We estimated the daily intakes of chlorpyrifos and cypermethrin via ingestion of indoor dust and outdoor soils using the Stochastic Human Exposure and Dose Simulation Model on a probabilistic approach for Taiwan’s homes. Variable information for the daily intake estimation, such as concentration, ingestion rate, body weight, was adopted from previous studies. Monte Carlo simulation was performed with 1,000,000 iterations to simulate a single daily intake, which was shown in terms of percentage of the Acceptable Daily Intake (ADI) of either insecticide. The daily intakes were minimal with a 99% probability; at 99.9th percentile, however, the total intakes leaped to 13.1% and 20.0% of the respective ADIs of chlorpyrifos and cypermethrin. The sensitivity analysis indicated that concentration was the most determinant variable. Compared to the data of daily intakes via dietary ingestion of vegetables derived from a previous study, the estimated intakes by this study were considerable at the highest percentile, which referred to insecticide residues few days after insecticide application. Consequently, the non-dietary ingestion exposure to either insecticide was negligible in most cases; nevertheless, for those with indoor insecticide applications, the daily intakes for young children could be of concern. Frequently home cleaning is recommended to reduce the exposure.

The study of precipitation amount at different time scales constitutes an important issue in climate research and risk assessment. When dealing with daily totals, a frequent but sometimes underestimated problem is at what time the observation day begins. The choice of different starting times may lead to incompatibility between stations and incorrect identification of extreme events. In this work, the problem of temporal misalignment between precipitation datasets characterized by different starting time of the observation day is analyzed. The most widely used adjustment methods (1day and uniform shift) and two methods based on reanalysis (NOAA and ERA5) are evaluated in terms of temporal alignment, precipitation statistics and percentile distributions. As test series, the precipitation amount collected from 9 a.m. local time (09 LT) on the previous day to 09 LT on the target day (9-9 datasets) of the Padua and nearby stations in the period 1993-2022 have been selected. Results show that the reanalysis-based methods, in particular ERA5, outperform the others in temporal alignment, regardless the station. But, for the periods in which reanalysis data are not available, “1day” method, which shifts the daily amount back one calendar day, and “unif” method, which distributes uniformly the daily total from a 2-day moving window surrounding the target date, can be considered valid alternatives. On the other side, concerning the precipitation statistics, the reanalysis-based methods are not the best option, as they increase the precipitation frequency and reduce the mean value over wet days, NOAA much more than ERA5. Nevertheless, the uniform method provides a larger deviation from the original daily series. The use of the series of a station nearby the target one, which is mandatory in case of missing data, gives similar or better results than applying any adjustment method to the 9-9 series. General conclusions can hardly be drawn as they depend on the method and station. For the Padua dataset, the analysis was repeated at monthly and seasonal resolution. In general, the adjustment series show the most relevant changes in the precipitation statistics in summer and less temporal alignment with the original series in summer and autumn, the two seasons mainly affected by heavy rains in Padua. Finally, the percentiles distribution, analyzed for all the methods and stations, indicates that any adjustment method underestimates the percentile values, except ERA5. Only Legnaro, the station most correlated with Padua, gives results like ERA5.

By using the Black-Derman-Toy (BDT) model, we predict the future trend of the riskless rate, and then we build an equation that relates the market price of zero-coupon bonds and the theoretical price of zero-coupon bonds calculated using a binomial option pricing model. Based on this, we can find the implied daily return μ, implied natural upturn probability p, and implied daily volatility σ with respect to different time-to-maturity values of zero-coupon bonds. With these results, we can give some suggestions to bond traders.

The aim of this study was to examine usual daily micronutrient intake of Chinese children based on data from the 2011 China Health and Nutrition Survey. We analyzed data from 4 to 17-year-old participants, who provided dietary data on 3 consecutive days combined with the household weighing method in 2011. Usual daily intake of each nutrient was estimated using a mixed effects model based on the China Food Composition published in 2002 and 2004. The means, medians and percent below Estimated Average Requirements (EAR) were reported for selected micronutrients, including calcium, sodium, potassium, iron, zinc, selenium, vitamin A, thiamine, riboflavin and vitamin C. For sodium and potassium, means and the distribution of intakes were compared to the Adequate Intake (AI) level. The average usual daily intakes of all micronutrients increase with age and the intakes of boys higher than girls in the same age group. The average of calcium intakes increased from 272mg/d in 4-6y to 391mg/d in 14-17y, but the percentage of inadequate calcium intake remained very high (>96%). The prevalence of inadequacy of calcium was the highest among the mineral nutrients reported in this study. As the requirement of micronutrient increased with age, the percentage of subjects with inadequate intake increased in 11-17 age groups. Among the 14-17y, the percentages of study participants with dietary intakes of calcium, iron, zinc, selenium, vitamin A, thiamine, riboflavin and vitamin C below the EAR were 96.8%, 18.8%, 37.6%, 72.8%, 36.8%, 91.8%. 85.9% and 75.5%, respectively. Among the 11-13y, the percentages of study participants with dietary intakes of iron, zinc and vitamin A below the EAR were 23.5%, 41.5%, and 41.6%, respectively. Thus, the micronutrients deficiency is a problem in Chinese Children. Nutrition education and intervention programs are needed to address the nutritional gaps.

Background: Antimicrobial consumption data in Latin America is scarce and usually spread out within different sources for AMC calculations, making it difficult to both standardize and compare regions through similar time frames. The main objective was to analyze antimicrobial consumption trends in Social Security tertiary care hospitals in Costa Rica in the period spanning January 2017 to December 2021, using both defined daily doses (DDD)/100 bed days and DDD/100 discharges. Methods: Retrospective observational study of antimicrobial consumption. Global consumption trends were calculated and expressed in DDD/100 bed days and DDD/100 discharges. Trends in antimicrobial consumption were analyzed using a simple linear regression model to determine potential differences in antimicrobial usage throughout the study’s duration. Results: A statistically significant increase in the consumption expressed in DDD/100 discharges was observed in the following groups: carbapenems: 35.62% (p<0.0001), trimethoprim-sulfamethoxazole: 62.50% (p<0.0001), echinocandins: 20.73% (p=0.01) and azole antifungals: 61.58% (p<0.0001). Additionally, a statistically significant increase of 40.43% in the consumption of azole antifungals expressed in DDD/100 bed days was observed (p=0.0008). In contrast, a statistically significant decrease in consumption expressed in DDD/100 discharges was identified for cephalosporins -21.97% (p<0.0001) and macrolides -51.67% (p<0.0001). Conclusions: This five-year analysis demonstrated trends over time in overall antimicrobial consumption measured in DDD/100 bed days do not correlate with trends in DDD/100 discharge rates. Continually, the comparison between DDD/100 bed days and DDD/100 discharges allows for complementary comparisons to be made regarding antimicrobial exposure in a clinical setting.

Patients with schizophrenia had higher mortality risks and the role of antipsychotic medications remained inconclusive. In an aging society, elderly schizophrenia patients warrant increased attention. In this study, we aimed to explore medication dosage associations with mortality in schizophrenia patients, using Taiwan's national healthcare database from 2010 to 2014, with 102,964 patients with schizophrenia, and a subgroup of 6,433 elderly patients, compared to an age- and gender-matched control group. The findings revealed that schizophrenia patients with no antipsychotic exposure had the highest mortality risk as compared to the control sample—with a 3.61 and 3.37-fold risk for overall and cardiovascular mortality respectively in age and gender-adjusted model, followed by high, low, and moderate exposure groups. A similar pattern was observed in elderly schizophrenia patients but high exposure to antipsychotics was associated with the highest risk in both overall and cardiovascular mortality in elderly patients, with a 3.01, and 2.95-fold risk), respectively. In conclusion, the use of antipsychotics is beneficial to patients with schizophrenia, with recommended exposure levels being low to moderate. In elderly patients, high antipsychotic exposure was associated with the highest mortality risk. We should pay more attention to antipsychotic dosage in elderly schizophrenia patients.

This study explores the relationship between mental and physical therapeutic through three dimensions: man-environment relationships; a sense of place and symbolic landscapes. The study used a combination of qualitative and quantitative research methods. Local residents living in the coastal area of Xinglin Bay are the research objects. Quantitative data analysis revealed that the frequency of residents' visits was an important variable affecting their physical and treatment perceptions. In addition, the significance is higher for females than for males. The text analysis shows that the environment, especially the ecological restoration of water quality and migratory birds, is of great significance to the identity of local residents. Daily activities contribute to a sense of place and are what make the coast a place of therapeutic landscape function.

