ALBERT

Description: Stunting is highly prevalent in Indonesian children. The objective of this study was to identify the associations of stunting with morbidity, parental education and socioeconomic status (SES) in Indonesian children. The study population was part of the South East Asian Nutrition Surveys (SEANUTS). A total of 2236 Indonesian children aged 0.5 to 12 years, who had participated in the SEANUTS, were included in this study. Stunting was defined as height for age Z-score (HAZ) ≤ −2 using WHO criteria and severe stunting as HAZ ≤ −3. Information on morbidity, parental education and family SES were collected by structured questionnaires. ANOVA was used for evaluating differences across groups, with or without correction for confounders. The results showed that the overall prevalence of stunting was 31.4%. HAZ in stunted children was associated with disease incidence, including frequency, parental education and family income. There were no significant differences in HAZ values in stunted children with one or more bouts of infectious, digestive tract or respiratory tract illnesses compared to stunted children with no reported illness. The prevalence of stunting in Indonesian children was high and was strongly associated with child morbidity, parental education and SES.

Description: Background: In Spain, colorectal cancer screening using the fecal occult blood test, targeted towards the 50–69 age bracket, was implemented on different dates. We aim to assess the temporal trend of colorectal cancer (CRC) screening uptake according to the year of screening implementation in each region and to identify predictors for the uptake of CRC screening. Methods: A cross-sectional study with 12,657 participants from the Spanish National Health Surveys 2011 and 2017 was used. Uptake rates were analyzed according to the date that the screening program was implemented. Results: For regions with programs implemented before 2011, the uptake rate increased 3.34-fold from 2011 to 2017 (9.8% vs. 32.7%; p 〈 0.001). For regions that implemented screening within the 2011–2016 period, the uptake rose from 4.3% to 13.2% (3.07-fold; p 〈 0.001), and for regions that implemented screening after 2016, the uptake increased from 3.4% to 8.8% (2.59-fold; p 〈 0.001). For the entire Spanish population, the uptake increased 3.21-fold (6.8% vs. 21.8%; p 〈 0.001). Positive predictors for uptake were older age, Spanish nationality, middle-to-high educational level, suffering chronic diseases, non-smoking and living in regions where screening programs were implemented earlier. Conclusions: The different periods for the implementation of CRC screening as well as sociodemographic and health inequalities may have limited the improvement in the screening uptake from 2011 to 2017 in Spain.

Description: While food insecurity (FI) has been extensively studied in many countries, there have been few empirical contributions in Poland to date. The main objective of our research was to identify the socio-demographic factors affecting the risk of FI in Poland within 2014–2019. Moreover, we aimed to examine the effects of the family-oriented social program “Family 500+” by comparing the situation in various types of households with children a few years before and after the program was launched. The analysis was based on the set of eight-item FI indicators adopted by the Food and Agriculture Organization using the Gallup World Poll nationally representative survey data. Based on our results the most vulnerable groups in the context of FI were identified. We confirmed the importance of education, gender, age, marital status, household composition, status of employment and income in preventing FI. The effectiveness of the support program in reducing FI was demonstrated as households with at least three children experienced significant improvement in the FI status during the studied years. These findings should be especially important in the context of the impact of the COVID-19 pandemic on FI. As FI can affect the quality and quantity of food choices it is associated with a poorer health status, which increases the risk of infection, including COVID-19, and worsens recovery prognosis. Planning an efficient response to the pandemic requires a comprehension of the increased risk of exposure experienced by people, especially those who are food insecure.

Description: The lack of a universal simulation method for triboelectric nanogenerator (TENG) makes the device design and optimization difficult before experiment, which protracts the research and development process and hinders the landing of practical TENG applications. The existing electrostatic induction models for TENGs have limitations in simulating TENGs with complex geometries and their dynamic behaviors under practical movements due to the topology change issues. Here, a dynamic finite element method (FEM) model is proposed. The introduction of air buffer layers and the moving mesh method eliminates the topology change issues during practical movement and allows simulation of dynamic and time-varying behaviors of TENGs with complex 2D/3D geometries. Systematic investigations are carried out to optimize the air buffer thickness and mesh densities, and the optimized results show excellent consistency with the experimental data and results based on other existing methods. It also shows that a 3D disk-type rotating TENG can be simulated using the model, clearly demonstrating the capability and superiority of the dynamic FEM model. Moreover, the dynamic FEM model is used to optimize the shape of the tribo-material, which is used as a preliminary example to demonstrate the possibility of designing a TENG-based sensor.

Description: In 2017, the Government of Mozambique declared localized acute malnutrition crises in a range of districts across Mozambique including Cabo Delgado. This is in spite of intensive efforts by different non-governmental organizations (NGO) and the Government of Mozambique to expand access to information on good nutritional practices as well as promote nutrition-specific interventions, such as cooking demonstrations, home gardens and the distribution of micronutrient powder to children. This paper examines and discusses key nutritional influences on the health of pregnant and breastfeeding mothers in Cabo Delgado province, Mozambique. We conducted 21 key informant interviews (KIIs) with a wide range of stakeholders and 16 in-depth interviews (IDIs) with women. In addition, we conducted four focus group discussions with each of the following groups: (1) pregnant adolescent girls, (2) pregnant women 〉20 yrs, (3) women 〉20 yrs with babies 20 yrs of children

Description: Environmental protection and sustainable development have become an inevitable trend in many areas, including the energy industry. The development of energy supply networks is strongly correlated with the economics of energy sources as well as ecological and socio-political issues. However, the energy supply network is often distant from the social perspective. This paper therefore combines examination of perceptions and awareness of general public (web-based questionnaire) and top energy experts (a Delphi survey) on the energy supply network and identifies their potential integration in energy supply decision making processes. The results showed that public should be better informed as well as integrated into designing energy supply network as the prosumers gain power and the energy suppliers will no longer dominate the market. Public actors are ready to shape sustainable energy supply and also willing to pay 5.8% more for a sustainable energy supply. The majority are prepared to invest in renewable energy supply network close to their place of residence. Another result is that the public is calling for a shift in priority towards more sustainable and socially friendlier energy supply rather than focusing mainly on the economic and technical perspectives.

Description: Knowledge gaps remain regarding the cardiorespiratory impacts of ambient volatile organic compounds (VOCs) for the general population. This study identified contributing sources to ambient VOCs and estimated the short-term effects of VOC apportioned sources on daily emergency hospital admissions for cardiorespiratory diseases in Hong Kong from 2011 to 2014. We estimated VOC source contributions using fourteen organic chemicals by positive matrix factorization. Then, we examined the associations between the short-term exposure to VOC apportioned sources and emergency hospital admissions for cause-specific cardiorespiratory diseases using generalized additive models with polynomial distributed lag models while controlling for meteorological and co-pollutant confounders. We identified six VOC sources: gasoline emissions, liquefied petroleum gas (LPG) usage, aged VOCs, architectural paints, household products, and biogenic emissions. We found that increased emergency hospital admissions for chronic obstructive pulmonary disease were positively linked to ambient VOCs from gasoline emissions (excess risk (ER%): 2.1%; 95% CI: 0.9% to 3.4%), architectural paints (ER%: 1.5%; 95% CI: 0.2% to 2.9%), and household products (ER%: 1.5%; 95% CI: 0.2% to 2.8%), but negatively associated with biogenic VOCs (ER%: −6.6%; 95% CI: −10.4% to −2.5%). Increased congestive heart failure admissions were positively related to VOCs from architectural paints and household products in cold seasons. This study suggested that source-specific VOCs might trigger the exacerbation of cardiorespiratory diseases.

Description: Although fatigue usually goes unnoticed, it is a symptom that poses great challenges to patients with fibromyalgia and is a strong limitation. The aim of this study is to identify and describe the variables involved in fatigue in nine different situations of the Goal Pursuit Questionnaire (GPQ) that may occur in the daily lives of women with fibromyalgia, according to an ABC (Antecedents–Behaviors–Consequences) model. This study followed a qualitative descriptive research method and a deductive–inductive hybrid approach based on a phenomenological paradigm. Twenty-six women with fibromyalgia participated in focus group discussions between February and March of 2018. Thematic content analysis was carried out from transcribed verbatim interviews. We identified nine major themes that emerged from the participants’ conversations: self-imposed duties, muscle fatigue, overwhelming feeling of tiredness, difficulty thinking, difficulty concentrating, negative emotions, lifestyle changes, affected everyday activities, and lack of motivation for daily activities and social interactions. We conclude that the ABC model allowed certain elements to emerge regarding the fatigue experience, highlighting its importance as a symptom in fibromyalgia. This additional analysis of the ABC model showed that fatigue can be described through the 4 U’s Rule, which is integrated by these four adjectives: (1) Unpredictable, (2) Uncontrollable, (3) Unseen, and (4) Unintelligible. Identifying these characteristics can contribute to a better understanding of fibromyalgia in addition to better treatment for these patients.

Description: Traumatic brain injury (TBI), a global public health concern, may lead to death and major disability. While various short-term, small-sample, and cross-sectional studies on TBI have been conducted in South Korea, there is a lack of clarity on the nationwide longitudinal TBI trends in the country. This retrospective study investigated the epidemiological TBI trends in South Korea, using a population-based dataset of the National Health Insurance (2008–2017). The crude and age adjusted TBI incidence and mortality values were calculated and stratified by age, sex, and TBI diagnosis. The age-adjusted incidence per 100,000 people increased until 2010 and showed a decreasing trend (475.8 cases in 2017) thereafter; however, a continuously decreasing age-adjusted mortality trend was observed (42.9 cases in 2008, 11.3 in 2017). The crude incidence rate increased continually in those aged 〉70 years across all the TBI diagnostic categories. The mortality per 100,000 people was significantly higher among participants aged ≥70 years than in the other age groups. We observed changing trends in the TBI incidence, with a continuously decreasing overall incidence and a rapidly increasing incidence and high mortality values in older adults. Our findings highlight the importance of active TBI prevention in elderly people.

Description: Little is known regarding the neuroanatomical correlates of patients with deficit schizophrenia or persistent negative symptoms. In this meta-analysis, we aimed to determine whether patients with deficit schizophrenia have characteristic brain abnormalities. We searched PubMed, CINAHL and Ovid to identify studies that examined the various regions of interest amongst patients with deficit schizophrenia, patients with non-deficit schizophrenia and healthy controls. A total of 24 studies met our inclusion criteria. A random-effects model was used to calculate a combination of outcome measures, and heterogeneity was assessed by the I2 statistic and Cochran’s Q statistic. Our findings suggested that there was statistically significant reduction in grey matter volume (−0.433, 95% confidence interval (CI): −0.853 to −0.014, p = 0.043) and white matter volume (−0.319, 95% CI: −0.619 to −0.018, p = 0.038) in patients with deficit schizophrenia compared to healthy controls. There is also statistically significant reduction in total brain volume (−0.212, 95% CI: −0.384 to −0.041, p = 0.015) and white matter volume (−0.283, 95% CI: −0.546 to −0.021, p = 0.034) in patients with non-deficit schizophrenia compared to healthy controls. Between patients with deficit and non-deficit schizophrenia, there were no statistically significant differences in volumetric findings across the various regions of interest.

Description: In this paper, 3D-printed electromagnetic (or microwave) encoders with synchronous reading based on permittivity contrast, and devoted to the measurement of displacements and velocities, are reported for the first time. The considered encoders are based on two chains of linearly shaped apertures made on a 3D-printed high-permittivity dielectric material. One such aperture chain contains the identification (ID) code, whereas the other chain provides the clock signal. Synchronous reading is necessary in order to determine the absolute position if the velocity between the encoder and the sensitive part of the reader is not constant. Such absolute position can be determined as long as the whole encoder is encoded with the so-called de Bruijn sequence. For encoder reading, a splitter/combiner structure with each branch loaded with a series gap and a slot resonator (each one tuned to a different frequency) is considered. Such a structure is able to detect the presence of the apertures when the encoder is displaced, at short distance, over the slots. Thus, by injecting two harmonic signals, conveniently tuned, at the input port of the splitter/combiner structure, two amplitude modulated (AM) signals are generated by tag motion at the output port of the sensitive part of the reader. One of the AM envelope functions provides the absolute position, whereas the other one provides the clock signal and the velocity of the encoder. These synchronous 3D-printed all-dielectric encoders based on permittivity contrast are a good alternative to microwave encoders based on metallic inclusions in those applications where low cost as well as major robustness against mechanical wearing and aging effects are the main concerns.

