. Analysis of the prototype demonstrates a reliable method in decision making, which concludes with overall improvements in the system's confidentiality, integrity, and availability. The result indicates that the decision protocol must be significantly considered in a reliable distribution system. It is recommended that the pharmaceutical distribution systems adopt a relevant protocol to design their blockchain solution. Continuous research is required further to increase performance and reliability within blockchain distribution systems.
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Blockchain , Confidencialidade , Preparações Farmacêuticas , Reprodutibilidade dos Testes , TecnologiaRESUMO
Introduction: SARS-CoV-2 is a Betacoronavirus belonging to the Sarbecovirus subgenus of the Coronavidae family, antigenically distinct from SARS CoV, with which it has a genetic similarity of about 76% of nucleotides (1). It causes the Covid-19 disease in humans, which mainly affects the respiratory system, through inflammatory and procoagulant mechanisms at the level of alveolar microcirculation. Material and method: There are 145 patients infected with SARS-CoV-2, treated in the Colentina Surgery Clinic during March-August 2020, whose cases were analysed to identify some elements that would help to improve the medical management of these patients from multiple perspectives. Discussion: There was a slight predominance of male impairments, and the ages of interest were mostly over 60 years. The cases that required surgery were in an absolute minority (14 cases). The operations were performed only in conditions of a surgical emergency. Mortality was high (24,13%).
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COVID-19/epidemiologia , Centro Cirúrgico Hospitalar/organização & administração , Hospitais , Humanos , Masculino , Pessoa de Meia-Idade , Romênia , Resultado do TratamentoRESUMO
Smart Meters provide detailed energy consumption data and rich contextual information that can be utilized to assist electricity providers and consumers in understanding and managing energy use. The detection of human activity in residential households is a valuable extension for applications, such as home automation, demand side management, or non-intrusive load monitoring, but it usually requires the installation of dedicated sensors. In this paper, we propose and evaluate two new metrics, namely the sliding window entropy and the interval entropy, inspired by Shannon's entropy in order to obtain information regarding human activity from smart meter readings. We emphasise on the application of the entropy and analyse the effect of input parameters, in order to lay the foundation for future work. We compare our method to other methods, including the Page-Hinkley test and geometric moving average, which have been used for occupancy detection on the same dataset by other authors. Our experimental results, using the power measurements of the publicly available ECO dataset, indicate that the accuracy and area under the curve of our method can keep up with other well-known statistical methods, stressing the practical relevance of our approach.
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Thin films of an organic nonlinear optical (NLO) material, N, N-dimethyl-p-(2,2-dicyanovinyl) aniline (DCVA), have been grown in space and on the ground by physical vapor transport in an effusive ampoule arrangement. The thin film growth technique developed on the ground is a direct result of information gleaned from experiments in microgravity. This paper covers the results of our experimental investigations for establishing "ideal" terrestrial conditions for deposition of a DCVA film. The active control during the deposition process was exercised by three deposition variables: the material source temperature, the background pressure external to the growth ampoule and the substrate temperature. Successful growth occurred when the difference in temperature between the source material and the copper substrate was 14 degrees C and the background nitrogen pressure was such that the transport was either diffusive or convective. A qualitative diffusion limited boundary was estimated to occur at a pressure of approximately 20 torr. We have probed the DCVA thin films with visible-near infrared reflection absorption spectroscopy, polarized Fourier transform infrared spectrometry, differential interference contrast optical microscopy, and stylus profilometry.