Type Of Notification Research Articles

Notifications Related to Fraud and Adulteration in the Rapid Alert System for Food and Feed (RASFF) in 2000–2021

Fraudulent and adulterated food is produced mainly to reduce prices and attract consumers’ attention whilst threatening their economic interests, health, and safety. As such, this type of activity should be eliminated. This study’s aim was to identify the most common hazards related to food fraud and adulteration, reported in the Rapid Alert System for Food and Feed (RASFF) between 2000 and 2021, taking into account the product category (including individual products), country of origin, and notification type. We used Microsoft Excel (filtering, vertical-searching, transposition, and pivot table functions) and Statistica 13.3 (two-way joining cluster analysis) to analyse similarities between the hazards identified throughout the research period. Notifications relating to food fraud and adulteration accounted for 18.7% of all RASFF notifications, fluctuating between 1000 and 1200 per year in recent years. These mainly included hazards related to composition and novel foods in dietetic foods, food supplements and fortified foods, sulphites in fruits and vegetables, colours in cereals and bakery products, or Sudan in herbs and spices. Dietetic foods, dietary supplements, and fortified foods were mainly reported as alerts and information notifications, meaning that they were already available on the common European internal market. The other products originated mainly from outside the European Union (Asia—Turkey, Uzbekistan, India and Africa—Ghana, Nigeria) and were submitted on the basis of border rejections. Therefore, it is necessary to continue closely monitoring imported products at the EU border to ensure food safety, avoiding fraud and adulteration and protecting consumers’ financial interests.

Objective monitoring of loneliness levels using smart devices: A multi-device approach for mental health applications.

Loneliness is linked to wide ranging physical and mental health problems, including increased rates of mortality. Understanding how loneliness manifests is important for targeted public health treatment and intervention. With advances in mobile sending and wearable technologies, it is possible to collect data on human phenomena in a continuous and uninterrupted way. In doing so, such approaches can be used to monitor physiological and behavioral aspects relevant to an individual's loneliness. In this study, we proposed a method for continuous detection of loneliness using fully objective data from smart devices and passive mobile sensing. We also investigated whether physiological and behavioral features differed in their importance in predicting loneliness across individuals. Finally, we examined how informative data from each device is for loneliness detection tasks. We assessed subjective feelings of loneliness while monitoring behavioral and physiological patterns in 30 college students over a 2-month period. We used smartphones to monitor behavioral patterns (e.g., location changes, type of notifications, in-coming and out-going calls/text messages) and smart watches and rings to monitor physiology and sleep patterns (e.g., heart-rate, heart-rate variability, sleep duration). Participants reported their loneliness feeling multiple times a day through a questionnaire app on their phone. Using the data collected from their devices, we trained a random forest machine learning based model to detect loneliness levels. We found support for loneliness prediction using a multi-device and fully-objective approach. Furthermore, behavioral data collected by smartphones generally were the most important features across all participants. The study provides promising results for using objective data to monitor mental health indicators, which could provide a continuous and uninterrupted source of information in mental healthcare applications.

Emergency Department Presentations for Injuries Following Agency-Notified Child Maltreatment: Results From the Childhood Adversity and Lifetime Morbidity (CALM) Study.

Child maltreatment (CM) is associated with negative health outcomes in adulthood, including deliberate self-harm (DSH), suicidal behaviours, and victimisation. It is unknown if associations extend to emergency department (ED) presentations for non-DSH related injuries. Birth cohort study data was linked to administrative health data, including ED presentations for non DSH related injuries and agency-reported and substantiated notifications for CM. Adjusted analyses (n = 6087) showed that any type of agency-reported notification for CM was significantly associated with increased odds of ED presentation for injuries (aOR = 1.57; 95% CI 1.32-1.87). In moderation analyses, women yielded significantly higher odds of notified and substantiated physical abuse, substantiated emotional abuse, and being subject to more than one type of substantiated abuse than males. ED presentations for injuries could be a proxy for risky behaviours, disguised DSH/suicidal behaviours, or physical abuse. The consistent findings in women may point to victimisation via interpersonal violence.