Description: This paper presents a vulnerable road user (VRU) tracking algorithm capable of handling noisy and missing detections from heterogeneous sensors. We propose a cooperative fusion algorithm for matching and reinforcing of radar and camera detections using their proximity and positional uncertainty. The belief in the existence and position of objects is then maximized by temporal integration of fused detections by a multi-object tracker. By switching between observation models, the tracker adapts to the detection noise characteristics making it robust to individual sensor failures. The main novelty of this paper is an improved imputation sampling function for updating the state when detections are missing. The proposed function uses a likelihood without association that is conditioned on the sensor information instead of the sensor model. The benefits of the proposed solution are two-fold: firstly, particle updates become computationally tractable and secondly, the problem of imputing samples from a state which is predicted without an associated detection is bypassed. Experimental evaluation shows a significant improvement in both detection and tracking performance over multiple control algorithms. In low light situations, the cooperative fusion outperforms intermediate fusion by as much as 30%, while increases in tracking performance are most significant in complex traffic scenes.

Description: The purpose of the current study is to analyze the relationships between physical fitness, selective attention, and academic performance in pre-teens. The sample here consists of 135 participants between the ages of 10 and 12 (M = 11.05; SD = 0.61), with 39.26% female (n = 53) and 60.74% male (n = 82) participants. Horizontal and vertical jump distances, speed, and cardio-respiratory fitness were evaluated to assess physical fitness. The d2 Test of Attention was used to evaluate selective attention. In addition, data were obtained regarding participant academic performance by analyzing the academic performance. The results show significant relationships between the measures analyzed, highlighting positive associations between physical fitness, cognitive functioning, and academic performance. Thus, participants who were fitter scored better on tests of attention (Z133 = −4.07; p 〈 0.00007, Cohen’s d = 0.75, 95% CI (0.39, 1.11)) and concentration (t133 = −3.84; p 〈 0.0007, Cohen’s d = 0.69, 95% CI (0.33, 1.05)), as well as having higher academic performance (Z133 = −2.84; p 〈 0.0035, Cohen’s d = 0.39, 95% CI (0.04, 0.75)). Cardiorespiratory fitness was the measure of physical fitness that best explained these relationships. The results suggest that maintaining and improving the physical fitness of children and adolescents may help their brain function develop better.

Description: Flat surfaces captured by 3D point clouds are often used for localization, mapping, and modeling. Dense point cloud processing has high computation and memory costs making low-dimensional representations of flat surfaces such as polygons desirable. We present Polylidar3D, a non-convex polygon extraction algorithm which takes as input unorganized 3D point clouds (e.g., LiDAR data), organized point clouds (e.g., range images), or user-provided meshes. Non-convex polygons represent flat surfaces in an environment with interior cutouts representing obstacles or holes. The Polylidar3D front-end transforms input data into a half-edge triangular mesh. This representation provides a common level of abstraction for subsequent back-end processing. The Polylidar3D back-end is composed of four core algorithms: mesh smoothing, dominant plane normal estimation, planar segment extraction, and finally polygon extraction. Polylidar3D is shown to be quite fast, making use of CPU multi-threading and GPU acceleration when available. We demonstrate Polylidar3D’s versatility and speed with real-world datasets including aerial LiDAR point clouds for rooftop mapping, autonomous driving LiDAR point clouds for road surface detection, and RGBD cameras for indoor floor/wall detection. We also evaluate Polylidar3D on a challenging planar segmentation benchmark dataset. Results consistently show excellent speed and accuracy.

Description: In this study, we proposed a semi-automated and interactive scheme for organ contouring in radiotherapy planning for patients with non-small cell lung cancers. Several organs were contoured, including the lungs, airway, heart, spinal cord, body, and gross tumor volume (GTV). We proposed some schemes to automatically generate and vanish the seeds of the random walks (RW) algorithm. We considered 25 lung cancer patients, whose computed tomography (CT) images were obtained from the China Medical University Hospital (CMUH) in Taichung, Taiwan. The manual contours made by clinical oncologists were taken as the gold standard for comparison to evaluate the performance of our proposed method. The Dice coefficient between two contours of the same organ was computed to evaluate the similarity. The average Dice coefficients for the lungs, airway, heart, spinal cord, and body and GTV segmentation were 0.92, 0.84, 0.83, 0.73, 0.85 and 0.66, respectively. The computation time was between 2 to 4 min for a whole CT sequence segmentation. The results showed that our method has the potential to assist oncologists in the process of radiotherapy treatment in the CMUH, and hopefully in other hospitals as well, by saving a tremendous amount of time in contouring.

Description: An essential aspect in the interaction between people and computers is the recognition of facial expressions. A key issue in this process is to select relevant features to classify facial expressions accurately. This study examines the selection of optimal geometric features to classify six basic facial expressions: happiness, sadness, surprise, fear, anger, and disgust. Inspired by the Facial Action Coding System (FACS) and the Moving Picture Experts Group 4th standard (MPEG-4), an initial set of 89 features was proposed. These features are normalized distances and angles in 2D and 3D computed from 22 facial landmarks. To select a minimum set of features with the maximum classification accuracy, two selection methods and four classifiers were tested. The first selection method, principal component analysis (PCA), obtained 39 features. The second selection method, a genetic algorithm (GA), obtained 47 features. The experiments ran on the Bosphorus and UIVBFED data sets with 86.62% and 93.92% median accuracy, respectively. Our main finding is that the reduced feature set obtained by the GA is the smallest in comparison with other methods of comparable accuracy. This has implications in reducing the time of recognition.

Description: Automated tracking of physical fitness has sparked a health revolution by allowing individuals to track their own physical activity and health in real time. This concept is beginning to be applied to tracking of cognitive load. It is well known that activity in the brain can be measured through changes in the body’s physiology, but current real-time measures tend to be unimodal and invasive. We therefore propose the concept of a wearable educational fitness (EduFit) tracker. We use machine learning with physiological data to understand how to develop a wearable device that tracks cognitive load accurately in real time. In an initial study, we found that body temperature, skin conductance, and heart rate were able to distinguish between (i) a problem solving activity (high cognitive load), (ii) a leisure activity (moderate cognitive load), and (iii) daydreaming (low cognitive load) with high accuracy in the test dataset. In a second study, we found that these physiological features can be used to predict accurately user-reported mental focus in the test dataset, even when relatively small numbers of training data were used. We explain how these findings inform the development and implementation of a wearable device for temporal tracking and logging a user’s learning activities and cognitive load.

Description: : The main purpose of this work is to study the effectiveness of using FeCeOx nanocomposites doped with Nb2O5 for the purification of aqueous solutions from manganese. X-ray diffraction, energy–dispersive analysis, scanning electron microscopy, vibrational magnetic spectroscopy, and mössbauer spectroscopy were used as research methods. It is shown that an increase in the dopant concentration leads to the transformation of the shape of nanoparticles from spherical to cubic and rhombic, followed by an increase in the size of the nanoparticles. The spherical shape of the nanoparticles is characteristic of a structure consisting of a mixture of two phases of hematite (Fe2O3) and cerium oxide CeO2. The cubic shape of nanoparticles is typical for spinel-type FeNbO4 structures, the phase contribution of which increases with increasing dopant concentration. It is shown that doping leads not only to a decrease in the concentration of manganese in model solutions, but also to an increase in the efficiency of adsorption from 11% to 75%.

Description: A common design concept of the piezoelectric force sensor, which is to assemble a bump structure from a flat or fine columnar piezoelectric structure or to use a specific type of electrode, is quite limited. In this paper, we propose a new design of cylindrical piezoelectric sensors that can detect multidirectional forces. The proposed sensor consists of four row and four column sensors. The design of the sensor was investigated by the finite element method. The response of the sensor to various force directions was observed, and it was demonstrated that the direction of the force applied to the sensor could be derived from the signals of one row sensor and three column sensors. As a result, this sensor proved to be able to detect forces in the area of 225° about the central axis of the sensor. In addition, a cylindrical sensor was fabricated to verify the proposed sensor and a series of experiments were performed. The simulation and experimental results were compared, and the actual sensor response tended to be similar to the simulation.

Description: Background: Cervical cancer is one of the most common cancers in women and about 90% of cervical cancer can be reduced by regular screening. The Pap smear has been well in place as a primary cervical screening method since 1950s; however, coverage is still not optimal. This study explored the feasibility of HPV self-sampling in two under-screened population groups in Hong Kong (HK): never screened and not regularly screened females, to estimate the uptake rate and preference rate in the future. Materials and Methods: This was a cross-sectional study to explore the acceptability and feasibility of HPV self-sampling in two age groups: aged 25–35 and aged ≥45, which were reported as the highest proportion of the under-screened population in HK between 2017 and 2018. The study invited eligible women from an HPV study cohort to perform HPV self-sampling at home by themselves. The number of specimens returned from participants was recorded and used to determine the feasibility of HPV self-sampling in the community. The participants were asked to fill in the questionnaires before and after HPV self-sampling to indicate their attitudes, acceptability, and future preference for HPV self-sampling as an acceptable alternative primary cervical cancer screening method. Results: A total of 177 subjects participated in the present study and have achieved a good overall uptake rate of 73% (129/177) who returned the self-collected cervicovaginal sample for HPV testing. Among the under-screened population, there was a higher response rate in aged ≥45 than those aged 25–35. The findings also revealed that women who were under-screened, including those who have never been screened, were more likely to prefer HPV self-sampling than those who had regular screening. This study found that the acceptability of HPV self-sampling was fairly positive among the respondents. The findings also indicated that HPV self-sampling was not only beneficial to enhance their health awareness but also to promote the cervical cancer screening uptake rate, especially among the under-screened or never screened populations. Conclusions: HPV self-sampling would be a solution to overcome the perceived barriers in clinician-based screening. The findings also indicated that it could be feasible to use as an alternative primary cervical cancer screening.

Description: Public health recommendations and governmental measures during the new coronavirus disease (COVID-19) pandemic have enforced numerous restrictions on daily living including social distancing, isolation, and home confinement. While these measures are imperative to mitigate spreading of COVID-19, the impact of these restrictions on psychosocial health is undefined. Therefore, an international online survey was launched in April 2020 to elucidate the behavioral and lifestyle consequences of COVID-19 restrictions. This report presents the preliminary results from more than one thousand responders on social participation and life satisfaction. Methods: Thirty-five research organizations from Europe, North-Africa, Western Asia, and the Americas promoted the survey through their networks to the general society, in 7 languages (English, German, French, Arabic, Spanish, Portuguese, and Slovenian). Questions were presented in a differential format with questions related to responses “before” and “during” confinement conditions. Results: 1047 participations (54% women) from Asia (36%), Africa (40%), Europe (21%), and others (3%) were included in the analysis. Findings revealed psychosocial strain during the enforced COVID-19 home confinement. Large decreases (p 〈 0.001) in the amount of social activity through family (−58%), friends/neighbors (−44.9%), or entertainment (−46.7%) were triggered by the enforced confinement. These negative effects on social participation were also associated with lower life satisfaction (−30.5%) during the confinement period. Conversely, the social contact score through digital technologies significantly increased (p 〈 0.001) during the confinement period with more individuals (+24.8%) being socially connected through digital technology. Conclusion: These preliminary findings elucidate the risk of psychosocial strain during the early COVID-19 home confinement period in 2020. Therefore, in order to mitigate the negative psychosocial effects of home confinement, implementation of national strategies focused on promoting social inclusion through a technology-based solution is strongly suggested.

Description: The study portrays the social and health care master’s students’ (N = 19) perceptions on the changes in work practices due to digitalisation, with a special focus on online counselling. Furthermore, the data include thoughts on the impact digitalised interaction, i.e., online counselling, has on their work and professional identities. The students studied how the motivational interviewing method combined with a solution-focused counselling approach is applicable in online settings by using simulation pedagogy. The data consisted of students’ learning diaries. Furthermore, the data were analysed using inductive content analysis. The results show that the digitalisation of work practices demands blended professionalism, which allows the professional to work both face-to-face and online with clients. In addition, the education of social and health care professionals needs to address the lack of competences and skills in digitalised work practices and provide a conceptual and practical understanding of blended professionalism in the sector.

Description: In Japan’s response to the coronavirus disease 2019 (COVID-19), virus testing was limited to symptomatic patients due to limited capacity, resulting in uncertainty regarding the spread of infection and the appropriateness of countermeasures. System dynamic modelling, comprised of stock flow and infection modelling, was used to describe regional population dynamics and estimate assumed region-specific transmission rates. The estimated regional transmission rates were then mapped against actual patient data throughout the course of the interventions. This modelling, together with simulation studies, demonstrated the effectiveness of inbound traveler quarantine and resident self-isolation policies and practices. A causal loop approach was taken to link societal factors to infection control measures. This causal loop modelling suggested that the only effective measure against COVID-19 transmission in the Japanese context was intervention in the early stages of the outbreak by national and regional governments, and no social self-strengthening dynamics were demonstrated. These findings may contribute to an understanding of how social resilience to future infectious disease threats can be developed.