(1)Background：To date, no studies have epidemiologically examined whether the concentration of particulate matter (PM) 2.5 and its ionic components is related to the prevalence of skin symptoms. Therefore, this study aimed to clarify this association in patients with allergic diseases. (2)Methods: From February 1 to May 31, 2020, we evaluated the daily prevalence of skin symptoms in outpatients with allergic diseases being treated at Fukuoka Hospital, Fukuoka, Japan, and measured the concentration of PM2.5 and its ionic components. （3）Results: Univariate analysis showed a statistically significant association between skin symptoms and the concentration of PM2.5 and the ionic components SO42-, NH4+, K+, and Mg2+, and multivariate analysis showed a statistically significant association between the daily prevalence of skin symptoms and the concentration of the ionic components SO42- or Mg2+. (4)Conclusions: Our findings indicate that the concentration of some PM2.5 ionic components may affect skin symptoms in patients with allergic diseases.

: Background: The aim of this study was to evaluate Phenylketonuria (PKU) patients’ oral health habits and the efficiency of tailored recommendations for PKU patients in Latvia on the correct management of oral hygiene. The-free amino acid formula can negatively impact PKU patient’s oral health as it contains a high amount of complex carbohydrates. Materials and methods: In this study with a one-month interval pre and post implementation of oral hygiene recommendations, two questionnaires regarding oral hygiene habits and knowledge were prepared and provided by trained medical personnel to be filled in for all diagnosed PKU patients in Latvia who were not lost to follow-up. Results: Based on the questionnaires among the PKU patients under 18 years of age, 27% cleaned their teeth once a day. However, 6% of patients did not engage in regular teeth brushing at all. Among PKU patients over and 18 years of age, 26% brushed their teeth only once a day. Additionally, a mere 39% of PKU patients ≥18 years of age and 17% < 18 years of age incorporated flossing into their oral hygiene routine. In total, 45% of PKU patients ≥18 years of age and 44% < 18 years of age visited a dentist once a year, but 40% ≥18 years of age and 39% <18 years of age visited a dentist less often than once per year. After reading the recommendations, a remarkable number of PKU patients < 18 years of age had improved their daily oral hygiene routine, including toothbrushing (25%) and flossing (23%). Conclusion: Given the unique dietary requirements and the implementation of these daily at-home oral health practices, motivation and regular reminders should result in better oral health of PKU patients and cooperation with clinicians.

Meteorological observations over the last four decades are of paramount importance to investigate the ongoing climate change. The assessment of the reliability of any climatic time series is thus mandatory to draw correct conclusions. This evaluation involves homogeneity tests to detect artificial discontinuities whose identification is facilitated by metadata availability. In this work, daily minimum and maximum temperature measurements collected in Padua, Italy, between 1980 and 2022, are examined. Hourly observations began in 1993 and since the aim is to study long term behavior of the temperature, the focus is on daily averages and extremes. Over this period, the weather station of Padua center underwent many changes, in location or instrument; therefore, some tests have been used to identify and remove the effects of these variations and obtain a homogeneous time series. The homogeneity tests applied must be able to identify change-points both in the middle and at the extremes of the series. Some well-known absolute tests have been applied to investigate shift in the mean value: Standard Normal Homogeneity test (SNH), Buishand U and range tests, Pettitt test, F-test, STARS. Some relative tests have been applied too, which are generally more reliable than absolute tests, because they consider the information from neighboring stations. As relative tests rely on the homogeneity and quality of the reference series, several nearby stations and two reanalysis datasets (ERA5 and MERIDA) have been considered, to enhance the picture of the local situation and provide more robust conclusions. The applied tests identify change-points in the years in which a change in instrument or location of the station have occurred, confirming that these changes have compromised the homogeneity of the series. The sub-series obtained splitting the observations in correspondence of these change-points have been homogenized with respect a selected period; corrections must be applied also to future measurements to extend the time series properly.

To monitor adherence to diets and to design and evaluate nutritional interventions it is essential to obtain objective knowledge about eating behavior. In most research, measures of eating behavior are based on self-reporting, such as 24-h recalls, food records (food diaries), and food frequency questionnaires. Self-reporting is prone to inaccuracies due to inaccurate and subjective recall and other biases. Recording behavior using non-obtrusive technology in daily life would overcome this. We here provide an up-to-date systematic overview encompassing all (close-to) publicly or commercially available technologies to automatically record eating behavior in real-life settings. 1328 studies were screened and after applying defined inclusion and exclusion criteria, 122 studies were included for in-depth evaluation. Technologies in these studies were categorized by what type of eating behavior they measure and which type of sensor technology they use. In general, we found that relatively simple sensors are often used. Depending on the purpose, these are mainly motion sensors, microphones, weight sensors, and photo cameras. While several of these technologies are commercially available, there is still a lack of publicly available algorithms that are needed to process and interpret the resulting data. We argue that future work should focus on developing robust algorithms and validating these technologies in real-life settings. Combining technologies (e.g., prompting individuals for self-reports at sensed, opportune moments) is a promising route toward ecologically valid studies of eating behavior.

Objective: The objective of the present study was to evaluate the activities of daily living using the Barthel Index, before and after the infection by SARS-COV-2 and to see if the results vary according to sex. Methods: The activities of daily living of 68 cohabiting geriatric patients, 34 men and 34 women, in 2 nursing homes were measured before and after SARS-COV-2 infection using the Barthel index. Results: The Covid 19 infection affects the performance of daily life activities in institutionalized elderly in nursing homes, and it does so especially the older the subject, regardless of sex. Conclusions: The Covid 19 pandemic, in addition to having claimed some victims, especially in the elderly population, has reduced the ability of these people to carry out their activities of daily life, considerably worsening their quality of life despite have been able to overcome the disease.

Power Electronic development determines introduction of nonlinear devices in Electric Power Systems. Introduction of nonlinear devices increase current harmonics in Transmission and Distribution Power Systems. Distribution transformers and feeders increase power losses and their nominal parameters are reduced. Present work introduces a procedure to evaluate maximum permissible load in single phase distribution transformers with massive introduction of a new type of nonlinear load which changes daily demand graphs.

Introduction Our aim was to determine the impact of antimicrobial stewardship tools (AST) and COVID-19 pandemic on antibiotic consumption (AC). Methods We used the national software Consores to determine AC in DDD / 1000 days of hospitalization from 2017 to 2022 in voluntary private hospitals in France. The AST considered were 1/ internal guidelines 2/ list of antibiotics with restricted access 3/ presence of an antibiotic referent or 4/ an ID specialist 5/ proof of annual meeting on antimicrobial resistance. Institutions with dedicated units for COVID-19 patients were specified. Results In 30 institutions total AC varied from (means) 390 to 405 DDD/1000 DH from 2017 to 2022. Fluoroquinolones and amoxicillin / clavulanate consumption decreased from 50 to 36 (p = 0.003) and from 112 to 77 (p = 0.025) respectively, but consumption of piperacillin / tazobactam increased from 9 to 21 (p < 0.001). Over the study period, 10 institutions with ≤ 2 AST had lower AC compared to 20 institutions with ≥ 3 AST (p < 0.01). COVID-19 units opened in 10 institutions were associated with a trend toward higher macrolide consumption from 15 to 25 from 2017 to 2020 (p = 0.065) and with an acceleration of piperacillin / tazobactam consumption from 2020 to 2022 (p ≤ 0.003). Conclusion Antibiotic consumption in 30 private hospitals in France was inversely related to the number of AST. The COVID-19 pandemic was associated with limited impact on AC but special attention should be paid on piperacillin / tazobactam consumption.

Background: Health management is gaining importance as a business resource to enhance employee well-being. The rise of remote work during COVID-19 impacted lifestyle habits. This study explores the impact of tele-exercise intervention on remote workers' lifestyle habits, aiming to improve health and productivity. Methods: This study divided into remote (G1) and face-to-face (G2) groups. Over three months, G1 followed a 30-minute weekly exercise program. Measurements and questionnaires were collected at three time points covering areas like presenteeism, weight, sleep, stress, job satisfaction, and happiness. Data underwent Two-way repeated measures ANOVA, Autocorrelation, Correlation Analysis, and Correspondence Analysis to assess differences and relationships between G1 and G2. Results: ANOVA showed that a significant difference was observed in Daily Stress (DS) between G1 and G2, with G1 exhibiting higher DS. Autocorrelation Analyses showed for G1 that strong relationships each of BMI, Presenteeism (PST), Daily Stress (DS), Stress Relief (SR), Sleep Quality (SQ), Purpose of Work (PW), and Satisfaction of Life (SL) in the time frame. Correlation Analysis showed for G1 that the pairs of PRS and SQ, and DS and SL had strong positive relationships, and the pairs of BMI and PRS, and BMI and SQ had strong negative relationships. Autocorrelation Analyses showed for G2 that strong relationships each of SR, Stress due to Remote Work (SRW), ST, SQ, and PW in the time frame. Correspondence Analysis showed that that G1 was encompassed in a job and life satisfaction area, and G2 was encompassed in a sleep and stress for weight control area.