Machine Learning-Assisted Wearable Thermo-Haptic Device for Creating Tactile Sensation

The tactile modality is an important source of human experience and emotional expression, either on its own or by intensifying and complementing other senses, influencing our interactions with objects, people, animals and other beings. Following this, developed haptic devices transmit information to the user using tactile stimuli to increase or change sensory input. Haptics are an important factor that makes virtual worlds and remote interpersonal interaction tangible. Haptic feedback consists of more components that make an experience physically perceptible and realistic. Haptic feedbacks are widely used in mobile and wearable devices to convey various types of notifications to users. In this study, it was aimed to develop a new generation of wearable gloves against the hypoesthesia problem by combining artificial intelligence and thermohaptic, which are popular in many fields.

Contributing Factors to Adverse Events in Long-Term Care Facilities in Ireland, a Content Analysis

ObjectivesThere is substantial research on contributing factors to adverse events (AEs) in acute settings. Little is known about AEs in long-term care facilities (LTCFs). Our aim was to identify contributing factors to AEs from LTCFs for older persons and people with disability to inform quality improvement. DesignContent analysis of statutory notifications of AEs from LTCFs using a modified version of the Human Factors Analysis and Classifications System (HFACS) applied to health care. SettingA sample of high risk-rated notifications of AEs received by the regulator in 2018 and 2019 was drawn from the Database of Statutory Notifications from Social Care in Ireland (n = 156). MethodsTwo researchers independently analyzed notifications to identify contributing factors using our modified HFACS. The number of factors identified in each level, subcategory, and nanocode of the HFACS was calculated along with percentage representation of factors within notifications and percentage contribution of individual factors to the total number of factors identified. The number and percentage contributions of factors were also calculated, disaggregated by notification type. ResultsContributing factors from all levels of the HFACS were identified. The most common contributing factor was “Resident factors” followed by “Unsafe acts.” No contributing factors were attributed to 68 notifications (43.6%). Multiple contributing factors were attributed to 45 notifications (28.8%). The largest percentage of factors was identified in notifications of serious injuries (27.4%). Conclusion and ImplicationsIt is the responsibility of LTCFs to account for “Resident factors” in system design, risk management, and care plans. Developing systems and processes that identify where residents have higher risk of harm may reduce the occurrence of high-risk events and thus improve resident safety. The large proportion of notifications where no contributing factors were identified suggests the need for improved reflection and reporting from LTCFs and for more specific questions on notification forms.

AIoT in Agriculture: Safeguarding Crops from Pest and Disease Threats.

A significant proportion of the world's agricultural production is lost to pests and diseases. To mitigate this problem, an AIoT system for the early detection of pest and disease risks in crops is proposed. It presents a system based on low-power and low-cost sensor nodes that collect environmental data and transmit it once a day to a server via a NB-IoT network. In addition, the sensor nodes use individual, retrainable and updatable machine learning algorithms to assess the risk level in the crop every 30 min. If a risk is detected, environmental data and the risk level are immediately sent. Additionally, the system enables two types of notification: email and flashing LED, providing online and offline risk notifications. As a result, the system was deployed in a real-world environment and the power consumption of the sensor nodes was characterized, validating their longevity and the correct functioning of the risk detection algorithms. This allows the farmer to know the status of their crop and to take early action to address these threats.

The impact of indirect notification of a cancer diagnosis and a risk model based on it to predict the prognosis of postoperative stage T3 esophageal cancer patients.