Description: This study examined postural control during single leg stance test with progressively increased balance-task difficulty in soccer players with unilateral transfemoral amputation (n = 11) compared to able-bodied soccer players (n = 11). The overall stability index (OSI), the anterior/posterior stability index, and the medial/lateral stability index during three balance tasks with increasing surface instability were estimated. The oculomotor and visuomotor contribution to postural control in disabled athletes was analyzed. Oculomotor function, simple and choice reaction times, and peripheral perception were assessed in a series of visuomotor tests. The variation in OSI demonstrated significantly greater increases during postural tests with increased balance-task difficulty in the able-bodied soccer players compared to amputees (F(2,40) = 3.336, p 〈 0.05). Ocular mobility index correlated (p 〈 0.05) with OSI in conditions of increasing balance-task difficulty. Moreover, speed of eye-foot reaction has positive influence (p 〈 0.05) on stability indexes in tasks with an unstable surface. Amputee soccer players displayed comparable postural stability to able-bodied soccer players. Disabled athletes had better adaptability in restoring a state of balance in conditions of increased balance-task difficulty than the controls. The speed of visuomotor processing, characterized mainly by speed of eye-foot reaction, significantly contributed to these results.

Description: Families play an important role in helping teenagers avoid using tobacco, cannabis, and opioids, but some parents may underestimate the risk of their children using those substances. This study aimed to determine parents’ perceived likelihood of their child initiating tobacco, cannabis, and opioid use, as well as the control they have in preventing their child from using those substances. We surveyed 427 parents of children aged 0–18 years old using the online Amazon Mechanical Turk platform in the spring of 2019. We measured participants’ perceived likelihood of their child initiating tobacco, cannabis, or opioid use before the age of 18 compared to other children, using a five-point Likert scale. This perceived likelihood was dichotomized between optimistic (less likely than average) and non-optimistic (average or more likely than average). Independent variables included parental tobacco use, perceived parental control, and perceived severity of the behavior. Participants with missing data and participants with children who had already initiated substance use were excluded from statistical analyses. Mean age of participants was 38.1 years (Standard Deviation 8.4); 67% were female. Level of parental optimism was 59% for cannabis, 77% for tobacco, and 82% for opioids. Perceived severity was significantly lower for cannabis use (71/100) than tobacco (90/100) and opioid use (92/100) (p 〈 0.001). Current smokers were less likely than never smokers to be optimistic about their child’s risk of initiating using tobacco (Adjusted Odds Ratio (AOR): 0.18 [95% Confidence Interval (CI) 0.10–0.34]) or cannabis (AOR: 0.21 [95% CI 0.12–0.38]). Parental perceived likelihood of a child initiating substance use represents an understudied and potential target for substance use prevention.

Description: Recent evidence suggests that traffic noise may negatively impact mental health. However, existing systematic reviews provide an incomplete overview of the effects of all traffic noise sources on mental health. We conducted a systematic literature search and summarized the evidence for road, railway, or aircraft noise-related risks of depression, anxiety, cognitive decline, and dementia among adults. We included 31 studies (26 on depression and/or anxiety disorders, 5 on dementia). The meta-analysis of five aircraft noise studies found that depression risk increased significantly by 12% per 10 dB LDEN (Effect Size = 1.12, 95% CI 1.02–1.23). The meta-analyses of road (11 studies) and railway traffic noise (3 studies) indicated 2–3% (not statistically significant) increases in depression risk per 10 dB LDEN. Results for road traffic noise related anxiety were similar. We did not find enough studies to meta-analyze anxiety and railway or aircraft noise, and dementia/ cognitive impairment and any traffic noise. In conclusion, aircraft noise exposure increases the risk for depression. Otherwise, we did not detect statistically significant risk increases due to road and railway traffic noise or for anxiety. More research on the association of cognitive disorders and traffic noise is required. Public policies to reduce environmental traffic noise might not only increase wellness (by reducing noise-induced annoyance), but might contribute to the prevention of depression and anxiety disorders.

Description: The primary purpose of this study was to describe obesity, body composition, convenience food consumption, physical activity, and muscle strength among Asian American youth compared to other racial/ethnic groups. The secondary purpose was to examine whether obesity, body composition, convenience food consumption, physical activity, and muscle strength differed by acculturation levels among Asian American youth. A secondary analysis was conducted using data from 12,763 children aged 2 to 17 years that participated in the 2011–2018 US National Health and Nutrition Examination Survey (NHANES). In the NHANES interview, acculturation, dietary behavior, and physical activity questionnaires were administered. The acculturation level was indicated by the language spoken at home. In the NHANES examination, anthropometry, dual-energy X-ray absorptiometry (DXA), and muscle strength assessments were conducted. Compared to non-Hispanic White American boys, Asian American boys had similar levels of obesity, central obesity, and fat mass. Among the five racial/ethnic groups examined, lean body mass, muscle mass, convenience food consumption, and daily physical activity were the lowest in the Asian group. More acculturated Asian American boys, but not girls, were more likely to be obese (OR = 3.28 (1.63, 6.60)). More acculturated Asian American youth more frequently consumed convenience food (1.4 more meals/month (1.2, 1.6)). This study highlights the obesity problem among Asian American boys, which worsens with acculturation to America. The study results also suggest that although Asian American youth consume less convenience food overall than non-Hispanic White American youth, increasing acculturation may negatively influence food choices.

Description: The novel coronavirus disease 2019 (COVID-19) is a global pandemic spreading worldwide, and Italy represented the first European country involved. Healthcare workers (HCWs) facing COVID-19 pandemic represented an at-risk population for new psychosocial COVID-19 strain and consequent mental health symptoms. The aim of the present study was to identify the possible impact of working contextual and personal variables (age, gender, working position, years of experience, proximity to infected patients) on professional quality of life, represented by compassion satisfaction (CS), burnout, and secondary traumatization (ST), in HCWs facing COVID-19 emergency. Further, two multivariable linear regression analyses were fitted to explore the association of mental health selected outcomes, anxiety and depression, with some personal and working characteristics that are COVID-19-related. A sample of 265 HCWs of a major university hospital in central Italy was consecutively recruited at the outpatient service of the Occupational Health Department during the acute phase of COVID-19 pandemic. HCWs were assessed by Professional Quality of Life-5 (ProQOL-5), the Nine-Item Patient Health Questionnaire (PHQ-9), and the Seven-Item Generalized Anxiety Disorder scale (GAD-7) to evaluate, respectively, CS, burnout, ST, and symptoms of depression and anxiety. Females showed higher ST than males, while frontline staff and healthcare assistants reported higher CS rather than second-line staff and physicians, respectively. Burnout and ST, besides some work or personal variables, were associated to depressive or anxiety scores. The COVID-19 pandemic represents a new working challenge for HCWs and intervention strategies to prevent burnout and ST to reduce the risk of adverse mental health outcomes are needed.

Description: The aim of this study was to identify a best practice method to cost the health benefits of active transport for use in infrastructure planning in New South Wales, Australia. We systematically reviewed the international literature covering the concept areas of active transport and cost and health benefits. Original publications describing a method to cost the health benefits of active transport, published in 2000–2019 were included. Studies meeting the inclusion criteria were assessed against criteria identified in interviews with key government stakeholders. A total of 2993 studies were identified, 53 were assessed for eligibility, and 19 were included in the review. The most commonly studied active transport modes were cycling (n = 8) and walking and cycling (n = 6). Exposures considered were physical activity, road transport related injuries and air pollution. The most often applied economic evaluation method was cost benefit analysis (n = 8), and costs were commonly calculated by monetising health outcomes. Based on evaluation of models against the criteria, a Multistate Life Table model was recommended as the best method currently available. There is strong and increasing interest in quantifying and costing the health benefits of active transport internationally. Incorporating health-related economic benefits into existing regulatory processes such as cost benefit analyses could provide an effective way to encourage the non-health sector to include health impacts in infrastructure measures.

Description: Rescue workers present an elevated risk for posttraumatic stress disorder (PTSD) and recently, research has begun to focus on coping styles and social support as protective factors in this population. Associations in the particular group of search and rescue dog handlers still lack evidence. The aim of the study is to investigate if functional cognitions and social support also decrease the risk for PTSD. Active voluntary rescue dog handlers (n = 116) rated levels of resilience, sense of coherence, and social acknowledgment (SAQ; subscales general disapproval, familial disapproval, recognition), in addition to a trauma checklist and PTSD symptoms. Linear regression analyses and two different graph models were calculated to explore associations, as well as potential pathways. Controlling for trauma exposure, the SAQ general disapproval emerged as the only significant predictor in the regression model. In the graph models, SAQ familial disapproval was linked to SAQ recognition and SAQ general disapproval. The latter, together with a sense of coherence manageability, affected PTSD re-experiencing symptoms through resilience. The findings are in line with earlier work. The study underlines the importance of targeting resilience and manageability, as well as enhancing social support in prevention programs for PTSD in canine search and rescue teams. Future research is warranted to further investigate model stability and replicate findings.

Description: Many human activities are tactile. Recognizing how a person touches an object or a surface surrounding them is an active area of research and it has generated keen interest within the interactive surface community. In this paper, we compare two machine learning techniques, namely Artificial Neural Network (ANN) and Hidden Markov Models (HMM), as they are some of the most common techniques with low computational cost used to classify an acoustic-based input. We employ a small and low-cost hardware design composed of a microphone, a stethoscope, a conditioning circuit, and a microcontroller. Together with an appropriate surface, we integrated these components into a passive gesture recognition input system for experimental evaluation. To perform the evaluation, we acquire the signals using a small microphone and send it through the microcontroller to MATLAB’s toolboxes to implement and evaluate the ANN and HMM models. We also present the hardware and software implementation and discuss the advantages and limitations of these techniques in gesture recognition while using a simple alphabet of three geometrical figures: circle, square, and triangle. The results validate the robustness of the HMM technique that achieved a success rate of 90%, with a shorter training time than the ANN.

Description: In recent years, field-effect transistors (FETs) have been very promising for biosensor applications due to their high sensitivity, real-time applicability, scalability, and prospect of integrating measurement system on a chip. Non-carbon 2D materials, such as transition metal dichalcogenides (TMDCs), hexagonal boron nitride (h-BN), black phosphorus (BP), and metal oxides, are a group of new materials that have a huge potential in FET biosensor applications. In this work, we review the recent advances and remarkable studies of non-carbon 2D materials, in terms of their structures, preparations, properties and FET biosensor applications. We will also discuss the challenges facing non-carbon 2D materials-FET biosensors and their future perspectives.

Description: Strokes are a time-dependent medical emergency. The training of emergency medical service (EMS) professionals is essential to ensure the activation of stroke codes with pre-notification, as well as a rapid transfer to achieve early therapy. New assessment scales for the detection of patients with suspected large vessel occlusion ensures earlier access to endovascular therapy. The aim of this study was to evaluate the impact on an online training intervention focused on the Rapid Arterial oCclusion Evaluation (RACE) scoring of EMS professionals based on the prehospital stroke code in Catalonia from 2014 to 2018 in a pre–post intervention study. All Catalonian EMS professionals and the clinical records from primary stroke patients were included. The Kirkpatrick model guided the evaluation of the intervention. Data were collected on the knowledge on stroke recognition and management, pre-notification compliance, activated stroke codes and time performance of EMS professionals. Knowledge improved significatively in most items and across all categories, reaching a global achievement of 82%. Pre-notification compliance also improved significantly and remained high in the long-term. Increasingly higher notification of RACE scores were recorded from 60% at baseline to 96.3% in 2018, and increased on-site clinical care time and global time were also observed. Therefore, the online training intervention was effective for increasing EMS professionals’ knowledge and pre-notification compliance upon stroke code activation, and the wide adoption of a new prehospital scale for the assessment of stroke severity (i.e., the RACE scale) was achieved.

Description: A substantial amount of attention has been devoted towards the potential sport legacy of the Olympic Games. In spite of the increasing academic interest in this topic, there is a knowledge gap as far as sport legacy is concerned by types of different sports. The authors bridge this gap by analysing the evolution of 43 different Olympic/Paralympic sport modalities in the two-year period after the London 2012 Olympics. By using data from the Active People Survey with a sample of 165,000 people annually, and considering some demographic variables and the effect of the economic environment, the paper aims to test the existence of a sport legacy. We have applied time series analysis and ARIMA models for controlling for economic influence and seasonal adjustment and for making comparisons among participation rates. The results show, for the total of the sports analysed, that there were 336,000 individuals who increased their frequency of participation, while there was no significant increase in the number of new participants in these sports. When we develop the analysis for types of sports, London 2012 is positively associated not only with the frequency of participation in some types of sport but also with an increase in the number of new sport participants. Gender and age differences are also detected. The results show the differences of sport legacy by type of sports. Moreover, this research has elucidated an important unrecognised aspect of the effect of the Olympic Games and perhaps major events: that they can become a major policy tool for reversing sporting inequalities.