Instrumental activities of daily living (IADL) training is critical in clinical practice of occupational therapy (OT) for stroke patients. In the conventional approaches, the therapists simulate various occupational tasks in their healthcare settings or reach their nearby real circumstances for the training. As an alternative technology, immersive virtual reality (IVR) has been used widely in stroke rehabilitation for years; however, limited research has compared occupational performances between virtual and real environments. Our team has established a novel IVR shopping training system for stroke rehabilitation. We recruited 10 stroke patients from our department to test the system. All patients attempted to implement shopping tasks in the virtual and real environments respectively. The Wilcoxon test showed no significant differences between virtual and real environments in memory capacity and time-consuming for implementing tasks, and memory capacities in virtual and real environments presented excellent correlations with the IADL assessment. This study suggests that IVR shopping tasks can be used as an alternative approach in rehabilitation when there is limited resource for implementing shopping training in a real environment, while the psychometric property, clinical effect and the effect transferred to the real environment induced by virtual training require further study.

Bovine respiratory disease is still a major concern in feedlots and has major economic impact. Another consequence of respiratory infections is the use of antimicrobial molecules to control bacterial pathogens. This can participate to the emergence and shedding of antimicrobial re-sistance that can threaten animal as well as human health. Appeasing pheromones with their capacity to reduce stress and thus their ability to preserve the functions of the immune system have been proposed to reduce the use of antimicrobial substances. In the current report we as-sessed the effect of appeasing pheromone administration on bovine health and performance during the fattening period. Zootechnical and health parameters as well as whole blood immune transcript expressions were measured over weeks in young bulls to determine the effect of the pheromone. We observed a reduction of clinical signs at day 30 in young bulls who received the pheromone and a higher expression of interleukin 8 transcripts in this group than in the control group. Our results are in line with previous reports in bovine and other mammals and ask for further studies to shed more light on the beneficial impact of appeasing pheromones and to de-cipher their exact mechanisms of action.

This paper serves a survey and empirical evaluation of the state-of-the-art in activity recognition methods using accelerometers. We examine research that has focused on the selection of activities, the features that are extracted from the accelerometer data, the segmentation of the time-series data, the locations of accelerometers, the selection and configuration trade-offs, the test/retest reliability, and the generalisation performance. Furthermore, we study these questions from an experimental platform and show, somewhat surprisingly, that many disparate experimental configurations yield comparable predictive performance on testing data. Our understanding of these results is that the experimental setup directly and indirectly defines a pathway for context to be delivered to the classifier, and that, in some settings, certain configurations are more optimal than alternatives. We conclude by identifying how the main results of this work can be used in practice, specifically in experimental configurations in challenging experimental conditions.

Electrification coverage in Sarawak is the lowest at 78.74%, compared to Peninsular Malaysia at 99.62% and Sabah at 82.51%. Kapit, Sarawak with its 88.4% populations located in rural areas and mostly situated along the main riverbanks has great potential to generate electrical energy by hydrokinetic system. Yearly water velocity data is the most significant parameter to perform hydrokinetic analysis study. Nevertheless, the data retrieved from local river databases are inadequate for river energy analysis, thus hindering its progression. Instead, flow rates and rainfall data had been utilised to estimate the water velocity data. This signifies no estimation of water velocity in an unregulated river by using water level data had been made. Therefore, a novel technique of estimating the daily average water velocity data in unregulated rivers is proposed. The modelling of regression equation for water velocity estimation was performed and two regression model equations were generated to estimate both water level and water velocity on-site and proven to be valid as the coefficient of determination values had been R² = 87.4% and R²=87.9%, respectively. The combination of both regression model equations can be used to estimate long-term time series water velocity data for type-C unregulated river in remote areas.

With an aging population, the prevalence of geriatric diseases is increasing, especially among older individuals who live alone. This study investigates the potential of using TV viewing patterns to detect these diseases by analyzing variables such as daily average viewing time, peak viewing hours, and channel-switching behaviors. Significant correlations between TV viewing patterns and early indicators of geriatric diseases (depression, activities of daily living (ADL) performance, and cognitive function) were found. The correlations between the Korean form of the Geriatric Depression Scale (KGDS) and daily average viewing time and excessive channel switching were 0.320 and 0.308, respectively. The Korean version of the Modified Barthel Index (KMBI) showed correlations of -0.313 with daily average viewing time and -0.352 with excessive channel switching. Participants were divided into groups based on scores, and significant differences in peak viewing hours were observed among the different groups. The Korean version of the Mini-Mental State Examination (MMSE-K) groups showed significant differences at 3, 4, and 5 PM. The KGDS and KMBI groups showed significant differences at 8 PM and midnight and 1 AM and 2 AM, respectively. These findings suggest that TV viewing patterns can serve as effective early diagnostic indicators for geriatric diseases.

Background: Depressive symptoms are a serious public health problem that are associated with BADL and IADL disabilities in Chinese adults.Objective: The limitation of activities of daily living (ADL) affects the mental health of older adults. We distinguished activities of daily living into basic activities of daily living (BADL) and instrumental activities of daily living (IADL) to explore the relationship between these two limitations and depressive symptoms among older Chinese adults using nationally representative cross-sectional data. In addition, this study explored the relationships between BADL, IADL and depression risk in elderly people at the individual and provincial levels and in rural and urban subgroups.Methods: The China Health and Retirement Longitudinal Study(CHARLS) survey used a multistage probability‒proportional‒to-size (PPS) sampling technique. Province-level socioeconomic characteristics were merged with microdata for respondents over 60 years of age from the 2020 China Health and Retirement Longitudinal Study (CHARLS 2020) Wave 5 (n=10,036) by the author. The respondents were asked whether their BADL and IADL were limited . The risk of depression was assessed using the 10-item Center for Epidemiological Studies Depression Scale(CES-D 10). The chi-squared test was used to explore whether having a disability that limits BADL and IADL were associated with mental health status. A binary logistic regression model was used to evaluate this association further after controlling for confounding factors.Results: Overall, 27.5% (2759/10036) and 25.7% (2776/10036) of the participants over 60 years of age were limited in their BADL and IADL, respectively. Regression analyses revealed that older adults whose BADL were not limited (OR=1.942, 95% CI: 1.638–2.303, P < .001) and whose IADL were not limited (OR=1.775, 95% CI: 1.485–2.122, P < .001) had a lower risk of depression than older adults whose BADL and IADL were limited. In addition, older adults who were female (P <.001), were 60-69 years (P < .005), had a partner (P <0.001), were literate (P <.001), lived in a rural area (P <.001), had a retirement pension (P <.001), had 3 or more children (P < .001), did not have any chronic diseases (P < .001), had a fair SRH score (P < .001), drank alcohol (P < .001), exercised (P < .005), did not participate in social activities (P < .001), or had an above average per capita household consumption (P < .001) lived in provinces with the first quartile of GDP per capita (P < .001) and lived in provinces with the second quartile of the number of beds in medical institutions per 10,000 persons (P < .001) were more likely to experience depressive symptoms, while smoking had no effect. In a binary logistic regression, older adults who were single (OR=0.669, 95% CI=0.551, 0.812), illiterate (OR=0.646, 95% CI=0.504, 0.828), living in rural areas (OR=1.485, 95% CI=1.270, 1.735), without retirement pensions (OR=0.671, 95% CI=0.582, 0.819) and with very bad SRH scores (OR=0.411, 95% CI=0.311, 0.544) had a greater risk of depressive symptoms. In the binary logistic regression analysis of the urban and rural subgroups separately, the results indicated that old people whose BADL or IADL were not limited were associated with a risk of depression, especially rural (P < .001) and urban (P < .001) participants.Conclusions: The present study provides evidence of an association between BADL, IADL and depression in older Chinese adults. This study revealed that individuals with limited BADL and limited IADL were predominantly depressed older adults. Binary logistic regression models suggested that disabilities limiting BADL and IADL were more likely to be associated with depressive symptoms in rural Chinese older adults. Older adults should be encouraged to participate in moderate physical and social activities to prevent physical dysfunction. The government and social work organisations should pay attention to the mental health of older adults in rural areas.

The developments of confirmed daily Sars-CoV-2 infections can be modeled a posteriori in a comparatively simple and satisfactory way by means of a special exponential function: its exponential coefficient varies exponentially with time itself. This property enables the function to directly simulate the „daily case“ curve fragments observed for the first waves of the current epidemics in a number of counties and countries. Linear combinations of two or more of the functions allow for the modeling of the complete curves observed in the vast majority of all regions for which case number developments have been tabulated.

