Background: Globally, infections are the third leading cause of neonatal mortality. Predominant risk factors for facility-born newborns are poor hygiene practices that span both the facility and home environments. Current improvement interventions focus on only one environment and tar-get limited caregivers, primarily birth attendants and mothers. To inform the design of a hand hygiene behaviour change intervention in rural Cambodia, a formative mixed-methods research study was conducted to investigate the context specific behaviours and determinants of hand-washing among healthcare workers, maternal and non-maternal caregivers along the early new-born care continuum. Methods: Direct observations of hygiene practices of all individuals providing care to 46 newborns across eight facilities and associated communities were completed and hand hygiene compliance assessed in analysis. Semi structured interactive interviews were subsequently conducted with 35 midwives and household members to explore the corresponding cognitive, emotional, and environmental factors influencing the observed key hand hygiene behaviours. Results: Hand hygiene opportunities during newborn care were frequent in both set-tings (n = 1319) and predominantly performed by mothers, fathers and non-parental caregivers. Compliance to hand hygiene protocol across all caregivers, including midwives, was inadequate (0%). Practices were influenced by the lack of accessible physical infrastructure, time, increased workload, low infection risk perception, nurture-related motives, norms and inadequate knowledge. Conclusion: Our findings indicate that an effective intervention in this context should be multi-modal to address the different key behaviour determinants and target a wide range of caregivers.

: Mistrust, amplified by numerous artificial intelligence (AI) related incidents, has caused the energy and industrial sectors to be amongst the slowest adopter of AI methods. Central to this issue is the black-box problem of AI, which impedes investments and fast becoming a legal hazard for users. Explainable AI (XAI) is a recent paradigm to tackle this challenge. Being the backbone of the industry, the prognostic and health management (PHM) domain has recently been introduced to XAI. However, many deficiencies, particularly lack of explanation assessment methods and uncertainty quantification, plague this young field. In this paper, we elaborate a framework on explainable anomaly detection and failure prognostic employing a Bayesian deep learning model to generate local and global explanations from the PHM tasks. An uncertainty measure of the Bayesian model is utilized as marker for anomalies expanding the prognostic explanation scope to include model’s confidence. Also, the global explanation is used to improve prognostic performance, an aspect neglected from the handful of PHM-XAI publications. The quality of the explanation is finally examined employing local accuracy and consistency properties. The method is tested on real-world gas turbine anomalies and synthetic turbofan data failure prediction. Seven out of eight of the tested anomalies were successfully identified. Additionally, the prognostic outcome showed 19% improvement in statistical terms and achieved the highest prognostic score amongst best published results on the topic.

We aimed to explore university students’ perceptions and experiences of SARS-CoV-2 mass asymptomatic testing, social distancing and self-isolation during the COVID-19 pandemic. This qualitative study comprised of four rapid online focus groups conducted at a higher education institution in England during high alert (tier 2) national COVID-19 restrictions. Data were analysed thematically. Participants were purposively sampled university students (n = 25) representing a range of gender, age, living circumstances (on/off campus) and SARS-CoV-2 testing/self-isolation experiences. Six themes with 16 sub-themes emerged from the analysis of the qualitative data: ‘Term-time Experiences’, ‘Risk Perception and Worry’, ‘Engagement in Protective Behaviours’, ‘Openness to Testing’, ‘Barriers to Testing’ and ‘General Wellbeing’. Students described feeling safe on campus, believed most of their peers are adherent to protective behaviours and were positive towards asymptomatic testing in university settings. University communications about COVID-19 testing and social behaviours need to be timely and presented in a more inclusive way to reach groups of students who currently feel marginalised. Barriers to engagement with SARS-CoV-2 testing, social distancing and self-isolation were primarily associated with fear of the mental health impacts of self-isolation, including worry about how they will cope, high anxiety, low mood, guilt relating to impact on others and loneliness. Loneliness in students could be mitigated through increased intra-university communications and a focus on establishment of low COVID-risk social activities to help students build and enhance their social support networks. These findings are particularly pertinent in the context of mass asymptomatic testing programmes being implemented in educational settings and high numbers of students being required to self-isolate. Universities need to determine the support needs of students during self-isolation and prepare for the long-term impacts of the pandemic on student mental health and welfare support services.

The COVID-19-medical emergency has ended worldwide, yet there is still a need to evaluate the psychological impact of these years of unprecedented changes on students’ life. Methods: This study aims to assess and compare COVID-19-related stressors (Relationships-and-Academic-Life; Isolation; Fear-of-Contagion) and psychophysical symptoms reported by university students in April-2020, April 2021, and April 2022. The predictive role of COVID-19-related stressors on psychophysical symptoms within each time was also tested. Data were collected among 637 university students in April-2020 (n = 197), April-2021 (n = 200), April-2022 (n = 240). Results: In April-2022, perceived Isolation and Fear-of-Contagion decreased from the peak registered in April-2021, but stress related to Relationships-and-Academic-Life remained noteworthy high. A sharp and ongoing increase in psychophysical symptoms was found, with more than 50% of students reporting clinical levels of Sleep-Disorders, Depression, Psychoticism, and Interpersonal-Sensitivity. In April-2022, students still perceiving stress related to Relationships-and-Academic-Life and Isolation were at risk for Anxiety, Somatization, and Sleep-Disorders, while those still perceiving stress related to Fear-of-Contagion were also at risk for Depression, Obsessive-Compulsive, and Psychoticism. Conclusion: Findings emphasized the long-lasting detrimental effects of the COVID-19-related stress. Interventions must pinpoint the complex post-pandemic adjustment process and their effects on university students' psychophysical health.

Animal-assisted pedagogy (AAP) is well known in classroom practice, but scientific evidence is still lacking. At the same time, the biggest challenge in education systems worldwide is the social in-tegration of students. In a pre-post design, 30 heterogeneous students (16f/14m) from four different school classes (grades 5-7) were interviewed (problem-centred interview) about their social inclu-sion and their social climate in class before and after being taught selected subjects with a school dog (of different breeds) for one school term. At the second measurement point, they were also asked about their perception of AAP. The data was analysed both qualitatively (Kuckartz) and in terms of the number of quotes on the main topics using MAXQDA analysis software. The presence of a dog in the classroom leads to an improved social climate and more social integration. In ad-dition, the perception of the other students and the teacher changes to a more positive and friendly image. Through AAP, a new social role is added to the classroom, where caring and bonding are prioritised. Social interaction and norms are influenced and sterotypical and individual roles can be changed. Therefore, AAP can be a key to promoting social inclusion in the school environment.

The aim of Predictive Maintenance, within the field of Prognostics and Health Management (PHM), is to identify and anticipate potential issues in the equipment before these become critical. The main challenge to be addressed is to assess the amount of time a piece of equipment will function effectively before it fails, which is known as Remaining Useful Life (RUL). Deep Learning (DL) models, such as Deep Convolutional Neural Networks (DCNN) and Long Short-Term Memory (LSTM) networks, have been widely adopted to address the task, with great success. However, it is well known that this kind of black box models are opaque decision systems, and it may be hard to explain its outputs to stakeholders (experts in the industrial equipment). Due to the large number of parameters that determine the behavior of these complex models, understanding the reasoning behind the predictions is challenging. This work presents a critical and comparative revision on a number of XAI methods applied on time series regression model for PM. The aim is to explore XAI methods within time series regression, which have been less studied than those for time series classification. The model used during the experimentation is a DCNN trained to predict the RUL of an aircraft engine. The methods are reviewed and compared using a set of metrics that quantifies a number of desirable properties that any XAI method should fulfill. The results show that GRAD-CAM is the most robust method, and that the best layer is not the bottom one, as is commonly seen within the context of Image Processing.

(1) Background: Benefits and timing of percutaneous dilatational tracheostomy (PDT) in Intensive Care Unit (ICU) COVID-19 patients are still controversial. PDT is considered a high risk procedure for transmission of SARS CoV-2 to health care workers (HCWs). The present study analyzed optimal timing of PDT, clinical outcomes of patients undergoing PDT and safety of HCWs performing PDT. (2) Methods: 133 COVID-19 patients underwent PDT in our ICU from April 1, 2020 to March 31, 2021, 23 patients were excluded and 110 patients were enrolled. A trained medical team was dedicated to the PDT procedure. Demographic, clinical history and outcome data were collected. Patients who underwent PDT were stratified into two groups: early group, PDT ≤ 12 days from orotracheal-intubation (OTI) and late group, >12 days from OTI; HCW surveillance program was performed. (3) Results: Early group included 57 patients and late group included 53 patients. Early group patients showed shorter ICU length of stay and fewer days of mechanical ventilation than the late group (p<0.001). At day 7 after tracheostomy, early group patients required fewer intravenous anesthetic drugs and experienced an improvement of ventilation parameters, PaO2/FiO2-Ratio, PEEP and FiO2 (p<0.001). No difference in case fatality ratio between the two groups was reported. No SARS-CoV-2 infection was reported in HCWs performing PDT. (4) Conclusions: PDT was safe and effective for COVID-19 patients, since it improved respiratory support parameters, reduced ICU length of stay and duration of mechanical ventilation, and optimized the weaning process. The procedure was safe for all HCWs involved in the dedicated medical team. The development of standardized early PDT protocols should be implemented and PDT procedure could be considered as first line approach in ICU COVID-19 requiring prolonged mechanical ventilation.

As Chronic Non-Communicable Diseases (CNCD) increase, preventive approaches become more crucial. In this review, Calorie Restriction (CR) effects on human beings were evaluated, comparing benefits and risks of different CR diets: classic CR vs ketosis-inducing diets, including Intermittent Fasting (IF), Classic Ketogenic Diet (CKD), Fasting Mimicking Diet (FMD), Very-Low-Calorie Ketogenic Diet (VLCKD) and Spanish Ketogenic Mediterranean Diet (SKMD). Special emphasis on Insulin Resistance (IR) was placed, as it mediates Metabolic Syndrome (MS), a risk factor for CNCD, and predicts MS diagnosis. CR is the most robust intervention known to increase lifespan and health span, with high evidence and known biochemical mechanisms. CR improves cardiometabolic risk parameters, boosts exercise insulin sensitivity response, and there may be benefits of implementing moderate CR on healthy young and middle-aged individuals. However, there is insufficient evidence to support long-term CR. CKD is effective for weight and MS management, and may have additional benefits such as prevention of muscle loss and appetite control. SKMD has extreme significance benefits for all the metabolic parameters studied. Studies show inconsistent benefits of IF compared to classic CR. More studies are required to study biochemical parameters, reinforce evidence, identify risks, and seek effective and safe nutritional CR approaches.

Role identity theory describes the purpose and meaning in life that comes, in part, from occupying social roles. While robustly linked to health and well-being, this may become, however, when an individual is unable to fulfil the perceived requirements of an especially salient role in the way that they believe they should. Amid high rates of mental illness among public safety personnel, we interviewed a purposely selected sample of 21 paramedics from a single service in Ontario, Canada to explore incongruence between an espoused and able-to-enact paramedic role identity. Situated in an interpretivist epistemology, and using successive rounds of thematic analysis, we developed a framework for role identity dissonance wherein chronic, identity-relevant disruptive events cause emotional and psychological distress. While some participants were able to recalibrate their sense of self and understanding of the role, for others, this dissonance was irreconcilable, contributing to disability and lost time from work. In addition to contributing a novel perspective on paramedic mental health and well-being, our work also offers a modest contribution to the theory in using the paramedic context as an example to consider identity disruption through chronic workplace stress.

The review of previous works shows this study is the first attempt to analyse the lockdown effect using Natural Language Processing Techniques, particularly sentiment analysis methods applied at large scale. On the other hand, it is also the first of its kind to analyse the impact of COVID 19 on the university community jointly on staff and students and with a multi-country perspective. The main overall findings of this work show that the most often related words were family, anxiety, house and life. On another front, it has also been shown that staff have a slightly less negative perception of the consequences of COVID in their daily life. We have used artificial intelligence models like swivel embedding and the Multilayer Perceptron, as classification algorithms. The performance reached in terms of accuracy metric are 88.8% and 88.5%, for student and staff respectively. The main conclusion of our study is that higher education institutions and policymakers around the world may benefit from these findings while formulating policy recommendations and strategies to support students during this and any future pandemics.

Respiratory viral infections (RVI) are common reasons for healthcare consultations. The inpatient management of RVI consumes significant resources. From 2009-2014, we assessed the costs of RVI management in 4776 hospitalized chil-dren aged 0-18 years participating in a quality improvement program, where all ILI patients underwent virologic testing at the National Reference Centre followed by de-tailed recording of their clinical course. The direct (medical or non-medical) and indirect costs of inpatient management outside the ICU (“non-ICU”) versus management requiring ICU-care (“ICU”) added up to 2,767.14€ (non-ICU) vs. 29,941.71€ (ICU) for Influenza, 2,713.14€ (non-ICU) vs. 16,951.06€ (ICU) for RSV infections, and 2,767.33€ (non-ICU) vs. 14,394.02€ (ICU) for human rhinovirus (hRV) infections, respectively. Non-ICU inpatient costs were similar for all 8 RVI studied: Influenza, RSV, hRV, ade-novirus (hAdV), metapneumovirus (hMPV), parainfluenzavirus (hPIV), bocavirus (hBoV) and seasonal coronavirus (hCoV) infections. ICU-costs for Influenza however, ex-ceeded all other RVI. At the time of the study, Influenza was the only RVI with antivi-ral treatment options available for children, but only 9.8% of Influenza patients (non-ICU) and 1.5% of ICU-patients with Influenza received antivirals; only 2.9% were vac-cinated. Future studies should investigate the economic impact of treatment and pre-vention of Influenza-, COVID-19-, and RSV post vaccine introduction.