Chinese doctors are required to inform patients' direct relatives of a cancer diagnosis rather than the patients themselves. The disease may be hidden from patients by their family members, which could result in severe outcomes. We selected postoperative T3 esophageal cancer (EsC) patients hospitalized from June 2015 to December 2019 as research subjects. The patients were divided into a direct-notification group and an indirect-notification group. Several variables were used to evaluate both groups' 36-month progress-free survival (PFS). A risk prediction model of prognosis based on the risk score was established, which was assessed using the area under the curve (AUC) of the receiver operating characteristic curve. One hundred and thirteen patients were enrolled in the training group and forty-eight in the validation group. Cox multivariate regression analysis revealed that males, late stage, poor pathological differentiation, and indirect notification were independent worse risk factors for postoperative T3 stage EsC patients at 36-month PFS (hazard ratio (HR) = 0.454, 95% confidence interval (CI): 0.254-0.812, P = .008; HR = 1.560, 95% CI: 1.006-2.420, P = .047; HR = 0.595, 95% CI: 0.378-0.936, P = .025; HR = 2.686, 95% CI: 1.679-4.297, P < 0.001, respectively). The type of notification was the best correlation factor. The risk score was calculated as follows: risk score = 0.988 × cancer notification (indirect = 1, direct = 0)-0.790 × sex (female = 1, Male = 0) + 0.445 × stage (IIIB = 1, IIA + IIB = 0)-0.519 × pathological differentiation (moderately + well = 1, poorly = 0). The model had a sensitivity of 64.8% and specificity of 81.8%, with the AUC at 0.717 (95% CI: 0.614-0.810) in internal verification, and a sensitivity of 56.8% and specificity of 100%, with the AUC at 0.705 (95% CI: 0.651-0.849) in external validation. The model had good internal and external stability. The model showed a Brier score of 0.18. Indirect notification of a cancer diagnosis was an important negative predictor of postoperative EsC patients' PFS. The model displayed good accuracy and stability in the prediction of risk for cancer progression.

A data-driven approach for prioritising microbial and chemical hazards associated with dairy products using open-source databases

This study presents a data-driven approach for classifying food safety alerts related to chemical and microbial contaminants in dairy products using the Rapid Alert System for Food and Feed (RASFF) and the World Health Organization (WHO)’s Global Environmental Monitoring System (GEMS) food contaminants databases. This research aimed to prioritise microbial and chemical hazards based on their presence and severity through exploratory data analysis and to classify the severity of chemical hazards using machine learning (ML) approaches. It identified Listeria monocytogenes, Escherichia coli, Salmonella, Pseudomonas spp., Staphylococcus spp., Bacillus cereus, Clostridium spp., and Cronobacter sakazakii as the microbial hazards of priority in dairy products. The study also prioritised the top ten chemical hazards based on their presence and severity. These hazards include nitrate, nitrite, ergocornine, 3-MCPD ester, lead, arsenic, ochratoxin A, cadmium, mercury, and aflatoxin (G1, B1, G2, B2, G5 and M1). Using ML techniques, the accuracy rate of classifying food safety alerts as either ‘serious' or ‘non-serious' was up to 98 %. Additionally, the study identified Reference dose (RfD), substance amount, notification type, product, and substance as the most important features affecting the ML models' performance. These ML models (decision trees, random forests, k-nearest neighbors, linear discriminant analysis, and support vector machines) were also validated on an external dataset of RASFF alerts related to chemical contaminants in dairy products. They achieved an accuracy of up to 95.1 %. The study's findings demonstrate the models' robustness and ability to classify food safety alerts related to chemical contaminants in dairy products, even on new data. These results can enhance the development of more effective machine-learning models for classifying food safety alerts related to chemical contaminants in dairy products, highlighting the importance of developing accurate and efficient classification models for timely intervention.

Hazards in Products of Plant Origin Reported in the Rapid Alert System for Food and Feed (RASFF) from 1998 to 2020

The elimination or reduction of hazards in plants is an important part of the “From field to fork” strategy adopted in the European Green Deal, where a sustainable model is pursued in the food system. In the European Union (EU), the Rapid Alert System for Food and Feed (RASFF) is in place to provide information on risks in the food chain. The largest number of notifications in this system concerns plants, followed by products of animal origin and other products. The goal of the study was to examine RASFF notifications for products of plant origin with respect to hazard, year, product, notifying country, origin country, notification type, notification basis, distribution status and actions taken in 1998–2020. Data were extracted from the RASFF notifications’ pre-2021 public information database. A cluster analysis using joining and the two-way joining method was applied. The notifications mainly concerned aflatoxins in pistachios from Iran, ochratoxin A in raisins from Turkey, pesticide residues in peppers from Turkey, okra, curry, rice from India, tea from China and India, and pathogenic micro-organisms in sesame from India, and also basil, mint and betel from Thailand, Vietnam and Lao Republic. To ensure the safety of food of plant origin, it is necessary to adhere to good agricultural and manufacturing practices, involve producers in the control of farmers, ensure proper transport conditions (especially from Asian countries), ensure that legislative bodies set and update hazard limits, and ensure their subsequent control by the authorities of EU countries. Due to the broad period and scope of the studies that have been carried out and the significance of the European Union in the food chain, the research results can improve global sustainability efforts.

