Quantitative microbial spoilage risk assessment of plant-based milk alternatives by Geobacillus stearothermophilus in Europe

Geobacillus stearothermophilus is one of the predominant spoilers of UHT-treated food products, due to its extremely heat-resistant spores. However, the surviving spores should be exposed to temperature higher than their minimum growth temperature for a certain time to germinate and grow to spoilage levels. Considering the projected temperature increase due to climate change, the events of non-sterility during distribution and transportation are expected to escalate. Hence, the aim of this study was to build a quantitative microbial spoilage risk assessment (QMRSA) model to quantify the risk of spoilage of plant-based milk alternatives within Europe. The model consists of four main steps: 1. Initial contamination of raw materials 2. Heat inactivation of spores during UHT treatment 3. Partitioning 4. Germination and outgrowth of spores during distribution and storage. The risk of spoilage was defined as the probability of G. stearothermophilus to reach its maximum concentration (N_max = 10^7.5 CFU/mL) at the time of consumption. The assessment was performed for North (Poland) and South (Greece) Europe, and the risk of spoilage was estimated for the current climatic conditions and a climate change scenario. Based on the results, the risk of spoilage was negligible for the North European region, while the risk of spoilage in South Europe was 6.2 × 10^-3 95% CI (2.3 × 10^-3;1.1 × 10^-2) under the current climatic conditions. The risk of spoilage was increased for both tested countries under climate change scenario; from zero to 1.0 × 10^-4 in North Europe, risk multiplied 2 or 3 in South Europe depending on air conditioning implementation at consumer's place. Therefore, the heat treatment intensity and the use of insulated trucks during distribution were investigated as mitigation strategies and led to significant reduction of the risk. Overall, the QMRSA model developed in this study can support risk management decisions of these products by quantify the potential risk under current climatic conditions and climate change scenarios.

Over Expression of Cancer Stem Cell Marker CD44 and Its Clinical Significance in Patients with Oral Squamous Cell Carcinoma

Cancer stem cell marker CD44 is a cell-surface glycoprotein which is involved in various cellular functions such as cell-cell interactions, cell adhesion, haematopoiesis and tumour metastasis. The CD44 gene transcription is partly activated by beta-catenin and Wnt signalling pathway, the later pathway being linked to tumour development. However, the role of CD44 in oral squamous cell carcinoma (OSCC) is not well understood. We investigated the expression of CD44 in peripheral circulation, tumour tissues of oral cancer patients and oral squamous cell carcinoma cell lines by ELISA and quantitative (q)-RTPCR. Relative CD44s mRNA expression was significantly higher in peripheral circulation (p = 0.04), tumour tissues (p = 0.049) and in oral cancer cell lines (SCC4, SCC25 p = 0.02, SCC9 p = 0.03). Circulating CD44total protein levels were also significantly (p < 0.001) higher in OSCC patients that positively correlated with increasing tumour load and loco-regional spread of the tumour. The circulating tumour stem cell marker CD44 appears to be a potent indicator of tumour progression and may be useful for developing suitable therapeutics strategies for patients with oral squamous cell carcinoma.

Probabilistic risk analysis of unit trains versus manifest trains for transporting hazardous materials

When transporting hazardous materials by rail, train types (unit train or manifest train) can influence derailment and release risks in several ways. Unit trains only experience risks on mainlines and when arriving at or departing from terminals, while manifest trains experience additional switching risks in yards. A comprehensive risk assessment methodology is needed to quantitively compare shipments with unit trains and manifest trains, considering both mainline and yard operations. To fulfill this research gap, this paper constructs event chains for line-haul risks, arrival/departure risks, and yard switching risks using various probabilistic models and finally determines expected casualties as the consequences of a potential train derailment and release incident. Five illustrative scenarios are designed to analyze the best and worst cases and compare the transportation risk differences between service options using unit trains and manifest trains. The comparison results indicate that placing all tank cars at the positions with the lowest probability of derailing and switching tank cars alone in classification yards could provide the lowest risk estimate given the same transportation demand.

Machine learning-based model for predicting the esophagogastric variceal bleeding risk in liver cirrhosis patients

BACKGROUND

Liver cirrhosis patients are at risk for esophagogastric variceal bleeding (EGVB). Herein, we aimed to estimate the EGVB risk in patients with liver cirrhosis using an artificial neural network (ANN).