Description: Siamese network-based trackers consider tracking as features cross-correlation between the target template and the search region. Therefore, feature representation plays an important role for constructing a high-performance tracker. However, all existing Siamese networks extract the deep but low-resolution features of the entire patch, which is not robust enough to estimate the target bounding box accurately. In this work, to address this issue, we propose a novel high-resolution Siamese network, which connects the high-to-low resolution convolution streams in parallel as well as repeatedly exchanges the information across resolutions to maintain high-resolution representations. The resulting representation is semantically richer and spatially more precise by a simple yet effective multi-scale feature fusion strategy. Moreover, we exploit attention mechanisms to learn object-aware masks for adaptive feature refinement, and use deformable convolution to handle complex geometric transformations. This makes the target more discriminative against distractors and background. Without bells and whistles, extensive experiments on popular tracking benchmarks containing OTB100, UAV123, VOT2018 and LaSOT demonstrate that the proposed tracker achieves state-of-the-art performance and runs in real time, confirming its efficiency and effectiveness.

Description: The Internet of Medical Things (IoMT) couples IoT technologies with healthcare services in order to support real-time, remote patient monitoring and treatment. However, the interconnectivity of critical medical devices with other systems in various network layers creates new opportunities for remote adversaries. Since most of the communication protocols have not been specifically designed for the needs of connected medical devices, there is a need to classify the available IoT communication technologies in terms of security. In this paper we classify IoT communication protocols, with respect to their application in IoMT. Then we describe the main characteristics of IoT communication protocols used at the perception, network and application layer of medical devices. We examine the inherent security characteristics and limitations of IoMT-specific communication protocols. Based on realistic attacks we identify available mitigation controls that may be applied to secure IoMT communications, as well as existing research and implementation gaps.

Description: Monitoring biomass of forages in experimental plots and livestock farms is a time-consuming, expensive, and biased task. Thus, non-destructive, accurate, precise, and quick phenotyping strategies for biomass yield are needed. To promote high-throughput phenotyping in forages, we propose and evaluate the use of deep learning-based methods and UAV (Unmanned Aerial Vehicle)-based RGB images to estimate the value of biomass yield by different genotypes of the forage grass species Panicum maximum Jacq. Experiments were conducted in the Brazilian Cerrado with 110 genotypes with three replications, totaling 330 plots. Two regression models based on Convolutional Neural Networks (CNNs) named AlexNet and ResNet18 were evaluated, and compared to VGGNet—adopted in previous work in the same thematic for other grass species. The predictions returned by the models reached a correlation of 0.88 and a mean absolute error of 12.98% using AlexNet considering pre-training and data augmentation. This proposal may contribute to forage biomass estimation in breeding populations and livestock areas, as well as to reduce the labor in the field.

Description: The proportion of females participating in long-distance races has been increasing in the last years. Although it is well-known that there are differences in how females and males face a marathon, higher research may be done to fully understand the intrinsic and extrinsic factors affecting sex differences in endurance performance. In this work, we used triaxial accelerometer devices to monitor 74 males and 14 females, aged 30 to 45 years, who finished the Valencia Marathon in 2016. Moreover, marathon split times were provided by organizers. Several physiological traits and training habits were collected from each participant. Then, we evaluated several accelerometry- and pace-estimated parameters (pacing, average change of speed, energy consumption, oxygen uptake, running intensity distribution and running economy) in female and male amateur runners. In general, our results showed that females maintained a more stable pacing and ran at less demanding intensity throughout the marathon, limiting the decay of running pace in the last part of the race. In fact, females ran at 4.5% faster pace than males in the last kilometers. Besides, their running economy was higher than males (consumed nearly 19% less relative energy per distance) in the last section of the marathon. Our results may reflect well-known sex differences in physiology (i.e., muscle strength, fat metabolism, VO2max), and in running strategy approach (i.e., females run at a more conservative intensity level in the first part of the marathon compared to males). The use of accelerometer devices allows coaches and scientific community to constantly monitor a runner throughout the marathon, as well as during training sessions.

Description: Bioelectrocatalysis provides the intrinsic catalytic functions of redox enzymes to nonspecific electrode reactions and is the most important and basic concept for electrochemical biosensors. This review starts by describing fundamental characteristics of bioelectrocatalytic reactions in mediated and direct electron transfer types from a theoretical viewpoint and summarizes amperometric biosensors based on multi-enzymatic cascades and for multianalyte detection. The review also introduces prospective aspects of two new concepts of biosensors: mass-transfer-controlled (pseudo)steady-state amperometry at microelectrodes with enhanced enzymatic activity without calibration curves and potentiometric coulometry at enzyme/mediator-immobilized biosensors for absolute determination.

Description: Physical rehabilitation therapies for children present a challenge, and its success—the improvement of the patient’s condition—depends on many factors, such as the patient’s attitude and motivation, the correct execution of the exercises prescribed by the specialist or his progressive recovery during the therapy. With the aim to increase the benefits of these therapies, social humanoid robots with a friendly aspect represent a promising tool not only to boost the interaction with the pediatric patient, but also to assist physicians in their work. To achieve both goals, it is essential to monitor in detail the patient’s condition, trying to generate user profile models which enhance the feedback with both the system and the specialist. This paper describes how the project NAOTherapist—a robotic architecture for rehabilitation with social robots—has been upgraded in order to include a monitoring system able to generate user profile models through the interaction with the patient, performing user-adapted therapies. Furthermore, the system has been improved by integrating a machine learning algorithm which recognizes the pose adopted by the patient and by adding a clinical reports generation system based on the QUEST metric.

Description: Background: This study compared the efficacy of two multi-component m-health interventions with a wait-list control group on body weight (primary outcome), and secondary outcomes of cardiovascular risk factors, lifestyle behaviours, and mental health. Methods: Three-arm randomised controlled trial (Enhanced: physical activity, diet, sleep, Traditional: physical activity, diet, Control) with assessments conducted at baseline, 6 and 12 months. Participants (n = 116) were overweight or obese adults aged 19–65 (M = 44.5 [SD = 10.5]). The 6-month intervention was delivered via a smartphone app providing educational materials, goal-setting, self-monitoring and feedback, and also included one face-to-face dietary consultation, a Fitbit and scales. The trial was prospectively registered and conducted between May 2017 and September 2018. Group differences on primary and secondary outcomes were examined between the Pooled Intervention groups (Pooled Intervention = Enhanced and Traditional) and Control groups, and then between Enhanced and Traditional groups. Results: Nineteen participants (16.4%) formally withdrew from the trial. Compared with the Control group, average body weight of the Pooled Intervention group did not differ at 6 (between-group difference = −0.92, (95% CI −3.33, 1.48)) or 12 months (0.00, (95% CI −2.62, 2.62)). Compared with the Control group, the Pooled Intervention group significantly increased resistance training (OR = 7.83, (95% CI 1.08, 56.63)) and reduced energy intake at 6 months (−1037.03, (−2028.84, −45.22)), and improved insomnia symptoms at 12 months (−2.59, (−4.79, −0.39)). Compared with the Traditional group, the Enhanced group had increased waist circumferences (2.69, (0.20, 5.18)) and sedentary time at 6 months (105.66, (30.83, 180.48)), and improved bed time variability at 12 months (−1.08, (−1.86, −0.29)). No other significant differences were observed between groups. Conclusions: Relative to Controls, the Pooled Intervention groups did not differ on body weight but improved resistance training, and reduced energy intake and insomnia symptom severity. No additional weight loss was apparent when targeting improvements in physical activity, diet and sleep in combination compared with physical activity and diet.

Description: The Karlsruhe Tritium Neutrino (KATRIN) experiment aims at measuring the effective electron neutrino mass with a sensitivity of 0.2 eV/c2, i.e., improving on previous measurements by an order of magnitude. Neutrino mass data taking with KATRIN commenced in early 2019, and after only a few weeks of data recording, analysis of these data showed the success of KATRIN, improving on the known neutrino mass limit by a factor of about two. This success very much could be ascribed to the fact that most of the system components met, or even surpassed, the required specifications during long-term operation. Here, we report on the performance of the laser Raman (LARA) monitoring system which provides continuous high-precision information on the gas composition injected into the experiment’s windowless gaseous tritium source (WGTS), specifically on its isotopic purity of tritium—one of the key parameters required in the derivation of the electron neutrino mass. The concentrations cx for all six hydrogen isotopologues were monitored simultaneously, with a measurement precision for individual components of the order 10−3 or better throughout the complete KATRIN data taking campaigns to date. From these, the tritium purity, εT, is derived with precision of

Description: In this paper, we present a navigation strategy exclusively designed for social robots with limited sensors for applications in homes. The overall system integrates a reactive design based on subsumption architecture and a knowledge system with learning capabilities. The component of the system includes several modules, such as doorway detection and room localization via convolutional neural network (CNN), avoiding obstacles via reinforcement learning, passing the doorway via Canny edge’s detection, building an abstract map called a Directional Semantic Topological Map (DST-Map) within the knowledge system, and other predefined layers within the subsumption architecture. The individual modules and the overall system are evaluated in a virtual environment using Webots simulator.

Description: Although bullying and cyberbullying have been widely studied in diverse geographical areas, the number of studies in isolated regions, located in rainforests such as the Peruvian Amazonia, is low. Most research has been conducted in wealthy, Western countries, although disadvantaged areas are usually the most affected by various problems. Thus, the aims of this study were to validate bullying and cyberbullying measurement instruments among adolescents in the Peruvian Amazonia, to determine the prevalence rates of bullying and cyberbullying among this population, and to examine how bullying and cyberbullying relate to self-esteem, empathy, and social skills. The sample included 607 students from the region of Loreto (Peruvian Amazonia) who completed self-report questionnaires. Both questionnaires used in the sample were found to have good psychometric properties. Results showed that bullying and cyberbullying are prevalent among teenagers in the Amazonia. Low self-esteem and high affective empathy predicted bullying victimization. Being a bully was related to high assertiveness. Being a bully-victim was related to low self-esteem and low assertiveness. Cybervictims showed higher cognitive empathy. Cyberbullies showed higher affective empathy in comparison to uninvolved adolescents. Having low self-esteem and higher affective empathy were related to being a cyberbully/victim. This study provides a validated questionnaire that can be used for research and practice in the Amazonia. Based on the current results, tailored anti-bullying and anti-cyberbullying interventions with components focused on self-esteem, empathy, and social skills should be implemented in Peruvian secondary schools.

Description: In multi-target tracking scenarios with dense and heterogeneous clutter, there is a substantial increase in the false measurements that originated from the clutter within the validation gate, and consequently, the number of measurement-to-track association hypothesis grows rapidly in traditional multiple hypothesis tracker (MHT), leading to a sharp decrease in data association accuracy and tracking performance. A new multiple hypothesis tracker using validation gate with motion direction constraint (MHT-MDC) is proposed to solve these problems. In the MHT-MDC, a motion direction constraint (MDC) gate is designed by considering the prior target maneuvering information, which effectively reduces the volume of validation gate and, thus, diminishes the number of false measurements in the gate when the innovation covariance is large. Subsequently, the clutter density in the MDC gate is adaptively estimated by the conditional mean estimator of clutter density (CMECD), based on which the score functions in the MDC gate can be calculated. The MHT-MDC is compared with the MHT algorithm in simulations, and the experimental results demonstrate its superior tracking performance for weakly maneuvering targets in high clutter density scenarios.

Description: Over the last decade, video surveillance systems have become a part of the Internet of Things (IoT). These IP-based surveillance systems now protect industrial facilities, railways, gas stations, and even one’s own home. Unfortunately, like other IoT systems, there are inherent security risks which can lead to significant violations of a user’s privacy. In this review, we explore the attack surface of modern surveillance systems and enumerate the various ways they can be compromised with real examples. We also identify the threat agents, their attack goals, attack vectors, and the resulting consequences of successful attacks. Finally, we present current countermeasures and best practices and discuss the threat horizon. The purpose of this review is to provide researchers and engineers with a better understanding of a modern surveillance systems’ security, to harden existing systems and develop improved security solutions.

Description: The work investigates the application of artificial neural networks and logistic regression for the recognition of activities performed by room occupants. KNX (Konnex) standard-based devices were selected for smart home automation and data collection. The obtained data from these devices (Humidity, CO2, temperature) were used in combination with two wearable gadgets to classify specific activities performed by the room occupant. The obtained classifications can benefit the occupant by monitoring the wellbeing of elderly residents and providing optimal air quality and temperature by utilizing heating, ventilation, and air conditioning control. The obtained results yield accurate classification.

