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Abstract Recent advancements in high-resolution imaging have significantly improved our understanding of microstructural changes in the skin and their relationship to the aging process. Line Field Confocal Optical Coherence Tomography (LC-OCT) provides detailed 3D insights into various skin layers, including the papillary dermis and its fibrous network. In this study, a deep learning model utilizing a 3D ResNet-18 network was trained to predict chronological age from LC-OCT images of 100 healthy Caucasian female volunteers, aged 20 to 70 years. The AI-based protocol focused on regions of interest delineated between the segmented dermal-epidermal junction and the superficial dermis, exploiting complex patterns within the collagen network for age prediction. The model achieved a mean absolute error of 4.2 years and exhibited a Pearson correlation coefficient of 0.937 with actual ages. Furthermore, there was a notable correlation (r = 0.87) between quantified clinical scoring, encompassing parameters such as firmness, elasticity, density, and wrinkle appearance, and the ages predicted by deep learning model. This strong correlation underscores how integrating emerging imaging technologies with deep learning can accelerate aging research and deepen our understanding of how alterations in skin microstructure are related to visible signs of aging.

Abstract Background Additional doses of COVID-19 vaccine have been proposed as solutions to waning immunity and decreased effectiveness of primary doses against infection with new SARS-CoV-2 variants. However, the effectiveness of additional vaccine doses relies on widespread population acceptance. We aimed to assess the acceptance of additional COVID-19 vaccine doses (third and annual doses) among Canadian adults and determine associated factors. Methods We conducted a national, cross-sectional online survey among Canadian adults from October 14 to November 12, 2021. Weighted multinomial logistic regression analyses were used to identify sociodemographic and health-related factors associated with third and annual dose acceptance and indecision, compared to refusal. We also assessed influences on vaccine decision-making, and preferences for future vaccine delivery. Results Of 6010 respondents, 70% reported they would accept a third dose, while 15.2% were undecided. For annual doses, 64% reported acceptance, while 17.5% were undecided. Factors associated with third dose acceptance and indecision were similar to those associated with annual dose acceptance and indecision. Previous COVID-19 vaccine receipt, no history of COVID-19 disease, intention to receive an influenza vaccine, and increasing age were strongly associated with both acceptance and indecision. Chronic illness was associated with higher odds of acceptance, while self-reported disability was associated with higher odds of being undecided. Higher education attainment and higher income were associated with higher odds of accepting additional doses. Minority first language was associated with being undecided about additional doses, while visible minority identity was associated with being undecided about a third dose and refusing an annual dose. All respondents reported government recommendations were an important influence on their decision-making and identified pharmacy-based delivery and drop-in appointments as desirable. Co-administration of COVID-19 and influenza vaccines was viewed positively by 75.5% of the dose 3 acceptance group, 12.3% of the undecided group, and 8.4% of the refusal group. Conclusions To increase acceptance, targeted interventions among visible minority and minority language populations, and those with a disability, are required. Offering vaccination at pharmacies and through drop-in appointments are important to facilitate uptake, while offering COVID-19/influenza vaccine co-administration may have little benefit among those undecided about additional doses.

BackgroundVaccine coverage for 18-month-old children in Canada is often below the recommended level, which may be partially because of parental forgetfulness. SMS text message reminders have been shown to potentially improve childhood immunization uptake but have not been widely used in Alberta, Canada. In addition, it has been noted that language barriers may impede immunization service delivery but continue to remain unaddressed in many existing reminder and recall systems. ObjectiveThis study aimed to assess the effectiveness and acceptability of using SMS text messages containing a link to web-based immunization information in different languages to remind parents of their child’s 18-month immunization appointment. MethodsThe Childhood Immunization Reminder Project was a pilot intervention at 2 public health centers, one each in Lethbridge and Edmonton, Alberta, Canada. Two SMS text message reminders were sent to parents: a booking reminder 3 months before their child turned 18 months old and an appointment reminder 3 days before their scheduled appointment. Booking reminders included a link to the study website hosting immunization information in 9 languages. To evaluate intervention effectiveness, we compared the absolute attendance no-show rates before the intervention and after the intervention. The acceptability of the intervention was evaluated through web-based surveys completed by parents and public health center staff. Google Analytics was used to determine how often web-based immunization information was accessed, from where, and in which languages. ResultsFollowing the intervention, the health center in Edmonton had a reduction of 6.4% (95% CI 3%-9.8%) in appointment no-shows, with no change at the Lethbridge Health Center (0.8%, 95% CI −1.4% to 3%). The acceptability surveys were completed by 222 parents (response rate: 23.9%) and 22 staff members. Almost all (>95%) respondents indicated that the reminders were helpful and provided useful suggestions for improvement. All surveyed parents (222/222, 100%) found it helpful to read web-based immunization information in their language of choice. Google Analytics data showed that immunization information was most often read in English (118/207, 57%), Punjabi (52/207, 25.1%), Arabic (13/207, 6.3%), Spanish (12/207, 5.8%), Italian (4/207, 1.9%), Chinese (4/207, 1.9%), French (2/207, 0.9%), Tagalog (1/207, 0.5%), and Vietnamese (1/207, 0.5%). ConclusionsThe study’s findings support the use of SMS text message reminders as a convenient and acceptable method to minimize parental forgetfulness and potentially reduce appointment no-shows. The diverse languages accessed in web-based immunization information suggest the need to provide appropriate translated immunization information. Further research is needed to evaluate the impact of SMS text message reminders on childhood immunization coverage in different settings.