METHODS

We included 999 liver cirrhosis patients hospitalized at the Beijing Ditan Hospital, Capital Medical University in the training cohort and 101 patients from Shuguang Hospital in the validation cohort. The factors independently affecting EGVB occurrence were determined via univariate analysis and used to develop an ANN model.

RESULTS

The 1-year cumulative EGVB incidence rates were 11.9 and 11.9% in the training and validation groups, respectively. A total of 12 independent risk factors, including gender, drinking and smoking history, decompensation, ascites, location and size of varices, alanine aminotransferase (ALT), γ-glutamyl transferase (GGT), hematocrit (HCT) and neutrophil-lymphocyte ratio (NLR) levels as well as red blood cell (RBC) count were evaluated and used to establish the ANN model, which estimated the 1-year EGVB risk. The ANN model had an area under the curve (AUC) of 0.959, which was significantly higher than the AUC for the North Italian Endoscopic Club (NIEC) (0.669) and revised North Italian Endoscopic Club (Rev-NIEC) indices (0.725) (all P <  0.001). Decision curve analyses revealed improved net benefits of the ANN compared to the NIEC and Rev-NIEC indices.

CONCLUSIONS

The ANN model accurately predicted the 1-year risk for EGVB in liver cirrhosis patients and might be used as a basis for risk-based EGVB surveillance strategies.

Increased human risk caused by cascading hazards - A framework

Cascading hazards occur frequently. Unexpected casualties and losses of properties, or even impacts on the society and the environment may ensue from failure to anticipate the amplified risks induced by cascading hazards. Current risk assessment methods pay relatively less attention to quantifying the increased human risk related to "cascading" events. An improved framework for quantifying the human risk caused by cascading hazards is proposed in this paper. The framework considers the interactions among the cascading hazards and among the vulnerabilities of elements to these hazards. Its kernel is to scientifically anticipate and gear up for any new intensified hazards, which may otherwise lead to serious social aftermath. The framework is illustrated with a multi-hazard example close to the epicenter of the Wenchuan earthquake, which involved a chain of hazards including slope failures, a large debris flow, river damming, and flooding.

Prospective risk analysis of the online-adaptive artificial intelligence-driven workflow using the Ethos treatment system

PURPOSE

The recently introduced Varian Ethos system allows adjusting radiotherapy treatment plans to anatomical changes on a daily basis. The system uses artificial intelligence to speed up the process of creating adapted plans, comes with its own software solutions and requires a substantially different workflow. A detailed analysis of possible risks of the associated workflow is presented.

METHODS

A prospective risk analysis of the adaptive workflow with the Ethos system was performed using Failure Modes and Effects Analysis (FMEA). An interprofessional team collected possible adverse events and evaluated their severity as well as their chance of occurrence and detectability. Measures to reduce the risks were discussed.

RESULTS

A total of 122 events were identified, and scored. Within the 20 events with the highest-ranked risks, the following were identified: Challenges due to the stand-alone software solution with very limited connectivity to the existing record and verify software and digital patient file, unfamiliarity with the new software and its limitations and the adaption process relying on results obtained by artificial intelligence. The risk analysis led to the implementation of additional quality assurance measures in the workflow.

CONCLUSIONS

The thorough analysis of the risks associated with the new treatment technique was the basis for designing details of the workflow. The analysis also revealed challenges to be addressed by both, the vendor and customers. On the vendor side, this includes improving communication between their different software solutions. On the customer side, this especially includes establishing validation strategies to monitor the results of the black box adaption process making use of artificial intelligence.

