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In people with bone and soft tissue injuries of the wrist, hand and/or fingers, do feedback-guided exercises performed on a tablet touchscreen hasten return to work, reduce healthcare usage and improve clinical recovery more than a home exercise program prescribed on paper? Randomised, parallel-group trial with concealed allocation, assessor blinding and intention-to-treat analysis. Seventy-four workers with limited functional ability due to bone and soft tissue injuries of the wrist, hand and/or fingers. Participants in the experimental and control groups received the same in-patient physiotherapy and occupational therapy. Participants in the experimental group received a home exercise program using the ReHand tablet application, which guides exercises performed on a tablet touchscreen with feedback, monitoring and progression. Participants in the control group were prescribed an evidence-based home exercise program on paper. The primary outcome was the time taken to return to work. Secondary outcomes included: healthcare usage (number of clinical appointments); and functional ability, pain intensity, and grip and pinch strength 2 and 4 weeks after randomisation. Compared with the control group, the experimental group: returned to work sooner (MD –18 days, 95% CI –33 to –3); required fewer physiotherapy sessions (MD –7.4, 95% CI –13.1 to –1.6), rehabilitation consultations (MD –1.9, 95% CI –3.6 to 0.3) and plastic surgery consultations (MD –3.6, 95% CI –6.3 to –0.9); and had better short-term recovery of functional ability and pinch strength. In people with bone and soft-tissue injuries of the wrist, hand and/or fingers, prescribing a feedback-guided home exercise program using a tablet-based application instead of a conventional program on paper hastened return to work and improved the short-term recovery of functional ability and pinch strength, while reducing the number of required healthcare appointments. ACTRN12619000344190 [ABSTRACT FROM AUTHOR]

The article discusses the navigating manuscript rejection. Topics include the study demonstrating how common manuscript rejection is among faculty of all academic ranks in hopes to normalize rejection and open conversations about rejection in mentorship; approach, innovations related to the study design, and reason for the rejection of the study to quantify on the fate of manuscripts.

Abstract Question In people who have undergone surgical carpal tunnel release, do sensorimotor-based exercises performed on the touchscreen of a tablet device improve outcomes more than a conventional home exercise program prescribed on paper? Design Randomised, parallel-group trial with concealed allocation, assessor blinding, and intention-to-treat analysis. Participants Fifty participants within 10 days of surgical carpal tunnel release. Intervention Each participant was prescribed a 4-week home exercise program. Participants in the experimental group received the ReHand tablet application, which administered and monitored exercises via the touchscreen. The control group was prescribed a home exercise program on paper, as is usual practice in the public hospital system. Outcome measures The primary outcome was functional ability of the hand, reported using the shortened form of the Disabilities of the Arm, Shoulder and Hand (QuickDASH) questionnaire. Secondary outcomes were grip strength, pain intensity measured on a 10-cm visual analogue scale, and dexterity measured with the Nine-Hole Peg Test. Outcomes were measured by a blinded assessor at baseline and at the end of the 4-week intervention period. Results At Week 4, functional ability improved significantly more in the experimental group than the control group (MD –21, 95% CI –33 to –9) on the QuickDASH score (0 to 100). Although the mean estimates of effect on the secondary outcome also all favoured the experimental group, none reached statistical significance: grip strength (MD 5.6 kg, 95% CI –0.5 to 11.7), pain (MD –1.4 cm, 95% CI –2.9 to 0.1), and dexterity (MD –1.3 seconds, 95% CI –3.7 to 1.1). Conclusion Use of the ReHand tablet application for early rehabilitation after carpal tunnel release is more effective in the recovery of functional ability than a conventional home exercise program. It remains unclear whether there are any benefits in grip strength, pain or dexterity. Trial registration ACTRN12618001887268. [ABSTRACT FROM AUTHOR]

The article reviews the February 2020 issue of the periodical "Journal of Physiotherapy".