As the number of older adults with dementia increases, early diagnosis and intervention are crucially important. The purpose of this study was to conduct dementia screening on older adults to determine whether there are differences in daily activities of living, depression, loneliness, social support, and life satisfaction between older adults at high-risk for dementia compared with low-risk older adults. We hypothesized a negative relationship between high-risk older adults and these factors. This study also hypothesized a moderating effect for social support on the relationship between daily living activities and life satisfaction. This study used a cross-sectional design with survey data. Participants were recruited at 15 public community health centers in South Korea. A total of 609 older adults (male 208, female 401) living in the community were screened for early dementia, and 113 participants (18.9 %) were assigned to the high-risk group. As hypothesized, participants in the high-risk group showed significantly more negative results ​​in terms of activities of daily living, depression, loneliness, social support, and life satisfaction compared with participants in the low-risk group. The findings of this study provide a theoretical basis for the importance of early screening for dementia and policies for effective dementia prevention.

Understanding potential uptake and biodistribution of engineered nanoparticles in soil-grown plants is imperative for toxicity and risk assessment considering the oral exposure of edibles by humans. Herein, we assessed potential influence of particle size (25, 50, and 250 nm) and concentration (0, 50, 100, 200, and 500 mg/kg-soil) of Copper oxide nanoparticles (CuONPs) on: (1) the root system architecture, and the physicochemical attributes of soil at the soil-root interface, (2) leading to Cu transport and accumulation in root, stem, leaf and seed in soybean (Glycine max cv Kowsar) grown for entire lifecycle of 120 days, and compared with soluble Cu²⁺ ions and water-only controls, and (3) performed a comparative assessment of total seed Cu levels in soybean with other valuable food sources for Cu intake and discussed its human health implications. Our findings showed particle size- and concentration-dependent influence of CuONPs on Cu uptake and tissue distribution in root, stem, leaf and seed in soybean. Alterations in root architecture (root dry weight, root length, root volume, and root area) were dependent on the Cu compound type, Cu concentrations, and their interactions (p<0.05), except for root density. Concentration-response relationships for all three sized CuONPs, and Cu²⁺ ions, were linear. CuONPs and Cu²⁺ ions had inhibitory effects on root growth and development. Overall, soybean responses to smallest size CuONPs-25 nm were higher for all parameters investigated compared to two larger sized CuONPs (50 nm, 250 nm) or Cu²⁺ ions. Cu uptake/bioaccumulation differed among soybean tissues in the order: root > leaf > stem > seed. Despite reduced root architecture and seed yield, our smallest size CuONPs-25 nm led to increased total seed Cu uptake compared to the larger sized CuONPs and Cu²⁺ ions tested. Our findings also suggest that soil amendment by CuONPs, more so by the smallest size CuONPs-25 nm, could significantly improve nutritional Cu value in soybean seed as reflected by % Daily Values (DV), and are rated “Good” to “Very Good” according to the “World’s Healthiest Foods” rating. However, until the potential toxicity and risk from consumption of soybean seed is characterized in humans, caution should be exercised when the Cu fortified seeds are used for daily human consumption when addressing Cu deficiency and associated illnesses, globally.

Abstract: This study evaluates the effect of paravertebral spinal injection (PSI), utilizing both subjective and objective assessments in chronic low back pain (LBP) associated with facet joint arthrosis over a one-month duration. Subjective questionnaires included the Visual Analogue Scale (VAS) for pain, Oswestry Disability Index, Health Survey SF-12, and the short Falls Efficacy Scale International (FES-I). Objective assessments included in-clinic gait and timed-up-and-go (TUG) tests using wearable sensors, as well as 48-hour daily physical activity (DPA) monitored using a chest-worn tri-axial accelerometer. Subjective and objective measures were performed prior to treatment, immediately after the treatment, and one-month afterthe treatment. Eight LBP patients were recruited for this study (mean age = 54±13 years, body mass index = 31.41±6.52 kg/m2, 50% males). Results show significant decrease in pain (~55%, p<0.05) and disability (Oswestry scores, ~21%, p<0.05). In-clinic gait and TUG were also significantly improved (~16% and ~18% faster walking and shorter TUG, p<0.05); however, DPA (including percentage of physical activities (walking and standing) and the number of steps) showed no significant change after PSI (p>0.25; effect size≤0.44). We hypothesize that DPA may continue to be truncated by conditioned fear-avoidance, a psychological state that may prevent increase in daily physical activity to avoid pain.

Seventy-seven percent of Irish primary school children do not meet recommended physical activity (PA) guidelines [1]. The Daily Mile (TDM) is a primary school initiative designed to increase children’s PA output. This study evaluates TDM’s perceived effect on Irish primary school children’s health-related metrics. A mixed-methods study, comprising two data collection phases, used the RE-AIM framework to evaluate TDM [2]. Phase one involved teachers, principals and classroom assistants (n = 191) from TDM-registered schools completing a questionnaire. Two TDM-registered schools participated in phase two where, (i) interviews were conducted with each principal, (ii) a teacher sub-sample (n = 4) participated in a focus group and (iii) a child sub-sample (n = 14) participated in separate focus groups. TDM was perceived to positively impact markers of children’s health, including their PA behaviour, physical fitness and social wellbeing. Inclement weather (66.5%) and a lack of time (56.5%) were reported as the top-ranked implementation barriers. Moreover, TDM’s repetitive nature often left children feeling disinterested and resulted in some teachers modifying the initiative to maintain engagement levels. Maintaining the long-term implementation of TDM and its health benefits in primary schools may require bespoke amendments to the original format to preserve children’s engagement.

The concept of collecting data of people using a domestic space is not novel. However, the methods and processes used to decipher this raw data and transform it into useful and appropriate information (i.e., sequence, duration, and timing derived from domestic activities) have been challenging and the focus of many research groups. But how are the results of the decoded transposition received, interpreted and used by the various professionals (e.g., occupational therapists and architects) who consume the information? This paper describes the inclusive evaluation process undertaken, which involved architects, engineers and end-users (not the occupant, but the care team managing the occupant). Finally, our study evidence the importance of making accessible to a multidisciplinary audience spatial, temporal and sequential aspects derived from people's domestic routines. Shedding light on how a systematic approach to collecting, processing and mapping low-level sensor data into higher forms and representations can be a valuable source of knowledge for improving the domestic living experience.

Regeneration is crucial for forest continuity in natural and managed stands. Analyzing intra-annual dynamics improves the understanding between growth and climate, identifying survival thresholds. The objective was to determine microclimate constraints (rainfall, air and soil temperatures) over Nothofagus antarctica regeneration growing at closed, open, and edge forests in Patagonia. We measured stand characteristics (forest structure, understory, soil properties, animal use), microclimate, and daily growth of regeneration using dendrometers (n = 6) during two growing seasons. We found significant differences in the studied variables (e.g. overstory, light, soil, understory, animal use). These changes defined microclimate across overstory gradient (e.g. soil moisture), influencing the daily growth across seasons (lag, exponential, stationary). Rainfall influenced more than temperature. Daily growth in closed forests indicating shrinkage (-0.0082 mm day-1 without rain, and -0.0008 mm day-1 with 0.0-0.2 mm day-1 rainfall), while above 0.2 mm day-1 rainfall, growth always increased. Open forests presented shrinkage during days without rain (-0.0051 mm day-1), showing positive growths according rainfall. Edge forests always presented positive daily growths. The resilience of regeneration under these changed conditions was related with overstory. Main outputs indicated that regeneration was vulnerable during non-rainy days, suggesting the needs of long-term monitoring to develop better silvicultural proposals.

In March 2020 the World Health Organization declared the “pandemic state” due to COVID-19 imposing strict confinement of the world population. People were forced to spend more time at home, changing some daily routines, including social interactions, the possibility to perform sports, and diet habits. These changes could exert a greater impact on patients suffering from chronic diseases, such as endocrine patients. This study aimed to assess the effects of Covid-19 induced quarantine on daily habits in a group of patients with endocrine disorders, focusing on food consumption, eating, and sleep habits during the confinement. Eighty-five endocrine patients were enrolled. A structured interview was administered investigating: socio-demographic information, general medical conditions and habits adopted during the quarantine. All patients underwent the Spielberger State Anxiety Inventory (STAI-Y1) to assess state anxiety. Subjects had mainly a sedentary lifestyle. We found a significant increase in the number of cigarettes in smokers, an increase of meals consumed during the confinement and a high rate of sleep disorder occurrence, especially insomnia. The changes of daily habits were, probably, due to the alterations of routine, that determined more bore and inactivity during the day.