Studies have previously described the occurrence of multidrug-resistant (MDR) Escherichia coli in human and veterinary medical settings, livestock, and, to a lesser extent, in the environment and food. While they mostly analyzed foodborne E. coli regarding phenotypic and sometimes genotypic antibiotic resistance and basic phylogenetic classification, we have limited understanding of the in vitro and in vivo virulence characteristics and global phylogenetic contexts of these bacteria. Here, we investigated an E. coli strain (PBIO3502) isolated from a pork sausage in Germany in 2021 in-depth. Whole-genome sequence analysis revealed sequence type (ST)58, which is an emerging international high-risk clonal lineage. In addition to its MDR phenotype that mostly matched the genotype, PBIO3502 demonstrated pronounced virulence features, including in vitro biofilm formation, siderophore secretion, serum resilience, and in vivo mortality in Galleria mellonella larvae. Along with the genomic analysis indicating close phylogenetic relatedness of our strain with publicly available, clinically relevant representatives of the same ST, these results suggest the zoonotic and pathogenic character of PBIO3502 with the potential to cause infection in humans and animals. Also, our study highlights the necessity of the One Health approach while integrating human, animal, and environmental health, as well as the role of meat products and food chains in the putative transmission of MDR pathogens.

Intestinal parasitic infections pose a significant public health challenge in Northern Nigeria, with prevalence rates ranging from 20% to 70%. Traditional diagnostic methods, primarily microscopic examination of stool samples, face limitations such as low sensitivity and high costs. This research addresses these challenges by proposing an Artificial Intelligence (AI)-based platform for the identification and counting of intestinal parasites. Leveraging the You Only Look Once (YOLO) V8 model, trained on a dataset of 360 pre-processed and annotated images, the AI model demonstrated promising performance metrics. The precision-recall curve, average precision, mean average precision, and F1 score indicated reliable detection and classification across various parasite classes. The model exhibited a well-balanced trade-off between precision and recall, showcasing its potential as a cost-effective and accessible tool for improving the diagnosis and treatment of intestinal parasitic infections in resource-limited settings.

This study examined the effect of the media usage environment, particularly TV and mobile devices, on advertisement acceptance, lifestyle, and psychological satisfaction. Hypothesis pathways and comparative structural mediating effects were analyzed. Media and Consumer Research public data were used for empirical analysis. A total of 6,640 people who participated in sports activities were included in the study. The results demonstrated that TV and mobile device usage environments had similar effects on advertisement acceptance. While TV did not influence the pursuit of personal life, mobile device use environments affected the pursuit of personal life. Mobile device use environments had a greater effect on individual psychological satisfaction than TV. Adoption had a mediating effect on the influence of media usage environments on the pursuit of personal life. The pursuit of a personal life had a significant mediating effect on the influence of media use environments on psychological stability. This study revealed no differences in the effects of new and traditional media on advertisement acceptance, while new media had a greater influence on lifestyle and psychological satisfaction.

In May of 2022, millions of U.S. parents faced uncertainty in safely feeding their infants due to the infant formula shortage. Methods: An anonymous, electronic, cross-sectional, retrospective survey was used. Results: U.S. parents (n =187) whose infants were 10.2 weeks old during the short-age completed the survey. Eighty-one percent of parents switched formulas during the shortage, 87% switched because they could not find the formula they typically used, 34% switched 3-5 times, 29% of parents visited ≥ 4 stores/24 hours and 26% of parents traveled >20 miles/24 hours to purchase formula. Use of infant formula increased (p< 0.01); in infants requiring specialty for-mula, use of intact cow’s milk formula increased (p < 0.05) and use of premature infant formulas decreased (p < 0.05). Infants relying on specialty formulas experienced at least one undesirable outcome compared with non-specialty users. Parents used social media, relatives/friends, and healthcare providers for support during the shortage, but their helpfulness scores were suboptimal. Parents reported needs for greater infant formula availability, free prenatal lactation education and postpartum lactation support. Conclusions: Government, regulatory and healthcare policy oversight are needed to protect the infant feeding system, including more commercially available products, access to banked donor milk and lactation support.

Quality of life (QOL) is based on their perception of their position in life in respect to their goals, expectations, standards, and concerns, as well as their culture and value systems, their workflow and workplace situations while it influences quality of services. In this study we aim to report on dental and nursing academians’ QOL and well-being at the end of the third year of the COVID-19 pandemic. The World Health Organization Quality of Life-BREF Scale (WHOQOL-BREF) tool, recording Physical, Psychological, Social and Environmental dimensions of QOL, was used. The WHOQOL-BREF was modified on a spiritual, coaching/mentoring approach in a two-step designing and validated procedure. The modified SHQOL-BREF (Spiritual Healthcare version) designed for this study, was uploaded, and filled in online during April-June 2023. Staff (N=120, 75% female) of both departments of Dentistry (44.2%) and Nursing (55.8%) of the National and Kapodistrian university of Athens, participated in anonymity. QOL in terms of physical health was reported at a higher level (M=72.2 points) compared to social relationships (M=69 points), psychological health (M=65 points) and environment (M=59 points) (scores reported in 0-100 score). Overall QOL was rated at 66 points while satisfaction from health at 72 points. Job satisfaction (M1=3.2) and spirituality (M2=3.0) were reported at a medium level in a 5-point scale, while personal beliefs and values were reported at a high level (M3=4.0). Participants age presented a significant, moderate to strong effect on physical health [F(3,97)=2.89, p&lt;.05, η2p=.08] and on environment [F(3,97)=2.80, p&lt;.05, η2p=.08] and marital status on social relationships [F(1,97)=9.66, p&lt;.05, η2p=.09]. Married participants reported consistently higher levels of QOL compared to single participants, for all age groups. Department had a significant moderate effect on social relationships (F(1,97)=5.10, p&lt;.05, η2p=.05) and education a significant moderate to strong effect on psychological health (F(2,97)=3.74, p&lt;.05, η2p=.07). PhD level participants in both departments presented higher levels of psychological health compared to lower educational levels. Also, participants from the department of Dentistry reported higher levels of social relationships QOL in all educational groups, compared to the department of Nursing. Strategic planning on sustainability and QOL initiatives should be introduced after the COVID-19 pandemic for dental and nursing academic personnel to promote resilience and QOL scores.

While the global COVID-19 pandemic has been widely acknowledged to affect the mental health of health care workers (HCWs), attention to measures that protect those on the front lines of health outbreak response has been limited. In this cross-sectional study, we examine workplace contextual factors associated with how psychological distress was experienced in a South African setting where a severe first wave was being experienced with an objective of identifying factors that can protect against HCWs experiencing negative impacts. Consistent with mounting literature on mental health effects, we found a high degree of psychological distress (57.4% above General Health Questionnaire cut-off value) and a strong association between perceived risks associated with the presence of COVID-19 in the healthcare workplace and psychological distress (adjusted OR = 2.35, p <.01). Our research indicates that both training (adjusted OR 0.41, 95% CI 0.21 – 0.81) and the reported presence of supportive workplace relationships (adjusted OR 0.52, 95% CI 0.27 – 0.97) were associated with positive outcomes. This evidence that workplace resilience can be reinforced to better prepare for the onset of similar outbreaks in the future suggests that pursuit of further research into specific interventions to improve resilience is well merited.

Background: Micrococcus luteus is a commensal bacterial member on the human skin and is essential in keeping the balance among the various microbial flora of the skin. M. luteus strain Q24 or BLIS Q24^TM was isolated from the skin of a healthy human adult and has been identified to produce a unique antimicrobial spectrum that is inhibitory towards pathogenic bacteria associated with many skin diseases such as acne. It has been developed as a probiotic with potential applications in improving overall skin health.Aim: This study aimed to evaluate the perceived changes in skin quality following topical application of a formulation containing skin commensal probiotic BLIS Q24^TM. Materials and methods: A 28-day study involving 100 adult participants with self-reported normal skin with occasional blemishes or breakouts, topically applied a serum formulation containing BLIS Q24^TM to the face. Participants quantitatively evaluated the probiotic serum effect on their skin at baseline Day 0 and then again on Day 10, 20 and 28 of the application. In addition, participants maintained a photo diary to record the perceived changes to their skin.Results: A total of 96 participants completed this research. In comparison to the baseline (Day 0), within 10 days, a significant reduction in blackheads (48%), oiliness (48%), blemishes (57%), dry areas (23%), redness/rosacea (45%) and flaky and rough skin (38%) were reported. The probiotic serum was also effective in a significant reduction in fine lines and wrinkles (38%), whiteheads (41%), pimples (55%), age spots (29%), and acne (21%) by the end of 28 days of probiotic application. Overall, there’s agreement that probiotic serum delivers or exceeds consumer expectations from the concept and performs just as well, or better, than their regular moisturiser.Conclusions: An approach of delivering a live probiotic packaged in an innovative formula to improve several skin conditions in otherwise healthy individuals was found to be successful. This study highlights that a serum formulation containing BLIS Q24^TM has a positive impact on skin health with it being effective topically in reducing the appearance of skin blemishes, oiliness, wrinkles, redness, and dryness. BLIS Q24^TM offers the potential for the prevention of skin health-related issues and routine maintenance of skin microbiome for healthy skin.

This paper focuses on determining the State of Charge (SOC) of lithium-ion batteries when operating and the influence the State of Health (SOH) has on SOC determination. The paper studies the effects of the discharge rate on the battery performance and how it modifies the evaluation of the SOC. The article also analyzes the effects of battery aging on the determination of SOC. The online determination of SOC in lithium-ion batteries uses the linear behavior of battery discharge and how the discharge rate modifies the battery voltage slope. The paper develops a simple algorithm that relates the SOC of the battery with the online battery voltage. The proposed measurement method uses a very short controlled discharge at a specific rate that avoids unexpected interferences with the current operation of the battery during charge or discharge. We conducted a simulation process to evaluate the evolution of the SOC in Li-ion batteries for different operating stages. Experimental tests validate the proposed methodology, showing a close agreement between theoretical values and experimental results with 98% accuracy. The paper also deals with the determination of the aging factor in lithium batteries as a critical parameter to calculate the SOC. The method determines the aging factor using specific simulation for this goal. The results are compared to values obtained in an experimental test within high agreement (>93%). The proposed model applies to almost any lithium battery and is validated for a wide range of Battery State of Health, up to 50%, within accurate prediction, higher than 90%.

The school food environment is a suitable place to promote healthy habits, as it is a space for learning and constant social interaction, where children spend at least a third of their day, and have one to two meals. This study aimed to analyze the sale of food in the canteens of private schools in a capital in the Northeast of Brazil and verify the influence of it on students’ eating behavior. A cross-sectional, quantitative, multicenter study was carried out, taking place simultaneously in twenty capitals in Brazil. A checklist with 87 questions was applied to those responsible for the canteens in a representative sample of schools in each city. Frequencies and associations were performed using Pearson's Chi-Square test. The analysis of the foods sold, was based on the NOVA food classification from the Dietary Guidelines for the Brazilian Population, regarding the degree and extent of processing. Latent Class Analysis was carried out to group the canteens into similar response patterns, modeled with covariates, and the association was calculated with the Kruskal-Wallis and Duun tests or Fisher's Exact test. The results showed that students were very frequently offered ultra-processed, sugar-rich foods with low nutritional value; 88.7% of such foods had been chosen by managers as part of the menu because they are “students’ food preferences”. There is an average of 2.3 fresh foods in canteens compared to 7.5 varieties of ultra-processed foods. There must be stricter control over what is sold, to minimize student’s exposure to unhealthy foods.

Objective To investigate nailfold capillary parameters in community-dwelling individuals aged over 60 years who have hypertension and do not exercise regularly. Furthermore, the study examined the correlations between capillary function and other health-related indicators. Design A single- center pilot trial Setting Faculty of Health, Tsukuba University of Technology, Japan Participants hypertensive community-dwelling elderly people Intervention Microcirculation was observed before and 1 min after arm-curl exercise by means microscopy of capillary with non-exercised limb. Additionally, we examined other health-related indicators. Outcome measures: Acute effects of reperfusion on nailfold density, flow, and diameters. Secondary outcomes included the correlations between microvascular parameters and other health-related indicators. We hypothesized that brief exercise could enhance microcirculation reperfusion and correlate with other health-related parameters.　 Results: There were 20 participants with a mean (SD) age of 67.1 (5.8) years. The capillary flow rate changed from 2.3±6.7 to 2.7±0.2 log µm/s (P

This paper presents the development of a novel anti-violence device titled "no pAIn" (an acronym for Never Oppressed Protected by Artificial Intelligence Nonviolence system), which harnesses the power of artificial intelligence (AI). Primarily designed to combat violence against women, the device offers personal safety benefits for individuals across diverse demographics. Operating autonomously, it necessitates no user interaction post-activation. The AI engine conducts real-time speech recognition and effectively discerns genuine instances of aggression from non-violent disputes or conversations. Facilitated by its Internet connectivity, in the event of detected aggression, the device promptly issues assistance requests with real-time precise geolocation tracking to predetermined recipients, for immediate assistance. Its compact size enables discreet concealment within commonplace items like candy wrappers, or within purpose-built casings, or as wearable accessories. The device is battery-operated. The prototype was developed using a microcontroller board (Arduino Nano RP2040 Connect), incorporating an omnidirectional microphone and Wi-Fi module, all at a remarkably low cost. Subsequent functionality testing, performed in debug mode using the Arduino IDE serial monitor, yielded successful results. The AI engine exhibited exceptional accuracy in word recognition, complemented by a robust logic implementation, rendering the device highly reliable in discerning genuine instances of aggression from non-violent scenarios

The prevalence of Noncommunicable Diseases (NCDs) in South Africa is increasing annually, with the burden projected to escalate by 2030. Devastatingly, factors such as lifestyle changes, urbani- sation, and an aging population significantly contribute to a rising burden of Cardiovascular disease (CVDs), diabetes, and cancer which directly impact the mortality and morbidity rates seen in South Africa. Recognising this, the South African government has seen the need for emphasis on developing policies and interventions tar- geting physical inactivity to prevent and manage NCD, particularly cost-free and easy to administer training protocols. However, phys- ical inactivity remains a significant issue, leading to various health concerns in rural communities, including injuries and Fetal Alcohol Spectrum Disorders (FASD). Despite effort to promote physical ac- tivity, the prevalence of NCDs continues to rise, necessitating target- ed interventions to ensure equitable healthcare among South African citizens. On the Contrast, preservation and promotion of traditional games is vital as they offer indigenous populations accessible and culturally relevant means to maintain health and wellness. In this regard, it is important to recognize the importance of preserving and promoting traditional games as they potentially serve as a method for indigenous people to maintain their health and wellness in a way that is accessible and culturally relevant to them. These games have gained popularity in South Africa, with initiatives underway to show- case them globally fostering cultural exchange. Further, revitalizing and conserving these games can cultivate a culture of health and wellbeing in South Africa.