Description: To analyze the association between prostate cancer (PCa) risk and night shift work, chronotype, and sleep duration in the context of a population-based case-control study of incident prostate cancer in Spain, a total of 465 PCa cases and 410 controls were analyzed. Selection criteria were: (i) age 40–80 years, and (ii) residence in the coverage area of the reference hospitals for ≥6 months before recruitment. Exposure variables were: (i) night shift work (permanent or rotating); (ii) chronotype: morning, neither, or evening (Munich ChronoType Questionnaire) and (iii) sleep duration according to the recommendations of the American National Sleep Foundation. PCa aggressiveness was determined according to the International Society of Urology Pathology classification. Adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) were estimated using logistic regression models. Night shift work was associated with PCa, aOR = 1.47 (95% CI 1.02–2.11), especially for rotating night shifts, aOR = 1.73 (95% CI 1.09–2.75). The magnitude of the association between ever night work and PCa was higher in evening subjects with aOR = 3.14 (95% CI 0.91–10.76) than in morning chronotypes with an aOR = 1.25 (95% CI 0.78–2.00). Working night shifts, especially rotating night shifts, could increase PCa risk. This risk may be higher in people with an evening chronotype.

Description: Background: National School Lunch Program (NSLP) standards have improved school lunch dietary quality (DQ), however, further improvements could be made. Acceptability and feasibility of higher DQ are potential barriers. Thus, the purpose is to compare acceptability and feasibility of best practice (BPSL, optimizing DQ) with typical school lunches (TSL, meeting minimum NSLP standards) served separately and concurrently. Methods: Forty elementary school-aged participants were recruited for a randomized crossover trial. Participants attended three meal conditions (MC) choosing one of two meal types—MC1) BPSL1/BPSL2, MC2) TSL1/TSL2, MC3) BPSL/TSL. Acceptability included taste test surveys, weighted plate waste assessments, and hunger scales. Feasibility included meal cost, time, and skill and equipment requirements. Results: There were no significant differences in total taste test score, average total plate waste, or change in hunger (ps 〉 0.017) before or after adjusting for covariates. TSL was selected significantly more often in MC3 (TSL = 83.3%, BPSL = 16.7%, p = 0.001). Meal cost (p = 0.783) and skill and equipment requirements were not significantly different between meal types. BPSL required significantly longer preparation time (TSL = 60 ± 25 min, BPSL = 267 ± 101 min, p = 0.026). Conclusions: Results indicate few differences in acceptability and feasibility between BPSL and TSL. This study could inform decision and policy-makers seeking to improve school lunch DQ and acceptance of higher DQ meals.

Description: The study aimed to investigate the correlations among immune, haematological, endocrinological markers and fitness parameters, and assess if the physiological parameters could be a predictor of fitness values. Anthropometric, physical evaluations (countermovement jump—CMJ, 10 m sprint, VO2max, repeated sprint ability—RSA total time and index) and determination of blood (IL-6, IL-10, IL-17A and tumour necrosis factor) and salivary (testosterone and cortisol) samples parameters in 28 young male soccer players (age: 13.0 ± 0.2 years, body mass index (BMI): 19.5 ± 2.2 kg/m2) were analysed. To evaluate the dependence of the variables related to athletic performance, multiple linear regression with backward stepwise elimination was considered. A significant regression equation was found in CMJ (F(5,16) = 9.86, p 〈 0.001, R2 adjusted = 0.679) and in the RSA index (F(5,16) = 15.39, p 〈 0.001, R2 adjusted = 0.774) considering only five variables, in a 10 m sprint (F(4,17) = 20.25, p 〈 0.001, R2 adjusted = 0.786) and in the RSA total time (F(4,17) = 15.31, p 〈 0.001, R2 adjusted = 0.732) considering only four variables and in VO2max (F(9,12) = 32.09, p 〈 0.001, R2 adjusted = 0.930) considering nine variables. Our study suggests the use of regression equations to predict the fitness values of youth soccer players by blood and saliva samples, during different phases of the season, short periods of match congestion or recovery from an injury.

Description: The intrinsic heterogeneity property of concrete causes strong multiple scatterings during wave propagation, forming coda wave that follows very complex trajectories. As a superposition of multiply scattered waves, coda wave shows great sensitivity to subtle changes, but meanwhile lose spatial resolution. To make use of its sensitivity and turn the limitation into advantage, this paper presents an experimental study of three-dimensionally imaging local changes in concrete by application of inverse algorithms to coda wave measurements. Load tests are performed on a large reinforced concrete beam that contains multiple pre-existing millimeter-scale cracks in order to match real life situation. The joint effects of cracks and stresses on coda waves have been monitored using a network of fixed transducers placed at the surface. The global waveform decorrelations and velocity variations are firstly quantified through coda wave interferometry technique. Subsequently, two inverse algorithms are independently applied to map the densities of changes at each localized position. Using this methodology, the stress changes and subtle cracks in the concrete beam are detected and imaged for both temporal and spatial domains.

Description: The heat-exchanger/reactor (HEX reactor) is a kind of plug-flow chemical reactor which combines high heat transfer ability with good chemical performances. It was designed under the popular trend of process intensification in chemical engineering. Previous studies have investigated its characteristics and developed its nominal model. This paper is concerned with its fault tolerant control (FTC) applications. To avoid the difficulties and nonlinearities of this HEX reactor under chemical reactions, a two-layer, multiple-model structure is proposed for designing the FTC scheme. The first layer focuses on representing the nonlinear system with a bank of local linear models while the second layer uses model banks for approaching faulty situations. Model banks are achieved by system identification, and the corresponding controller banks are designed using model predictive control (MPC). The unscented Kalman filter (UKF) is introduced to estimate the states and form the fault detection and isolation (FDI) section. Finally, the FTC simulation and validation results are presented. The idea of a two-layer, multiple-model structure presents a general framework for FTC design of complex and highly nonlinear systems, such as the HEX reactor, whose mathematical model has been created. It implements the design process in an unusual way and is also worth trying on other cases.

Description: The range of applications of electromyography-based gesture recognition has increased over the last years. A common problem regularly encountered in literature is the inadequate data availability. Data augmentation, which aims at generating new synthetic data from the existing ones, is the most common approach to deal with this data shortage in other research domains. In the case of surface electromyography (sEMG) signals, there is limited research in augmentation methods and quite regularly the results differ between available studies. In this work, we provide a detailed evaluation of existing (i.e., additive noise, overlapping windows) and novel (i.e., magnitude warping, wavelet decomposition, synthetic sEMG models) strategies of data augmentation for electromyography signals. A set of metrics (i.e., classification accuracy, silhouette score, and Davies–Bouldin index) and visualizations help with the assessment and provides insights about their performance. Methods like signal magnitude warping and wavelet decomposition yield considerable increase (up to 16%) in classification accuracy across two benchmark datasets. Particularly, a significant improvement of 1% in the classification accuracy of the state-of-the-art model in hand gesture recognition is achieved.

Description: The purpose of this article is to study whether the position occupied by footballers on the pitch influences their life duration. It is known that various types of sporting activity (endurance, resistance, or mixed) may influence lifespan in different ways. However, there is a paucity of data regarding the role of different positions played in team sports such as football. Our research was based on elite international football players born before 1923 who took part in the first three football World Cups (n = 443) or played in the 1946/1947 season in the leading clubs of the main European leagues (n = 280). Goalkeepers were characterized by a 5–8-year longer life duration compared to their colleagues playing in other positions (World Cup: 82.0 ± 7.0 vs. 74.0 ± 8.0, p = 0.0047; European leagues: 83.0 ± 7.5 vs. 78.0 ± 8.0, p = 0.0023), with an absence of differences between defenders, midfielders, and forwards. Moreover, in both of the analyzed subgroups, the rate of survival until the 85th birthday was significantly higher among goalkeepers than among field players (p = 0.0102 and p = 0.0048, for both studied groups, respectively).

Description: Emotion recognition has been gaining attention in recent years due to its applications on artificial agents. To achieve a good performance with this task, much research has been conducted on the multi-modality emotion recognition model for leveraging the different strengths of each modality. However, a research question remains: what exactly is the most appropriate way to fuse the information from different modalities? In this paper, we proposed audio sample augmentation and an emotion-oriented encoder-decoder to improve the performance of emotion recognition and discussed an inter-modality, decision-level fusion method based on a graph attention network (GAT). Compared to the baseline, our model improved the weighted average F1-scores from 64.18 to 68.31% and the weighted average accuracy from 65.25 to 69.88%.

Description: In developing countries, markets are the main supply of horticultural products to populations, but this can pose a public health challenge due to the risk of the fecal-oral transmission of gut pathogens. This transmission is strongly associated with inadequate public sanitation or low standards of personal and domestic hygiene, and their prevalence can cause gastrointestinal diseases, which are the third leading cause of death in Mozambique. This study aims at assessing the risk for public health of horticultural products supply chain, from the farmers-vendors to the consumers, in municipal markets in Maputo-City, Mozambique. Surveys (75) were conducted on vendors and an observational analysis was performed in the markets under study. The results showed that 62% of the vendors had access to water from boreholes or artisanal sources and the issue “access to water” was significantly different between markets (p = 0.004). Of the vendors who wash their products (53.3%), only 7.5% use tap-water for this purpose, with the difference in attitudes being statistically significant between vendors in the markets (p = 0.035). The majority (60.4%) said that vegetables and fruits can cause diseases due to pesticides and only 31.3% believe that the diseases may be related to poor hygiene. Despite the vendors’ low knowledge of Good Hygiene Practices (GHP), we noticed that women have better practical assimilation of GHP when compared to men (p = 0.008). Although Maputo’s markets are struggling to achieve quality hygiene standards in a reliable and sustainable manner, their resources are limited and significantly different (p = 0.044) from market to market, and this problem remains a concern for the public-health authorities of the city. In conclusion, the provision of adequate drinking water and sewage disposal systems, together with education for health of vendors, can reduce the risk of contamination of fresh food by the more common organisms causing diarrhea in children, including intestinal parasites.

Description: With the emergence of the novel SARS-CoV-2 and the disease it causes; COVID-19, compliance with/adherence to protective measures is needed. Information is needed on which measures are, or are not, being undertaken. Data collected from the COVID Impact Survey, conducted by the non-partisan and objective research organization NORC at the University of Chicago on April, May, and June of 2020, were analyzed through weighted Quasi-Poisson regression modeling to determine the association of demographics, socioeconomics, and health conditions with protective health measures taken at the individual level in response to COVID-19. The three surveys included data from 18 regional areas including 10 states (CA, CO, FL, LA, MN, MO, MT, NY, OR, and TX) and 8 Metropolitan Statistical Areas (Atlanta, GA; Baltimore, MD; Birmingham, AL; Chicago, IL; Cleveland and Columbus, OH; Phoenix, AZ; and Pittsburgh, PA). Individuals with higher incomes, insurance, higher education levels, large household size, age 60+, females, minorities, those who have asthma, have hypertension, overweight or obese, and those who suffer from mental health issues during the pandemic were significantly more likely to report taking precautionary protective measures relative to their counterparts. Protective measures for the three subgroups with a known relationship to COVID-19 (positive for COVID-19, knowing an individual with COVID-19, and knowing someone who had died from COVID-19) were strongly associated with the protective health measures of washing hands, avoiding public places, and canceling social engagements. This study provides first baseline data on the response to the national COVID-19 pandemic at the individual level in the US. The found heterogeneity in the response to this pandemic by different variables can inform future research and interventions to reduce exposure to the novel SARS-CoV-2 virus.

Description: The objective of this study is to assess the effect of alcohol consumption, anxiety, and food restriction before and after consuming alcohol and body image on the risk of anorexia and bulimia in college students from Tijuana, Baja California, through predictive statistical models. A quantitative, descriptive, and cross-sectional design and a non-probabilistic sample of 526 college students from Tijuana, Baja California, México were used. Application of the scales (with acceptable psychometric properties) was conducted in classrooms. Through path analyses, four models were found with adequate indicators of goodness of fit: (1) risk of anorexia in women [Chi Square (X2) = 5.34, p = 0.376, Adjusted Determination Coefficient (R2)= 0.250]; (2) anorexia risk for men (X2 = 13.067, p = 0.192, R2 = 0.058); (3) risk of bulimia in women (X2 = 3.358, p = 0.645, R2 = 0.202); and bulimia risk for men (X2 = 14.256, p = 0.075, R2 = 0.284). The findings provide empirical evidence for the food and alcohol disturbance model.