Hazards in Seafood Notified in the Rapid Alert System for Food and Feed (RASFF) in 1996–2020

Seafood covering fish, crustaceans, molluscs and cephalopods is broadly recognised for its nutritional value and popularity, but it can pose some hazards to health to the potential consumer. The aim of the study was to analyse Rapid Alert System for Food and Feed (RASFF) notifications for seafood over the period 1996–2020 by hazard, year, product, notifying country, country of origin, notification type, notification basis, distribution status and action taken. The research applied cluster analysis using the joining and two-way joining methods. The main reported hazards were micro-organisms (Listeria, Salmonella, Escherichia coli, Vibrio, norovirus, mesophiles, Enterobacteriaceae and histamine), heavy metals (mercury and cadmium), veterinary products (nitrofuran, chloramphenicol and leucomalachite green), controls (poor temperature control and hygienic state), parasites (Anisakis) and additives/allergens (sulphite). The reported seafood products originated mainly from European and Asian countries and were notified on the basis of official or border controls, respectively. In order to minimize or eliminate risks, it is important to have the right activity of control authorities, appropriate legislation at the European and national levels and awareness at the different stages of the food chain.

ANALYSIS OF RASFF NOTIFICATIONS: 2021 FOOD AND FOOD CONTACT MATERIAL DATA REVIEW

Rapid Alert System for Food and Feed (RASFF) is a system that provides rapid information exchange to ascertain food safety. The aim of the current study is to prepare a detailed report of food and food contact material notifications of the year 2021 in RASFF portal. The related data in the internet tool were extracted and analyzed for subject, notification basis, notification type, products, notifying country, risk level, distribution status and measures taken. A total of 4438 notifications were identified and the most frequent hazard was pesticides. Alert, border rejection, information notification for attention, information notification for follow-up and news notification classes contained 1455, 1433, 972, 564 and 13 notices, respectively. The most frequently notifying country was Germany, followed by Spain. The mostly notified product category was fruits and vegetables and the majority of the cases had serious risk degree.

Public Reporting of Adverse Events From Long-Term Care Facilities for Older Persons and People With Disability in Ireland 2013-2019: Development of an Openly Accessible Database and Descriptive Analyses.

To describe the development of an analyzable database of statutory notifications received from long-term care facilities (LTCFs) and to describe trends in receipt of notifications from 2013 to2019. Description of database development with descriptive and trend analyses. LTCFs for older persons and for people with disability in Ireland. Data on notifications received and on centers were extracted from a system internal to the health and social services regulator and combined into an analyzable database. Variables were screened for personal information, cleaned, transformed, or redacted and combined into a database suitable for open access publication. Descriptive analyses of the volume of notifications, trends over time and breakdown by service type, notification type, and risk-rating were conducted. The Database of Statutory Notifications from Social Care in Ireland was developed and an open access version published in February 2021. Protection of personal data was an important consideration in publishing the data publicly. Uses of the database include examination of national trends and identification of determinants of adverse events and areas for quality improvement. The number of notifications received increased over time. Quarterly notifications contributed to the largest proportion of notifications (older persons, 36.7%; disability, 39.1%). This was followed by serious injury notifications in LTCFs for older persons (33.3%) and abuse allegation notifications in LTCFs for people with disability (36.0%). Less than 1% of individual notifications were risk-rated red (highest severity level of impact on resident welfare). The types of notifications that were collectively risk-rated highest were staff misconduct, abuse allegations, and outbreaks of infectious disease. The methodology and findings can inform publications of notifications, planning and resourcing for receipt and submission of notifications, target areas for quality improvement initiatives, mandating of timelines for receipt of notifications, and the mandating of notifications in legislation.