Introduction. Strontium-82/Rubidium-82 (⁸²Sr/⁸²Rb) generators are used widely for positron emission tomography (PET) imaging of myocardial perfusion. In this study, the ⁸²Rb isotope yield and production efficiency of two FDA-approved ⁸²Sr/⁸²Rb generators were compared.Methods. N=515 sequential daily quality assurance (QA) reports from 9 CardioGen-82® and 9 RUBY-FILL® generators were reviewed over a period of 2 years. A series of test elutions was performed at different flow-rates on the RUBY-FILL® system to determine an empirical correction-factor used to convert CardioGen-82® daily QA values of ⁸²Rb activity (dose-calibrator ‘maximum’ of 50 mL elution at 50 mL/min) to RUBY-FILL® equivalent values (integrated ‘total’ of 35 mL elution at 20 mL/min). The generator yield (⁸²Rb) and production efficiency (⁸²Rb yield / ⁸²Sr parent activity) were measured and compared after this conversion to a common scale. Results. At the start of clinical use, the system reported ⁸²Rb activity from daily QA was lower for CardioGen-82® vs RUBY-FILL® (2.3 ± 0.2 vs 3.0 ± 0.2 GBq, p<0.001) despite having similar ⁸²Sr activity. Dose-calibrator ‘maximum’ (CardioGen-82®) values were found to under-estimate the integrated ‘total’ (RUBY-FILL®) activity by ~24% at 50 mL/min. When these data were used to convert the CardioGen-82 values to a common measurement scale (integrated total activity) the CardioGen-82® efficiency remained slightly lower than the RUBY-FILL® system on average (88 ± 4% vs 95 ± 4%, p<0.001). The efficiency of ⁸²Rb production improved for both systems over the respective periods of clinical use.Conclusions. ⁸²Rb generator yield was significantly under-estimated using the CardioGen-82® vs RUBY-FILL® daily QA procedure. When generator yield was expressed as the integrated total activity for both systems, the estimated ⁸²Rb production efficiency of the CardioGen-82® system was ~7% lower than RUBY-FILL® over the full period of clinical use.

A rapid, precise, accurate and low cost method for the determination of vitamin E (α-tocopherol) in cereal products and biscuits was developed. The uncertainty was calculated for the first time and the methods were performed in different cereal products and biscuits, characterized as “superfoods”. The limits of detection and quantification were calculated. Accuracy and precision were estimated using the certified reference material FAPAS T10112QC and the determined values were in good accordance with the certified values. The health claims according to the daily reference values for vitamin E were calculated and the results proved that the majority of the samples examined showed %daily value higher than 15%.

In regions with limited precipitation information like Peru, many studies rely on precipitation data derived from satellite products (SPPs) and reanalysis products. These products provide near-real-time information and offer global spatial coverage, making them attractive for various applications. However, it is essential to consider their uncertainties when conducting hydrological simulations, especially in a key region like the Pacific drainage (Pd), where 56% of Peruvian population resides (including the capital Lima). This study evaluates the performance of three precipitation products: Reanalysis, ERA5-Land (top down approach), and two SPPs: GPM+SM2RAIN and SM2RAIN-ASCAT (bottom-up approaches). Hydrological modeling was conducted on 30 basins distributed across the Pd, which were grouped into five regions (I-V, ordered from south to north). The results showed that SM2RAIN-ASCAT performed well in regions I-III-IV, ERA5-Land in region II, and GPM+SM2RAIN in region V. The hydrological model GR4J was tested, and better efficiency criteria were obtained with SM2RAIN-ASCAT and GPM+SM2RAIN when comparing simulated versus observed streamflows. The hydrological modeling with SM2RAIN-ASCAT and GPM+SM2RAIN demonstrated satisfactory efficiency metrics (KGE > 0.75; NSE > 0.65). Additionally, ten hydrological signatures were quantified to assess the variability of simulated streamflows in each basin, with metrics such as Mean Flow (Q mean), 5th Quantile Flow (Q5), and 95th Quantile Flow (Q95) showing overall better performance. Finally, the results of this study demonstrate the reliability of using bottom-up satellite products in Pd basins.

Although Support Vector Machines (SVM) are widely used for classifying human motion patterns, their application in the automatic recognition of dynamic and static activities of daily life in the healthy older adults is limited. Using a body mounted wireless inertial measurement unit (IMU), this paper explores the use of SVM approach for classifying dynamic (walking) and static (sitting, standing and lying) activities of the older adults. Specifically, data formatting and feature extraction methods associated with IMU signals are discussed. To evaluate the performance of the SVM algorithm, the effects of two parameters involved in SVM algorithm—the soft margin constant C and the kernel function parameter $\mathsf{\gamma }$—are investigated. The changes associated with adding white-noise and pink-noise on these two parameters along with adding different sources of movement variations (i.e., localized muscle fatigue and mixed activities) are further discussed. The results indicate that the SVM algorithm is capable of keeping high overall accuracy by adjusting the two parameters for dynamic as well as static activities, and may be applied as a tool for automatically identifying dynamic and static activities of daily life in the older adults.

Water is an indispensable natural resource that is often prodigiously threatened by anthropomorphic activities. This study evaluated the physicochemical properties of water and selected heavy metals in edible muscles of a piscivorous fish (Protopterus annectens) from Nyabarongo and Nyabugogo rivers of Rwanda. Edibility health risk was evaluated using the target hazard quotient method. Water samples were taken in triplicate from Ruliba station and Kirinda bridge on Nyabarongo river and Giticyinyoni on Nyabugogo river. Fish samples were obtained from the sampling stations on Nyabarongo river. All samples were analyzed following standard methods and analytical results indicated that the average temperature, pH, total dissolved solids and electrolytic conductivity of water from the rivers were within WHO acceptable limits. The statistical mean concentrations of the ionic components of the water samples were 1.61 ± 0.03, 0.53 ± 0.002, 0.24 ± 0.02 and 0.051 ± 0.01 mg/L for Fe, Mn, Cu and Pb respectively at Ruliba station and 0.63 ± 0.02, 0.02 ± 0.002, 0.09 ± 0.01, 0.06 ± 0.002 and 0.75 ± 0.02 mg/L for Fe, Mn, Zn, Cr and Pb respectively at Kirinda bridge. Water from Giticyinyoni had 1.57 ± 0.02, 0.49 ± 0.03, 0.29 ± 0.058, 0.43 ± 0.058, 0.15 ± 0.00 and 0.59 ± 0.058 mg/L of Fe, Mn, Cu, Zn, Cr and Pb respectively. Zinc, Cu, Cr and Cd were below detection limits in samples from Ruliba station and Kirinda bridge (Nyabarongo river). Edible muscles of P. annectens from Nyabarongo river contained 272.8 ± 0.36, 292.2 ± 0.25, 8.8 ± 0.36, 135.2 ± 0.15, 148.0 ± 0.21 and 432. 0 ± 0.50 mgkg^-1 for Fe, Mn, Cu, Zn, Cr and Pb at Ruliba station and 336.0 ± 0.70, 302.6 ± 1.22, 6.4 ± 0.26, 44.7 ± 0.20, 138.2 ± 0.17 and 302.4 ± 1.50 mgkg^-1 for Fe, Mn, Cu, Zn, Cr and Pb respectively at Kirinda bridge. Health risk assessment indicated that consumption of the edible muscles of P. annectens may lead to deleterious health effects as reflected by values of target hazard quotients being greater than one. Therefore, the Rwandese government should lay strategies to reduce pollution of the rivers. Further research should evaluate the heavy metal content of metabolically active organs of P. annectens from Nyabarongo river as well as the microbiological profile of water from the rivers.

Background: Data on the benefits of rapid microbiological testing on antimicrobial consumption (AC) and antimicrobial resistance patterns(ARP) are scarce. We evaluated the impact of a protocol based on rapid techniques on AC and ARP in intensive care (ICU) patients. Methods: Retrospective pre(2018) and post-intervention(2019-21) study in ICU patients. A rapid diagnostic algorithm was applied from 2019 in patients with lower respiratory tract infection. Incidence of nosocomial infection, ARP, and AC as DDD(defined daily dose) were monitored. Results: A total of 3635 patients were included, 987(pre-intervention) and 2648(post-intervention). A median age was 60 years, 64% male, with APACHE II of 19 points and SOFA of 3 points. Overall ICU mortality of 17.2% without differences between the periods. An increase in the number of infections was observed in the post-intervention period(44.5% vs 17.9%, p<0.01), especially due to an increase in ventilator-associated pneumonia(44.6% vs 25%,p<0.001). AC decreased from 128.7 DDD in 2018 to 66.0 DDD in 2021(Rate Ratio=0.51). A recovery of P.aeruginosa susceptibility of 23% for Piperacillin/tazobactam and 31% for Meropenem was observed. Conclusion: The implementation of an algorithm based on rapid microbiological diagnostic techniques allowed a significant reduction in AC and ARP without affecting the prognosis of critically ill patients.