This research work has been based on a previous study by the authors that characterized the behavior of a polyimide-coated FBG sensor in a structural monitoring system. Sensors applied to structural health monitoring are affected in the presence of a state of multidirectional strains simultaneously. The previous study observed the influence of transverse strain (ε_y) while keeping longitudinal strain constant (ε_x), where the direction x is the direction of the optical fiber. The present study developed an experimental methodology which has consisted of carrying out a campaign of biaxial tests on cruciform specimens with three embedded FBG sensors coated with polyimide, acrylate and ORMOCER®. Applying the Strain–Optic Theory as reference, a comparison of the results obtained with the different coatings has been studied. This experimental work has done it possible to study the influence of transverse strain (ε_y) in the longitudinal measurement of each of the FBG sensor and the influence of the coating material. Finally, the calibration procedure as well as the strain sensitivity factor K for each sensor has been defined.

Background: Patients with bipolar disorder (BD) receive traditional Chinese Medicine (TCM) for unmet clinical needs with psychotropic medications. However, the clinical characteristics of practices and outcomes of TCM in BD are not fully understood. This cohort study investigated the clinical characteristics, principal diagnoses, TCM interventions, and TCM prescriptions in patients with BD. Methods: 12,113 patients with BD were withdrawn from Taiwan's longitudinal health insurance database 2000 (LHID 2000) between 1996 and 2013. Chi-squared test for categorical variables and independent t-test for continuous variables. A p-value less than 0.05 indicated significance. Results: One-thousand and three hundred nineteen patients who visited TCM clinics after the diagnosis of BD were in the TCM group, while those who never visited TCM were in the non-TCM group (N= 1,053). Compared to the non-TCM group, patients in the TCM group had younger average age, a higher percentage of female individuals, more comorbidities of anxiety and alcohol use disorders, and higher mood stabilizer usage rates. The TCM group exhibited pain-related indications, including joint pain, myalgia, myositis, headache, and sleep disturbances. Corydalis yanhusuo and Shu-Jing-Huo-Xue-Tang were the most useful single herb and herbal formulas. Conclusions: Physicians need to be aware of the use of TCM in Patients with BD.

This study analyzes the convergence between artificial intelligence (AI) and management accounting in hospital contexts. Management accounting plays a central role in the effectiveness of planning, control and decision-making in healthcare institutions such as hospitals. The application of AI in this scenario offers powerful tools to improve accounting processes, optimize operational efficiency and maximize the use of available resources, resulting in an improvement in the quality of care provided to patients. Through in-depth analysis, the article explores how AI is bringing about a revolution in hospital management accounting, presenting case studies illustrating its successful implementation, outlining the tangible benefits.

Heavy metal pollution poses a significant threat to global populations, particularly impacting human health. Developing countries, characterized by chemical engineering and mining industrial activities, often contribute to diverse heavy metal contaminants. Consumption of water contaminated with heavy metals, prevalent in such regions, can lead to severe health risks, including gastric cancer. Addressing the urgent issue of heavy metal pollution, this paper employs a bibliographic approach to explore the latest literature on heavy metal pollution. The study discusses recent research findings and potential methods for the treatment and mitigation of heavy metal pollution, emphasizing the pressing need for effective solutions to safeguard public health.

Home-dwelling older people without health services might develop health issues and challenges. To live longer at home and manage well, it is important to promote health-promotion towards this target group. One approach is through health-promotion dialogues conducted by healthcare professionals in the municipality. The aim of this study is to explore healthcare professionals’ experiences who are conducting health-promotion dialogues to older home-dwellers over 75 years without services. Focus-groups were used to collect data, and a total of nine participants formed three focus groups. Thematic analysis was applied to analyse the material, which resulted in one major theme “The challenging dialogues” comprising three sub-themes, “Mobilise coping skills and health awareness”, “Uncover vulnerability”, and “The ambiguity of the dialogues”. The findings were also discussed by using empowerment as a theoretical lens. The health-promotion conversation uses a resource perspective for elderly to remain independent in old age and can reveal vulnerability and underlying needs. The conversation purpose appears ambiguous for the target group, which leads to unclear service expectations and rejections of the offer. Nevertheless, it seems to be important that this health-promotion service to a larger degree addresses a clear purpose in order to meet the needs of the target group in a broader sense in the aging process.

This review explores the transformative impact of sensor technologies in early disease detection. It highlights recent advancements in nanotechnology-based sensors, particularly focusing on their applications in identifying disease biomarkers at early stages. The integration of these sensors with artificial intelligence for predictive analytics in healthcare is also discussed. Applications in cancer, infectious diseases, and chronic disease management underscore their diverse utility. Challenges in sensor technology adoption and future directions, including multiplexed sensors and wearable devices, are examined. This review underscores sensors' potential in enhancing disease management and patient outcomes.

This study analyzes the convergence between artificial intelligence (AI) and management accounting in hospital contexts. Management accounting plays a central role in the effectiveness of planning, control and decision-making in healthcare institutions such as hospitals. The application of AI in this scenario offers powerful tools to improve accounting processes, optimize operational efficiency and maximize the use of available resources, resulting in an improvement in the quality of care provided to patients. Through in-depth analysis, the article explores how AI is bringing about a revolution in hospital management accounting, presenting case studies illustrating its successful implementation, outlining the tangible benefits.

This study presents a comprehensive assessment of indoor particulate matter (PM) concentrations, focusing on PM1, PM2.5, and PM10 in five Primary Health Centers (PHCs): Arakale, Federal College of Agriculture (FECA), Iju, Oba-Ile, and Owode within Akure Local Government Areas in Nigeria. The primary novelty of this research lies in its detailed exploration of the toxicity potential of these PM fractions, providing valuable insights into the local air quality and associated health risks. The study assesses the health implications by calculating the toxicity potential (TP), Relative Risk (RR), Excess Risk (ER), and Attributable Fractions (AF) for cardiopulmonary and lung cancer mortality. The results reveal varying RR values for all-cause mortality, with Arakale showing a slight elevation (RR: 1.061), indicating potential health risks. ER values for cardiopulmonary mortality range from 14.728±7.25 to 19.04±0.38, emphasizing the substantial excess risk associated with long-term PM2.5 exposure. The study also uncovers AF for cardiopulmonary mortality ranging between 11.03±0.31 to 19.22±0.04, underscoring the significant contribution of PM to cardiovascular and respiratory health risks. Similarly, AF for lung cancer mortality ranges from 10.03±0.012 to 17.13±0.10, highlighting the substantial association between PM2.5 exposure and lung cancer risk. These findings underscore the urgent need for targeted air quality management strategies and public health interventions in the studied locations to mitigate the heightened health risks associated with particulate matter pollution. The calculated RR, ER, and AF values offer crucial insights into the complex relationship between PM exposure and adverse health outcomes, providing a foundation for informed decision-making and future research endeavors.

As ethically motivated vegans (EMV) frequently feel responsible for suffering caused by the consumption of animal products, feelings of guilt are therefore an important issue for many of them. To date, studies on the experience and handling of guilt in vegans have rarely been identified. Therefore, we investigated this topic using a qualitative design. N=64 interviews with N=57 EMV were analyzed using content analysis. Key results are that they perceive guilt as a psychological and sometimes even as a physical influencing factor. They describe how feelings of guilt arise in combination with anger, revulsion and pity thereby affecting their thinking and behavior. Some experience even corporal strain, a physical heaviness. Others helped the transition to a vegan diet to get rid of guilt and to feel emotional and partially also physical relieve. In contrast, others were faced with new problems: no dissociation from other people’s guilt, heightened awareness of one’s own perception, more compassion, and a stronger sense of responsibility. Some even registered an increased tendency to depression and self-destructive thoughts. Beyond its limitations, our study is one of the first illustrating the possible impact of feelings of guilt on mental and physical well-being EMV may sense and suffer from.

Home enteral nutrition (HEN) is recommended for patients with nutritional requirements who can stay in the familiar environment. HEN guidelines recommend assessing health-related quality of life (HRQoL) to evaluate the effect of the treatment. NutriQoL® is a specific questionnaire developed to assess HRQoL in patients receiving HEN and validated in Spanish population. An observational, descriptive, and prospective study was carried out in two Spanish hospitals to describe the evolution of HRQoL, nutritional and health status in patients receiving HEN in routine clinical practice. Fifty-seven patients participated in the study, of whom 36 were followed-up after their inclusion. Most of them were at risk or moderate malnutrition (61.1%) or showed severe malnutrition (27.8%) at baseline. Patients with HEN showed an overall good HRQoL with a mean basal NutriQoL® score of 69.4, which increased to 74.3 after 12 months of follow-up; fifteen patients showed a clinically significant difference (≥4 points) after three months. The proportion of at-risk or severely malnourished patients decreased at the end of the follow-up period and, according to the physicians, their health status improved. Additionally, physicians considered useful the HRQoL evaluation in clinical practice. In conclusion, HRQoL is probably related to nutritional status improvement and, thus, should be considered for nutritional evaluation in clinical practice.

In a rapidly evolving global landscape characterized by increased international travel, migration, and ecological shifts, this study sheds light on the emergence of protozoal and helminthic infections targeting the central nervous system (CNS) within Europe. Despite being traditionally associated with tropical regions, these infections are progressively becoming more prevalent in non-endemic areas. By scrutinizing the inherent risks, potential outcomes, and attendant challenges, this study underscores the intricate interplay between diagnostic limitations, susceptibility of specific population subsets, and the profound influence of climate fluctuations. The contemporary interconnectedness of societies serves as a conduit for the introduction and establishment of these infections, warranting comprehensive assessment. This study emphasizes the pivotal role of heightened clinician vigilance, judicious public health interventions, and synergistic research collaborations to mitigate the potential consequences of these infections. Though rare, their profound impact on morbidity and mortality underscores the collective urgency required to safeguard the neurological well-being of the European populace. Through this multifaceted approach, Europe can effectively navigate the complex terrain posed by these emergent infections.

Lifestyle health has been recognized as an evidence-based innovation that defines how daily habits and practices impact both the prevention and treatment of disease and provides an important adjunctive component to overall health. Specifically, an approach with small changes over time can have a dramatic impact on the health and well-being of individuals not only, in general, but also can be applied to skin health. However, lifestyle health factors to improve skin well-being have not been discussed extensively and/or well promulgated. The narrative for this overview focuses on providing a summary for topic background information, but more importantly, presents four lifestyle factors that can improve dermal health [i.e., factor 1: nutrition - diet; factor 2: rest (sleep); factor 3: movement/physical exercise, and factor 4: social and community associations]. This was accomplished by identifying previous journal articles and reviews with emphasis over the last five years (from January 2018 through July 2023; 156 out of 190 references cited or 82 %) using scientific search databases. The main conclusions of this overview encourage the concept that lifestyle health factors such as nutrition/diet, rest/sleep, movement/physical exercise, and community/social interactions support enhanced skin health and well-being with aging. Plus, social media interventions that aim to promote dietary, sleep and physical activity changes might be an application to improve skin health in the future.

Background: Micronutrient deficiencies are common at the time of cancer diagnosis and are associated with worse prognosis. Little is known about them in cancer rehabilitation. Methods: Data from routine health related quality of life (HRQOL) were analyzed at an inpatient cancer rehabilitation center. Rehabilitation patients completed the EORTC QLQ-C30 questionnaire before and after multidisciplinary rehabilitation treatment, and three month after discharge. Selenium and zinc status was measured in whole blood at these three time points. In case of selenium deficiency up to 600 µg selenium per day as sodium selenite was supplemented. Results: A total of 271 patients (breast, colon, and pancreatic cancer) were included in the analysis. There was clinically meaningful improvement in many domains of the EORTC QLQ-C30 during rehabilitation. However, effect often waned in the three months after. Prevalence for selenium deficiency varied between 34 to 90 percent depending on cancer type (breast &lt; colon &lt; pancreas). In contrast, zinc deficiency was rare. Daily selenium supplementation of 600 µg was more efficient to correct selenium deficiency compared to 300 µg selenium per day. Rehabilitation and increasing selenium status after rehabilitation were associated with improved global quality of life, physical and emotional functioning, and fatigue. In cancer patients with decreasing selenium status, values of global quality of life, physical and emotional functioning, and fatigue were back to the values at the beginning of rehabilitation. Conclusions: Selenium deficiency is common in cancer patients admitted to a cancer rehabilitation clinic. Selenium supplementation during rehabilitation effectively corrected selenium deficiency in most cases. The positive effects of rehabilitation persisted longer, when selenium status did not decrease after rehabilitation.

To date, the impact of COVID-19 vaccination on formerly menstruating women remains unknown. For this reason, a retrospective observational cross-sectional study was conducted (N= 548) using an online survey. General characteristics, medical history, and adverse events following COVID-19 vaccination were recorded. In comparison with the first dose, significantly higher percentages of respondents experienced menstrual-related disturbances (dose 1: 38.5% vs. dose 2: 44.8%; McNemar=9.15; mid P-value=0.002), as well as the simultaneous occurrence of two or more of these symptoms (dose 1: 11.2% vs. dose 2: 15.3%; McNemar=13.53; mid P-value=0.044) after receiving the second one. Among them, those related with the length and flow stand out, being of long-term nature in about 17-20% of cases. Interindividual factors influencing this unexpected event after receiving the dose 1 may include weight (AOR 1.02, CI 95% 1.01–1.03, P&lt;.001), perimenopause (AOR 2.28, CI 95% 1.37–3.77, P=.001), pre-existing diagnoses of non-autoimmune rheumatic/articular conditions (AOR 0.31, CI 95% 0.10–1.00, P=0.05), hormonal contraceptive use (AOR 0.25, CI 95% 0.07-0.82, P=0.02), suffering from other vaccine side effects − such as arm pain (AOR 0.61, CI 95% 0.39–0.95, P=0.03), headache (AOR 0.53, CI 95% 0.35 – 0.80, P=.003), swollen glands (AOR 0.29, CI 95% 0.15 – 0.60, P=.001) and nauseas (AOR 0.35, CI 95% 0.14 – 0.86, P=0.02) – and the number of previous pregnancies (AOR 2.70, CI 95% 1.54 – 4.76, P=.001). Formerly menstruating women may experience long-term menstrual-related disturbances following COVID-19 vaccination.