Background: Public health departments in Canada are currently facing the challenging task of planning and implementing coronavirus disease 2019 (COVID-19) vaccination programs. Objective: To collect and synthesize information regarding COVID-19 vaccination program planning in each province and territory of Canada, including logistic considerations, priority groups, and vaccine safety and effectiveness monitoring. Methods: Provincial/territorial public health leaders were interviewed via teleconference during the early planning stage of COVID-19 vaccination programs (August–October 2020) to collect information on the following topics: unique factors for COVID-19 vaccination, intention to adopt National Advisory Committee on Immunization (NACI) recommendations, priority groups for early vaccination, and vaccine safety and effectiveness monitoring. Data were grouped according to common responses and descriptive analysis was performed. Results: Eighteen interviews occurred with 25 participants from 11 of 13 provinces/territories (P/Ts). Factors unique to COVID-19 vaccination included prioritizing groups for early vaccination (n=7), public perception of vaccines (n=6), and differing eligibility criteria (n=5). Almost all P/Ts (n=10) reported reliance on NACI recommendations. Long-term care residents (n=10) and healthcare workers (n=10) were most frequently prioritized for early vaccination, followed by people with chronic medical conditions (n=9) and seniors (n=8). Most P/Ts (n=9) are planning routine adverse event monitoring to assess vaccine safety. Evaluation of effectiveness was anticipated to occur within public health departments (n=3), by researchers (n=3), or based on national guidance (n=4). Conclusion: Plans for COVID-19 vaccination programs in the P/Ts exhibit some similarities and are largely consistent with NACI guidelines, with some discrepancies. Further research is needed to evaluate COVID-19 vaccination programs once implemented.

Contexte : Les services de santé publique du Canada sont actuellement confrontés à la tâche difficile de planifier et de mettre en œuvre des programmes de vaccination contre la maladie à coronavirus 2019 (COVID-19). Objectif : Recueillir et synthétiser les informations concernant la planification du programme de vaccination contre la COVID-19 dans chaque province et territoire du Canada, y compris les considérations logistiques, les groupes prioritaires et la surveillance de l’innocuité et de l’efficacité du vaccin. Méthodes : Les responsables provinciaux et territoriaux de la santé publique ont été interrogés par téléconférence au cours de la phase initiale de planification des programmes de vaccination contre la COVID-19 (août à octobre 2020) afin de recueillir des informations sur les sujets suivants : facteurs uniques pour la vaccination contre la COVID-19, intention d’adopter les recommandations du Comité consultatif national de l’immunisation (CCNI), groupes prioritaires pour les premières phases de la vaccination et surveillance de l’innocuité et de l’efficacité du vaccin. Les données ont été regroupées en fonction des réponses communes et une analyse descriptive a été réalisée. Résultats : Dix-huit entretiens ont eu lieu avec 25 participants de 11 des 13 provinces et territoires. Les facteurs uniques de la vaccination contre la COVID-19 comprenaient la hiérarchisation des groupes pour les premières phases de la vaccination (n = 7), la perception des vaccins par le public (n = 6) et des critères d’éligibilité divergents (n = 5). Presque toutes les provinces et territoires (n = 10) ont déclaré s’appuyer sur les recommandations du CCNI. Les résidents des établissements de soins de longue durée (n = 10) et les travailleurs de la santé (n = 10) ont été le plus souvent prioritaires pour les premières phases de la vaccination, suivis des personnes souffrant de maladies chroniques (n = 9) et des personnes âgées (n = 8). La plupart des provinces et territoires (n = 9) prévoient une surveillance systématique des effets indésirables pour évaluer l’innocuité des vaccins. L’évaluation de l’efficacité devait se faire au sein des services de santé publique (n = 3), par des chercheurs (n = 3) ou sur la base de directives nationales (n = 4). Conclusion : La planification des programmes de vaccination contre la COVID-19 dans les provinces et territoires présente certaines similitudes et est largement conforme aux directives du CCNI, avec quelques divergences. Des recherches supplémentaires sont nécessaires pour évaluer les programmes de vaccination contre la COVID-19 une fois qu’ils auront été mis en œuvre.