Description: In recent years, a series of matching pursuit and hard thresholding algorithms have been proposed to solve the sparse representation problem with ℓ0-norm constraint. In addition, some stochastic hard thresholding methods were also proposed, such as stochastic gradient hard thresholding (SG-HT) and stochastic variance reduced gradient hard thresholding (SVRGHT). However, each iteration of all the algorithms requires one hard thresholding operation, which leads to a high per-iteration complexity and slow convergence, especially for high-dimensional problems. To address this issue, we propose a new stochastic recursive gradient support pursuit (SRGSP) algorithm, in which only one hard thresholding operation is required in each outer-iteration. Thus, SRGSP has a significantly lower computational complexity than existing methods such as SG-HT and SVRGHT. Moreover, we also provide the convergence analysis of SRGSP, which shows that SRGSP attains a linear convergence rate. Our experimental results on large-scale synthetic and real-world datasets verify that SRGSP outperforms state-of-the-art related methods for tackling various sparse representation problems. Moreover, we conduct many experiments on two real-world sparse representation applications such as image denoising and face recognition, and all the results also validate that our SRGSP algorithm obtains much better performance than other sparse representation learning optimization methods in terms of PSNR and recognition rates.

Description: Background: The monitoring of bioaerosol concentrations in the air is a relevant endeavor due to potential health risks associated with exposure to such particles and in the understanding of their role in climate. In this context, the atmospheric concentrations of bacteria were measured from January 2018 to May 2020 at Saclay, France. The aim of the study was to understand the seasonality, the daily variability, and to identify the geographical origin of airborne bacteria. Methods: 880 samples were collected daily on polycarbonate filters, extracted with purified water, and analyzed using the cultivable method and flow cytometry. A source receptor model was used to identify the origin of bacteria. Results: A tri-modal seasonality was identified with the highest concentrations early in spring and over the summer season with the lowest during the winter season. Extreme changes occurred daily due to rapid changes in meteorological conditions and shifts from clean air masses to polluted ones. Conclusion: Our work points toward bacterial concentrations originating from specific seasonal-geographical ecosystems. During pollution events, bacteria appear to rise from dense urban areas or are transported long distances from their sources. This key finding should drive future actions to better control the dispersion of potential pathogens in the air, like persistent microorganisms originating from contaminated areas.

Description: At present, the state-of-the-art approaches of Visual Question Answering (VQA) mainly use the co-attention model to relate each visual object with text objects, which can achieve the coarse interactions between multimodalities. However, they ignore the dense self-attention within question modality. In order to solve this problem and improve the accuracy of VQA tasks, in the present paper, an effective Dense Co-Attention Networks (DCAN) is proposed. First, to better capture the relationship between words that are relatively far apart and make the extracted semantics more robust, the Bidirectional Long Short-Term Memory (Bi-LSTM) neural network is introduced to encode questions and answers; second, to realize the fine-grained interactions between the question words and image regions, a dense multimodal co-attention model is proposed. The model’s basic components include the self-attention unit and the guided-attention unit, which are cascaded in depth to form a hierarchical structure. The experimental results on the VQA-v2 dataset show that DCAN has obvious performance advantages, which makes VQA applicable to a wider range of AI scenarios.

Description: Present-day science indicates that developing sensors with excellent sensitivity and selectivity for detecting early signs of diseases is highly desirable. Electrochemical sensors offer a method for detecting diseases that are simpler, faster, and more accurate than conventional laboratory analysis methods. Primarily, exploiting non-noble-metal nanomaterials with excellent conductivity and large surface area is still an area of active research due to its highly sensitive and selective catalysts for electrochemical detection in enzyme-free sensors. In this research, we successfully fabricate Metal-Organic Framework (MOF) FeBDC-derived Fe3O4 for non-enzymatic electrochemical detection of glucose. FeBDC synthesis was carried out using the solvothermal method. FeCl2.4H2O and Benzene-1,4-dicarboxylic acid (H2BDC) are used as precursors to form FeBDC. The materials were further characterized utilizing X-ray Powder Diffraction (XRD), Scanning Electron Microscopy (SEM), and Fourier-Transform Infrared Spectroscopy (FTIR). The resulting MOF yields good crystallinity and micro-rod like morphology. Electrochemical properties were tested using Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) with a 0.1 M of Phosphate Buffer Saline (PBS pH 7.4) solution as the supporting electrolyte. The measurement results show the reduction and oxidation peaks in the CV curve of FeBDC, as well as Fe3O4. Pyrolysis of FeBDC to Fe3O4 increases the peak of oxidation and reduction currents. The Fe3O4 sample obtained has a sensitivity of 4.67 µA mM−1.cm−2, a linear range between 0.0 to 9.0 mM, and a glucose detection limit of 15.70 µM.

Description: In this work, we present a network architecture with parallel convolutional neural networks (CNN) for removing perspective distortion in images. While other works generate corrected images through the use of generative adversarial networks or encoder-decoder networks, we propose a method wherein three CNNs are trained in parallel, to predict a certain element pair in the 3×3 transformation matrix, M^. The corrected image is produced by transforming the distorted input image using M^−1. The networks are trained from our generated distorted image dataset using KITTI images. Experimental results show promise in this approach, as our method is capable of correcting perspective distortions on images and outperforms other state-of-the-art methods. Our method also recovers the intended scale and proportion of the image, which is not observed in other works.

Description: The food environment is well documented as an important emphasis for public health intervention. While theoretical models of the relationship between the food environment and dietary outcomes have been proposed, empirical testing of conceptual models has been limited. The purpose of this study was to explore which factors in nutrition environments are significantly associated with dietary outcomes in two urban, low-income, and minority food desert communities. This study analyzed cross-sectional data based on 796 participants from the Food in Our Neighborhood Study. Participants were recruited based on a random sample of addresses in neighborhood study areas, Philadelphia, PA (n = 393) and Trenton, NJ (n = 403). Main dietary outcomes were Healthy Eating Index (HEI) scores and fruit and vegetable consumption subscores computed from ASA24® assessments. Exploratory factor analysis was conducted and yielded a model of four factors with 22 items. Among four factors that emerged, three factors (Perceptions of Neighborhood Food Availability; and Household Food Challenges) were significantly correlated with dietary outcomes. My Store’s Quality and Perceptions of Neighborhood Food Availability were positively correlated with vegetable consumption subscore. The Household Food Challenges factor was negatively correlated with both vegetable subscore and overall HEI score (i.e., more household challenges were associated with lower dietary scores). These findings confirmed the importance of perceived nutrition environments and household food challenges in predicting dietary outcomes among residents of two urban, low-income, and minority food desert communities.

Description: The low efficiency of the closed-loop supply chain in construction and demolition waste (CDW) recycling has restricted the green development of China’s construction industry. Additionally, the government’s reward–penalty mechanism has a huge influence on green development. This study aimed to investigate the effect of green development performance (GDP) and the government’s reward–penalty mechanism on the decision-making process of production and recycling units, as well as to reveal the optimal strategies under different conditions. Therefore, the strategies’ evolutionary paths of production and recycling units were investigated by using evolutionary game theory. Firstly, an evolutionary game model between production units and recycling units was proposed under the government’s reward–penalty mechanism. Then, the evolutionary stability strategies in different scenarios were discussed. Finally, the effects of the relevant parameters on the evolutionary paths of the game model were analyzed using numerical simulations. The main conclusions are as follows. (1) When the range of GDP changes, the evolutionary stable strategy changes accordingly. GDP plays a positive role in promoting the high-quality development of the CDW recycling supply chain, but an increase in GDP can easily lead to the simultaneous motivation of free-riding. (2) The government’s reward–penalty mechanism effectively regulates the decision-making process of production and recycling units. An increase in the subsidy rate and supervision probability helps to reduce free-riding behavior. Moreover, the incentive effect of the subsidy probability on recycling units is more obvious, while the effect of the supervision probability on improving the motivation of active participation for production units is more remarkable. This paper not only provides a decision-making basis to ensure production and recycling units to make optimal strategy choices under different conditions but also provides a reference for the government to formulate a reasonable reward–penalty mechanism that is conducive to a macro-control market.

Description: Honey is an extensively utilized sweetener containing sugars and water, together with small quantities of vitamins, minerals, fatty acids, amino acids and proteins. Naturally produced by honeybees (Apis mellifera) from floral nectar, honey is increasingly sold as a health food product due to its nutritious features. Certain honeys are retailed as premium, trendy products. Honeybees are regarded as environmental monitors, but few reports examine the impact of environment on Australian honey trace elements and minerals. In higher density urban and industrial environments, heavy metals can be common, while minerals and trace elements can have ubiquitous presence in both agricultural and urban areas. Honey hives are traditionally placed in rural and forested areas, but increasingly the trend is to keep hives in more urban areas. This study aimed to determine the levels of 26 minerals and trace elements and assess elemental differences between honeys from various regional Queensland and Australian sources. Honey samples (n = 212) were acquired from markets, shops and supermarkets in Queensland while urban honeys were purchased online. The honey samples were classified into four groups according to their regional sources: urban, rural, peri-urban and blend honey. Elemental analyses of honey were performed using ICP-MS and ICP-OES after microwave and hot block digestion. Considerable variations of essential trace elements (Co, Cu, Cr, Fe, Mn, Mo and Zn) and mineral levels (Ca, K, Mg, Na and P) were found in honeys surveyed. There were significant differences (p 〈 0.05) between urban and rural honey samples for B, Na, P, Mn, K, Ca and Cu. Significant differences (p 〈 0.05) were also found between blend and urban honey samples for K, Cu, P, Mn, Sr, Ni, B and Na. Peri-urban versus urban honeys showed significant differences in P, K and Mn. For rural and peri-urban honeys, the only significant difference (p 〈 0.05) was for Na. Toxic heavy metals were detected at relatively low levels in honey products. The study revealed that the Queensland/Australian honey studied is a good source of K and Zn and would constitute a good nutritional source of these elements.

Description: The prevalence of hypertension among women in Korea aged 65 years or older is 61.7%. Past research has emphasized the importance of health-promoting behaviors in hypertension management for the elderly. The purpose of this cross-sectional study was to identify the effects of self-efficacy, depression, trait anger, and anger expression on the health-promoting behaviors of elderly women with hypertension. Self-report questionnaires were completed by 208 women aged 65 and older (age range: 65 to 85) diagnosed with hypertension by physicians and living in the communities of G city and N city of Gyeonggi-do in South Korea. A hierarchical regression analysis revealed that exercise (β = 0.36, p 〈 0.001) had the most significant effect on health-promoting behaviors, followed by depression (β = −0.31, p 〈 0.001), trait anger (β = 0.21, p = 0.002), anger control (β = 0.20, p 〈 0.001), religion (β = 0.18, p = 0.001), and self-efficacy (β = 0.18, p = 0.003). Trait anger and anger control were identified to have a more significant effect on health-promoting behaviors than self-efficacy. Thus, health-promoting behaviors were influenced by exercise, depression, anger, religion, and self-efficacy. It is necessary to implement a nursing intervention strategy which pays attention to these factors to improve health-promoting behaviors of Korean community-dwelling elderly women.

Description: Children with autistic spectrum disorder (ASD) often exhibit uncontrollable disruptive behaviour during transfer to the operating room and operating table and at the induction of anaesthesia (sleep). This process often involves the physical restraining of children. These children are then lifted onto the operating table by healthcare staff after being anaesthetized. This predisposes children to fall risk and hospital staff to musculoskeletal injuries. We developed two concept mobility devices, IMOVE-I and -II, based on robotics systems comprising of restraint modules and multi-positional modality (sitting, supine, Trendelenburg). The aim was to intuitively secure children to facilitate the safe induction of sleep and ease of transfer onto operating tables upon sleep. IMOVE-I loads the child in standing position using a dual arm restraint module that is activated by trained healthcare staff. IMOVE-II loads the child in the sitting position by motivating the self-application of restraints. Opinions were obtained from 21 operating theatre healthcare staff with experience in the care of ASD children and parents with ASD children. The mean satisfaction rating of IMOVE-I was 5.62 (95% CI 5.00, 6.27) versus 8.10 (95% CI 7.64, 8.55) in IMOVE-II, p 〈 0.001. IMOVE-II is favoured over IMOVE-I in system operation and safety, ease of use and module functionality.

Description: Surface electromyogram (EMG) is a noninvasive measure of muscle electrical activity and has been widely used in a variety of applications. When recorded from the trunk, surface EMG can be contaminated by the cardiac electrical activity, i.e., the electrocardiogram (ECG). ECG may distort the desired EMG signal, complicating the extraction of reliable information from the trunk EMG. Several methods are available for ECG removal from the trunk EMG, but a comparative assessment of the performance of these methods is lacking, limiting the possibility of selecting a suitable method for specific applications. The aim of the present study is therefore to review and compare the performance of different ECG removal methods from the trunk EMG. To this end, a synthetic dataset was generated by combining in vivo EMG signals recorded on the biceps brachii and healthy or dysrhythmia ECG data from the Physionet database with a predefined signal-to-noise ratio. Gating, high-pass filtering, template subtraction, wavelet transform, adaptive filtering, and blind source separation were implemented for ECG removal. A robust measure of Kurtosis, i.e., KR2 and two EMG features, the average rectified value (ARV), and mean frequency (MF), were then calculated from the processed EMG signals and compared with the EMG before mixing. Our results indicate template subtraction to produce the lowest root mean square error in both ARV and MF, providing useful insight for the selection of a suitable ECG removal method.