Prostate cancer is driven by acquired genetic alterations, including those impacting the epigenetic machinery. With African ancestry a significant risk factor for aggressive disease, we hypothesize that dysregulation among the roughly 656 epigenetic genes may contribute to prostate cancer health disparities. Interrogating prostate tumor genomic data from 109 men of southern African and 56 men of European Australian ancestry, we found African-derived tumors to present with a longer tail of epigenetic driver gene candidates (72 versus 10). Biased towards African-specific drivers (63 versus 9 shared), many are novel to prostate cancer (18/63) including several putative therapeutic targets (CHD7, DPF3, POLR1B, SETD1B, UBTF and VPS72). Through clustering of all variant types and copy number alterations, we describe two epigenetic PCa taxonomies capable of differentiating patients by ancestry and predicted clinical outcomes. We identified top genes in African and European-derived tumors that represent a multifunctional “generic machinery”, alteration to which may be instrumental in epigenetic dysregulation and prostate tumorigenesis. In conclusion, numerous somatic alterations in the epigenetic machinery drive prostate carcinogenesis but African-derived tumors appear to achieve this with greater diversity amongst such alterations. The greater novelty observed in African-derived tumors illustrates the significant clinical benefit to be derived from a much needed African tailored approach to prostate cancer healthcare aimed at reducing prostate cancer health disparities.

Chronic non-communicable diseases (NCDs) are major public health problems and a significant financial burden on public health systems. By 2030, mortality due to NCDs, such as cardiovascular diseases, cancer, respiratory diseases, and diabetes, is predicted to increase in Brazil. A peculiar aspect of NCDs involves their long-term and integrated care management. This paper proposes a chronic disease management platform based on artificial intelligence to deliver digital health services everywhere. The proposed platform is anchored and built with healthcare 4.0 technologies, such as wearable devices, the internet of medical things, and artificial intelligence cloud-based solutions that allow the deployment of a smart healthcare system. In addition, the paper presents the feasibility of the platform in a diabetes prediction study case. For the study case, an initial dataset was established with bio-impedance, oxygen concentration, pulse rate, skin impedance, and skin temperature attributes. A baseline was implemented with ten regression models to assess the prediction performance of the mean squared error, root mean squared error, and r-squared score to compare predictive findings with capillary blood glucose measurements. Results evidence that the decision tree regressor and three ensemble methods (bagging decision tree regressor, random forest regressor, and AdaBoost regressor) yielded improvement over the other models. Moreover, a comparison among those models revealed that the decision tree regressor outperforms them and presents promissory outcomes.

Objective: To describe the methodology used and the results found in the implementation of Lean in Emergencies in the Emergency sector of the Hospital de Clínicas of the Federal University of Uberlândia (HC-UFU), verifying the difficulties and particularities that involved the process, as well as the result obtained. Material and methods: For the comparison between the periods before (T1), contemporary (T2) and after (T3) the implementation of Lean, hospital data were used , and the indicators corresponding to 10 variables were analyzed: Male Hospitalization and Female Hospitalization; High Male and High Female; Male Transfer and Female Transfer, Male Death <24h and Female Death <24h; Male Death >24h and Female Death >24h and general occupancy rate. All raw data related to the 36 months of evaluation were provided by the HC-UFU Statistics sector in spreadsheets without identifying patients. The indicators were compared to each other in the three analyzed periods, with the study directed as follows: Previous stage - Pre -intervention (T1): considered between the months of April 2017 to March 2018, completing 12 months before the implementation of Lean; Intra-intervention stage - contemporary (T2): considered between the months of April 2018 to March 2019, in a total of 12 months which was the implementation period; Post-Intervention Stage (T3): later: considered between the months of April 2019 to March 2020, completing 12 months after the implementation of Lean. The Lean in Emergencies scores (NEDOCS and LOS) were only recorded during the period that the implementation team was able to record and were used only to demonstrate trend over time. Comparison of the indicators with those found in other hospital units that also implemented Lean was carried out based on bibliographical research. Results and Discussion: The analysis of the behavior of the indicators did not demonstrate effectiveness related to the implementation of the system in the emergency sector. The failure to obtain better indicators can be attributed to discontinuity in monitoring the project, the lack of involvement of the clinical staff and alignment with the needs of the staff training academy, the difficulty of understanding the project by local and regional public entities. geographical location where the hospital is located, and by users of the health system who were not properly informed about the development of the project. These aspects should be considered in future management projects that may be implemented in the hospital. Despite the result of the implementation of Lean in the emergency sector not having reached the expected goals, the attempt showed windows of opportunity for future action on points that can improve the hospital management process and that should be tested in the next experiences. Conclusion: The methodology followed for the implementation of Lean in Emergencies in the emergency sector of the hospital did not produce improvement in hospital indicators.

Payments for Ecosystem Services are a voluntary market-based instrument to remunerate provider(s) of ecosystem services by those who benefit from them. Our research aimed to create an ex-post evaluation framework to identify bottlenecks and elements hindering the success of a solution-driven PES scheme. The framework was applied to a case study to test its feasibility and concerns the provision of health and recreational services in the Medvednica Nature Park (Zagreb, Croatia). The framework was set up through three main sources: the study of PES implementation project documentation, semi-structured interviews with visitors and key stakeholders and web-scraping of TripAdvisor reviews of the park. The main findings confirmed society's interest in the park, but the lack of mapping, quantification, economic valuation and accounting of the services analysed, society's little or no demand to pay for their provision and confused knowledge of the property rights of some ecosystem service providers in the area limit the success of the PES scheme. The framework was useful to describe the chosen PES scheme and to identify bottlenecks and fragilities of the system in place, allowing to correct its application flaws and, on the other hand, to demonstrate its replicability in other contexts.

Background: Occupational accidents contribute 46-65% of hepatitis B virus (HBV) infections among healthcare workers (HCWs). Vaccine against HBV infection offers protection of more than 90%. Despite availability of the vaccines in Tanzania, it’s uptake among HCWs in primary health facilities remains understudied. This study explored HBV vaccine uptake and associated factors among HCWs in rural and urban settings of north western Tanzania. Methodology: A cross-sectional analytical study was conducted between June and July in 2022 among HCW in Misungwi and Ilemela districts. Data were collected using a self-administered questionnaire and analyzed using IBM SPSS® version 25. Results: A total of 402 HCWs were recruited, their mean age was 34.9±7.77 years. Approximately half (54.7% (220/402) of HCWs had received at least one shot of HBV vaccine with only (18% (76/402) being fully vaccinated. Ilemela showed significantly higher uptake (χ2=23.64, df=1, p=0.00) of HBV vaccine as compared to their counterparts in Misungwi. Being male (aOR=2.38, 95% CI 1.28-4.45, p=0.006), working in urban (aOR=5.75, 95% CI 2.91-11.35, p=0.00) and employment duration of more than two years (aOR=3.58, 95%CI 1.19-10.74, p=0.023) were significantly associated with higher odds of HBV vaccination. Moreover, high perceived susceptibility to HBV infection (aOR=2.20, 95% CI1.02-4.75, p=0.044) and history of needle prick injuries (aOR=6.87, 95%CI 3.55-13.26, p=0.00) were also significantly associated with higher odds of HBV vaccination. Conclusion: There was low uptake of HBV vaccine among HCW in primary health facilities with a noteworthy difference between rural and urban settings.. Therefore, advocacy campaigns as well as resource mobilization towards promotion of HBV vaccination in primary health facilities are pivotal.

Human adenoviruses are one of the most important pathogens detected in acute respiratory diseases in pediatrics and immunocompromised patients. In 1953, Wallace Rowe described it for the first time in oropharyngeal lymphatic tissue. To date, more than 85 types of HAdV have been described, with different cellular tropisms. They can cause respiratory and gastrointestinal symptoms, even urinary tract inflammation, although most infections are asymptomatic. However, there is a population at risk that can develop serious and even lethal conditions. These viruses have a double-stranded DNA genome, 25-48 kbp, 90 nm in diameter, without a mantle, stable in the environment, and resistant to fat-soluble detergents. Currently the diagnosis is made with lateral flow immunochromatography or molecular biology through a polymerase chain reaction. The objective of this review is to recognize the variability of HAdV, the pandemic potential that a recombinant could present between HAdV-3 and 7 viral types, known to produce aggressive outbreaks in health facilities. The review determined the characteristics of HAdV, from the infection to treatment, vaccine development and the evaluation of the social determinants of health associated with HAdV, guiding the necessary measures for future sanitary control, and preventing disasters such as the SARS-CoV-2 pandemic.

First responders, such as police officers, paramedics, and fire-fighters are at an increased risk of experiencing negative mental health outcomes compared to the general population. This predisposition can partially be attributed to common occupational stressors, such as poor workplace culture and mistreatment from leadership, which may provoke strong feelings of betrayal and humiliation. The Workplace Assessment Scale (WAS) was developed as there is currently no appropriate measure to assess such feelings in the first responder population. The scale consists of the Betrayal Subscale and the Humiliation Subscale, each comprised of 5 Likert scale questions which ask participants to report the frequency at which they experience specific feelings associated with their workplace. This pilot validation study was conducted to assess preliminary reliability and validity of the WAS, using data which was originally collected as part of a larger first responder-based observational study. Based on 21/22 (95%) participant responses, the internal consistency appeared to be strong for both sub-scales as well as the overall questionnaire. However, item 9 will likely require modification or deletion from the scale. The validity analysis found no significant correlations between WAS and other psychiatric scales. Additional research is needed for further analysis and validation of the WAS.

Evidence indicates that unhealthy eating habits constitute multilevel obstacles threatening our health and well-being—studies suggesting that consumer choices turn irremovably towards Western diets. Mediterranean diets (MD) have been identified as one of the most effective in preventing and treating overweight and obesity. Considering this scientific substantiation in prevention and treatment activity, the purpose of this investigation is to verify this evidence. In our prospective interventional study, we examined the effect of MD on body weight in a female cohort sample. The analyzed group consisted of (n=181) females divided into three distinct groups based on their age (tricenarian, quadragenarian, and quinquagenarian). Anthropometric (weight, BMI, FATP, VFATL, FFM, TBW, and BMR), biochemical examinations (urea, creatinine, uric acid, ALT, AST, GGT, CHOL, HDL-CH, non-HDL, LDL-CH, TAG, GLU, and CRP) and comprehensive, personalized three months MD program was completed on the examined subjects. We didn’t establish convincing evidence of MD on weight reduction and its magnitude of correlation with a positive correspondence on selected determinants in all groups combined. There is a challenge to construct more robust prospective cohort studies that will incorporate add-on critical integrands that will be appropriate to monitor, evaluate and predict weight management in experimenting.

Large structures such as wind turbines are subject to environmental factors and varying operational loads which may result in structural damage, making components of these large structures prone to performance and mechanical degradation. The use of high-definition optical vision sensors in digital image correlation (DIC) allow for the application of a non-destructive image registration technique in which it measures finite three-dimensional deformations on surfaces through correlations of a unique pattern or set of unique localized patterns. However, the physical placement of an artificial marker such as a unique speckled pattern on the surface of the structure is time-consuming and often impractical for large structures. Therefore, we propose a novel auto-mated methodology that searches and segments salient and unique regions of an image as well as for all subsequent images to assist in performing efficient displacement measurements for vibrational study and structural health monitoring purposes. Our algorithm is validated on a con-trolled set of images, as well as on a small structure and large real-world wind turbine, which suggests the algorithm’s efficacy without the use of artificial markers for large structural health monitoring.

Abstract: Understanding social media networks and group interactions are crucial to the ad-vancement of linguistic and cultural behaviour. This includes the manner in which people ac-cessed advice on health, especially during the global lockdown periods. Some people turned to social media to access information on health where most activities were curtailed with isolation rules, especially for older generations. Facebook public pages, groups and verified profiles, using "senior citizen health", "older generations", and "healthy living" keywords were analysed over a 12-month period to analyse the engagement promoting good mental health. CrowdTangle was used to source English language status updates, photo and video sharing information which resulted in an initial 116,321 posts and 6,462,065 interactions Data analysis and visualisation were used to explore large datasets, including natural language processing for “Message” content discovery, word frequency and correlational analysis and co-word clustering. Preliminary results indicate strong links to healthy aging information shared on social media which showed correla-tions to global daily confirmed case and daily death totals. The results can be used to identify public concerns early on and address mental health issues in the senior generation on Facebook.

High costs for the repair of concrete structures can be prevented if damage at an early stage of degradation is detected and precautionary maintenance measures are applied. To this end, we use numerical wave propagation simulations to identify simulated damage in concrete using convolutional neural networks (CNN). Damage in concrete subjected to compression is modeled at the mesoscale using the discrete element method. Ultrasonic wave propagation simulation on the damaged concrete specimens are performed using the rotated staggered finite-difference grid method. The simulated ultrasonic signals are used to train a CNN based classifier capable of classifying three different damage stages (microcrack initiation, microcrack growth and microcrack coalescence leading to macrocracks). The performance of the classifier is improved by refining the dataset via an analysis of the averaged envelope of the signal. The classifier using the refined dataset has an overall accuracy of 90%.

