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Effective access control techniques are in demand, as electronically assisted healthcare services require the patient’s sensitive health records. In emergency situations, where the patient’s well-being is jeopardized, different healthcare actors associated with emergency cases should be granted permission to access Electronic Health Records (EHRs) of patients. The research objective of our study is to develop machine learning techniques based on patients’ time sequential health metrics and integrate them with an Attribute Based Access Control (ABAC) mechanism. We propose an ABAC mechanism that can yield access to sensitive EHRs systems by applying prognostic context handlers where contextual information, is used to identify emergency conditions and permit access to medical records. Specifically, we use patients’ recent health history to predict the health metrics for the next two hours by leveraging Long Short Term Memory (LSTM) Neural Networks (NNs). These predicted health metrics values are evaluated by our personalized fuzzy context handlers, to predict the criticality of patients’ status. The developed access control method provides secure access for emergency clinicians to sensitive information and simultaneously safeguards the patient’s well-being. Integrating this predictive mechanism with personalized context handlers proved to be a robust tool to enhance the performance of the access control mechanism to modern EHRs System.

Miniaturization of electrochemical detection ofPseudomonas aeruginosaquorum sensing molecules at a liquid/liquid interface through facilitated proton transfer reactions.

Diesel engine exhausts from a common rail 3.0 L F1C diesel engine were analyzed at two different load conditions of the WLTC testing cycle downstream of both the diesel particulate filter (DPF) and selective catalytic reactor (SCR) to verify their effect on the characteristics of carbon particulate matter. An array of chemical, physical and spectroscopic techniques (gas chromatography coupled with mass spectrometry (GC-MS), mobility analyzer, UV-Visible absorption and fluorescence spectroscopy) was applied for characterizing polycyclic aromatic hydrocarbons (PAH), heavy aromatic compounds and soot, constituting the particulate matter (PM) sampled from the exhaust. The engine was operated in half load (HL) (188 Nm, representing the more common condition for engine in urban traffic) and full load (FL) (452 Nm, representing the best performance of the engine operation) conditions, at the same engine speed (2000 rpm). Soot formation was enhanced in HL condition, with respect to FL, but, just because of the much lower soot amount, the after-treatment systems in this last condition resulted to be less efficient in the soot abatement. Indeed, the abatement through DPF was about 40% lower in the FL condition with respect to HL condition, and any significant further concentration decrease was found after SCR, in both conditions. By contrast, PAH concentration after DPF abatement was found to be higher in the HL with respect to FL condition. A further PAH concentration decrease of about 30% was found after the SCR in the HL condition whereas in FL the reduction was only about 5-6%. Also the heavy aromatic compounds having molecular weight above the GC-MS detection limit (300 u), were mitigated by SCR. Therefore, SCR did not cause a further soot reduction, whereas it was effective in largely reducing PAH and heavy aromatics emissions, especially in the lower temperature condition featuring the half-load condition, when combustion efficiency is worse. Moreover, SCR system reduced the emission of small particles probably due to an enhanced agglomeration of particles, with beneficial effect on the harmfulness to human health.

The report “Effects of Air Temperature Modified by Vulnerability Factors” was prepared as a milestone by researchers in the EU Project EXHAUSTION*. This report summarises the evidence on the interactive effects of high air temperature and various vulnerability factors, including the environmental, socio-economic, and individual behavioral factors on heart- and lung-related deaths and diseases (cardiopulmonary mortality and morbidity) across Europe. The study was conducted at the city, small-area (e.g., municipalities), and individual level. The findings show a greater vulnerability to heat for people living in urban areas with dense population, high air pollution levels, low coverage of green spaces, as well as areas with low Gross Domestic Product. Moreover, people with chronic pre-existing diseases and the elderly were found to be at greater risk. The findings highlight the urgent need to improve the urban environment as well as the health status and living conditions in European cities to contrast the impacts of heat and future climate change. This report alerts stakeholders and policymakers that targeted climate change adaptation measures need to be considered to protect vulnerable population and thereby increase European resilience to climate change.

Various sociodemographic and behavioral health factors have been reported to influence the development of metabolic syndrome (Mets). In addition, the effects of various sociodemographic and health related characteristics on single-person households appear to be influenced by sex. Considering the surge in the number of single-person households globally, we conducted a sex-stratified analysis of the factors that affect the development of Mets among single-person Korean households. We used secondary data from the 2016–2018 Korea National Health and Nutrition Examination Survey (KNHANES) for this study. A total of 1830 participants (aged ≥19 years) without any missing data were analyzed in this study. The chi-square test and multiple logistic regression were used to analyze the study data. The results of the multiple logistic regression analysis showed that the significant risk factors for Mets in men were age, body mass index (BMI), subjective health status, subjective recognition of body shape, household income, and sleep hours, whereas age, BMI, subjective health status, exercise, and sleep hours were the significant risk factors for Mets in women. Specialized sex-specific health policies and programs are needed to reduce the prevalence of Mets in single-person households.

The ocean provides resources key to human health and well-being, including food, oxygen, livelihoods, blue spaces, and medicines. The global threat to these resources posed by accelerating ocean acidification is becoming increasingly evident as the world’s oceans absorb carbon dioxide emissions. While ocean acidification was initially perceived as a threat only to the marine realm, here we argue that it is also an emerging human health issue. Specifically, we explore how ocean acidification affects the quantity and quality of resources key to human health and well-being in the context of: (1) malnutrition and poisoning, (2) respiratory issues, (3) mental health impacts, and (4) development of medical resources. We explore mitigation and adaptation management strategies that can be implemented to strengthen the capacity of acidifying oceans to continue providing human health benefits. Importantly, we emphasize that the cost of such actions will be dependent upon the socioeconomic context; specifically, costs will likely be greater for socioeconomically disadvantaged populations, exacerbating the current inequitable distribution of environmental and human health challenges. Given the scale of ocean acidification impacts on human health and well-being, recognizing and researching these complexities may allow the adaptation of management such that not only are the harms to human health reduced but the benefits enhanced.

Radiation (RT) remains the most frequently used treatment against cancer. The main limitation of RT is its lack of specificity for cancer tissues and the limited maximum radiation dose that can be safely delivered without damaging the surrounding healthy tissues. A step forward in the development of better RT is achieved by coupling it with other treatments, such as photodynamic therapy (PDT). PDT is an anti-cancer therapy that relies on the light activation of non-toxic molecules—called photosensitizers—to generate ROS such as singlet oxygen. By conjugating photosensitizers to dense nanoscintillators in hybrid architectures, the PDT could be activated during RT, leading to cell death through an additional pathway with respect to the one activated by RT alone. Therefore, combining RT and PDT can lead to a synergistic enhancement of the overall efficacy of RT. However, the involvement of hybrids in combination with ionizing radiation is not trivial: the comprehension of the relationship among RT, scintillation emission of the nanoscintillator, and therapeutic effects of the locally excited photosensitizers is desirable to optimize the design of the hybrid nanoparticles for improved effects in radio-oncology. Here, we discuss the working principles of the PDT-activated RT methods, pointing out the guidelines for the development of effective coadjutants to be tested in clinics.