Long-term nonlinear relationship between PM2.5 and ten leading causes of death

Air pollution has become a major concern worldwide. Many epidemiological studies have proved relationships between fine particulate matter (PM_2.5) and various diseases, but most studies only use short-term and models for specific groups to derive relationships with acute diseases. This makes it difficult to understand long-term exposure, nonlinear relationships, and spatial-temporal health risks regarding chronic diseases. Therefore, this study proposed to analyze and map PM_2.5 exceedance probability from long-term spatial-temporal monitoring data using radial basis function estimation. We then constructed and compared multiple linear regression and generalized additive models to investigate linear and nonlinear relationships between long-term average PM_2.5 concentration, PM_2.5 potential probability for exceeding the standard, and standardized mortality for the top ten causes of death in all towns and villages in Taiwan nationally from 2010 to 2017. Linear models indicate that increasing PM_2.5 concentration increased malignant neoplasm, pneumonia, and chronic lower respiratory disease mortalities; chronic liver diseases; and cirrhosis; whereas heart diseases and esophagus cancer mortality decreased. For the nonlinear model results, it can be found that there were also significant nonlinear relationships between PM_2.5 concentration and malignant mortalities for neoplasm, heart disease, diabetes; and trachea, bronchus, lung, liver, intrahepatic bile duct, and esophagus cancer. Thus, long-term exposure to PM_2.5 may be a significant risk factor for multiple acute and chronic diseases. Results from this study can be directly applied worldwide to provide air quality and health management references for governments, and important information on long-term health risks for local residents in the study area.

Covid-19 infection risk on US domestic airlines

Working with recent data and research findings, we estimate the probability that an air traveler in economy class would have contracted Covid-19 on a US domestic jet flight over the nine-month period June 2020 to February 2021. The estimates take account of the rates of confirmed Covid-19 infections in the US, flight duration, fraction of seats occupied, and some demographic differences between US air travelers and US citizens as a whole. Based on point estimates, the risk of contracting Covid-19 in-flight exceeded 1 in 1000 on a fully-loaded two-hour flight at the height of the pandemic over the nine months, but was about 1 in 6000 on a half-full flight when the pandemic was at a low ebb. However, these estimates are subject to substantial uncertainty, with the 10th percentiles of various risk distributions only about 1/7 as large as the medians, and the 90th percentiles about four times as large. Based on seat-occupancy levels on US flights for each month over June 2020 to February 2021, the median risk estimate for that period is 1 in 2250, while the mean risk estimate is 1 in 1450. Indirect effects arose because those who contracted Covid-19 on US airplanes could in turn infect others.

Real-Time Continuous Glucose Monitoring Can Predict Severe Hypoglycemia in People with Type 1 Diabetes: Combined Analysis of the HypoDE and DIAMOND Trials

Objective: We combined data from two landmark trials (DIAMOND and HypoDE) to examine the diagnostic performance of low glucose measurements derived from open and masked continuous glucose monitoring (CGM) to predict the occurrence of future severe hypoglycemia (SH). Methods: We analyzed hypoglycemia parameters (low blood glucose index [LBGI], % <70 mg/dL, 54-69 mg/dL [level 1 hypoglycemia] and <54 mg/dL [level 2 hypoglycemia]) from masked CGM over 14 days during baseline and from open CGM over 14 days after randomization. We used receiver operating characteristics (ROC) curves to evaluate the screening performance of these measures to predict future SH. Positive likelihood ratios were calculated to indicate the overall diagnostic performance of these parameters. Results: Data from 288 individuals with type 1 diabetes (mean age 45.6 ± 12.8 years, diabetes duration 20.7 ± 13.7 years, HbA1c 8.2% ± 1.0%, Hypoglycemia Unawareness Score 3.4 ± 2.1) were analyzed. Area under ROC-curve (AUC) for LBGI and % <70 mg/dL ranged between 0.68 and 0.75, indicating that LBGI and % <70 mg/dL could significantly predict future SH. Significance of AUC regarding % <54 mg/dL were mixed (0.63-0.72). Positive and negative likelihood ratios ranged between 1.82 to 3.40 and 0.56 to 0.32, respectively. Suggested optimal cutoff values were remarkedly lower in open CGM than in masked CGM. Conclusion: These results indicate that CGM-derived hypoglycemic parameters have a good screening performance to significantly predict future clinical hypoglycemia. In addition, this analysis suggests that cutoff values to indicate elevated hypoglycemia risk in the future are substantially lower in open CGM than in masked CGM. ClinicalTrials.gov registration numbers: HypoDE: NCT02671968. DIAMOND: NCT02282397.