Blade Health Monitoring (BHM) is often necessary in power plants and in aviation to prevent excessive blade vibration and cracks. This article proposes a network of blade tip timing sensors operated in a distributed BHM system. A number of cooperating agents is implemented in smart conditioning units which can autonomously operate in an adverse environment and communicate with other nodes via a serial interface. The project uses special versions of reduced instruction set chips that are able to operate near the hot section of the engine. Due to the limited number of types of microprocessors available in the extended temperature range grading, it was necessary to fully utilize the limited hardware resources and implement preemptive multitasking. For this purpose, a custom operating system and communication protocol were designed. The protocol hosts the middle layer which hides the implementation of the distributed system. The presented architecture ensures the sufficient computational capacity in individual nodes of the network operated in adverse conditions. It is scalable and resistant to transmission errors.

Immersion in forest environments was shown to produce beneficial effects to human health, in particular psychophysical relaxation, so much that this practice is increasingly recognized as a form of integrative medicine. Limited evidence exists about both statistical significance and size of the effects conditioned on personal characteristics, as well as on the main external variables. The primary purpose of this study was to substantiate the very concept of forest therapy by means of the quantification and significance of the psychological effects, stratified by gender, age groups and place of residence. A preliminary qualitative analysis of the main determinants, in particular the method of conducting, the meteorological comfort and the concentration of volatile organic compounds in the forest atmosphere, was afforded. Seven forest therapy sessions were performed in late summer though early fall, resulting in 150 psychological self-assessment questionnaires administered before and after each session. The results were comparable or even better than others reported in the international literature. Moreover, preliminary evidence arose about different functionality towards specific psychological indexes conditioned at least on gender and age groups, as well as meteorological comfort, structured programs and, possibly, volatile organic compounds showed an impact on the outcomes.

Industries of the food sector have made a great effort to control SARS-CoV-2 indirect transmission, through objects or surfaces, by updating cleaning and disinfection protocols previously focused on inactivating other pathogens, as well as food spoilage microorganisms. The information, although scarce at the beginning of the COVID-19 pandemic, has started to be sufficiently reliable to avoid over-conservative disinfection procedures. This work reviews the literature to propose a holistic view of the disinfection process where the decision variables, such as type and concentration of active substance, are optimised to guarantee the inactivation of SARS-CoV-2 and other usual pathogens and spoilage microorganisms while minimising possible side-effects on the environment and animal and human health.

Supported Wellbeing Centres have been set up in UK hospital trusts in effort to mitigate the psychological impact of COVID-19 on healthcare workers, although the extent to which these are utilised and the barriers and facilitators to access are not known. The aim of the study was to determine facility usage and gather insight into employee wellbeing and the views of employees towards this provision. The study included i) 17-week service use monitoring, ii) employee online survey with measures of wellbeing, job stressfulness, presenteeism, turnover intentions, job satisfaction, and work engagement as well as barriers and facilitators to accessing the Wellbeing Centres. Over 17 weeks, 14,934 facility visits were recorded across two sites (peak attendance in single week n= 2,605). Facilities were highly valued, but the service model was resource intensive with 134 wellbeing buddies supporting the centres in pairs. 819 hospital employees completed an online survey (88% female; 37.7% working in COVID-19 high risk areas; 52.4% frontline workers; 55.2% had accessed a wellbeing centre). There was moderate-to-high job stress (62.9%), low wellbeing (26.1%), presenteeism (68%) and intentions to leave (31.6%). Wellbeing was higher in those that accessed a wellbeing centre. Work engagement and job satisfaction were high. Healthcare organisations are urged to mobilise access to high-quality rest spaces and Psychological First Aid, but this should be localised and diversified. Strategies to address presenteeism and staff retention should be prioritised, and high dedication of healthcare workers should be recognised.

Despite the recognition of the importance of stakeholder inclusion into decisions about new solutions offered to society, responsible innovation (RI) has stalled at the point of articulating a process of governance with a strongly normative loading, without clear practical guidelines toward implementation practices. The principles of RI direct us to involve the user early in the innovation process. However, it lacks direction of how to involve users and stakeholders into this process. In this article, we try to understand how to empower users to become a part of innovation process though empirical cases. Based on 11 cases of firms innovating in digital health and welfare services, we look on firm practices for user integration into their innovation process, as well as how user’s behavior is changing due to new trends such as availability of information and digitalization of services. We try to explore this question through lenses of responsible innovation in the emerging field of digital healthcare.

In this paper, we introduce a non-invasive approach for monitoring bridge infrastructure with ground-based interferometric radar. This approach is called the mirror mode, since it utilises the flat surface of the bridge underside as a mirror to reflect the signal to a corner reflector on the ground placed opposite of the radar sensor. For proving the feasibility of this approach, a measurement campaign has been carried out at an exemplary bridge in Karlsruhe (Germany) including a radar sensor in mirror mode, a second radar sensor in the default mode and a laser profile scanner. We investigate the potential of this approach to monitor the bridge displacement in vertical direction and compare the results with the two other sensors. The derived results reveal the potential for monitoring bridge infrastructure. Finally, we propose further research aspects of this approach to analyse its capabilities and limitation in the context of non-invasive infrastructure monitoring.

On March 2020 strict measures took place in Finland to limit the COVID -19 pandemic. A majority of the Finnish COVID -19 –patients have been located in the southern Finland and consequently cared for in the HUS Helsinki University Hospital. During the ongoing pandemic, HUS personnel’s psychological symptoms are followed via an electronic survey, which also delivers information on psychosocial support services. The baseline survey in June 2020 was sent to 25494 HUS employees out of whom 4804 (19%) answered; altogether 62.4% of the respondents were nursing staff and 8.9% medical doctors. While the follow-up continues for a year and a half, this report shares the sociodemographic characteristics of the respondents and the first results of psychological symptoms from the baseline survey. Out of those who were directly involved in pandemic patients` care, 43.4% reported potentially traumatic COVID-19 pandemic-related experiences vs. 21.8% among the other (p &lt; 0.001). While over a half of the personnel was symptomless, a group of respondents reported pandemic work –related traumatic events and concurrent depressive, insomnia and anxiety symptoms. This highlights the need to ensure appropriate psychosocial support services to all traumatized personnel and PTEs were present especially among nursing staff.

In the Agriculture sector, control of plant leaf diseases is crucial as it influences the quality and production of plant species with an impact on the economy of any country. Therefore, automated identification and classification of plant leaf disease at an early stage is essential to reduce economic loss and to conserve the specific species. Previously, to detect and classify plant leaf disease, various Machine Learning models have been proposed; however, they lack usability due to hardware incompatibility, limited scalability and inefficiency in practical usage. Our proposed DeepLens Classification and Detection Model (DCDM) approach deal with such limitations by introducing automated detection and classification of the leaf diseases in fruits (apple, grapes, peach and strawberry) and vegetables (potato and tomato) via scalable transfer learning on A.W.S. SageMaker and importing it on AWS DeepLens for real-time practical usability. Cloud integration provides scalability and ubiquitous access to our approach. Our experiments on extensive image data set of healthy and unhealthy leaves of fruits and vegetables showed an accuracy of 98.78% with a real-time diagnosis of plant leaves diseases. We used forty thousand images for the training of deep learning model and then evaluated it on ten thousand images. The process of testing an image for disease diagnosis and classification using AWS DeepLens on average took 0.349s, providing disease information to the user in less than a second.

This paper presents a Multilayer Perceptron and Support Vector Machine algorithms approach to predict the number of COVID19 infections in different countries of America. It intends to serve as a tool for decision-making and tackling the pandemic that the world is currently facing. The models were trained and tested using open data from the European Union repository where a time series of confirmed contagious cases was modeled until May 25, 2020. The hyperparameters as number of neurons per layer were set up using a tabu list algorithm. The countries selected to carry out the study were Brazil, Chile, Colombia, Mexico, Peru and the United States. The metrics used are Pearson's correlation coefficient (CP), Mean Absolute Error (MAE), and Mean Percentage Error (MPE). For the testing stage we obtained the following results: Brazil, CP=0.65, MAE=2508 and MPE=17%; Chile, CP=0.64, MAE=504, MPE=16%; Colombia, CP=0.83, MAE=76, MPE=9%; Mexico, CP=0.77, MAE=231, MPE=9%; Peru, CP=0.76, MAE=686, MPE=18% and the United States of America, CP=0.93, MAE=799, MPE=4%. This resulted in powerful machine learning tools although it is necessary to use specific algorithms depending on the data and the stage of the country’s pandemic.

Background: SARS-CoV-2 has resulted in a global pandemic, COVID-19. The disease has spread outrageously from Wuhan, china to rest of the world affecting millions of people. The human transmission is mainly known to occur by aerosols. As almost every dental procedure is associated with aerosol production, oral health care professionals are at a high risk of getting the infection. An attempt has been made to render cohesive practical suggestions for dental professionals amid COVID-19 outbreak. Objectives: The paper aims at providing evidence based information in managing dental patients during this pandemic. Material and Methods: The paper provides a broad overview of predominant findings based on electronic database search regarding COVID-19 outbreak and its effect on dental practice. Conclusion: Dental care should not be neglected due to the pandemic. Thorough knowledge about the disease and its prevention will not only help us in providing care to these patients but will also help in preventing the nosocomial spread of infection.

Internet of things security will be a big challenge for the enterprises working behind the build-up of the internet of things, and it’s application. With IoT, another buzzword is blockchain-based cryptocurrency bitcoin. Blockchain technology has proven itself as one of the most secured existing technology. In this paper, we have discussed the significant challenges that will come up in identity management due to the heterogeneity of devices. We have proposed a solution for privacy preservation using secure identity management and possible communication methodology by using public key-based cryptography used in the blockchain. We have taken the ecosystem of smart home management and smart health management. At last, we have concluded with the discussion of futuristic applications of blockchain in other applications of the internet of things.

Objective: This study investigated the effect of the hierarchical medical system under the national health insurance program on resident’s healthcare-seeking behavior in Taiwan. Background: Healthcare authorities in Taiwan initiated the allowance reduction of outpatient visits at regional hospitals and higher hierarchical hospitals from 2018. The ultimate goal is to implement a hierarchical medical system and provide the residents accessible as well as consistent medical services. Methods: This research was conducted through the questionnaire survey method and data were collected between August and December 2018 from the records of subjects who had recently sought medical attention. A total of 1,340 valid questionnaires were returned. Results: Regarding the effect on healthcare-seeking behavior, the following factors were significant: being aged between 40 to 49 (p＜.1), subjects with an educational background of junior high school (p＜.05), those who were not aware of the policy (p＜.001), and an awareness about both the hierarchical medical system and the policy to reduce outpatient visits to large hospitals (p＜.001). Conclusion: The public should be made aware about the hierarchical medical system to improve healthcare.

In this paper, a novel pendulum-type accelerometer based on hetero-core fiber optics has been proposed for structural health monitoring targeting large-scale civil infrastructures. Vibration measurement is a non-destructive method for diagnosing the failure of structures by assessing natural frequencies and other vibration patterns. The hetero-core fiber optic sensor utilized in the proposed accelerometer can serve as a displacement sensor with robustness to temperature changes in addition to immunity to electromagnetic interference and chemical corrosions. Thus the hetero-core sensor inside the accelerometer measures applied acceleration by detecting the rotation of an internal pendulum. A series of experiments showed that the hetero-core fiber sensor linearly responded to the rotation angle of the pendulum ranging within ±5°, and furthermore the proposed accelerometer could reproduce the waveform of input vibration in a frequency band of several Hz order.

Demographic change is leading to the aging of German society. As long as the baby boom co-horts are still of working age, the working population will also age - and decline as soon as this baby boom generation gradually reaches retirement age. At the same time, there has been a trend towards increasing absenteeism (times of inability to work) in companies since the zero years, with the number of days of absence increasing with age. We present a novel stochastic forecast approach that combines population forecasting with forecasts of labor force participation trends, considering epidemiological aspects. For this, we combine a stochastic Monte Carlo-based cohort-component forecast of the population with projections of labor force participation rates and morbidity rates. This article examines the purely demographic effect on the economic costs associated with such absenteeism due to the inability to work. Under expected future employment patterns and constant morbidity patterns, absenteeism is expected by close to 5 percent by 2050 relative to 2020, associated with increasing economic costs of almost 3 percent. Our results illustrate how strongly the pronounced baby boom/ baby bust phenomenon determines demographic development in Germany in the midterm.

C-reactive protein (CRP) and leukocytes are blood biomarkers involved in "Inflamm-Aging", which is a risk factor for the onset and progression of age-related diseases. Studies show that higher serum concentrations of these biomarkers are associated with functional disability, increased risk of low muscle strength, decreased muscle mass and mortality in the elderly. The objective was to estimate the predictive power and discriminating criteria of C-reactive protein and leukocyte concentrations for the risk of adverse health factors in the elderly within 30 days after hospital discharge (HD). Prospective cohort study using exploratory methods and blood biomarkers with 135 older adults admitted to medical and surgical clinics at a government hospital. The elderly were monitored at home after 30 days of HD for adverse health factors (rehospitalization, falls, amount of medication consumed, disability in basic and instrumental activities of daily living and mortality). CRP> 2.4; ≥ 0.7 and> 24.7 mg / dL and leukocytes ≥ 6.410; ≥ 8.690 and> 8.310 mm³ were discriminant for rehospitalization, falls and mortality within 30 days after HD, respectively. The cut-off points described may be used as a reference in the screening of hospitalized elderly vulnerable to adverse health events after hospital discharge.

Dams are a critical infrastructure system for many communities, but they are also one of the most challenging to inspect. Dams are typically very large and complex structures, and the result is that inspections are often time-intensive and require expensive, specialized equipment and training to provide inspectors with comprehensive access to the structure. The scale and nature of dam inspections also introduces additional safety risks to the inspectors. Unmanned aerial vehicles (UAV) have the potential to address many of these challenges, particularly when used as a data acquisition platform for photogrammetric three-dimensional (3D) reconstruction and analysis, though the nature of both UAV and modern photogrammetric methods necessitates careful planning and coordination for integration. This paper presents a case study on one such integration at the Brighton Dam, a large-scale concrete gravity dam in Maryland, USA. A combination of multiple UAV platforms and multi-scale photogrammetry was used to create two comprehensive and high-resolution 3D point clouds of the dam and surrounding environment at intervals. These models were then assessed for their overall quality, as well as their ability to resolve flaws and defects that were artificially applied to the structure between inspection intervals. The results indicate that the integrated process is capable of generating models that accurately render a variety of defect types with sub-millimeter accuracy. Recommendations for mission planning and imaging specifications are provided as well.