Abstract: Objective: To assess the measurement equivalence of an interactive voice response (IVR) version of the EQ-5D with the original paper version. Methods: Subjects were randomly assigned to: 1) paper then IVR, or 2) IVR then paper and asked to complete the questionnaire two days apart. The analyses tested mean differences (repeated measures analysis of variance) and reliability (intraclass correlation coefficient [ICC]). Equivalence of the means was established if the 95% confidence interval (CI) of the mean difference was within the minimally important difference interval: −0.035 to 0.035 for the EQ-5D index and −3 to 3 for the visual analog scale (EQ VAS). ICC adequacy was tested by comparing the ICC 95% lower CI with a critical value of 0.70. Results: The analyses included 113 subjects for the index and 109 subjects for the EQ VAS. For the index, the adjusted means of the paper and IVR versions were 0.789 ± 0.016 and 0.798 ± 0. 017, respectively. The 95% CI of the mean difference was −0.024 to 0.006, within the equivalence interval. The ICC was 0.894 (95% lower CI 0.857), significantly greater than 0.70. For the EQ VAS, the adjusted means were 71.94 ± 1.87 for paper and 74.63 ± 1.79 for IVR. The 95% CI of the mean difference was −4.347 to −1.049, partially within the equivalence interval. The ICC was 0.887 (95% lower CI 0.840), significantly greater than 0.70. Conclusions: The results provide evidence that the EQ-5D scores on the IVR version were sufficiently equivalent to those obtained on the paper version. [Copyright &y& Elsevier]

The article offers information on reduction of disease activity in axial spondyloarthritis from High intensity exercise for three months, as compared with standard care.

The article discusses the approaches for gluteal tendinopathy which includes education plus exercise and corticosteroid injection.

The article discusses the airway pressure for infants with meconium aspiration syndrome which includes mechanical ventilation and medical care .

Objective: To explore the barriers associated with the adoption of the Alberta Nutrition Guidelines for Children and Youth in schools according to characteristics of the innovation (guidelines) and the organization (schools). Design: Cross-sectional telephone survey. Setting and Participants: Schools in Alberta, Canada. Principals from 357 schools. Main Outcome Measure: Barriers to adopting the nutrition guidelines. Analysis: A 19-question telephone survey, including open- and closed-ended questions, was used to obtain information regarding schools' characteristics and barriers to adopting the guidelines. Qualitative data were coded according to common themes a priori, based on constructs from the Diffusion of Innovations framework. Results: Schools reported many barriers related to the relative advantage, compatibility, and complexity of adopting the guidelines. Parents' resistance to change and cost were the key reported barriers. Lack of knowledge, student preferences, the physical location of the school, and barriers related to the provision of healthful food were also reported. Conclusions and Implications: Disseminating guidelines without providing adequate support for their implementation may not promote change within the school setting. School nutrition initiatives need to involve the parents and have access to sufficient financial and human resource support. [ABSTRACT FROM AUTHOR]

Much statistical teaching and many research reports focus on the 'null hypothesis significance test'. Yet the correct meaning and interpretation of statistical significance tests is elusive. Misinterpretations are both common and persistent, leading many to question whether significance tests should be used at all. While most take aim at the arbitrary declaration of p < 0.05 as a threshold for determining 'significance', others extend the critique to suggest the 'p-value' should be dispensed with entirely. P-values and significance tests are still widely used as if they give a measure of the size and importance of relationships, even though this misunderstanding has been observed and discussed for many years. We argue that p-values and significance tests are intrinsically misleading. Point estimates of relationships and confidence intervals give direct information about the effect and the uncertainty of the estimate without recourse to interpreting how a particular p-value might have arisen or indeed referring to them at all. In this paper we briefly outline some of the problems with significance testing, offer a number of examples selected from a recent issue of the International Journal of Nursing Studies and discuss some proposed responses to these problems. We conclude by offering some guidance to authors reporting statistical tests in journals and present a position statement that has been adopted by the International Journal of Nursing Studies to guide its' authors in reporting the results of statistical analyses. While stopping short of calling for an outright ban on reporting p-values and significance tests we urge authors (and journals) to place more emphasis on measures of effect and estimates of precision/uncertainty and, following the position of the American Statistical Association, emphasise that authors (and readers) should avoid using 0.05 or any other cut off for a p-value as the basis for a decision about the meaningfulness/importance of an effect. If point estimates and confidence intervals are used, then the p-value may be redundant and can be omitted from reports. When authors talk about 'significance' they need to be explicit when referring to statistical significance and we recommend authors adopt the language of 'importance' when talking about effect sizes to avoid any confusion. [ABSTRACT FROM AUTHOR]