Excess deaths by sex and Age Group in the first two years of the COVID-19 pandemic in the United States

The COVID-19 pandemic hastened hundreds of thousands of deaths in the United States. Many of these excess deaths are directly attributed to COVID-19, but others stem from the pandemic’s social, economic, and health care system disruptions. This study compares provisional mortality data for age and sex subgroups across different time windows, with and without COVID-19 deaths, and assesses whether mortality risks are returning to pre-pandemic levels. Using provisional mortality reports from the CDC, we compute mortality risks for 22 age and sex subgroups in 2021 and compare against 2015–2019 using odds ratios. We repeat this comparison for the first twelve full months of the COVID-19 pandemic in the United States (April 2020–March 2021) against the next twelve full months (April 2021–March 2022). Mortality risks for most subgroups were significantly higher in 2021 than in 2015–2019, both with and without deaths involving COVID-19. For ages 25–54, Year 2 (April 2021–March 2022) was more fatal than Year 1 (April 2020–March 2021), whereas total mortality risks for the 65 + age groups declined. Given so many displaced deaths in the first two years of the COVID-19 pandemic, mortality risks in the next few years may fall below pre-pandemic levels. Provisional mortality data suggest this is already happening for the 75 + age groups when excluding COVID-19 deaths.

A nexus approach engaging water rights transfer for addressing water scarcity in energy and food production under uncertainty

Water rights transfer is significantly required for alleviating the ever-intensive water crisis, particularly for arid watersheds with abundant farmland and fossil fuels. However, focusing solely on the re-allocation of water rights and disregarding agricultural water saving potential imperil the security of Water-Energy-Food (WEF) nexus. Furthermore, randomness in water availability leads to water shortage risks and subsequent impact on the whole system. In this study, a risk-based optimization model (RWEF) was proposed to promote inter-sectoral water rights transfer through encouraging energy sector to invest in agricultural water-saving works and get paid back in water rights. Chance-constrained programming is incorporated to analyze the trade-offs between system benefits and water-shortage risks. The developed model was applied to the Inner Mongolia section of the Yellow River Basin, China to verify its effectiveness, considering different development levels of food and energy industries. Results indicated that 488 million m³ of water could be transformed from agriculture to energy, without compromising agricultural production. The main recipients of transferred water rights would be traditional coal-based industries, while it would be difficult for thermal power and most modern coal chemical industries to participate. The construction of water-saving works would help safeguard agricultural production under risks. Compared against two alternative models without water rights transfer mechanism, the average benefit acquired from RWEF under varied water-shortage risks would be at least 68% higher. Particularly, when confronted with extreme water-shortage risk and increased production demands, RWEF would still be able to support agricultural and energy production, while the alternative models being incapable.

Biological Invasions in Neotropical Regions: Continental Ichthyofauna and Risk Assessment Protocols

The objectives of this study were to compare four risk assessment protocols for non-native species in neotropical regions and to assess the potential application of these tools for the management of invasive species and conservation of the ichthyofauna in Brazil. The protocols Fish Invasiveness Screening Kit (FISK), Aquatic Species Invasiveness Screening Kit (AS-ISK), European Non-Native Species in Aquaculture Risk Assessment Scheme (ENSARS) and Fish Invasiveness Screening Test (FIST) were applied for the species Oreochromis niloticus, Coptodon rendalli, Poecilia reticulata and Apteronotus aff. albifrons, whose sources of introduction are aquaculture and fishkeeping. The species were classified as low, medium or high risk of invasion. The scores of the species O. niloticus, C. rendalli and P. reticulata classified them as high risk of invasion in all protocols, whereas A. aff. albifrons had medium risk in the protocols FISK and AS-ISK and low risk in the FIST. Although the results were similar for species whose impacts are widely described, less studied species may have their classification compromised by the lack of evidences in the literature. Despite the difficulties for practical application, the use of these tools may be encouraged, considering the potential threats of other invasive species emerging in Brazil. The comparison between the methods showed that the use of AS-ISK, combined with ENSARS in cases of introductions by aquaculture, provides important answers about ecological impacts on natural environments and about the stages of the aquaculture production chain that should be better inspected.

A protocol for screening potentially invasive non-native species using Weed Risk Assessment-type decision-support tools

There is increasing use worldwide of electronic decision-support tools to identify potentially invasive non-native species so as to inform policy and management decisions aimed at preventing or mitigating the environmental and socio-economic impacts of biological invasions. This study reviews the analytical approaches used to calibrate scores generated by the Weed Risk Assessment and subsequent adaptations thereof and provides a protocol for: (i) the identification of the assessor(s) who will carry out the screenings; (ii) the definition of the risk assessment area; (iii) the criteria for selection of the species for screening; and (iv) the a priori categorisation of the species into invasive or non-invasive necessary to compute the thresholds by which to distinguish between high-risk and medium-risk non-native species. This analytical approach represents an evidence-based and statistically robust means with which to inform decision-makers and stakeholders about policy and management of potentially invasive species and is expected to serve as a general reference of forthcoming screening applications of Weed Risk Assessment-type toolkits.