Description: In recent years, industrial production has become more and more automated. Machine cutting tool as an important part of industrial production have a large impact on the production efficiency and costs of products. In a real manufacturing process, tool breakage often occurs in an instant without warning, which results a extremely unbalanced ratio of the tool breakage samples to the normal ones. In this case, the traditional supervised learning model can not fit the sample of tool breakage well, which results to inaccurate prediction of tool breakage. In this paper, we use the high precision Hall sensor to collect spindle current data of computer numerical control (CNC). Combining the anomaly detection and deep learning methods, we propose a simple and novel method called CNN-AD to solve the class-imbalance problem in tool breakage prediction. Compared with other prediction algorithms, the proposed method can converge faster and has better accuracy.

Description: This study used the Korean National Health Insurance (NHI) claims database from 2011 to 2017 to estimate the incidence and the incidence-based cost of cervical cancer and carcinoma in situ of cervix uteri (CIS) in Korea. The primary outcome was the direct medical cost per patient not diagnosed with cervical cancer (C53) or CIS (D06) 2 years prior to the index date in the first year after diagnosis. A regression analysis was conducted to adjust for relevant covariates. The incidence of cervical cancer tended to decrease from 2013 to 2016, while that of CIS increased. In particular, the incidence rate of CIS in women in their 20 s and 30 s increased by 56.8% and 28.4%, respectively, from 2013 to 2016. The incidence-based cost of cervical cancer and CIS was USD 13,058 and USD 2695 in 2016, respectively, which increased from 2013. Multivariate regression analysis suggested that age was the most influential variable of the cost in both patient groups, and the cost was highest in those aged over 60, i.e., the medical cost was significantly lower in younger women than their older counterparts. These findings suggest that targeting younger women in cervical cancer prevention is a reasonable option from both economic and public health perspectives.

Description: Background: In this study, medical and socio-demographic characteristics of foreign language patients in prehospital emergency medical care are analyzed and compared with non-foreign language patients. Methods: We performed retrospective chart review of rescue operations in four emergency medical service stations in Northern Germany over seven months as part of the DICTUM Rescue study (DRKS00016719). We performed descriptive analyses including test statistics and used partial correlation to adjust for patients’ sex and age. Results: Patients with limited German proficiency were served in 2.2% of all 7494 covered rescue operations. On average, these patients were two decades younger than their German speaking counterparts. There were significantly more patients with limited German proficiency with gynecological and obstetric problems, especially births, as well as psychiatric disorders, especially suicide attempts. Conclusions: Our findings suggest that the existing preventive programs for pregnant women and people at risk of suicide do not sufficiently reach patients with limited German proficiency. Additionally, giving birth and psychiatric breakdowns are exceptional and sensitive situations, both for patients and the paramedic staff, where the ability to communicate safely appears to be of enormous importance to enable safe treatment.

Description: In this article, we present a new method of dehazing based on the Koschmieder model, which aims to restore an image that has been affected by haze. The difficulty is to improve the estimation of the transmission and the atmospheric light that generally suffer from the nonhomogeneity and the random variability of the environment. The keypoint is to enhance the dehazing of very bright regions of the image in order to improve the treatment of the sky that is often overestimated or underestimated compared to the rest of the scene. The approach proposed in this paper is based on two main contributions: 1. an L0 gradient optimization function weighted by a set of Gaussian filters and based on an iterative algorithm for optimization convergence. Unlike the existing methods using a single value of the atmospheric light for the whole image, our method uses a set of values neighboring an initial estimated value. The fusion is then applied based on Laplacian and Gaussian pyramids to combine all the relevant information from the set of images constructed from atmospheric lights and improves the contrast to recover the colors of the sky without any artifacts. Finally, the results are validated by three criteria: an autocorrelation score (ZNCC), a similarity measure (SSIM) and a visual criterion. The experiments carried out on two datasets show that our approach allows a better dehazing of the images with higher SSIM and ZNCC measurements but also with better visual quality.

Description: Japan has the highest life expectancy in the world. However, this does not guarantee an improved quality of life. There is a gap between life expectancy and healthy life expectancy. This study aimed to reveal the features of healthy life expectancy across all secondary medical areas (n = 344) in Japan and examine the relationship among healthcare resources, life expectancy, and healthy life expectancy at birth. Data were collected from Japan’s population registry and long-term insurance records. Differences in healthy life expectancy by gender were calculated using the Sullivan method. Maps of healthy life expectancy were drawn up. Descriptive statistics and correlation analysis were used for analysis. The findings revealed significant regional disparities. The number of doctors and therapists, support clinics for home healthcare facilities and home-visit treatments, and dentistry expenditure per capita were positively correlated with life expectancy and healthy life expectancy (correlation coefficients 〉 0.2). They also revealed gender differences. Despite controlling for population density, inequalities in healthy life expectancy were observed, highlighting the need to promote social policies to reduce regional disparities. Japanese policymakers should consider optimal levels of health resources to improve life expectancy and healthy life expectancy. The geographical distribution of healthcare resources should also be reconstituted.

Description: As aging populations continue to grow, primarily in developed countries, there are increasing demands for the system that monitors the activities of elderly people while continuing to allow them to pursue their individual, healthy, and independent lifestyles. Therefore, it is required to develop the activity of daily living (ADL) sensing systems that are based on high-performance sensors and information technologies. However, most of the systems that have been proposed to date have only been investigated and/or evaluated in experimental environments. When considering the spread of such systems to typical homes inhabited by elderly people, it is clear that such sensing systems will need to meet the following five requirements: (1) be inexpensive; (2) provide robustness; (3) protect privacy; (4) be maintenance-free; and, (5) work with a simple user interface. In this paper, we propose a novel senior-friendly ADL sensing system that can fulfill these requirements. More specifically, we achieve an easy collection of ADL data from elderly people while using a proposed system that consists of a small number of inexpensive energy harvesting sensors and simple annotation buttons, without the need for privacy-invasive cameras or microphones. In order to evaluate the practicality of our proposed system, we installed it in ten typical homes with elderly residents and collected the ADL data over a two-month period. We then visualized the collected data and performed activity recognition using a long short-term memory (LSTM) model. From the collected results, we confirmed that our proposed system, which is inexpensive and non-invasive, can correctly collect resident ADL data and could recognize activities from the collected data with a high recall rate of 72.3% on average. This result shows a high potential of our proposed system for application to services for elderly people.

Description: Health-promoting behaviors help prevent chronic illness. Health-promoting behaviors of nursing students can affect not only their own health, but also the health of their future patients, for whom they can act as role models. Nursing students should participate in health-promoting behaviors; however, nursing students often have unhealthy behaviors. This study aimed to investigate the factors affecting health-promoting behaviors in nursing students. A descriptive, self-report survey of 304 nursing students from three universities in South Korea was conducted. Subjects’ general characteristics, health perceptions, health concerns, and health-promoting behaviors were collected. Of the total participants, 90.1% were female and the mean age was 20.4 years. The mean score for health-promoting behaviors was 2.47, higher than the midpoint. The mean for the subscale of physical activity among health-promoting behaviors was the lowest. The main factors affecting health-promoting behaviors were gender, health perceptions, health concern, and time per week spent searching online for health-related information. The main factors affecting physical activity were gender, health concern, and time per week spent searching online for health-related information. Based on the study findings, it is recommended that a program to empower nursing students to perform health-promoting behaviors be incorporated into the nursing education curriculum with regard to unique needs based on gender. Specifically, it would be effective to develop programs that are easily accessible via the Internet.

Description: For many centuries, hunter-gatherer societies relied on subsistence practices and traditional diets. However, forces of globalization have increased market involvement, thereby fueling the nutrition transition of hunter-gatherer societies. We review the academic literature on market involvement of hunter-gatherer societies in the Western Amazon and its consequences on diet, health and well-being. First, we elaborate on four main determinants of market involvement (accessibility, monetary income, wild meat trade and social capital), showing how each determinant draws individuals toward or away from markets. Thereafter, we discuss how these determinants alter diet, health and well-being. Our results add to the understanding of the complex relations between market involvement, dietary change, health and well-being of indigenous societies. Furthermore, they bring to light that additional research is needed on the topic to support decision-makers and help preserve indigenous values.

Description: The Internet of Things (IoT) is an industry-recognized next intelligent life solution that increases the level of comfort, efficiency, and automation for citizens through numerous sensors, smart devices, and cloud stations connected physically. As an important application scenario of IoT, the Internet of Vehicles (IoV) plays an extremely critical role in the intelligent transportation field. In fact, the In-Vehicle Network of smart vehicles that are recognized as the core roles in intelligent transportation is currently the Controller Area Network (CAN). However, the In-Vehicle CAN bus protocol has several vulnerabilities without any encryption, authentication, or integrity checking, which severely threatens the safety of drivers and passengers. Once malicious attackers hack the vehicular gateway and obtain the access right of the CAN, they may control the vehicle based on the vulnerabilities of the CAN bus protocol. Given the severe security risk of CAN, we proposed the CANsec, a practical In-Vehicle CAN security evaluation tool that simulates malicious attacks according to major attack models to evaluate the security risk of the In-Vehicle CAN. We also show a usage case of the CANsec without knowing any information from the vehicle manufacturer.

Description: Disease prevention is a multifaceted construct that has been widely studied. Nevertheless, in spite of its importance, it is still not sufficiently considered by the general population. Since the reasons for this lack of consideration are not yet fully understood, we created an Online Prevention Survey (OPS) to investigate the role of both sociodemographic and psychological factors in predicting individuals’ spontaneous participation in secondary prevention programs. The results revealed that younger people, men, manual workers, unemployed people, and those who do not regularly practise physical activity were less likely to spontaneously participate in such programs. Furthermore, an analysis of the psychological determinants of the willingness to participate in secondary prevention programs showed that depressive symptoms negatively predict it, while an individual’s perception of receiving high social support acts as a positive predictor. Based on these results, we suggest the need for implementing new tailored approaches to promote prevention initiatives to those segments of the population which are more reluctant to spontaneously undertake prevention paths.

Description: The instrument transformers scenario is moving towards the adoption of a new generation of low-power instrument transformers. This disruptive change also requires that the modeling, characterization, and testing of those devices must be improved. Therefore, this study focuses on a smart approach developed by the authors in a previous study to estimate the output of low-power voltage transformers (LPVT). The approach—which is based on a sort of modeling in the frequency domain (the so-called sinc-response)—allows obtaining the behavior of the LPVT at rated and distorted conditions. Experimental tests performed on off-the-shelf devices confirm the applicability and effectiveness of the proposed approach when estimating the output response of LPVTs.

Description: The main factors influencing the shape of the beach, shoreline and seabed include undulation, wind and coastal currents. These phenomena cause continuous and multidimensional changes in the shape of the seabed and the Earth’s surface, and when they occur in an area of intense human activity, they should be constantly monitored. In 2018 and 2019, several measurement campaigns took place in the littoral zone in Sopot, related to the intensive uplift of the seabed and beach caused by the tombolo phenomenon. In this research, a unique combination of bathymetric data obtained from an unmanned surface vessel, photogrammetric data obtained from unmanned aerial vehicles and ground laser scanning were used, along with geodetic data from precision measurements with receivers of global satellite navigation systems. This paper comprehensively presents photogrammetric measurements made from unmanned aerial vehicles during these campaigns. It describes in detail the problems in reconstruction within the water areas, analyses the accuracy of various photogrammetric measurement techniques, proposes a statistical method of data filtration and presents the changes that occurred within the studies area. The work ends with an interpretation of the causes of changes in the land part of the littoral zone and a summary of the obtained results.

Description: With the development of flexible electronic materials, as well as the wide development and application of smartphones, the cloud, and wireless systems, flexible wearable sensor technology has a significant and far-reaching impact on the realization of personalized medical care and the reform of the consumer market in the future. However, due to the high requirements for accuracy, reliability, low power consumption, and less data error, the development of these potential areas is full of challenges. In order to solve these problems, this review mainly searches the literature from 2008 to May 2020, based on the PRISMA process. Based on them, this paper reviews the latest research progress of new flexible materials and different types of sensors for monitoring vital signs (including electrophysiological signals, body temperature, and respiratory frequency) in recent years. These materials and sensors can help realize accurate signal detection based on comfortable and sustainable observation, and may likely be applied to future daily clothing.