Modification of IoT Enabled Fertibotix Machine

Abstract: Soil is of great importance to agriculture, especially the moisture and nutrients in the soil are the essential ingredients for growing plants and crops. Therefore, benefits and importance of a soil moisture and nutrient monitoring system in modern agriculture and gardening is undeniable. It can also be an interesting feature of an intelligent home or smart agriculture system using the internet of things (IoT) technology. This paper presents an IoT application in Arduino platform aiming to monitor the change in soil moisture and Nitrogen (N), Phosphorus (P), Potassium (K) (NPK) value for an indoor plant using moisture sensors and optical transducers. Other functionalities and important features of this prototype include online data display infographic as user feedback, level-based nutrient classification for enabling proper type of fertilizer selection, hardware and e-mail notification of moisture and nutrients' easily accessible and user-friendly smartphone app.

Change of HPV vaccination rates in Japan: the effect of individual notifications implemented by local governments.

In Japan, in June 2013, The Ministry of Health, Labor and Welfare (MHLW) decided to temporarily suspend its official recommendation for the participation of girls in the national immunization program. The HPV vaccination rate in Japan soon declined to below 1%. In October 2020, the MHLW notified that the municipalities could and should begin to individually notify girls and their parents targeted for routine vaccination. We have examined how that type of individual notification has affected the number of vaccinations. From 12municipalities (with a combined total population of approximately 4.06 million), we collected vaccination data for all girls who attended grades 6 through 10 from April 2019 to March 2021. We analyzed the number of initial-round vaccinations that occurred by month and the timing and the subjects of the individual notifications. The annual vaccination rate for tenth-grade students in 2020 in the six municipalities that had implemented individual notification was 9.46% (342/3618), which was significantly higher than the rate of 3.22% (54/1676) in the three municipalities that had not implemented individual notification (p < 0.001). On the other hand, the annual vaccination rate for the sixth to ninth-grade students in 2020 in the six municipalities that had implemented individual notification was not significantly (p = 0.56) higher than the rate in the three municipalities that did not: 1.43% (197/13,785) versus 1.33% (83/6260), respectively. This study clearly demonstrates the importance of providing information for routine vaccination directly to the targets and their parents.

Notifications on Pesticide Residues in the Rapid Alert System for Food and Feed (RASFF).

Pesticides are commonly used to protect plants against various pests and to preserve crops, but their residues can be harmful for human health. They are the third most widely reported hazard category in the European Rapid Alert System for Food and Feed (RASFF). The purpose of the study was to identify the most frequently notified pesticides in the RASFF in 1981–2020, considering: year, notification type, product category, origin country, notifying country, notification basis, distribution status and action taken. The data from the RASFF database was processed using: filtering, transposition, pivot tables and then subjected to cluster analysis: joining (tree clustering) and two-way joining methods. Pesticides were most commonly reported in fruits and vegetables and herbs and spices following border controls and rejections. The products usually came from India or Turkey and were not placed on the market or were not distributed and then destroyed. The effectiveness of the European Union border posts in terms of hazards detection and mutual information is important from the point of view of protecting the internal market and ensuring public health. It is also necessary to increase the awareness of pesticide users through training and the activity of control authorities in the use of pesticides.

Analysis of RASFF notifications on cereals and cereal-based products contaminated with mycotoxins in the period from 01/01/2015 to 31/12/2019

The Rapid Alert System for Food and Feed (RASFF) is designed to respond promptly to the health risks associated with food, food contact materials or feed by enabling fast exchange of information between bodies and institutions involved in the system. Mycotoxins, secondary metabolites produced by moulds, are common contaminants found in cereals and cereal-based product all over the world that can be harmful to human (and animal) health. The aim of this study was to analyse RASFF notifications on cereals and cereal-based products contaminated with mycotoxins in the period from 01/01/2015 to 31/12/2019. All data were downloaded from the RASFF database (RASFF portal) and processed in MS Excel 2010. The collected data provided information on the: notifying country, country(ies) of origin and distribution of the contaminated product, notification basis, notification type, risk decision, distribution status, action taken, type of mycotoxin and specific cereal or cereal-based product in which the mycotoxin has been determined. Nearly half of the reported food products originated from Italy, Pakistan, India, Serbia and Sri Lanka. More than half notifications were published by Germany, Switzerland, Italy and Belgium. Only in less than one-fifth of the notifications the country of origin of the contaminated product was also the notifying country. Contaminated products in more than two-thirds of cases were maize, rice and rye grains and their products. Aflatoxin B1 was the most frequent mycotoxin, present in more than two-fifths of contaminated cereals and cereal-based products. The majority of the notifications were classified as alert notifications and a large majority of total number of notifications were of serious risk. Regarding the distribution status, over two-fifths of contaminated products were distributed to other member countries and in almost half of the notifications contaminated products were withdrawn or recalled.