The almost inevitable descriptive statistics exercise that is undergone once data collection is complete, prior to inferential statistics, requires the acquisition of basic descriptors which may include standard deviation and quartiles. This paper provides pointers as to how to do this in Microsoft Excel™ and explains the relationship between the two. [ABSTRACT FROM AUTHOR]

Objectives To compare the diagnostic performance of computerized and paper-and-pencil memory tests in detection of mild cognitive impairment (MCI) and dementia. Design Diagnostic studies comparing computerized or paper-and-pencil memory tests with the standard diagnostic criterion for MCI or dementia were identified from OVID databases. The primary outcome was the diagnostic performance of memory tests for detection of MCI, and detection of dementia was the secondary outcome. Risk of bias and reporting quality in included studies was assessed. Setting and Participants Participants with MCI and dementia in any kind of setting. Measures Bivariate random-effects models were used to combine the diagnostic performance of memory tests and presented with a summary receiver-operating characteristic curve. Results A total of 58 studies with 18,450 participants with mean age ranging from 55 to 84 years were included. For the verbal memory tests on patients with MCI, computerized tests showed diagnostic accuracy of 0.89 sensitivity (95% confidence interval [CI] 0.69–0.97) and 0.82 specificity (95% CI 0.70–0.90), whereas paper-and-pencil tests showed diagnostic accuracy of 0.86 sensitivity (95% CI 0.82–0.90) and 0.82 specificity (95% CI 0.76–0.86). For the visual memory tests on MCI patients, computerized tests showed diagnostic accuracy of 0.79 sensitivity (95% CI 0.71–0.84) and 0.80 specificity (95% CI 0.71–0.86), whereas paper-and-pencil tests showed diagnostic accuracy of 0.80 sensitivity (95% CI 0.67–0.89) and 0.68 specificity (95% CI 0.51–0.81). The findings were also comparable to those with dementia. Conclusions/Implications Both verbal and visual computerized memory tests showed comparable diagnostic performance to the paper-and-pencil tests. Computerized cognitive tests show a great potential to use as an alternative to paper-and-pencil tests. When the records can be digitalized, long-term monitoring of cognitive function will be feasible for better management of dementia. [ABSTRACT FROM AUTHOR]

In the literature, modifying the baseline distributions and proposing novel approach of the existing probability models play an important role in the analysis of real-world phenomena as well as the development of new distributions essentially stems from the need to adequately characterize environmental and lifetime events. In this paper, we introduce a new model by applying maximum compound technique to the baseline distributions for modeling more types data used in different case of studies including symmetric, asymmetric, skewed and complex data sets. The proposed model called univariate maximum Harris extended Rayleigh distribution and three parameters characterize it, and it is regarded as strong competitor for widely applied symmetrical and non symmetrical models. The paper offers varied fundamental distributional and mathematical properties of the suggested distribution, such as conditional probability and its expectation, as well as quantile and moment-generating functions. The model's parameters are estimated by applying numerous procedures including maximum likelihood estimation, Expectation–Maximization iterative method and Bayesian approach. Bayesian estimation is performed via various loss functions such as square error, Linex and general entropy functions. As well as, approximate and Bootstrap methods are used to construct the confidence interval for the unknown parameters of the proposed model. Additionally, we illustrated different extensive simulation experiments to see the potential of the suggested estimation methods which give satisfactory performance results. In the end, we applied two real data sets for illustrative purposes. In our illustration, we have compared the practicality of the recommended model with several well-known competing distributions. [ABSTRACT FROM AUTHOR]