The persistence of geographic inequities in vaccination coverage often evidences the presence of zero-dose and missed communities and vulnerabilities to vaccine-preventable diseases. These inequities were exacerbated in many places during the COVID-19 pandemic, due to severe disruptions to vaccination services. Understanding changes in zero-dose prevalence and associated risk factors in the context of the COVID-19 pandemic is, therefore, critical to designing effective strategies to reach vulnerable populations. Using data from nationally representative household surveys conducted before the COVID-19 pandemic in 2018 and during the pandemic in 2021 in Nigeria, we fitted Bayesian geostatistical models to map the distribution of three vaccination coverage indicators: receipt of DTP1, MCV1 and any of the four basic vaccines (BCG, OPV0, DTP1 and MCV1), and corresponding zero-dose estimates independently at 1x1 km resolution and the district level during both time periods. We also explored changes in the factors associated with non-vaccination at the national and regional levels using multilevel logistic regression models. Our results revealed no increases in zero-dose prevalence due to the pandemic at the national level, although considerable increases were observed in a few districts. We found substantial subnational heterogeneities in vaccination coverage and zero-dose prevalence both before and during the pandemic, showing broadly similar patterns in both time periods. Areas with relatively higher zero-dose prevalence occurred mostly in the north and a few places in the south in both time periods. We also found consistent areas of low coverage and high zero-dose prevalence using all three zero-dose indicators, revealing areas in greatest need. At the national level, risk factors related to socioeconomic/ demographic status (e.g., maternal education), maternal access to and utilization of health services and remoteness were strongly associated with the odds of zero dose in both time periods, while those related to communication were mostly relevant before the pandemic. These associations were also supported at the regional level, but we additionally identified risk factors specific to zero dose in each region; for example, communication and cross-border migration in the northwest. Our findings can help guide tailored strategies to reduce zero-dose prevalence and boost coverage levels in Nigeria.

Background and objectives: Only a few studies analyzed the physical activity level of elderly people living alone in local communities and evaluated the relationship between it and mental health. The purpose of this study was to investigate the relationship between physical activity and depression in the elderly living alone and to provide basic data for the prevention of depression in the elderly. Materials and Methods: We analyzed 256 elderly people living alone aged 65 years or older who completed the 2014 Korea National Health and Nutrition Examination Survey. Depression was defined as a score of 10 or higher using Patient Health Questionnaire-10(PHQ-9). This study investigated walking per week, days of muscular strength exercise performance in the past one week, days of flexibility exercise in the past one week, mean hours in a sitting position per day, the numbers of days and hours conducting a high intensity physical activity in the past one week, and numbers of days and hours conducting a medium intensity physical activity in the past one week to define physical activity. Our study presented prevalence odds ratios (pOR) and 95% confidence interval (CI) by using complex sample logistic regression analysis in order to identify the relationship between physical activity and depression. Results: The results of complex sample logistic regression analysis showed that flexibility exercise was significantly related to depression (p <0.05). On the other hand, the mean hours in a sitting position per day, aerobic physical activity, walking, and muscular strength exercise were not significantly related to geriatric depression. Conclusions: The results of our study implied that persistent flexibility exercise might be more effective to maintain a healthy mental status than muscular strength exercise. A longitudinal study is required to prove the causal relationship between physical activity and depression in the old age.

Healthy diet interventions have been shown to improve depressive symptoms, but there is a need for randomized controlled trials (RCTs) that are double-blind and investigate biological mechanisms. The primary objectives of this randomized controlled pilot trial were to test the palatability of the meals and acceptability of the intervention in preparation for a future 8-week RCT which will investigate whether a healthy Nordic diet improves depressive symptoms in individuals with major depressive disorder, and associated biological mechanisms. Depressed (n=10) and non-depressed (n=6) women and men were randomized to receive either a healthy Nordic diet (ND) or a control diet (CD) for 8 days. Participants were blinded to diet allocation and study hypotheses. Health questionnaires were completed before and after the intervention, and, throughout the study, questionnaires assessed ratings of liking and sensory properties of the meals, adherence, and open-ended feedback. In the ND group, 75% of participants consumed no non-study foods, compared to 50% of CD participants. The meals of both diets, on average, received good ratings for liking and sensory properties, though the ND ratings were somewhat higher. Overall, results were positive and informative, indicating that the planned RCT will be feasible and well-accepted, with some proposed modifications.

The physiological response to a psychological stressor broadly impacts energy metabolism. In-versely, changes in energy availability affect the physiological response to the stressor in terms of hypothalamus, pituitary adrenal axis (HPA) and sympathetic nervous system activation. Glu-cocorticoids, the endpoint of the HPA axis, are critical checkpoints in endocrine control of ener-gy homeostasis and have been linked to metabolic diseases including obesity, insulin resistance and type 2 diabetes. Glucocorticoids, through the glucocorticoid receptor, activate transcription of genes associated with glucose and lipid regulatory pathways and thereby control both physi-ological and pathophysiological systemic energy homeostasis. Here, we summarize the current knowledge of glucocorticoid functions in energy metabolism and systemic metabolic dysfunc-tion, particularly focusing on glucose and lipid metabolism. There are elements in the external environment that induce lifelong changes in the HPA axis stress response and glucocorticoid levels, the most prominent are early-life adversity, or exposure to traumatic stress. We hypothe-sise that when the HPA axis is so disturbed after early-life adversity, it will fundamentally alter hepatic gluconeogenesis, inducing hyperglycaemia, and hence crystalise the significant lifelong risk of developing either the metabolic syndrome, or type 2 diabetes. This gives a “Jekyll and Hyde” role to gluconeogenesis, providing the necessary energy in situations of acute stress, but driving towards pathophysiological consequences when the HPA axis has been altered.

After three years of the onset of the pandemic, there is scarce evidence about how COVID-19 disease affect the female reproductive system, and consequently, the menstrual cycle. Since the common causes of secondary amenorrhea are considered as exclusion criteria in the studies about menstrual changes following SARS-CoV-2 infection, the prevalence of this event and the influencing factors in formerly menstruating women remains unknown. A retrospective observational cross-sectional study was conducted on Spanish adult women (N= 17,512), using an online survey; a subpopulation of SARS-CoV-2-infected-formerly menstruating women was included in the present analysis (n= 72). Collected data included general characteristics, medical history, and specific information about COVID-19 disease. 38.9% of the respondents experienced menstrual-related disturbances after suffering from the COVID-19 disease, unexpected vaginal bleeding being the most common (20.8%). Other alterations related with the length – “shorter” by 12.5% − and the flow − “heavier than usual” 30.3% − of the menstrual bleeding were reported. The binary logistic regression showed that being a perimenopausal woman (AOR 4.608, CI 95%, 1.018 – 20.856, p = 0.047) and having heavy menstrual bleeding (AOR 4.857, CI 95%, 1.239 – 19.031, p=0.023) are influential factors. This evidence could help health professionals to provide scientifically up-to-date information to their patients, empowering them to actively manage their reproductive health, especially in those societies where menstrual health is still a taboo.

Growing evidence suggests that healthcare provider advice may increase tobacco cessation, reduce alcohol use, and improve the adoption of desirable lifestyle behaviors among patients. However, how brief interventions and other provider-patient interactions can shape cumulative adoption of multiple modifiable behaviors is less well studied for diabetes prevention and control. Using weighted internet panel survey data from a large socio-demographically diverse urban population in the United States (n=1,003), the present study describes differences in group characteristics among those who had been “ever diagnosed” with prediabetes/diabetes versus those who had not. It also examines the associations between the cumulative adoption of lifestyle behaviors and each of the following: a) lifetime prediabetes/diabetes diagnosis; b) brief lifestyle intervention exposure (i.e., received provider advice/encouragement); and c) recent provider-patient communication about diabetes. There were several group differences in “ever diagnosed” prediabetes/diabetes status by age, employment status, health status, nutrition knowledge, blood pressure/hypertension diagnosis, and diabetes-related health behaviors (p<0.05). Each of the three provider-patient interactions of interest were positively associated with a higher cumulative sum of adopted modifiable lifestyle behaviors for diabetes prevention and management. Results suggest that provider advice/provider-patient interactions of any type can have a salutary impact on whether individuals with prediabetes or type 2 diabetes will engage in recommended lifestyle behavior modifications.

Toxoplasmosis is a zoonosis of warm-blooded animals, affecting also humans, caused by Toxo-plasma gondii, an obligate intracellular parasite with a complex biological cycle. Toxoplasmosis is considered a re-emerging zoonosis and an important public health threat, also for the absence, up to now, of efficient vaccines and preventive measures. Sources of transmission to humans are environmental or food-borne, mainly through the consumption of raw and undercooked meat, predominantly of Sus scrofa, considered highly susceptible to T. gondii. Mainly in the last dec-ades, an effective strategy to counter animal infectious diseases was based on the discovery of resistance immuno-genetic markers, possibly to be used for association studies between geno-typic and phenotypic traits and consequently in Marker Assisted Selection. Until now, this gen-otyping approach has never been adopted for T. gondii infection, so this study aimed, for the first time, to fill this gap. In particular, pigs, reared in different farms of Central Italy, were serologically characterized by an ELISA assay performed on diaphragm meat juice. Out of 179 tested animals, 98 resulted seropositive (54.74%), 57 seronegative (31.84%) and 24 doubtful (10.6%), underlining a possible re-emerging diffusion of this protozoan in the investigated areas. Atten-tion was firstly focused on IL-18 gene, encoding for a pro-inflammatory cytokine that plays a key role starting from the upstream steps of the immunity pathway towards T. gondii. A RT-PCR assay followed by Sanger sequencing of IL-18 cDNA was de novo developed. For this interleukin, at this stage, genetic analysis has not highlighted significant polymorphic variations compared to the reference sequence, except for a seropositive animal. However, the outcomes of this pre-liminary innovative study will be investigated in depth analyzing other relevant genetic re-gions and other target genes.

AbstractIntroduction: Increasing knowledge of obstetric danger signs (ODS) and encouraging birth preparedness and complication readiness (BPCR) practices are strategies to increase skilled maternal health service utilization in low-income countries. One of the methods to increase mothers' knowledge about ODS and promote BPCR practice is through health education intervention (HEI). However, the effect of context-specific community-based health education led by women's groups on these outcomes has not been comprehensively studied, and the existing evidence is inconclusive. Thus, we aimed to evaluate the effect of a context-specific community-based HEI led by women's groups on mothers' knowledge regarding ODS and BPCR practices in southern Ethiopia.Methods: An open-label, two-arm parallel group cluster-randomized controlled trial was conducted from January to August 2023 on pregnant women from 24 clusters (kebeles) (12 interventions and 12 controls) in the northern zone of the Sidama region. The Open Data Kit smartphone application was utilized to collect data. The intention-to-treat analysis was used to compare outcomes between groups. We fitted multi-level mixed-effects modified Poisson regression with robust standard error to account for between and within cluster effects. Results: One thousand and seventy pregnant women (540 in the intervention and 530 in the control clusters) responded to this study, making the overall response rate 95.02%. Excessive vaginal bleeding (94.3% in the interventional group vs. 88.7% in the control group) was the commonest ODS mentioned during childbirth. Overall, 68.7% of women in the intervention group and 36.2% of mothers in the control group had good knowledge of ODS (P-value < 0.001). Saving money and materials (97.1% in the interventional group vs. 92.7% in the control group) was the most frequently practiced BPCR plan. Overall, 64.3% of women in the intervention group and 38.9% of mothers in the control group practiced BPCR (P-value < 0.001). HEI significantly increased overall knowledge of ODS (adjusted risk ratio [ARR]: 1.71; 99% CI: 1.14-2.57) and improved overall BPCR practice (ARR: 1.55; 99% CI: 1.02-2.39). Conclusions: A community-based HEI led by women's groups improved mothers' knowledge regarding ODS and BPCR practices in a rural setting in southern Ethiopia. Interventions designed to increase women's knowledge of ODS and improve BPCR practice must implement context-specific, community-based HEI that aligns with World Health Organization recommendations. Trial registration: NCT05865873

Sensory Processing Sensitivity (SPS) is a trait describing inter-individual differences in sensitivity to environments, both positive and negative ones. SPS has attracted growing societal interest. However, (neuro)scientific evidence is lagging behind. We critically discuss how to measure SPS, how it relates to other theories of Environmental Sensitivity and other temperament and personality traits, how SPS interacts with environments to influence (a)typical development, what the underlying aetiologies and mechanisms are, and its relation to mental disorders involving sensory sensitivities. Drawing on the diverse expertise of the authors, we set an agenda for future research to stimulate the field. We conclude that SPS is a heritable, evolutionarily conserved trait, linked to increased risk for psychopathology and stress-related problems in response to negative environments, as well as to greater benefits (e.g., intervention responsivity, positive mood) in positive environments. We need advances in objective assessment of SPS, understanding mechanisms, differentiating it from (seemingly) related mental disorders, to exploit the potential of SPS to improve mental health, preserve human capital, and prevent adverse effects.

Background: The epidemiological situation generated by COVID-19 has cast into sharp relief the delicate balance between public health priorities and the economy, with businesses obliged to toe a line between employee health and continued production. In an effort to detect as many cases as possible, isolate contacts, cut transmission chains and limit the spread of the virus in the workplace, mass testing strategies have been implemented in both public health and industrial contexts to minimize the risk of disruption in activity. Objective: To evaluate the economic impact of mass workplace testing strategy as carried out by a large automotive company in Catalonia in terms of health and healthcare resource savings. Methodology: Analysis of health costs and impacts based on the estimation of mortality and morbidity avoided because of screening and the resulting savings in healthcare costs. Results: The economic impact of the mass workplace testing strategies (using both PCR and RAT tests) was approximately €10.44 per test performed or €5,575.49 per positive detected. 38% of this figure corresponds to savings derived from better use of health resources (hospital beds, ICU beds and follow-up of infected cases), while the remaining 62% corresponds to improved health rates due to avoided morbidity and mortality. In scenarios with higher positivity rates and a greater impact of the infection on health and the use of health resources, these results could be up to ten times higher (€130.24 per test performed or €69,565.59 per positive detected). Conclusion: In the context of COVID-19, preventive actions carried out by the private sector to safeguard industrial production also have concomitant public benefits in the form of savings in healthcare costs. Thus, governmental bodies need to recognize the value of implementing such strategies in private settings and facilitate them through, for example, subsidies.