A causality analysis of risks to perishable product supply chain networks during the COVID-19 outbreak era: An extended DEMATEL method under Pythagorean fuzzy environment

In nowadays world, firms are encountered with many challenges that can jeopardize business continuity. Recently, the coronavirus has brought some problems for supply chain networks. Remarkably, perishable product supply chain networks, such as pharmaceutical, dairy, blood, and food supply chains deal with more sophisticated situations. Generally, during pandemic outbreaks, the activities of these industries can play an influential role in society. On the one hand, products of these industries are considered to be daily necessities for living. However, on the other hand, there are many new restrictions to control the coronavirus prevalence, such as closing down all official gatherings and lessening the work hours, which subsequently affect the economic growth and gross domestic product. Therefore, risk assessment can be a useful tool to forestall side-effects of the coronavirus outbreaks on supply chain networks. To that aim, the decision-making trial and evaluation laboratory approach is used to evaluate the risks to perishable product supply chain networks during the coronavirus outbreak era. Feedback from academics was received to identify the most important risks. Then, experts in pharmaceutical, food, and dairy industries were inquired to specify the interrelations among risks. Then, Pythagorean fuzzy sets are employed in order to take the uncertainty of the experts' judgments into account. Finally, analyses demonstrated that the perishability of products, unhealthy working conditions, supply-side risks, and work-hours are highly influential risks that can easily affect other risk factors. Plus, it turned out that competitive risks are the most susceptive risk in the effect category. In other words, competition among perishable product supply chain networks has become even more fierce during the coronavirus outbreak era. The practical outcomes of this study provide a wide range of insights for managers and decision-makers in order to prevent risks to perishable product supply chain networks during the coronavirus outbreak era.

The impact of geo-environmental factors on global COVID-19 transmission: A review of evidence and methodology

Studies on Coronavirus Disease 2019 (COVID-19) transmission indicate that geo-environmental factors have played a significant role in the global pandemic. However, there has not been a systematic review on the impact of geo-environmental factors on global COVID-19 transmission in the context of geography. As such, we reviewed 49 well-chosen studies to reveal the impact of geo-environmental factors (including the natural environment and human activity) on global COVID-19 transmission, and to inform critical intervention strategies that could mitigate the worldwide effects of the pandemic. Existing studies frequently mention the impact of climate factors (e.g., temperature and humidity); in contrast, a more decisive influence can be achieved by human activity, including human mobility, health factors, and non-pharmaceutical interventions (NPIs). The above results exhibit distinct spatiotemporal heterogeneity. The related analytical methodology consists of sensitivity analysis, mathematical modeling, and risk analysis. For future studies, we recommend highlighting geo-environmental interactions, developing geographically statistical models for multiple waves of the pandemic, and investigating NPIs and care patterns. We also propose four implications for practice to combat global COVID-19 transmission.

Implementation of the failure modes and effects analysis in a Hospital Radiopharmacy Unit

AIM

The aim of this study is the implementation in a Hospital Radiopharmacy Unit of a risk analysis methodology in order to proactively identify possible failure modes and prioritize corrective measures.

MATERIALS AND METHODS

By means of the failure modes and effects analysis (FMEA), the possible failure modes of each of the stages of the processes of prescription, preparation, and administration of radiopharmaceuticals for diagnostic and therapy were identified. From the variables of severity, probability and detectability, the risk was quantified using the Risk Priority Number (RPN) for each failure mode, sub-process, and type of radiopharmaceutical. Improvement measures were established and the reduction in the RPN value was calculated.

RESULTS

A total of 96 failure modes were identified (58 for diagnostic radiopharmaceuticals and 38 for therapy). Biunivocal identification of the patient with the radiopharmaceutical is the failure mode with the highest RPN (60) and the radiolabeling cell sub-process the one that has the highest risk (RPN 286). As a result of the improvement measures, the overall RPN was reduced by 22% for diagnostic radiopharmaceuticals and 20% for therapy. This reduction would be 46% and 31% respectively if radiopharmacy software and a barcode technology in the administration were implemented.