Solar irradiance is one of the most important parameters that need to be estimated and modeled before engaging in any solar energy project. This article describes a non-linear regression model based on genetic programming technique for estimating solar irradiance in a specific region in the United Arab Emirates. The genetic programming is an evolutionary computing technique that enables automatic search for complex solutions. The best nonlinear modeling function that can estimate the global solar radiation on horizontal will be developed taking into account measured meteorological data. A reference approach to model the solar radiation is first presented. An enhanced approach is then presented which consists of multi nonlinear functions of regression in a parallel structure where each function is designed to estimate the global solar irradiance in a specific seasonal period of the year. Statistical analysis measures have been used to evaluate the performance of the proposed approaches. The obtained results are comparable with the outcomes of models developed by other researchers in the field.

Increasingly, public health research standards call for engaging communities who live with health issues under investigation to help ensure that results translate into effective public health measures. Here, we share guiding principles for community-driven epidemiologic research developed over a decade conducting research sought and controlled by participating communities. These principles provide a roadmap for epidemiologic research that effectively addresses community priorities while meeting academic standards: research questions are developed collaboratively in community-university partnerships; knowledge takes shape from information donated by participants through methods that turn information into scientifically useful data and analysis that reveals data patterns that address research questions; thus, knowledge is generated collaboratively by academic researchers and community partners; academic researchers are bound by ethical, professional, scientific, contractual, and other legal standards to be responsible stewards of information donated by participants; community review protocols ensure that interpretation and presentation of research results reflect the voices of all partners; meaningful community review creates the trust needed for open access to research results as required of academic researchers; all partners share credit for achievements. Lacking models for operationalizing these principles, we developed specific guidelines for research project initiation, data use, authorship, acknowledgment, and data dissemination. Conventions in academia present formidable challenges to effective community engagement and are often at odds with calls from community organizations and funding agencies to conduct research driven by community priorities and values. We hope others can benefit from time and effort we have spent crafting solutions that bridge this divide.

Background: An outbreak of an unknown respiratory illness caused by a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan in Hubei Province, China, in December 2019 and was referred to as coronavirus disease-2019 (COVID-19). Soon after, it was declared as a global pandemic by the World Health Organization (WHO) in March 2020. SARS-CoV-2 mainly infects the respiratory tract with different outcomes ranging from asymptomatic infection to severe critical illness leading to death. Different SARS-CoV-2 variants are emerging of which three have raised concerns worldwide due to their high transmissibility among populations. Objective: To study the prevalence of COVID-19 in the region of Nabatieh-South Lebanon during the past year and assess the presence of SARS-CoV-2 variants and their effect on the spread of infection during times of lockdown. Methods: In our study, 37,474 nasopharyngeal swab samples were collected and analyzed for the detection of SARS-CoV-2 virus in suspected patients attending a tertiary health care center in South Lebanon during the period between 16 March 2020 and 21 February 2021. Results: The results demonstrated a variation in the prevalence rates ranging from less than 1% during full lockdown of the country to 8.4% upon easing lockdown restrictions and reaching 27.5% after the holidays and 2021 New Year celebrations. Interestingly, a new variant(s) appeared starting January 2021 with a significant positive association between the prevalence of positive tests and the percentage of the variant(s). Conclusions: Our results indicate that the lockdown implemented by the Lebanese officials was an effective intervention to contain COVID-19 spread. Our study also showed that lifting lockdown measures during the holidays, which allowed indoor crowded gatherings to occur, caused a surge in COVID-19 cases and rise in the mortality rates nationwide. More importantly, we confirmed the presence of a highly transmissible SARS-CoV-2 variant(s) circulating in the Lebanese community from at least January 2021 onwards.