Description: The advances of the Internet of Things, robotics, and Artificial Intelligence, to give just a few examples, allow us to imagine promising results in the development of smart buildings in the near future. In the particular case of elderly care, there are new solutions that integrate systems that monitor variables associated with the health of each user or systems that facilitate physical or cognitive rehabilitation. In all these solutions, it is clear that these new environments, usually called Ambient Assisted Living (AAL), configure a Cyber-Physical System (CPS) that connects information from the physical world to the cyber-world with the primary objective of adding more intelligence to these environments. This article presents a CPS-AAL for caregiving centers, with the main novelty that includes a Socially Assistive Robot (SAR). The CPS-AAL presented in this work uses a digital twin world with the information acquired by all devices. The basis of this digital twin world is the CORTEX cognitive architecture, a set of software agents interacting through a Deep State Representation (DSR) that stored the shared information between them. The proposal is evaluated in a simulated environment with two use cases requiring interaction between the sensors and the SAR in a simulated caregiving center.

Description: Gait is a characteristic that has been utilized for identifying individuals. As human gait information is now able to be captured by several types of devices, many studies have proposed biometric identification methods using gait information. As research continues, the performance of this technology in terms of identification accuracy has been improved by gathering information from multi-modal sensors. However, in past studies, gait information was collected using ancillary devices while the identification accuracy was not high enough for biometric identification. In this study, we propose a deep learning-based biometric model to identify people by their gait information collected through a wearable device, namely an insole. The identification accuracy of the proposed model when utilizing multi-modal sensing is over 99%.

Description: Rising adult asthma prevalence (AAP) rates and asthma emergency room (AER) visits constitute a large burden on public health in Utah (UT), a high-altitude state in the Great Basin Desert, USA. This warrants an investigation of the characteristics of the counties with the highest asthma burden within UT to improve allocation of health resources and for planning. The relations between several predictor environmental, health behavior and socio-economic variables and two health outcome variables, AAP and AER visits, were investigated for UT’s 29 counties. Non-parametric statistical comparison tests, correlation and linear regression analysis were used to determine the factors significantly associated with AER visits and AAP. Regression kriging with Utah small area data (USAD) as well as socio-economic and pollution data enabled local Moran’s I cluster analysis and the investigation of moving correlations between health outcomes and risk factors. Results showed the importance of desert/mining dust and socio-economic status as AAP and AER visits were greatest in the south of the state, highlighting a marked north–south divide in terms of these factors within the state. USAD investigations also showed marked differences in pollution and socio-economic status associated with AAP within the most populous northern counties. Policies and interventions need to address socio-economic inequalities within counties and between the north and south of the state. Fine (PM2.5) and coarse (PM10) particulate matter monitors should be installed in towns in central and southern UT to monitor air quality as these are sparse, but in the summer, air quality can be worse here. Further research into spatiotemporal variation in air quality within UT is needed to inform public health interventions such as expanding clean fuel programs and targeted land-use policies. Efforts are also needed to examine barriers to routine asthma care.

Description: With the Internet of Things (IoT), the number of monitoring applications deployed is considerably increasing, whatever the field considered: smart city, smart agriculture, environment monitoring, air pollution monitoring, to name a few. The LoRaWAN (Long Range Wide Area Network)architecture with its long range communication, its robustness to interference and its reduced energy consumption is an excellent candidate to support such applications. However, if the number of end devices is high, the reliability of LoRaWAN, measured by the Packet Delivery Ratio (PDR), becomes unacceptable due to an excessive number of collisions. In this paper, we propose two different families of solutions ensuring collision-free transmissions. The first family is TDMA (Time-Division Multiple Access)-based. All clusters transmit in sequence and up to six end devices with different spreading factors belonging to the same cluster are allowed to transmit in parallel. The second family is FDMA (Frequency Divsion Multiple Access)-based. All clusters transmit in parallel, each cluster on its own frequency. Within each cluster, all end devices transmit in sequence. Their performance are compared in terms of PDR, energy consumption by end device and maximum number of end devices supported. Simulation results corroborate the theoretical results and show the high efficiency of the solutions proposed.

Description: Federated learning (FL) is a privacy-preserving technique for training a vast amount of decentralized data and making inferences on mobile devices. As a typical language modeling problem, mobile keyboard prediction aims at suggesting a probable next word or phrase and facilitating the human-machine interaction in a virtual keyboard of the smartphone or laptop. Mobile keyboard prediction with FL hopes to satisfy the growing demand that high-level data privacy be preserved in artificial intelligence applications even with the distributed models training. However, there are two major problems in the federated optimization for the prediction: (1) aggregating model parameters on the server-side and (2) reducing communication costs caused by model weights collection. To address the above issues, traditional FL methods simply use averaging aggregation or ignore communication costs. We propose a novel Federated Mediation (FedMed) framework with the adaptive aggregation, mediation incentive scheme, and topK strategy to address the model aggregation and communication costs. The performance is evaluated in terms of perplexity and communication rounds. Experiments are conducted on three datasets (i.e., Penn Treebank, WikiText-2, and Yelp) and the results demonstrate that our FedMed framework achieves robust performance and outperforms baseline approaches.

Description: Local governments and Health Boards are seeking to develop integrated services to promote well-being. Social participation and physical activity are key in promoting well-being for older people. The Health Precinct is a community hub in North Wales that people with chronic conditions are referred to through social prescribing. To improve community-based assets there is a need to understand and evidence the social value they generate. Data collection took place October 2017–September 2019. Social Return on Investment (SROI) analysis was used to evaluate the Health Precinct. Stakeholders included participants aged 55+, participants’ families, staff, the National Health Service and local government. Participants’ health and well-being data were collected upon referral and four months later using the EQ-5D-5L, Campaign to End Loneliness Scale and the Rosenberg Self-Esteem Scale. Family members completed questionnaires at four months. Baseline data were collected for 159 participants. Follow-up data were available for 66 participants and 38 family members. The value of inputs was £55,389 (attendance fees, staffing, equipment, overheads), and the value of resulting benefits was £281,010; leading to a base case SROI ratio of £5.07 of social value generated for every £1 invested. Sensitivity analysis yielded estimates of between 2.60:1 and 5.16:1.

Description: We present analyses of Global Navigation Satellite System (GNSS) carrier phase observations in multiple kinematic scenarios for different receiver types. Multi-GNSS observations are recorded on high sensitivity and geodetic-grade receivers operating on a moving zero-baseline by conducting terrestrial urban and aerial flight experiments. The captured data is post-processed; carrier phase residuals are computed using the double difference (DD) concept. The estimated noise levels of carrier phases are analysed with respect to different parameters. We find DD noise levels for L1 carrier phase observations in the range of 1.4–2 mm (GPS, Global Positioning System), 2.8–4.6 mm (GLONASS, Global Navigation Satellite System), and 1.5–1.7 mm (Galileo) for geodetic receiver pairs. The noise level for high sensitivity receivers is at least higher by a factor of 2. For satellites elevating above 30 ∘ , the dominant noise process is white phase noise. For the flight experiment, the elevation dependency of the noise is well described by the exponential model, while for the terrestrial urban experiment, multipath and diffraction effects overlay; hence no elevation dependency is found. For both experiments, a carrier-to-noise density ratio (C/N 0 ) dependency for carrier phase DDs of GPS and Galileo is clearly visible with geodetic-grade receivers. In addition, C/N 0 dependency is also visible for carrier phase DDs of GLONASS with geodetic-grade receivers for the terrestrial urban experiment.

Description: Hemoglobinopathies represent the most common single-gene defects in the world and pose a major public health problem, particularly in tropical countries, where they occur with high frequency. Diagnosing hemoglobinopathies can sometimes be difficult due to the coexistence of different causes of anemia, such as thalassemia and iron deficiency, and blood transfusions, among other factors, and requires expensive and complex molecular tests. This work explores the possibility of using spectral confocal microscopy as a diagnostic tool for thalassemia in pediatric patients, a disease caused by mutations in the globin genes that result in changes of the globin chains that form hemoglobin—in pediatric patients. Red blood cells (RBCs) from patients with different syndromes of alpha-thalassemia and iron deficiency (including anemia) as well as healthy (control) subjects were analyzed under a Leica TCS SP8 confocal microscope following different image acquisition protocols. We found that diseased RBCs exhibited autofluorescence when excited at 405 nm and their emission was collected in the spectral range from 425 nm to 790 nm. Three experimental descriptors calculated from the mean emission intensities at 502 nm, 579 nm, 628 nm, and 649 nm allowed us to discriminate between diseased and healthy cells. According to the results obtained, spectral confocal microscopy could serve as a tool in the diagnosis of thalassemia.

Description: Paddy mesocosms comprising of rice (Oryza sativa), snail (Pomacea canaliculata), and worm (Tubifex tubifex) were used to assess the damage caused by two acids (HNO3 and H2SO4) at predicted no-effect concentration (PNEC) and hazardous concentration for 50% of species (HC50) levels. In the fourth week, the fresh weight and shoot height of O. sativa at H2SO4-HC50 were reduced by 83.2% and 30.3%, respectively. Wilted leaves (%) at HC50 were approximately twice that at PNEC. No P. canaliculata and T. tubifex were recovered at HC50. At H2SO4-PNEC, the length and weight of P. canaliculata were reduced by 7.4% and 25.9%, respectively, whereas fewer adult (46.5%) and juvenile (84%) T. tubifex were recovered. In the 20th week, rice growth and productivity were correlated with initial pH (pHi) and nitrogen levels. Poor correlation with chlorophyll at the active tillering stage suggests the disturbance of nutrient uptake by roots. Partial least squares path modeling (PLS-PM) results further supported that the pHi directly affects grain yield and quality, as well as plant growth. The indirect effect via intervening fourth-week-variables was also substantial. Therefore, it is important to measure initial pH upon acid spill to estimate the risk to the paddy ecosystem. Information on the change in soil properties associated with acidity will also aid in predicting the yield and quality of grain to be harvested.

Description: This study examines how an occupational commitment and a fun work environment serve as important mechanisms that influence the job demands–turnover intentions relationship. On the basis of the job demands–resources model, the study explored the relationship between job demands, occupational commitment, fun at work, and turnover intention. The hypotheses were (1) that job demands would be positively associated with predicted turnover intention; (2) that occupational commitment would mediate the job demands–turnover intention link and (3) that a fun environment would moderate the relationship between job demands and occupational commitment and between job demands and turnover intention. The study sampled 294 seafarers using an online survey, and applied descriptive, correlative analysis and the PROCESS Macro to test the hypotheses. Findings provide preliminary support for the three hypotheses, and contribute to a better understanding of the mechanism determining seafarers’ turnover intention. The results suggest the importance of holding appropriate group activities on-board to help seafarers alleviate fatigue and stress.

Description: Collaborative representation (CR)-based classification has been successfully applied to plant disease recognition in cases with sufficient training samples of each disease. However, collecting enough training samples is usually time consuming and labor-intensive. Moreover, influenced by the non-ideal measurement environment, samples may be corrupted by variables introduced by bad illumination and occlusions of adjacent leaves. Consequently, an extended collaborative representation (ECR)-based classification model is presented in this paper. Then, it is applied to cucumber leaf disease recognition, which constructs a pure spectral library consisting of several representative samples for each disease and designs a universal variation spectral library that deals with linear variables superimposed on samples. Thus, each query sample is encoded as a linear combination of atoms from these two spectral libraries and disease identity is determined by the disease of minimal reconstruction residuals. Experiments are conducted on spectral curves extracted from normal leaves and the disease lesions of leaves infected with cucumber anthracnose and brown spot. The diagnostic accuracy is higher than 94.7% and the average online diagnosis time is short, about 1 to 1.3 ms. The results indicate that the ECR-based classification model is feasible in the fast and accurate diagnosis of cucumber leaf diseases.

Description: Photoacoustic imaging (PAI) combines optical contrast with ultrasound spatial resolution and can be obtained up to a depth of a few centimeters. Hand-held PAI systems using linear array usually operate in reflection mode using a dark-field illumination scheme, where the optical fiber output is attached to both sides of the elevation plane (short-axis) of the transducer. More recently, bright-field strategies where the optical illumination is coaxial with acoustic detection have been proposed to overcome some limitations of the standard dark-field approach. In this paper, a novel multiangle long-axis lateral illumination is proposed. Monte Carlo simulations were conducted to evaluate light delivery for three different illumination schemes: bright-field, standard dark-field, and long-axis lateral illumination. Long-axis lateral illumination showed remarkable improvement in light delivery for targets with a width smaller than the transducer lateral dimension. A prototype was developed to experimentally demonstrate the feasibility of the proposed approach. In this device, the fiber bundle terminal ends are attached to both sides of the transducer’s long-axis and the illumination angle of each fiber bundle can be independently controlled. The final PA image is obtained by the coherent sum of subframes acquired using different angles. The prototype was experimentally evaluated by taking images from a phantom, a mouse abdomen, forearm, and index finger of a volunteer. The system provided light delivery enhancement taking advantage of the geometry of the target, achieving sufficient signal-to-noise ratio at clinically relevant depths.