Carbon monoxide (CO) is a colorless, odorless gas emitted from carbon fuel combustion. In this study we monitored indoor carbon monoxide (CO) levels for 120 homes over three seasons in the North Denver metropolitan region as part of an environmental justice initiative to quantify health and social well-being impacts from a major freeway construction upgrade nearby. Urban outdoor CO levels are typically very low (less than 1 ppm in Denver) due to air pollution control strategies and technologies implemented over the past several decades. However, people can still be exposed to higher than outdoor levels of CO in their homes due to the operation of indoor appliances that use carbon fuels such as natural gas. Our data show that ~10% of the homes had consistent daily average levels of CO above 3.5 ppm and 24-57% of the homes showed peaks greater than 9 ppm. While much higher levels can result in CO poisoning and fatalities, these lower levels of CO have been associated with adverse health impacts, especially pregnant women, and sensitive populations. Our results highlight the need for increasing awareness regarding CO exposures in homes with gas appliances and motivate the transition from non-electrified homes toward electrification.

Despite the extensive literature on missing data theory and cautionary articles emphasizing the importance of realistic analysis for healthcare data, a critical gap persists in incorporating domain knowledge into missing data problem formulation, assumption specification, and method development. In this paper, we highlight the gap particularly for observational data from healthcare facilities. We address this gap by identifying ten fundamental missingness scenarios arising during data measurement, recording, and pre-processing in observational health data, influenced by physicians, patients, healthcare facilities, and data scientists. We analyze the effect of scenarios on estimand formulation, missing data identification, estimation, and sensitivity analysis. To emphasize how domain-informed analysis can improve method reliability, we conduct simulation studies under the influence of various missingness scenarios. We compare the results of three common methods in medical data analysis (complete-case analysis, Missforest imputation, and inverse probability weighting estimation) for two estimands (variable mean estimation and classification accuracy). We advocate for our analysis approach as a reference for the analysis of observational health data. Furthermore, we posit that the proposed analysis framework is applicable to other medical domains, including medical wearable data analysis.

Efficient triaging and referral assessment are critical in ensuring prompt medical intervention in the Community Health Care (CHC) system. However, the existing triaging systems in many Community Health Services are an intensive, time-consuming process and often lack accuracy, particularly for various symptoms that might represent heart failure or other health-threatening conditions. There is a noticeable limit of research papers describing AI technologies for triaging patients. This paper proposes a novel quantitative data-driven approach using machine learning (ML) modelling to improve the community clinical triaging process. Furthermore, this study aims to employ the feature selection process and machine learning power to reduce the triaging process’s waiting time and increase accuracy in clinical decision-making. The model was trained on medical records of “Heart Failure” patients’ dataset, which included demographics, past medical history, vital signs, medications, and clinical symptoms. A comparative study was conducted using the list of machine learning algorithms where XGBoost demonstrated the best performance among other ML models. The triage levels of 2,35,982 patients achieved an accuracy of 99.94%, precision of 0.9986, recall of 0.9958, and f1-score of 0.9972 within 0.059 seconds. The proposed diagnostic model can be implemented for the CHC decision system and be developed further for other medical conditions.

Indigenous peoples around the world are revitalizing their ancestral beliefs, practices, and languages, including traditional understandings of health and wellbeing. In the Aotearoa (New Zealand) context, a number of ground-breaking Māori health and wellbeing related models have emerged, each with their own unique applications and offerings. We sought in these qualitative studies to explore and identify some key sources of wellbeing for Māori individuals. Nine interviews were conducted with members of Māori communities to identify key themes of Māori wellbeing. A Reflexive Thematic Analysis was performed on these data, and then a further fifteen interviews were conducted to revise, refine, and reposition the previously generated themes. The Ngaruroro describes wellbeing as the embodied and active process of being in good relation with your 1) here tāngata (social and familial ties), 2) te taiao (the environment), and 3) taonga tuku iho (cultural treasures), while doing what you can to make lifestyle choices that are conducive to the health of your 4) tinana (body) and 5) wairua (spirit), while cultivating a balanced 6) ngākau (inner-system), fulfilling 7) matea (core needs), and exercising your 8) mana (authority). These themes illustrate and reiterate that Māori wellbeing is dynamic, interconnected, and holistic.

This study aimed to conduct importance-performance analyses (IPAs) based on the perception of Korean middle-school students toward health management awareness during the post-coronavirus disease 2019 (COVID-19) era. Data were collected from 867 Korean middle-school students via online and offline surveys between May and June 2023. A frequency analysis, a reliability analysis, an IPA based on the entire target students, and an IPA depending on sex were carried out with the collected data, and they revealed the following. First, the IPA results regardless of sex indicated that four factors of the mental health were located in the third quadrant with one factor of the same variable in the fourth quadrant. The three factors of the disease management were located in the third quadrant. As for physical activity, two factors were located in the first quadrant, one in the second quadrant, and one in the third quadrant. As for sleep management, two factors were located in the second quadrant, one in the third quadrant, and one in the first quadrant. As for the eating management, two factors were located in the third quadrant, and one in the fourth quadrant. As for the social distancing variable, all four factors were located in the third quadrant. As for the hygiene management, two factors were located in the first quadrant, one in the third quadrant, and one in the fourth quadrant. Furthermore, the IPA results indicated gender differences in regular sports and vigorous movement activities associated with the physical activity. Additionally, a gender difference was observed in regular diet associated with the eating management. This study proposed possible measures for encouraging adolescents to recognize the importance of health and increase their health-related performance during the COVID-19 endemic phase.

The early detection of small cracks in large structures is a crucial requirement for the implementation of structural health monitoring (SHM) system with a low transducer density. This work presents the results of the analysis of scattering of a submillimeter notch type defect with semielliptical shape with a groove at constant width 100µm in a 4.1mm thick aluminum plate. The defect is investigated with an ultrasonic guided wave (UGW) A0 mode at 550 kHz to cover long range in a thick plate. The mode selection is obtained by interdigital transducers designed to operate with 5mm central wavelength. The novel contribution is the assessment of the scattering amplitudes at different orientations of the defect when the distance is large as 35 cm in pulse-echo mode or 70 cm in pitch-catch mode. The system model is based on Finite Element Model (FEM) simulations and the results are in good agreement with experimental tests. The detection of the defect is obtained by comparing the scattered signals from the defect with base line signals of the pristine laminate. The analysis of scattering features and the efficient excitation with a probing UGW show the potential implementation in real structural health monitoring (SHM) systems.

As breast cancer continues to take a devasting public health toll, most primary prevention approaches are targeted at individual actions. We have proposed, instead, developing systemic, population approaches to preventing the disease. We used a combined qualitative-quantitative methodology, Group Concept Mapping (GCM), to identify Importance and Feasibility ratings of systemic interventions across a wide spectrum of approaches and stakeholders. Participants (n=351) from across the state of California sorted 84 potential interventions into topical piles, and then rated each intervention on perceived Importance and Feasibility. Multidimensional scaling and cluster analysis identified eleven clusters or themes of interventions. Participants rated interventions on Importance and Feasibility differently depending on the region of the state in which they lived. The results of this study underscore the importance of sharing health information with and seeking public health solutions from community partners in general and from beyond the urban areas usually studied.

AbstractBackground: Empowering Communities, Combating HIV/AIDS: The Indispensable Role of Community-Based Strategies in Awareness and PreventionObjective: Highlight the significance of community-based approaches in addressing the ongoing HIV/AIDS pandemic through enhanced awareness, reduced stigma, and effective prevention measures.Method: This article provides a theoretical analysis of community-based HIV/AIDS interventions, drawing upon key strategies and successful examples from diverse settings.Results: Community-based initiatives emerge as critical factors in empowering individuals and communities to take ownership of their health. Through culturally-sensitive education, accessible testing, and comprehensive support services, these initiatives effectively diminish the social stigma surrounding HIV/AIDS and promote preventative behaviors. Examples of successful programs illustrate the potential of community-driven approaches to achieve measurable reductions in transmission rates and improved health outcomes.Conclusion: The fight against HIV/AIDS necessitates robust community engagement. Community-based interventions, grounded in local knowledge and addressing specific needs, offer a promising pathway towards fostering health equity, reducing stigma, and ultimately curtailing the spread of the virus. Further research and investment in these initiatives are crucial to ensuring their scalability and sustained impact on global HIV/AIDS prevention efforts.

(1) Background: Environmental and public health research has given considerable attention to the impact of air quality on brain health, with systematic reviews widespread. No literature review has been done for cognitive frailty – a multidimensional syndrome combining physical frailty and cognitive impairment and their apparent co-dependence, linked to increased vulnerability and adverse health outcomes, including dementia. Instead, cognitive decline and frailty is implicitly explored through research on air quality and comorbid cognitive and physical decline in elderly populations. (2) Methods: A scoping review was conducted to explore the need for a systematic review. Combining Arksey and O’Malley [1] and PRISMA-ScR checklist [2], a scoping review of SCOPUS using ‘cogniti*’ + ‘resilience’ + ‘air quality’ or ‘cogniti*’ + ‘ageing’ + ‘air quality’ resulted in N=2503 articles, screened and reduced using inclusion and exclusion criteria, to N=16 articles. (3) Results: Air quality appears to be a critical risk factor for cognitive decline, even at air quality levels below WHO targets. Moderate long-term ambient air pollution appears linked to increased risk of cognitive frailty, suggesting earlier and more active interventions to protect older people. There are varied effects on cognition across the life course, with both emotional and functional impacts. Effects may be more detrimental to elderly people with existing conditions, including economic and health inequalities. Generalisation of results is limited due to the absence of a dose-response, variations in methods, controlling for comorbid effects, and variance across studies. (4) Conclusions: The findings support the need for more research and a more extensive summary of the literature.

In response to new developments of work and employment in high-income countries (HICs), psychosocial aspects of work and health received increased attention. In contrast, middle-income countries (MICs) are mainly concerned with severe challenges of noxious and dangerous material work environments, poor employment conditions, and deficient social policies, leaving psychosocial aspects in a marginal role at best. More recently, differences between these two worlds were even aggravated by the COVID-19 pandemic. Yet, with economic globalisation and growing worldwide interconnectivity, the world of work in MICs is being rapidly transformed, sharing several concerns with modern Western societies. In this process, psychosocial occupational health will become an increasingly pressing issue. This contribution explores to what extent psychosocial aspects of work and health are already addressed in research originating from MICs. A selective focus on recent findings from two regions, Asia Pacific and Latin America, reveals a high degree of awareness of, and inquiry into, work-stress related problems within these countries. Importantly, in addition to incorporating research progress from HICs, these analyses identify new aspects within specific cultural and socio-economic environments, thus enriching the international state of art.

Background The workload of nurses in the intensive care unit (ICU) can affect the quality of nursing services. Aim This study aimed to determine the relationship between the nursing activity score and missed care in patients hospitalized in the ICU in Zanjan, Iran. Methods This observational and prospective study was conducted from April 3 to September 18 in 2021. In this study, the tools used included a patient and nurses' profile questionnaire, Nursing Activity Score (NAS). Missed care was observed in the 301 patients for whom the NAS was calculated. Analysis of variance (ANOVA) was used to investigate the differences in mean levels of missed care. Logistic regression models were used to assess the association between factors and missed nursing care. Results Results show that the Medical ICU's mean NAS was 76.31 (95% CI: -13.06 -14.89). In 9 dimensions of care, the extent of missed care was 40.7%. In the care dimensions of assessment, hand hygiene, and infection control, the mean NAS had a statistically significant increase at higher levels of missed care (P<.5). Furthermore, work experience was identified as a protective factor for missed care (OR =.59, 95% CI: .37–.94, χ2= =4.97, p =.026). Conclusion The study revealed a high incidence of missed care. The study revealed that the mean workload was high in certain dimensions of care such as assessment, hand hygiene, and infection control. The increase in workload for nurses results in lost care. Nonetheless, the utilization of experienced nurses can help mitigate this problem. However, utilizing experienced nurses can help reduce this problem.

The prevalence of digital devices in modern society has raised concerns about the potential neg-ative effects of blue light emissions on eye health and biological rhythms. Research into blue light emissions from digital devices and their potential impact on eye health emphasizes the importance of understanding and quantifying the extent and scope of blue light emissions produced by commonly used screens (smartphones, tablets and computers). This comparative study specifically evaluates three popular Apple devices: iPhone 12 mini®, iPad Pro 12.9® and MacBook Pro®. The devices' spectral power was measured using a spectroradiometer while displaying text and a game at different brightness levels. The study also examines the effectiveness of blue-blocking lenses from well-known brands. The research highlights the importance of quantifying blue light emissions and understanding their potential impact on eye health. By doing so, appropriate measures can be developed to mitigate adverse effects on ocular structures. Above all, this research provides valuable information about the risks associated with exposure to blue light, showing that all tested devices have blue wavelength peaks between 445 nm and 455 nm. By recognizing and addressing the potential negative impacts of blue light, the risks of eye health problems can be reduced and ensure more responsible and conscious use of digital devices.

Water is one of the most critical factors affecting environmental health. For this reason, estimating and monitoring the behavior of water in nature and preventing water pollution before it occurs are advantageous to avoid problems that may occur in terms of environmental health. In order to predict the behavior of water, the hydrological cycle needs to be evaluated on a basin basis. At this point, hydrological models can be used to make mathematical representations of hydrologi-cal processes. These models play an essential role in predicting and monitoring problems such as poor water quality, pollution, particle and sediment transport, and proliferation of oil and petro-leum derivatives among frequently encountered issues in environmental health. In this study, a 2D surface water model was created using soil and water assessment tool (SWAT) to simulate the lotic ecosystem and existing water quality in Tatlıçay Basin and to propose solutions for im-proving environmental health in Cankiri provincial center in Türkiye. The accuracy of the input data and the validity of the model were checked with the calibration and validation studies by using the monthly or 3-monthly observation data of the General Directorate of State Hydraulic Works’ flow observation & water quality stations from 2016 to 2020. The aim was to provide the opportunity to produce fast, accurate, and practical solutions in the face of negative scenarios with this model. This modelling study obtained successful results in the calibration and valida-tion process with very few observed data. With this study, a significant contribution to the litera-ture on environmental health is made, as there aren't many examples of hydrological modeling from the Middle East.