Analysis of RASFF notifications on allergens in cereals and cereal-based products in the period from 01/01/2015 to 31/12/2019

The aim of this study was to analyse RASFF notifications on allergens in cereals and cereal-based products in the period from 01/01/2015 to 31/12/2019. Allergies caused by food intake due to the presence of an allergen can pose a serious danger to the health of consumers. In order to promptly respond to any health risks related to food, food contact materials, or feed, The Rapid Alert System for Food and Feed (RASFF) enables quick information exchange between the bodies and institutions involved in the system. All data on allergens in cereals and cereal-based products were downloaded from the RASFF database (RASFF portal) and processed in MS Excel 2010. The collected data provided information on the: notifying country, country(ies) of origin and distribution of the food product in question, notification basis, notification type, risk decision, distribution status, action taken, allergen present and respective food product. More than half of the reported food products originated from Italy, Germany, United Kingdom and Netherlands. Almost half of notifications were published by United Kingdom, Germany, Italy and Spain. The most common allergens were milk, gluten and soya. Products in question in more than two-fifths of cases were pastry (sweet or savoury). The majority of the notifications were classified as alert notifications and a vast majority of total number of notifications were of serious risk. Allergen notifications were mainly based on official controls on the market and on company's own check but some were based on food poisoning. Just over two-thirds of products in question were distributed to other (member and non-member) countries and in over two-thirds of the notifications products in question were withdrawn or recalled.

Encouraging Hearing Loss Prevention in Music Listeners Using Personalized Technology: Questionnaire Study.

BackgroundNoise-induced hearing loss (NIHL) affects millions of people despite being almost completely preventable. For recreational music listening through personal listening equipment (such as earbuds), it seems that listeners do not yet have a way to accurately assess their risk of developing hearing loss and prevent it accordingly.ObjectiveThe aim of this study is to analyze the perceived utility of a hypothetical device that encourages NIHL prevention based on listeners’ exposure to noise and to determine the most effective methods of such encouragement. Here, we describe 3 different potential NIHL risk notification method types, as follows: auditory, external visual, and visual.MethodsAn open, web-based survey was created on Google Forms, and the link was posted to Amazon’s Mechanical Turk as well as music-related Reddit communities. The survey was designed to gauge each respondent’s self-assessed NIHL awareness, willingness to lower their audio if reminded, and NIHL risk notification type preference. The likelihood of a specific notification type to encourage NIHL prevention among its users was based on the average of each user’s responses to 2 survey questions. Data collection started on July 13, 2020, and ended on July 17, 2020.ResultsOf the 116 respondents, 92 (79.3%) reported having prior awareness about NIHL; however, 60 (51.7%) described doing nothing to prevent it despite 96 (82.8%) feeling a moderate, high, or extreme risk of developing NIHL. Of those who already prevented NIHL, 96% (53.5/56) described using estimates to guide their prevention instead of using data. A Kruskal-Wallis test corrected for ties showed that despite the visual NIHL risk notification type being selected by the highest number of participants (84/116, 72.4%), the auditory type had a significantly higher (H1=6.848; P=.03) average percentage likelihood of encouraging NIHL prevention (62%, SD 24%) among the 40 respondents who chose it, with a median likelihood of 56% (95% CI 50%-75%). The visual type’s average likelihood was 50% (SD 28.1%), with a median of 50% (95% CI 37.5%-56.3%). Regardless of the NIHL risk notification type, 69% (80/116) of respondents were not opposed to using NIHL risk notifications and lowering their audio volume accordingly.ConclusionsThe hypothetical device detailed here was thought to be useful because most respondents (82.8%, 96/116) felt an extreme to moderate risk of developing NIHL and such a device could provide accurate data to those who currently use estimates to prevent NIHL, and most respondents were willing to act on NIHL risk notifications. The most effective NIHL risk notification type seemed to be the auditory type, but many aspects of this study need further research to determine which implementation method should reach the public.