Evidence indicates that the use of sedative–hypnotics, including benzodiazepines and z-drugs, is linked to an increased risk of falls and fractures. Nonetheless, the potential exacerbation of this risk by orexin receptor antagonists, which are novel therapeutic agents for treating insomnia, remains uncertain despite their escalating prevalence in clinical practice. We systematically searched four electronic databases from inception to April 17, 2024. In addition, we performed a quality assessment; calculated pooled odds ratios (ORs) to assess the relationship between the use of orexin receptor antagonists and the occurrence of falls or fractures; evaluated heterogeneity across the included studies; and conducted sensitivity analyses. The meta-analysis encompassed eight papers, comprising a total of 46,636 subjects. These papers included 5 case-control studies and 3 randomized controlled trials (RCTs), collectively encompassing ten studies. Analysis of the included case-control studies (pooled adjusted OR = 0.75, 95% confidence interval [CI] = 0.00–1.50, I2 = 66.2%, k = 3) and RCTs (OR = 0.68, 95% CI = 0.31–1.50, I2 = 45.9%, k = 5) indicated that the use of orexin receptor antagonists did not elevate the risk of falls. Similarly, analysis of the included case-control studies revealed no significant increase in the risk of fractures associated with the use of orexin receptor antagonists (pooled adjusted OR = 1.01, 95% CI = 0.82–1.20, I2 = 40.1%, k = 2). This meta-analysis suggests that the use of orexin receptor antagonists for treating insomnia does not escalate the risk of falls or fractures, although the data for lemborexant and daridorexant are limited. • The utilization of orexin receptor antagonists did not heighten the risk of falls. • The use of suvorexant did not elevate the risk of falls. • The use of orexin receptor antagonists did not increase the risk of fractures. [ABSTRACT FROM AUTHOR]

The calculation of descriptive statistics includes the calculation of standard error and confidence interval, an inevitable component of data analysis in inferential statistics. This paper provides pointers as to how to do this in Microsoft Excel™. [ABSTRACT FROM AUTHOR]

Contingency tables may be required to perform chi-test analyses. This provides pointers as to how to do this in Microsoft Excel and explains how to set up methods to calculate confidence intervals for proportions, including proportions with zero numerators. [ABSTRACT FROM AUTHOR]

In this article, the author shares his views on how the results section of an article can be made effective for publishing scientific papers. He mentions that result section should be written in the past tense and the main text of the result section should include tables and figures, including demographic characteristics and lifestyle variables. He also points out that estimates of results can be presented with 95% confidence intervals.

False alarms are detrimental to the safety of industrial processes and are often removed by alarm deadbands. However, most of the existing methods design alarm deadbands based on historic data samples under the assumption of stationarity, and may not achieve the desired performance in reducing false alarms for non-stationary process variables. This paper proposes an adaptive method to update alarm deadbands for non-stationary process variables to remove false alarms. Two technical challenges are addressed in this paper. First, time instants of statistically significant changes in process variables are detected based on mean values of maximum amplitude deviations between process variables and alarm trippoints. Second, when to update an alarm deadband width after detecting a mean change is determined based on a confidence interval of the designed width developed from Bayesian estimation rule. Numerical and industrial examples are provided to illustrate the proposed method and compare with alarm deadbands with fixed widths. [ABSTRACT FROM AUTHOR]

This paper investigates constant-stress accelerated life tests interrupted by a progressive type-I interval censoring regime. We provide a model based on the Chen distribution with a constant shape parameter and a log-linear connection between the scale parameter and stress loading. Inferential methods, whether classical or Bayesian, are employed to address model parameters and reliability attributes. Classical methods involve the estimation of model parameters through maximum likelihood and midpoint techniques. Bayesian approximations are achieved via the utilization of the Metropolis–Hastings algorithm, Tierney-Kadane procedure, and importance sampling methods. Furthermore, we engage in a discourse on the estimation of confidence intervals, making references to both asymptotic confidence intervals and credible intervals. To conclude, we furnish a simulation study, a corresponding discussion, and supplement these with an analysis of real data. [ABSTRACT FROM AUTHOR]