CONCLUSIONS

The application of the FMEA methodology as a risk analysis tool allows to identify the critical points of the processes related to radiopharmaceuticals and prioritize measures to reduce the risk.

Safety optimization in an accident-prone aquatic context: A qualitative study of drowning risk detection by public pool lifeguards

INTRODUCTION

Drownings occur in French public swimming pools (PCP) in spite ofconstant supervision by qualified lifeguards. This studyhypothesizesthat organizational aspects may affect the mission of pool supervision andtakes a systemic approach that views safety as an emergent property, and drowning as a multifactorial and long-term process that is not restricted to the end of an accidental sequence.

METHOD

We conducted a qualitative survey at four municipal poolsin France based on 30 semi-structured interviews.

RESULTS

The findings revealed that several interrelated elements influence the detection by lifeguards of bathers in distress: (a) their training, their conception of the profession, and the reasons that led them to enter this occupation; (b) their representations of the drowning risk and the evaluation of their ability to perceive such situations; (c) the question of regulation; and (d) the methods of dealing with this framework in daily operations, which involves trade-offs and appropriations at each level of the system.

CONCLUSIONS

In order to identify the most significant influences, it seems relevant:(a) to shift the focus away from these professionals; and (b) to prioritize an analysis of the functioning of the risk management system as a whole, not just critical or post-accident periods. In order to reduce the risk to swimmers, it seems preferable to identify the source of the constraints that weigh daily on lifeguards in charge of pool supervision.The functioning of PSP's is the end result of joint regulation processes likely to influence, positively or negatively, the identified feedback loops. An analysis of the pool supervision can help to identify early warning signs of vulnerability (which can sometimes be acted upon at low cost),identify the practical implications, and makepreventive recommendations.

Can there be a common, risk-based framework for decisions around live insect trade?

A network of scientists involved in shipment of live insects has met and generated a series of articles on issues related to live insect transport. The network is diverse, covering large-scale commercial interests, government operated areawide control programmes, biomedical research and many smaller applications, in research, education and private uses. Many insect species have a record of safe transport, pose minimal risks and are shipped frequently between countries. The routine shipments of the most frequently used insect model organism for biomedical research, Drosophila melanogaster, is an example. Successful large scale shipments from commercial biocontrol and pollinator suppliers also demonstrate precedents for low-risk shipment categories, delivered in large volumes to high quality standards. Decision makers need access to more information (publications or official papers) that details actual risks from the insects themselves or their possible contaminants, and should propose proportionate levels of management. There may be harm to source environments when insects are collected directly from the wild, and there may be harm to receiving environments. Several risk frameworks include insects and various international coordinating bodies, with experience of guidance on relevant risks, exist. All stakeholders would benefit from an integrated overview of guidance for insect shipping, with reference to types of risk and categories of magnitude, without trying for a single approach requiring universal agreement. Proposals for managing uncertainty and lack of data for smaller or infrequent shipments, for example, must not disrupt trade in large volumes of live insects, which are already supporting strategic objectives in several sectors.

[Risk communication of policy advising scientific organisations: a thematic outline using the example of the German Federal Institute for Risk Assessment]

Regulierungswissenschaftliche Organisationen wie das Bundesinstitut für Risikobewertung (BfR) sehen sich in ihrer wissenschaftsbasierten Risikokommunikation mit diversen Herausforderungen konfrontiert: Einerseits wird die Kommunikation gesundheitlicher Risiken immer komplexer und dementsprechend voraussetzungsreicher, weshalb unter anderem Fragen nach der Gesundheitskompetenz von Verbraucherinnen und Verbrauchern sowie zielgruppengerechter Risikokommunikation an Bedeutung gewinnen. Andererseits sehen sich die Wissensbestände regulierungswissenschaftlicher Organisationen zunehmend der Politisierung und öffentlichen Kritik ausgesetzt. In diesem Rahmen werden Fragen nach der Objektivität und Vertrauenswürdigkeit von Gutachten, Risikobewertungen und Stellungnahmen sowie der Legitimierung und Reputation regulierungswissenschaftlicher Organisationen relevant. Zusätzlich intensiviert wird dies durch das Aufkommen neuer Akteure in den sozialen Medien, die eigene Informations- und Kommunikationsmaterialien produzieren und veröffentlichen. In diesem Kontext verbreitete Fehl‑, Des- und Malinformationen stellen eine weitere Herausforderung dar, welche eng mit Fragen nach einer adäquaten Kommunikation über gesundheitliche Risiken sowie der Stabilisierung von Legitimität, Reputation und Vertrauenswürdigkeit zusammenhängt.