Residues of veterinary drugs in fish and fish products: An analysis of RASFF data over the last 20 years

An analysis of the notifications in the European Union (EU) Rapid Alert System for Food and Feed (RASFF) portal due to residues of veterinary drugs in fish and fish products over the period 2001–2021 was conducted examining the following data: number and type of notifications; year of notification; notification basis; notifying country; country of origin; action taken; distribution status; risk decision; fish product type; residue found. A total of 292 notifications were found (mean number/year 9.8 ± 13.8 SD), mostly information notifications (60.9%). The most common notification basis was “border control - consignment detained” (38.4%), followed by “official control on the market” (37.9%) and “border control - consignment released” (13.7%). Over half (54.1%) of the notifications were issued by the United Kingdom, Germany and Spain, dominant countries in the fish processing market. Thirty-one countries of origin were recorded, but 48.6% of the notifications were referred to products from Vietnam, followed by China (15.7%), that are among the leading fish producing countries. The most common actions taken were re-dispatch (23.3%), followed by recall from consumer (10.3%), withdrawal from recipients (9.9%), destruction (9.6%), and import not authorised (9.2%). Overall, 28.8% of the notifications involved fish products belonging to the Pangasiidae family ( Pangasius spp. and Pangasianodon spp.), followed by tilapia (12.7%), trout (11.0%), eel (8.6%), catfish (7.9%) and salmon (3.4%). Triphenylmethane dyes and their metabolites were the most frequent category of residues found, accounting for 51.4% of the total notifications, followed by a wide range of antibiotics classes, of which nitrofurans and metabolites (19.5%) were the most common, while amphenicols (6.8%), quinolones and fluoroquinolones (6.5%), sulphonamides and potentiators (5.1%), tetracyclines and metabolites (3.4%) and other classes were less represented. Avermectins and unspecified residues were also found in a few cases (2.7%). The annual frequency of these issues varied and was probably influenced by dedicated monitoring plans, as well as by specific sanitary problems occurring in farms. Nevertheless, by providing historical trends and current issues, our analysis identified hazards to be closely monitored, through coordinated official controls especially in the most involved countries. • 20 years of RASFF notifications for veterinary drugs residues in fish products were analysed. • Triphenyl-methane dyes were the most frequent residue found (51.4% notifications). • Several antibiotics classes were found, mainly nitrofurans (19.5% of the notifications). • Historical and current issues to be specifically monitored were pointed out.

Takeover performance of older drivers in automated driving: A review

IntroductionThe introduction of automated vehicles to the road environment brings new challenges for older drivers. Level 3 of conditional automation requires drivers to take over control of their vehicle whenever the automated system reaches its limits. Even though autonomous vehicles may be of great benefit to older drivers in terms of safely maintaining their mobility, a better understanding of their takeover performance remains crucial. The objective of this review of the literature is to shed more light on the effects that aging has on takeover performance during automated driving. MethodsThree database searches were conducted: PsychINFO, Web Of Sciences, and TRID. Studies from the last decade which included groups of older drivers were reviewed. ResultsAfter checking through abstracts and texts of articles, 9 articles, 4 proceedings papers, and 1 technical report were included in this review. All studies included a driving simulator that refers to level 3 of automation (which requires supervision by the driver). Five out of fourteen studies showed that older adults had poorer takeover performance (in terms of takeover time and takeover quality) than younger adults. However, several factors, such as the type of non-driving related task (NDRT), were seen to influence takeover performance in older adults. Speed, type and duration of notification interval, distribution and duration of driving modes, and number of takeovers were all also factors of influence. ConclusionThis review synthesizes the results of 14 articles which investigate the effects of age-related changes on takeover performance. Various external factors as NDRTs, speed, type and duration of notification to take over, duration of the automated phase, distribution of the automated/manual phases may affect takeover performance in older adults. Even if the majority of articles showed that older adults are globally slower at taking over a vehicle than younger adults, findings concerning take over quality yield divergent results. It's probably due to age related cognitive changes, particularly in executive functions or to a great heterogeneity in this population. This literature review highlights the need to develop new research on the impact of aging on takeover performance.