Reliance on null hypothesis significance testing often leads to misinterpretation of research results. Common misinterpretations include that a statistically nonsignificant difference (p ≥ 0.05) implies no difference between groups, and that a statistically significant finding (p < 0.05) is unbiased and clinically important. We aimed to develop a tool — the Conclusion Generator — to mitigate these misconceptions. We reviewed the content of the Conclusion Generator and validated its output using published and simulated data. The Conclusion Generator is a free online application designed to generate conclusions for scientific papers based on the values and clinical interpretation of the point estimate and confidence interval. Both relative and absolute measures of effect are supported. It offers two modes for interpretation: (1) Statistical mode provides an accurate statistical interpretation of results, with an optional specification of superiority and noninferiority bounds; (2) Clinical mode evaluates the clinical importance of the point estimate and confidence limits as specified by the user. Both modes assume no uncontrolled biases. Users must specify the number of decimals, the direction of a beneficial effect (e.g. , relative risk <1 vs. >1), and the level of detail (concise vs. elaborated) for the output. The validation confirmed the Conclusion Generator's capability to interpret research results, considering random error and clinical relevance, while avoiding common misinterpretations associated with null hypothesis significance testing. The Conclusion Generator facilitates an appropriate interpretation of research results by emphasizing estimation and clinical relevance over hypothesis testing. [ABSTRACT FROM AUTHOR]

Wrist fractures are common injuries associated with high disability in the early recovery period. The impact of wrist fractures on safe return to drive is not understood. (1) To compare the proportion of adults who were drivers in car crashes before and after wrist fracture; (2) To examine potential factors (demographic and/or clinical) associated with increased odds of being a driver in a car crash following wrist fracture. Retrospective cohort study. Three state-wide government datasets (MainRoads Western Australia [WA], Hospital Morbidity Data Collection and the Emergency Department Data Collection) were used to obtain and link demographic, clinical and car crash information relating to adults with a wrist fracture sustained between 2008 and 2017. McNemar's tests were used to compare the proportion of drivers in a car crash within the 2 years prior to and following the fracture date. Multivariable logistic regressions were used to identify if any variables were associated with increased odds of crashing in the post-fracture period. Data relating to 37,107 adults revealed a 3.3% (95% CI 3.0%–3.6%, p < 0.05) decrease in the proportion of drivers in a car crash following wrist fracture, persisting for the entire 2 years post-fracture, when compared to the proportion who crashed before their fracture. Those with more severe wrist fracture injury patterns had 79%(95% CI 1.07–3.0, p = 0.03) higher odds of having a crash in the first 3 months following their injury, compared to those with isolated wrist fracture injuries. These results inform and update return to drive recommendations. The reduced proportion of drivers involved in crashes following wrist fracture persisted for 2 years; longer than the expected physical recovery timeframe. It is important that hand therapists actively educate the sub-group of adults with more severe wrist fracture injury patterns of the increased likelihood of car crash for the 3 months following their fracture. • This the first paper to report on car crashes following wrist fracture. • We provide much needed information to assist with return to drive decision-making. • Those with severe injury had 79% higher odds of crashing in the initial 3-months. • Education is recommended for the sub-group with 3-months of increased crash risk. [ABSTRACT FROM AUTHOR]

The prevalence of depression related to precarious employment (PE) has become a significant public health concern, given the declining trend of the standard employment relationship. Research has focused on the mental health detrimental effects of employment conditions, whereas there is scarce evidence concerning the burden of depression that could be prevented by targeting precariousness. This paper estimates the impact of PE on the risk of depression and the attributable fraction within the active and working salaried population in Spain. Observational cross-sectional on data drawn from the Spanish portion of European Health Survey 2020. After applying selection criteria and descriptives, binary logistic regression models stratified by sex are used to examine the associations between a 9-categories combination of employment precariousness and occupational social class, and depressive symptoms. There is a higher risk of depression among individuals in PE and among those who are unemployed, with a notable gradient based on occupational social class for women. Adjusting by sex, age and foreign-born origin, we estimate that approximately 15.0% (95% confidence interval [CI]: 1.0%–26.2%) of depression cases among the working population and 33.3% (95% CI: 23.2%-43.2) among the active population can be attributed to PE. These findings highlight the public health impact of PE on mental health, provide evidence to estimate the economic burden linked to employment-related mental health, and underscore the need for policy changes and interventions at the level of labour markets and workplaces to mitigate the detrimental effects of PE. [ABSTRACT FROM AUTHOR]