A mathematical model is proposed to analyze the spreading dynamics of COVID-19. By using the parameters of the model, namely the basic reproduction number (R0) and the attenuation constant (k), the daily number of infections (DNI) and the cumulative number of infections (CNI) are deduced and shown to be in good agreement with experimental data. This model effectively addresses three key issues: explaining the waveform pattern of DNI, predicting the occurrence of the second wave of infection, and understanding the competitive spread of two viruses in a region. The findings demonstrate that these significant challenges can be comprehensively tackled using a simple mathematical framework. The theoretical insights derived from this model hold potential in guiding the estimation of the severity of an infection wave and formulating effective strategies for the control and mitigation of epidemic outbreaks.

Background The purpose of this study was to clarify the relationship structure of quality of life (QOL) in survivors of breast cancer, including difficulty in daily life and negative experience as health-related indicators. Methods Participants were survivors of breast cancer for more than 2 years after primary breast cancer surgery and belonged to self-help groups. The assessment used FACT-B (QOL), HADS (anxiety and depression), SOC (sense of coherence), WHODAS 2.0 (difficulties in daily life), and CAOD (negative experiences). Bayesian structural equation modeling (BSEM) was performed to analyze the hypothesized model. If the causal model was significant, multiplication of the path coefficient from anxiety and depression to QOL, and from SOC to anxiety and depression, was considered a direct effect on QOL, and from SOC to difficulty in daily life, from difficulty in daily life to negative experiences, and from negative experiences to anxiety and depression were considered indirect effects on QOL. Results Goodness of fit of the model in the BSEM was satisfactory. The direct effect was 0.274, and indirect effect was 0.163. Conclusions These direct and indirect approaches to difficulties in daily life are very significant because they can provide a basis for development of support strategies to increase QOL.

Cyanobacteria (blue-green algae) may rapidly propagate under favorable conditions, forming dense blooms. As water blooms deteriorate, blue-green algae can generate potent toxins, potentially harmful to companion animals, wildlife, and even humans. One widely recognized cyanobacterial toxin is microcystin. This algal toxin has been implicated in surface waters globally, increasing liver cancer and/or disease risk amongst those who depend on sources prone to microcystin contamination. Interestingly, no study looked at weather conditions when connecting liver health outcomes to freshwater cyanotoxins. The purpose of this study was to determine if climate was an important determinant of liver mortality and total microcystins at the ecological level. Secondary data was used to evaluate the proposed hypothesis. Environmental data (CDC WONDER) and toxin data (USEPA) were used in multivariate regression analysis. Mean daily sunlight and total microcystins were significant predictors of age-adjusted chronic liver disease and cirrhosis death rates. Mean annual precipitation and mean daily max temperature were non-significant predictors. This study demonstrated how microcystins in combination with climate may increase liver mortality. The results can prompt others to study environmental exposures of terminal liver diseases, guiding environmental health and the water industry of human survival needs.

In recent experimental studies, we reported the aggravating effects of Asian sand dust (ASD) on male reproductive function in mice. However, the effects of fetal ASD exposure on male reproductive function have not been investigated. The present study investigated the effects of fetal ASD exposure on reproductive function in male offspring. Using pregnant CD-1 mice, ASD was administered intratracheally on days 7 and 14 of gestation, and the reproductive function of male offspring was determined at 5, 10, and 15 weeks after birth. The secondary sex ratio was significantly lower in the fetal ASD-exposed mice than in the controls. Histologic examination showed partial vacuolation of seminiferous tubules in immature mice. Moreover, daily sperm production (DSP) was significantly less in the fetal ASD-exposed mice than in the controls. DSP in the fetal ASD-exposed mice was approximately 10% less than the controls at both 5 and 10 weeks. However, both the histologic changes and the DSP decrease were reversed as the mice matured. These findings suggest that ASD exposure affects both the fetal development and the reproductive function of male offspring. In the future, it will be necessary to clarify the onset mechanisms of ASD-induced male fetus death and male reproductive disorders.

Recently, the Internet of Things (IoT) has attracted wide attention from many fields, especially healthcare, because of its large capacities of information perception and collection. In this paper, we present an IoT-based home telehealth system for providing smart healthcare management for individuals, especially older people. Each client node of the system is mainly composed of an electronic water meter that records the user's daily water usage and an unobtrusive sleep sensor that monitors the user's physiological parameters during sleep such as heart rate (HR), respiratory rate (RR), body movement (BM), and states on the bed or outside the bed. The sleep sensor senses the biosignals and states by a sensor matrix composed of 12 piezoelectric sensors. The collected data can be transmitted to a remote centralized cloud service by a wireless home gateway for analyzing the living pattern and rhythm of users. Furthermore, the periodic feedback of results can be provided to users themselves as well as their family and health advisers. In the present study, data collections from a total of 18 older subjects were made for one year to evaluate the effectiveness of the proposed system. By analyzing living pattern and rhythm, preliminary results indicate the effectiveness of the telehealth system and suggest the potential of the system regarding improvement of quality of life (QoL) of older people and promotion of their health.

Chronic obstructive pulmonary disease (COPD) is increasingly being recognized as a systemic disease rather than a mere disorder of the lungs. Central (respiratory) and peripheral (limb) muscle weakness are among the main pronounced systemic effects of COPD. While the disease primarily affects the lower limb muscles and contributes to gait impairment, COPD is also associated with an increasing risk of falls in patients (COPDp). Previous studies have reported higher rates of falls among COPDp (1.17 to 1.20 falls/person-year), amounting to four times higher than an age-matched healthy group. Potential fall risk factors include muscle weakness, impaired daily activities, cognitive dysfunction, and gait and balance impairment. Although COPDp often manifest many of these risk factors, there remains a gap in literature regarding falls during walking in this population. This study aimed to 1. analyze the literature to identify the risk factors of falling in COPDp, and 2. investigate the underlying mechanisms by which these risk factors can lead to increased prevalence of falling. The results suggest that in addition to the known risk factors of falling, low back pain and mental fatigue should also be considered as relevant risk factors in the treatment process of these patients. Moreover, respiratory problems, which are common in this population, have demonstrated pronounced effects on energy expenditure, gait, and other types of activities of daily living (ADLs), leading to reduced intensity, disrupted coordination of the trunk-pelvic structure with the lower limbs during gait, and altered motor control performance due to activation of muscles in an inefficient synergic manner. These problems potentially lead to the increased vulnerability of these patients to external disturbances and higher incidence risk of falls and injuries. Cognitive problems, which are typically due to reduced oxygen received by the brain, as well as general inflammation caused by COPD, also play a significant role in gait disruption and balance. Future research is warranted to determine the prevalence of falls in COPDp by examining the response of these patients to Medio-Lateral (ML) and Anterior-Posterior (AP) disturbances during gait in association with traditional and recommended fall risk factors.

This research investigates Haifa ports emissions’ contribution to the existing daily emission inventory level in the area. This research based on developed full bottom-up model framework that looks at the single vessel daily voyage through its port call stages. The main data sources for vessels movements used in this research are the Israel Navy`s movements log and Israel Administration of Shipping and Ports’ (ASP) operational vessel movements and cargo log. The Fuel Consumption (FC) data and Sulfur Content (SC) levels are based on an official Israel ASP survey data. Observation years in this research are 2010 - 2018 with focus on the Ocean-Going Vessels (OGV) type only. The results show that the vessel fleet calling at Israel ports is mainly vessels that have a lower engine Tier grade (i.e., Tier 0 and 1) which is considered a heavy contributor to Nitrogen Oxides (NOx) pollutant. The study recommends on an additional cost charged (selective tariff) to reflect the external social cost linked to the single vessel air pollution combined with supportive technological infrastructure and economic incentive tools (e.g. electric subsidy) to attract or influence vessel owners to assign vessels equipped with new engine Tier grades for calls at Israeli ports.

Sedation is a ubiquitous practice in ICUs and NCCUs. It has the benefit of reducing cerebral energy demands, but also precludes an accurate neurologic assessment. Because of this, sedation is intermittently stopped for the purposes of a neurologic assessment, which is termed a neurologic wake-up test (NWT). NWTs are considered to be the gold-standard in continued assessment of brain-injured patients under sedation. NWTs also produce an acute stress response that is accompanied by elevations in blood pressure, respiratory rate, heart rate, and ICP. Utilization of cerebral microdialysis and brain tissue oxygen monitoring indicates that this is not mirrored by alterations in overall cerebral metabolism, and seldom affects oxygenation. The hard contraindications for the NWT are preexisting intracranial hypertension, barbiturate treatment, status epilepticus, and hyperthermia. However, hemodynamic instability, sedative use for primary ICP control, and sedative use for severe agitation or respiratory distress are considered significant safety concerns. Despite ubiquitous recommendation, it is not clear if additional clinically relevant information is gleaned through its use, especially with the contemporaneous utilization of multimodality monitoring. Various monitoring modalities provide unique and pertinent information about neurologic function, however, their role in improving patient outcomes and guiding treatment plans has not been fully elucidated. There is a paucity of information pertaining to the optimal frequency of NWTs, and if it differs based on type of injury. Only one concrete recommendation was found in the literature, exemplifying the uncertainty surrounding its utility. The most common sedative used and recommended is propofol because of its rapid onset, short duration, and reduction of cerebral energy requirements. Dexmedetomidine may be employed to facilitate serial NWTs, and should always be used in the non-intubated patient or if propofol infusion syndrome (PRIS) develops. Midazolam is not recommended due to tissue accumulation and residual sedation confounding a reliable NWT. Thus, NWTs are well tolerated in most patients and remain recommended as the gold-standard for continued neuromonitoring. Predicated upon one expert panel, they should be performed at least one time per day. Propofol or dexmedetomidine are the main sedative choices, both enabling a rapid awakening and consistent NWT.