Der Artikel diskutiert verschiedene Lösungsansätze, darunter die Optimierung und visuelle Aufbereitung von Gesundheitsinformationen, die Ermöglichung gesellschaftlicher Partizipation und die Einbettung dieser Maßnahmen in das strategische Stakeholder- und Reputationsmanagement. Der Beitrag schließt mit einem Aufruf zu offenerer Diskussion inhärenter Dilemmata.

Open ventilator evaluation framework: A synthesized database of regulatory requirements and technical standards for emergency use ventilators from Australia, Canada, UK, and US

Development of emergency use ventilators has attracted significant attention and resources during the COVID-19 pandemic. To facilitate mass collaboration and accelerate progress, many groups have adopted open-source development models, inspired by the long history of open-source development in software. According to the Open-source Hardware Association (OSHWA), Open-source Hardware (OSH) is a term for tangible artifacts - machines, devices, or other physical things - whose design has been released to the public in such a way that anyone can make, modify, and use them. One major obstacle to translating the growing body of work on open-source ventilators into clinical practice is compliance with regulations and conformance with mandated technical standards for effective performance and device safety. This is exacerbated by the inherent complexity of the regulatory process, which is tailored to traditional centralized development models, as well as the rapid changes and alternative pathways that have emerged during the pandemic. As a step in addressing this challenge, this paper provides developers, evaluators, and potential users of emergency ventilators with the first iteration of a pragmatic, open-source assessment framework that incorporates existing regulatory guidelines from Australia, Canada, UK and USA. We also provide an example evaluation for one open-source emergency ventilator design. The evaluation process has been divided into three levels: 1. Adequacy of open-source project documentation; 2. Clinical performance requirements, and 3. Conformance with technical standards.

The Extent of Heavy Metal Pollution by Chemical Partitioning and Risk Assessment Code of Sediments of Sewage-Fed Fishery Ponds at East Kolkata Wetland, a Ramsar Site, India

Sewage contaminated with toxic metals is being naturally treated in ponds at East Kolkata Wetlands (EKW) for fish cultivation traditionally. From the aquatic phase, these metals get settled on sediment and undergo partitioning. Some fractions are available and may accumulate in the cultivated products. The present study highlights the degree of partition of heavy metals Lead (Pb), Cadmium (Cd) and Chromium (Cr) in these pond sediments. The study reveals that Pb and Cr are significant (39% and 30%, respectively) in Fe-Mn bound fractions. Residual fraction is in the order of Pb > Cr > Cd. The easily available fraction of metals recorded higher in Cd (43.0%) and Cr (42.0%).The risk assessment code (RAC) analysis records that these metals could be considered as potential risk group of metals for higher mobility and availability in these pond ecosystems and is a significant concern for aquaculture products.

Probabilistic risk analysis for coal mine gas overrun based on FAHP and BN: a case study

To analyze the risk of gas overrun in coal mines and improve the risk analysis, a novel risk analysis method was proposed based on FAHP and Bayesian network. The risk analysis framework consisted of causal reasoning, logical reasoning, and sensitivity analysis. The gas overrun risk analysis was conducted by taking the Laohutai Coal Mine in China as the research object. Specifically, based on prior knowledge and sample data, the probability of the gas overrun was 3.2%, belonging to a small probability event. However, the probability of gas concentration exceeding 1% was 12%, and there was still potential danger. Logical reasoning diagnosed and identified that wind speed and air leakage were the direct causes of gas overrun. Sensitivity analysis indicated that wind speed, human error, and ground stress were key factors of the gas overrun. The case study showed this fuzzy analytic hierarchy process (FAHP)-Bayesian network (BN)-based risk analysis method can provide real-time and dynamic decision support for gas overrun control and treatment in coal mines to ensure the safe and efficient mining.