Design of efficient test plans to assessing product reliability rapidly, is a critical step to obtain product reliability accurately. In this paper, we are adopted the problem of statistical inference of two generalized inverted exponential populations in a competing duration. To save the balance between the optimal test time and the number of failures needing for statistical inference, joint adaptive type-II hybrid progressive censoring scheme is applied. The model parameters are estimated with classical methods (maximum likelihood and bootstrap) for point estimate and the corresponding confidence intervals. Also, Bayes estimators of model parameters are computed under importance sample technique with the corresponding Bayes credible intervals. A real data sets are analyzed for illustrating purposes. The results are compared and assessed through Monte Carlo simulation study. [ABSTRACT FROM AUTHOR]

Rapid internet penetration and technological advancements have facilitated accessibility to internet-enabled devices globally. Since Asia lacks comprehensive data on internet addiction among college students, this review aims to estimate its pooled prevalence. This was a systematic review and meta-analysis. Searches were conducted in PubMed, Scopus, CINAHL, and MEDLINE from their inception through August 2022 using terms appropriate to internet addiction and Asian countries/territorial for publications in English peer-reviewed journals. The studies included those done on current college students and provided unambiguous indicators of the threshold of internet addiction. The pooled prevalence was calculated through a random-effects meta-analysis by RStudio software, and I 2 statistic was used to assess heterogeneity. The Joanna Briggs Institute critical appraisal checklist was used for quality assessment. Overall, between 2007 and 2021, 39 papers comprising 45 effect sizes and totaling 58,058 participants met the inclusion criteria. The pooled prevalence of internet addiction among Asian college students was 24.3% (95% confidence interval: 19.8%–29.5%, Q = 6234, df = 44, τ2 = 0.79, I 2 = 99.29%), and strikingly, this percentage increased over time. A high degree of heterogeneity was seen, and no publication bias was found. To our knowledge, this is the first comprehensive review report on Asian college students, which found that one-fifth suffer from internet addiction. The findings emphasize the significance of multidisciplinary prevention and management strategies to mitigate the harmful effects of internet addiction. Further research is warranted to develop a standardized diagnostic tool for a more precise estimation of internet addiction among this population. [ABSTRACT FROM AUTHOR]

Heterogeneity in agents' preferences is generally analysed through mixed logit models, which assume taste parameters are distributed in the population according to a certain mixing distribution. As a result, if the utility function is linear in attributes, the willingness to pay is the ratio of two random parameters and is itself random. This paper proposes a technique built on the Delta method, partly analytical and partly based on simulations, to obtain the sampling distribution of the willingness to pay, accounting for both heterogeneity and sampling error. The paper contributes to the literature by: (i) redressing some imprecisions in Bliemer and Rose (2013) that produce biased results; (ii) proposing a faster estimation process, compared to the Krinsky and Robb (1986, 1990) method that, relying on simulation only, proves computationally more demanding; (iii) comparing the performance of different methods using both synthetic and real data sets. The paper shows, via a Monte Carlo study, that the method we develop and the Krinsky and Robb one produce similar results, while outperforming that proposed by Bliemer and Rose. • Uncertainty in estimating Willingness To Pay under Mixed Logit Model arises from both heterogeneity and sampling error. • Delta method can be used, in combination with normal mixtures, to estimate both sources of uncertainty. • Both confidence and prediction intervals can be computed for Willingness To Pay by means of Delta method. • Delta method, being partly analytical, proves time-saving when compared to Krinsky and Robb method. [ABSTRACT FROM AUTHOR]