In this paper, the forecast horizon and solar variability influences on MHFM model based on multiscale decomposition, AR and NN models, are studied. This article follows the works published in [1] showing the performance of the MHFM using 3 multiscale decomposition methods and a forecast horizon equal to 1 hour. Several forecast horizon strategies and his influence on the MHFM performances are investigated. We show that the best strategy for a rRMSE variying from $4.43\%$ to $10.24\%$ is obtained for forecast horizons from $5$ minutes to $6$ hours. In a second part, the solar variability influence on the MHFM is studied. A classification based on a shows that the best performance of MHFM is obtained for clear sky days with a rRMSE of $2.91\%$ and worst for cloudy sky days with a rRMSE of $6.73\%$.

Repetitive transcranial magnetic stimulation (rTMS) with intensive occupational therapy improves upper limb motor paralysis and activities of daily living after stroke; however, amount of improvement according to paralysis severity remains unverified. Target activities for daily living using patients’ upper limb functions can be established by predicting the amount of change after treatment for each severity level of upper limb motor paralysis and further aid practice planning. This study estimated post-treatment score changes for each severity level of motor paralysis (no, poor, limited, notable, and full) stratified according to Action Research Arm Test (ARAT) scores before combined rTMS and intensive occupational therapy. Severity of motor paralysis was the fixed factor for analysis of covariance, delta (post-pre) of the scores was the dependent variable. Ordinal logistic regression analysis was used to compare changes in ARAT subscores in patients, divided according to paralysis severity before treatment. A multicenter retrospective cohort dataset analyzed 907 patients with stroke hemiplegia. Largest treatment-related changes in scores were observed in the Limited recovery group for upper limb motor paralysis and Full recovery group for quality-of-life activities using paralyzed upper limb. These results will help predict treatment effects and determine exercises and goal movements for occupational therapy after rTMS.

The present paper proposes a fractal analysis of the Covid-19 dynamics in 45 European countries. We introduce a new idea of using the box-counting dimension of the epidemiologic curves as a means of classifying the Covid-19 pandemic in the countries taken into consideration. The classification can be a useful tool in deciding upon the quality and accuracy of the data available. We also investigated the reproduction rate, which proves to have significant fractal features, thus enabling another perspective on this epidemic characteristic. Moreover, we studied the correlation between two meteorological parameters: global radiation and daily mean temperature and two Covid-19 indicators: daily new cases and reproduction rate. The fractal dimension differences between the analysed time series graphs could represent a preliminary analysis criterion, increasing research efficiency. Daily global radiation was found to be stronger linked with Covid-19 new cases than air temperature (with a greater correlation coefficient -0.386, as compared with -0.318), and consequently it is recommended as the first-choice meteorological variable for prediction models.

Antimicrobial use (AMU) is one of the major drivers of emerging antimicrobial resistance (AMR). Surveillance of AMU, a pillar of AMR stewardship (AMS), helps devise strategies to mitigate AMR. This descriptive, longitudinal retrospective study quantified the trends in human antibiotic utilization between 2010 and 2016 using data on all antibiotics imported for systemic human use into Tanzania's mainland. Regression and time series analyses were used to establish trends in antibiotics use. A total of 12,073 records for antibiotics were retrieved, totaling 154.51Daily Defined Doses per 1,000 inhabitants per day (DID) with a mean (± standard deviation) of 22.07 (±48.85) DID. The private sector contributed 93.76%% of utilized antibiotics. The top-ranking antibiotics were amoxicillin, metronidazole, tetracycline, ciprofloxacin and cefalexin. The DDIs and percentage contribution of these antibiotics were 53.78 (34.81%), 23.86 (15.44), 20.53 (13.29), 9.27 (6.0) and 6.94 (4.49), respectively. The time series model predicted significant increase in utilization(p-value =0.002). The model forecasted that by 2022, the total antibiotics consumed would reach 89.6 DIDs, corresponding to a 13-fold increase compared to 2010. Government intervention to curb inappropriate antibiotic utilization to mitigate the rising threat of antibiotic resistance should focus on implementing AMS programs in pharmacies and hospitals in Tanzania.

Precision farming, a labor-saving and highly productive management, is gaining popularity as the number of farmers declines in contrast to the increasing global food demand. However, it requires more efficient crop phenology observation and growth monitoring. One measure is the Leaf Area Index (LAI), which is essential for estimating biomass and yield, but its validation requires destructive field measurements. Remote sensing offers a non-destructive and effective method for ground- and UAV-based field observations. Thus, in this study, a method for indirect estimation of LAI was investigated using ground and UAV observation data. A weekly plant survey was done to measure the plant height, above-ground biomass, and light intensity. Furthermore, images from ground-based and UAV-based cameras were acquired to generate NDVI and the canopy height (CH), respectively. Using the canopy photosynthetic model, derived from Lambert-Beer’s law, the daily biomass was estimated by applying the weekly estimated LAI using CH, and the observed light intensity data as input. The results demonstrated the possibility of quantitatively estimating the daily growth biomass of rice plants, including its spatial variation. The near-real-time estimation method of rice biomass by integrating observation data at fields with numerical models can be applied to the management of major crops.

This paper presents a V2G strategy to flatten the daily load curve by considering the charging and discharging location of the electric vehicle to help understand the effect of the load generated by charging and discharging of the electric vehicle on the power grid. Based on the estimated share of electric vehicles, the assumption that electric vehicles go to work in the morning and leave in the afternoon was set, and the electric vehicle discharge power was calculated by reflecting both the characteristics of vehicles that go to work in the morning and the SMP1 and SMP2 plans. In addition, the electric vehicle charging power was calculated by reflecting the characteristics of vehicles returning home from work in the afternoon and the TOU rate system. In other words, in order to establish an efficient V2G strategy, a charging/discharging type-specific modeling was developed that considered all the characteristics of an electric vehicle commuting vehicle, and charging and discharging daily load using SMP1 and SMP2 rate plans for morning discharge and TOU1 and TOU2 rate plans for afternoon charging were applied. After calculating the curve, this value was compared and analyzed to evaluate the effect on grid leveling by adding the existing load. The analysis provides an accurate understanding of the impact of EV charging and discharging loads on the power grid according to V2G strategies. In this paper, it is helpful to apply EV charge and discharge management technology to avoid grid overload and minimize grid expansion by leveling the grid daily load curve by applying appropriate SMP and TOU rates through the establishment of an efficient V2G strategy by charge and discharge modeling.

During a sanitary crisis, excess mortality measures the number of all-cause deaths, beyond what we would have expected if that crisis had not occurred. The high number of COVID-19 deaths started a debate in Italy with two opposite positions: those convinced that COVID-19 deaths were not, by default, excess deaths, because many COVID-19 deaths were not correctly registered, with the most part attributable to other causes and to the overall crisis conditions, and those who presented the opposite hypothesis. We analyzed the curve of the all-cause excess mortality, during the period January 5, 2020 – August 28, 2022, compared to the curve of the daily confirmed COVID-19 deaths, investigating the association between excess mortality and the recurrence of COVID-19 waves in Italy. We compared the two curves looking for the corresponding highest peaks and we found that 5 out of the 6 highest peaks (83.3%) of the excess mortality curve have occurred, on average, just a week before the concomitant COVID-19 waves hit their highest peaks of daily deaths (Mean 6.4 days; SD 2.4 days). This temporal correspondence between the moments when the excess mortality peaked and the highest peaks of the COVID-19 deaths provides further evidence that the all-cause excess mortality wave has been mostly driven by COVID-19 deaths

Research has consistently found that people with mental illness (known as consumers) experience lower levels of participation in meaningful activities, which can limit their opportunities for recovery support. The aim of this study was to describe the outcomes of participation in a group program designed to address all stages of activity participation, known as Pathways to Participation (P2P). A descriptive longitudinal design was utilized, collecting data at three time points. Outcomes were measured by the Camberwell Assessment of Need Short Appraisal (CANSAS), Recovery Assessment Scale – Domains and Stages (RAS-DS), Behaviour and Symptom Identification Scale (BASIS-24), Living in the Community Questionnaire (LCQ) and time use diaries. All data was analysed using descriptive statistics, and Chi square analyses. Seventeen consumers completed baseline data, eleven contributed post program data and eight provided follow up data. Most were female (63.64%) and had been living with mental illness for 11.50 (± 7.74) years on average. Reductions in unmet needs and improvements in self-rated recovery scores were re-ported, but no changes were identified in either time use or psychosocial health. The findings indicate the P2P program may enable consumers to achieve positive activity and participation out-comes as part of their personal recovery.