This work discusses a waste heat recovery system (WHRS) applied to chimneys for heating water in residential buildings. A prototype illustrating the suggested system is implemented and tested. Different waste heat scenarios by varying the quantity of burned firewood (heat input) are experimented. The temperature at different parts of the WHRS and the gas flow rates of the exhaust pipes are measured. Measurements showed that the temperature of 95 L tank of water can be increased by 68 °C within one hour. Obtained results show that the convection and radiation exchanges at the bottom surface of the tank have a considerable impact on the total heat transfer rate of the water (as high as 70%).

This article presents an intelligent fuzzy logic controller (FLC) for controlling single-body heaving wave energy converter (WEC) or what is widely known as “Point Absorber”. The controller aims at maximizing the energy captured from the sea waves. The power take-off (PTO) limitations are addressed implicitly in the fuzzy inference system (FIS) framework. In order to enhance the WEC power capturing bandwidth and make it less susceptible to wave environment irregularities and the system parametric uncertainties, the controller is built to have a self-configurable capability. This also eliminates the need to repeatedly run in-situ tuning procedure of the fuzzy controller or switch between several controllers based on the operating conditions. The fuzzy membership functions (MFs) are optimally tuned using particle swarm optimization (PSO) algorithm. To alleviate the computational burden associated with performing on-line optimization, the fuzzy controller is tuned at a rate significantly lower than the system sampling time. The suggested PSO-FLC has shown promising results compared with the fixed structure fuzzy logic controller (FS-FLC) and other passive control strategies. Several computer simulations were carried out to evaluate the controller effectiveness by applying different sea-states and analyzing the resultant WEC dynamics.

This paper proposes a model that predicts the complexity of Boolean functions with only XOR/XNOR min-terms using back propagation neural networks (BPNNs) applied to Binary Decision Diagrams (BDDs). The BPNN model (BPNNM) is developed through the training process of experimental data already obtained for XOR/XNOR-based Boolean functions. The outcome of this model is a unique matrix for the complexity estimation over a set of BDDs derived from Boolean expressions with a given number of variables and XOR/XNOR min-terms. The comparison results of the experimental and BPNNM underline the efficiency of this approach, which is capable of providing some useful clues about the complexity of the circuit to be implemented. It also proves the computational capabilities of NNs in providing reliable classification of the complexity of Boolean functions.

This paper thermo-physically characterizes salt hydrate, paraffin wax and milk fat as phase change materials (PCMs). The three PCMs are compared in terms of improving heat sink (HS) performance for cooling electronic packaging. An experimental study is carried out on commercially available finned HS with and without PCM under natural ventilation (NV) and forced ventilation (FV) at different heat loads (4 W to 10 W). The results indicate that integration of all of the PCMs into the HS improves its cooling performance; however, milk fat lags behind the other two PCMs in terms of cooling produced. A three-dimensional pressure-based conjugate heat transfer model has been developed and validated with experimental results. The model predicts the parametric influence of PCM melting range, thermal conductivity and density on HS thermal management performance. The HS cooling performance improves with increased density and conductivity while it deteriorates with the wider melting range of the PCMs.

Background: Quantitative biomarkers of facial skin aging were investigated in 109 healthy Asian female volunteers, aged 20 to 70 years. Materials and Methods: In vivo 3D Line‐field Confocal Optical Coherence Tomography (LC‐OCT) imaging, enhanced by Artificial Intelligence (AI)‐based quantification algorithms, was utilized to compute various metrics, including stratum corneum thickness (SC), viable epidermal (VE) thickness, and Dermal‐Epidermal Junction (DEJ) undulation along with cellular metrics for the temple, cheekbone, and mandible. Results: Comparison with data from a cohort of healthy Caucasian volunteers revealed similarities in the variations of stratum corneum and viable epidermis layers, as well as cellular shape and size with age in both ethnic groups. However, specific findings emerged, such as larger, more heterogeneous nuclei in both layers, demonstrated by an increase in nuclei volume and their standard deviation, and increased network atypia, all showing significant age‐related variations. Caucasian females exhibited a flatter and more homogeneous epidermis, evidenced by a decreased standard deviation of the number of layers, and a less dense cellular network with fewer cells per layer, indicated by a decrease in cell surface density. Conclusion: Ethnicity‐wise comparisons highlighted distinct biological features specific to each population. Asian individuals showed significantly higher DEJ undulation, higher compactness, and lower cell network atypia compared to their Caucasian counterparts across age groups. Differences in stratum corneum and viable epidermal thickness on the cheekbone were also significant. LC‐OCT 3D imaging provides valuable insights into the aging process in different populations and underscores inherent biological differences between Caucasian and Asian female volunteers. [ABSTRACT FROM AUTHOR]