Objective: This study aimed to examine the relationship between health structure disparities and hospitalizations and deaths among the pediatric population in different regions. Method: The study employed an ecological time series design, utilizing population-based secondary data ob-tained from DATASUS, from the Brazilian Ministry of Health. The data included in this study encompassed the population aged zero to 19 years, health establishments, physicians working in health establishments, hospitalizations, and deaths related to Morbidities listed in the Interna-tional Classification of Diseases. The focus was explicitly on individuals diagnosed with Cere-bral Palsy and other paralytic syndromes. The data for this study were gathered from January 2018 to December 2021. TABNET was used for data collection, and Excel for tabulation and anal-ysis. Results: Analysis of health structure data across regions revealed notable disparities, par-ticularly in the North and Northeast regions, compared to other regions. These discrepancies prompted a decision to conduct a comparative assessment between these regions and the rest of the country. Conclusion: In the North region, a significant 50% difference in hospitalizations based on residence versus a place of care was observed for individuals with Cerebral Palsy and other paralytic syndromes, indicating the necessity for relocation to access appropriate medical treatment.

Self-medication with natural products during disease outbreaks in developing countries poses significant public health challenges yet remains relatively unexplored in the published literature. This study aims to assess the implications of such practices, address the state and quality of evidence, identify gaps in the literature, explore determinants and contributing factors, elucidating the implications, and propose possible solutions. Using a modified systematic literature review methodology, 20 articles were selected from 1,683 reports after applying rigorous selection criteria and quality assessment using the AXIS critical evaluation tool. The findings revealed a dearth of literature concerning the implications of self-medication with natural products during disease outbreaks, highlighting the need for further investigation in this domain. Key determinants included gender, acquisition, and ideological factors, while common side effects comprised diarrhoea, stomach pain, sweating, headache, and nausea/vomiting. Notably, self-medication with natural products was associated with reduced communication with healthcare providers, leading to underreported side effects. It also creates a false sense of safety which may potentially exacerbate the spread of the prevailing disease. In conclusion, the rampant use of natural products for self-medication necessitates increased awareness among the population, encouraging individuals to seek professional medical care and support when faced with disease outbreaks.

When “hijacked” by compulsive behaviors that affect the reward and stress centers of the brain, functional changes in dopamine circuitry occur as the consequence of pathological brain adaptation. As a brain explanans for mental health, with a central functional role in behavioral regulation from healthy reward seeking to pathological adaptation to stress in response to adversity, we may use dopamine regulation in interaction with other brain mechanisms, as discussed herein, to gather a deeper insight into environmentally triggered mental health changes to understand, for example, specific behavioral changes observed during and after the COVID-19 pandemic. Pandemic-related adversities, the stresses they engendered, and the long lockdown periods where people had to rely on digital tools to get feed-back rewards via the internet can be seen as the major triggers of changes in motivation and reward seeking behavior worldwide. The pathological adaptation of dopamine-mediated reward circuitry in the brain offers a highly plausible explanation why, when pushed by fate and circumstance into a physiological brain state of anti-reward, human behavior and mental health changes almost inevitably depending on individual vulnerability to stress. A unified conceptual account that places dopamine function at the centre of the current global mental health context is proposed.

: Background: Vaccine-related death is one of the leading causes of death among African Children. Vaccine coverage is a very important measure to decrease infant mortality. Covid-19 Pandemic has affected the healthcare system and may have disrupted vaccine coverage. Methods: DTP third doses (DTP3) Vaccine Coverage was extracted from UNICEF databases from 2012 to 2021( the last available date). Joinpoint regression was performed to detect the point where the trend changed. The annual percentage change (APC) with 95% confidence intervals (95% CI) was calculated for Africa and the regions. We compared DTP3 vaccination coverage in 2019 with 2021 in each country to verify compliance with WHO targets. Result: During the whole period, the vaccine coverage in Africa has increased with an Annual Percent change of 1.2% (IC 95% 0.9-1.5): We detected one Joint point in 2019. In 2019-2021, there was a decrease in DTP3 coverage with an APC of -3.5(95% -6.0;-0,9). (P< 0.001). Vaccination rates have decreased in many regions and countries during the last two years. Conclusions. COVID-19 has disrupted vaccine coverage, decreasing it all over Africa.

Public trust in science was tested and relied on during the SARS-CoV-2 pandemic, which has shaped global events since the WHO declaration in March 11, 2020. Public trust has been impacted through the government recommendations and mandates informed by public health guidance, including non-pharmaceutical and pharmaceutical interventions. The free-flow of ideas and in-formation so essential to the functioning of science has faced unprecedented challenge from widespread censorship in both the media and in scientific journals. This has created a poisoned environment for the building of trust between science and society. Scientific norms and ac-countability must be restored in order to rebuild the vital relationship between scientists and the public they serve.

The inverse Finite Element Method (iFEM) is a model-based technique to compute the displacement (and then the strain) field of a structure from strain measurements and a geometrical discretization of the same. Different literature works exploit the error between the numerically reconstructed strains and the experimental measurements to perform damage identification in a Structural Health Monitoring framework. However, only damage detection and localization are performed, without attempting a proper damage size estimation. The latter could be based on machine learning techniques, however, an a priori definition of the damage conditions would be required. To overcome these limitations, the present work proposes a new approach in which the damage is systematically introduced in the iFEM model to minimize its discrepancy with respect to the physical structure. This is performed with a maximum likelihood estimation framework, where the most accurate damage scenario is selected among a series of different models. The proposed approach is experimentally verified on an aluminum plate subjected to fatigue crack propagation, which enables the creation of a Digital-Twin of the structure itself. The strain field fed to the iFEM routine is experimentally measured with an Optical Backscatter Reflectometry fiber and the methodology is validated with independent observations of lasers and the Digital Image Correlation.

Background and Aims: Nurses are increasingly engaging with digital technologies to enhance safe, evidence-based patient care. Digital literacy is now considered a foundational skill and an integral requirement for lifelong learning, and includes the ability to search efficiently, critique information and recognise the inherent risk of bias in information sources. However, at many universities, digital literacy is assumed. In part, this can be linked to the concept of the Digital Native, a term first coined in 2001 by the US author Marc Prensky, to describe young people born after 1980 who have been surrounded by mobile phones, computers, and other digital devices their entire lives. The objective of this paper is to explore the concept of the Digital Native and how this influences undergraduate nursing education. Materials and Methods: A pragmatic approach has been used for this narrative review, working forward from Prensky’s definition of the Digital Native and backward from contemporary sources of information extracted from published health, education, and nursing literature. Results: The findings from this narrative review will inform further understanding of digital literacy beliefs and how these influence undergraduate nursing education. Recommendations for enhancing the digital literacy of undergraduate nursing students are also discussed. Conclusions: Digital literacy is an essential requirement for undergraduate nursing students and nurses, and is linked with safe, evidence-based patient care. The myth of the Digital Native negates the reality that exposure to digital technologies does not equate with digital literacy and has resulted in deficits in nursing education programs. Digital literacy skills should be a part of undergraduate nursing curricula, and National Nursing Digital Literacy competencies for entry into practice as a Registered Nurse should be developed and contextualised to individual jurisdictions.

TomoBreast hypothesized that hypofractionated 15 fractions/3 weeks image-guided radiation therapy (H-IGRT) can reduce lung-heart toxicity, as compared with normofractionated 25-33 fractions/5-7 weeks conventional radiation therapy (CRT). 123 women with stage I-II operated breast cancer were randomized to receive CRT (N=64) or H-IGRT (N=59). The primary endpoint used a four-items measure of the time to 10% alteration in any of patient self-reported measure, physician clinical evaluation, echocardiography or lung function tests, analyzed by intention-to-treat without exclusion. Results found comparable survivals, but H-IGRT significantly reduced the toxicity measured by lung diffusion capacity and alveolar volume as compared with CRT, G1 in 53% (31/59) versus 72% (44/61) patients, P=0.006; G2, 29% versus 48%, P=0.020. H-IGRT significantly reduced the risk of composite cardio-pulmonary alteration at 5 years, 10.2% versus 26.7%, P=0.024. In conclusion, TomoBreast is a proof-of-concept that image-guided radiation-therapy can improve the overall balance of lung-heart outcomes in breast cancer adjuvant therapy. Furthermore, the significance of the findings supports the efficacy of a small trial size design, which can be critical when clinical research resources are limited.

Atmospheric corrosion of aluminum aircraft structures occurs due to numerous reasons. A typical phenomenon leading to corrosion is the deliquescence of contaminants such as salts due to changes in relative humidity (RH) caused by aircraft operation at different altitudes and climate zones. Currently, corrosion of aircrafts is controlled by scheduled inspections. In contrast, the present contribution aims for a continuous monitoring approach by using the acoustic emission (AE) method to detect and further evaluate atmospheric corrosion. The AE method is frequently used for corrosion detection at typically immersion-like conditions or for corrosion types where stress-induced cracking is involved. However, it has not yet been demonstrated for atmospheric corrosion at unloaded aluminum structures. To address this question, the present investigation uses small droplets of a corrosive sodium chloride (NaCl) solution to induce atmospheric corrosion on aluminum alloy AA2024-T351. Operating conditions of an aircraft are simulated by a controlled variation in RH. In addition, videos of the corrosion site are recorded to visually observe the corrosion process. Pitting corrosion is generated and clearly measurable AE signals are detected. An automatic video processing algorithm looking for sudden changes on the corrosion site mainly detects hydrogen bubbles formed when aluminum reacts with aqueous solutions. A clear correlation between the observed pitting corrosion, the AE and the hydrogen bubble activity and the RH, i.e., the electrolyte present at the aluminum surface, is found. Thus, the findings demonstrate the applicability of the AE method for monitoring atmospheric corrosion of aluminum aircraft structures by today’s measurement equipment. Numerous potential effects that can cause measurable AE signals are investigated and discussed. Among these, bubble activity is clearly considered to be the most emissive one.

Online reinforcement learning (RL) algorithms are increasingly used to personalize digital interventions in the fields of mobile health and online education. Common challenges in designing and testing an RL algorithm in these settings include ensuring the RL algorithm can learn and run stably under real-time constraints, and accounting for the complexity of the environment, e.g., a lack of accurate mechanistic models for the user dynamics. To guide how one can tackle these challenges, we extend the PCS (Predictability, Computability, Stability) framework, a data science framework that incorporates best practices from machine learning and statistics in supervised learning (Yu and Kumbier, 2020), to the design of RL algorithms for the digital interventions setting. Further, we provide guidelines on how to design simulation environments, a crucial tool for evaluating RL candidate algorithms using the PCS framework. We illustrate the use of the PCS framework for designing an RL algorithm for Oralytics, a mobile health study aiming to improve users' tooth-brushing behaviors through the personalized delivery of intervention messages. Oralytics will go into the field in late 2022.

Being hospitalized is a threatening and stressful experience for many children. From a psychological point of view, children may experience increased feelings of anxiety and fear that can negatively interfere with behavioral, cognitive, and emotional outcomes. To limit these impacts on children's well-being and mental health, interventions that could contribute to protecting the emotional domain of hospitalized children are welcomed. The present research reported a single-setting case study intervention to evaluate the impact of educational play-based activity with a CoderBot robot in a pediatric short-term recovery ward (N=61). The methodology included multiple sources of data (i.e., children, parents, nurses), observations on the field, and a sequential (quantitative-qualitative) mixed-method approach to data analysis. Results supported the idea that robot-based activities were associated with increased participant well-being (particularly positive emotions). The conclusions of this pilot study discuss the strengths, limitations, and further developments of using robots with hospitalized children.

To determine the adequacy of management practices in Social Health Organization (SHO) in face of compliance guidelines established by Brazilian organizations. This was qualitative research. Data were gathered through interviews and documentary analysis and were analyzed through the interpretation of significances and content analysis. The entity structures the compliance function based on three axes: a) normative - institutionalization of the integrity program, ethical conduct, internal controls and risk management; b) commercial - institutionalization of mechanisms aimed at transparency and accountability of the funds raised. However, the Covid-19 pandemic generated unforeseen contingencies such as accountability for funds from private donations; c) organizational - adherence by top management in maintaining a structure for inspection and control of the institution’s processes and behaviors in the market in which it operates. Based on the analysis of documents there is 76% adequacy of adherence of management practices to the compliance guidelines. It is concluded that organizations that depend on resources and understand that the subsidies they receive, whether government, whether public or private donations, will make the necessary efforts to ensure high levels of compliance, their choices and conduct preserve their image and the achievement of greater credibility and legitimacy.

Most vulnerable individuals are particularly affected by the COVID-19 pandemic. This study takes place in a large city in France. The aim of this study is to describe the mobility of the homeless population at the begin-ning of the health crisis and to analyze its impact in terms of COVID-19 prevalence. From June to August 2020 and September to December 2020, 1272 homeless people were invited to be tested for SARS-CoV-2 antibodies and virus in and completed questionnaires. Our data show that homeless populations are sociologically dif-ferent depending on where they live. We show that people living on the street were most likely to be relocated to emergency shelters than other inhabitants. Some neighborhoods are points of attraction for homeless peo-ple in the city while others emptied during the health crisis, which had consequences for virus circulation. People with a greater number of different dwellings reported became more infected. This first study of the mo-bility and epidemiology of homeless people in time of pandemic provides unique information about mobility mapping, sociological factors of this mobility, mobility at different scales and epidemiological consequences. We suggest that homeless policies need to be radically transformed since actual model exposes people to infection in emergency.