High efficacy LED lamps combined with adaptive lighting control and greenhouse integrated photovoltaics (PV) could enable the concept of year-round cultivation and become a feasible option even in the harsh climate of the Nordic countries. Meteorological satellite data of this region was analyzed in a parametric study to evaluate the potential of these technologies. The generated maps showed monthly average temperatures fluctuating from -20°C to 20°C throughout the year. The natural photoperiod and light intensity also changed drastically, resulting in monthly average daily light integral (DLI) levels ranging from 45-50 mol·m-2·d-1 in summer and contrasting with 0-5 mol·m-2·d-1 during winter. To compensate, growth room cultivation independent from outdoor conditions could be used in winter. Depending on the efficacy of the lamps, the electricity required for sole-source lighting at 300 µmol·m-2·s-1 for 16 hours would be between 1.4 and 2.4 kWh·m-2·d-1. Greenhouses with supplementary lighting could help start the cultivation earlier in spring and extend it further into autumn. The energy required for lighting highly depends on several factors such as the natural light transmittance, the light threshold settings and the lighting control protocol, resulting in electric demands between 0.6 and 2.4 kWh·m-2·d-1. Integrating PV on the roof or wall structures of the greenhouse could offset some of this electricity, with specific energy yields ranging from 400 to 1120 kWh·kWp-2·yr-1 depending on the region and system design.

Falls, highly common in the constantly increasing global aging population, can have a variety of negative effects on their health, well-being, and quality of life, including restricting their capabilities to conduct Activities of Daily Living (ADLs), which are crucial for one’s sustenance. Timely assistance during falls is highly necessary, which involves tracking the indoor location of the elderly during their diverse navigational patterns associated with ADLs to detect the precise location of a fall. With the decreasing caregiver population on a global scale, it is important that the future of intelligent living environments can detect falls during ADL.s while being able to track the indoor location of the elderly in the real world. Prior works in these fields have several limitations, such as – the lack of functionalities to detect both falls and indoor locations, high cost of implementation, complicated design, the requirement of multiple hardware components for deployment, and the necessity to develop new hardware for implementation, which make the wide-scale deployment of such technologies challenging. To address these challenges, this work proposes a cost-effective and simplistic design paradigm for an Ambient Assisted Living system that can capture multimodal components of user behaviors during ADLs that are necessary for performing fall detection and indoor localization in a simultaneous manner in the real world. Proof of concept results from real-world experiments are presented to uphold the effective working of the system. The findings from two comparison studies with prior works in this field are also presented to uphold the novelty of this work. The first comparison study shows how the proposed system outperforms prior works in the areas of indoor localization and fall detection in terms of the effectiveness of its software design and hardware design. The second comparison study shows that the cost for the development of this system is the least as compared to prior works in these fields, which involved real-world development of the underlining systems, thereby upholding its cost-effective nature.

Sensors available on mobile devices allow the automatic identification of Activities of Daily Living (ADL). This paper describes an approach for the creation of a framework for the identification of ADL, taking in account several concepts, including data acquisition, data processing, data fusion, pattern recognition, and machine learning. These concepts can be mapped in a module of the framework, including the use and creation of several algorithms. For the development of a framework that works in several conditions, e.g., without Internet connection, these algorithms should take in account the hardware and software limitations of the mobile devices to run all main tasks locally. The main purpose of this paper is related to the presentation the sensors, algorithms, and architecture of the proposed approach.

Wear simulation aims to assess wear rates and their dependence on factors like load, kinematics, temperature, and implant orientation. Despite its significance, there's a notable gap in research concerning advancements in simulator control systems and the testing of clinically relevant waveforms. This study addresses this gap by focusing on enhancing the conventional proportional-integral-derivative (PID) controller used in joint simulators through the development of a fuzzy logic-based controller. Leveraging a single-input-multiple-output (SIMO) fuzzy logic control system, the study aimed to improve displacement control, augmenting the traditional Proportional-Integral (PI) tuning approach. Implementation and evaluation of a novel Fuzzy-PI control algorithm were conducted on the Leeds spine wear simulator. The study also included testing of daily-living (DL) profiles, particularly from the hip joint, to broaden the scope of simulation scenarios. While both the conventional PI controller and the Fuzzy-PI controller met ISO tolerance criteria for the spine flexion-extension (FE) profile at 1Hz, the Fuzzy-PI controller demonstrated superior performance at higher frequencies and with DL profiles due to its real-time adaptive tuning capability. The Fuzzy-PI controller represents a significant advancement in joint wear simulation, offering improved control functionalities and a more accurate emulation of real-world physiological dynamics.

Cognitive impairment in older adults is associated with poor gait performance, physical decline, falls and poor quality of life. This paper analyzes the feasibility and efficacy of a tango-based in-tervention in older people with cognitive impairment living in nursing homes. A multicenter study, with pre and post-test, was carried out. Intervention attendance, well-being, physical abilities (Short Physical Performance Battery), walking performance, functional capacities (Katz Index), and quality of life (Quality of Life in Alzheimer’s Disease) were assessed. Fifty-four participants (84.9 ± 6.7 years, Mini Mental State Examination 14.5 ± 7.4) completed the protocol. Intervention attendance was 92%, and the mean subjective well-being after each session was 4.5 ± 0.5 (on a five-point scale). Statistically significant improvement was found in the quality of life (p = 0.030). Non statistically significant changes were found in walking performance, physical abilities, or in functional capacities. The study shows feasibility and suggests evidence for the effects of Tango therapy on well-being and quality of life. Further studies are necessary to contrast these findings and to verify the role of Tango interventions as a holistic approach to prevent functional decline in older people with cognitive impairment.

BackgroundThe use of antimicrobials to treat food animals may result in antimicrobial residues in foodstuffs of animal origin. The European Medicines Association (EMA) and World Health Organization (WHO) define safe antimicrobial concentrations in food based on acceptable daily intakes (ADIs). It is unknown if ADI doses of antimicrobials in food could influence the antimicrobial susceptibility of human-associated bacteria. ObjectivesThis aim of this study was to evaluate if the consumption of ADI doses of erythromycin could select for erythromycin resistance in a Galleria mellonella model of Streptococcus pneumoniae infection. Methods A chronic model of S. pneumoniae infection in G. mellonella larvae was used for the experiment. Inoculation of larvae with S. pneumoniae was followed by injections of EMA (0.0875 μg/ml) and WHO (0.012 μg/ml) ADI doses of erythromycin proceeded by isolation of S. pneumoniae colonies on selective agar plates. Minimum inhibitory concentrations (MICs) of resistant colonies were measured, and whole genome sequencing (WGS) was performed followed by variant calling to determine the genetic modifications.   Results Exposure to single doses of both EMA and WHO ADI doses of erythromycin resulted in the emergence of erythromycin resistance in S. pneumoniae. Emergent resistance to erythromycin was associated with a mutation in rplA. Conclusion In our in vivo model, even single dose of erythromycin that are classified as acceptable by the WHO and EMA induced significant increases in erythromycin MICs in S. pneumoniae. These results suggest the need to include the induction of antimicrobial resistance (AMR) as a significant criterion for determining ADIs.

This article describes the use of the PI ProcessBook software tool for visualization and indirect monitoring of occupancy of SHC rooms from the measured operational and technical quantities for monitoring of daily living activities for support of independent life of elderly persons. The proposed method for data processing (predicting the CO₂ course using neural networks from the measured temperature indoor T_i (°C), temperature outdoor T_o (°C) and the relative humidity indoor rHi (%)) was implemented, verified and compared in MATLAB SW tool and IBM SPSS SW tool with IoT platform connectivity. Within the proposed method, the Stationary Wavelet Transform de noising algorithm was used to remove the noise of the resulting predicted course. In order to verify the method, two long-term experiments were performed, (specifically from February 8 to February 15, 2015, from June 8 to June 15, 2015) and two short-term experiments (from February 8, 2015 and from June 8, 2015). For the best results of the trained ANN BRM within the prediction of CO₂, the correlation coefficient R for the proposed method was up to 90%. The verification of the proposed method confirmed the possibility to use the presence of persons of the monitored SHC premises for rooms ADL monitoring.