Cervical fusion for degenerative disorders carries a known risk of adjacent segment disease (ASD), a complication that often requires surgical intervention to relieve symptoms. Proposed risk factors for development of ASD include both clinical and radiographic patient characteristics. However, the true impact of these risk factors is less understood due to limitations in sample sizes and loss to follow-up in individual studies. To review and critically examine current literature on the clinical risk factors associated with development of ASD in the cervical spine following ACDF. Systematic Review and Meta-Analysis. We systematically reviewed the literature in December 2019 according to the PRISMA guidelines. Methodological quality of included papers and quality of evidence were evaluated according to MINORS and GRADE framework. Meta-analysis was performed to compute the odds ratio(OR)with corresponding 95% confidence interval(CI)for dichotomous data, and mean difference(MD) with 95% CI for continuous variables. 6,850 records were obtained using database query. Title/abstract screening resulted in 19 articles for full review, from which 10 papers met the criteria for analysis. There were no significant differences in gender (OR 0.99, 95% CI 0.75–1.30), BMI (MD -0.09, 95% CI -0.46 to 0.29), smoking (OR 1.13, 95% CI 0.80–1.59), alcohol (OR 1.07, 95% CI 0.70–1.64), diabetes (OR 0.85, 95% CI 0.56–1.31), number of segments fused (OR 0.86, 95% CI 0.64–1.16), and preoperative JOA (MD -0.50, 95% CI -1.04 to 0.04). Age (MD 3.21, 95% CI 2.00–4.42), congenital/developmental stenosis (OR 1.94, 95% CI 1.06–3.56), preoperative NDI (MD 4.18, 95% CI 2.11 to 6.26), preoperative VAS (neck) (MD 0.54 95% CI 0.09–0.99), and preoperative VAS (arm) (MD 0.98, 95% CI 0.43–1.34) were found to be statistically significant risk factors. Patients with congenital stenosis, advanced age, and high preoperative NDI are at increased risk of developing ASD. [ABSTRACT FROM AUTHOR]

Background Noncommunicable disease development is related to impairments in glycemic and insulinemic responses, which can be modulated by fiber intake. Fiber's beneficial effects upon metabolic health can be partially attributed to the production of SCFAs via microbial fermentation of fiber in the gastrointestinal tract. Objectives We aimed to determine the effects of SCFAs, acetate, propionate, and butyrate on glycemic control in humans. Methods The CENTRAL, Embase, PubMed, Scopus, and Web of Science databases were searched from inception to 7 December 2021. Papers were included if they reported a randomized controlled trial measuring glucose and/or insulin compared to a placebo in adults. Studies were categorized by the type of SCFA and intervention duration. Random-effects meta-analyses were performed for glucose and insulin for those subject categories with ≥3 studies, or a narrative review was performed. Results We identified 43 eligible papers, with 46 studies within those records (n  = 913), and 44 studies were included in the meta-analysis. Vinegar intake decreased the acute glucose response [standard mean difference (SMD), −0.53; 95% CI, −0.92 to −0.14; n  = 67] in individuals with impaired glucose tolerance or type 2 diabetes and in healthy volunteers (SMD, −0.27; 95% CI, −0.54 to 0.00; n  = 186). The meta-analyses for acute acetate, as well as acute and chronic propionate studies, showed no significant effect. Conclusions Vinegar decreased the glucose response acutely in healthy and metabolically unhealthy individuals. Acetate, propionate, butyrate, and mixed SCFAs had no effect on blood glucose and insulin in humans. Significant heterogeneity, risks of bias, and publication biases were identified in several study categories, including the acute vinegar glucose response. As evidence was very uncertain, caution is urged when interpreting these results. Further high-quality research is required to determine the effects of SCFAs on glycemic control. [ABSTRACT FROM AUTHOR]

Cerebral palsy (CP) is a group of neuromotor diseases that develops as a result of damage to the developing central nervous system during the perinatal period. The condition is usually accompanied by musculoskeletal problems resulting in movement disorders. Gait improvement therefore, is an important part of its treatment. Roboticassisted gait training (RAGT) is a new potential rehabilitation tool for CP patients, however there is no clear evidence for the effectiveness of this method. Can robotic-assisted gait training improve walking function in children with CP? A systematic search was performed in five databases: MEDLINE (via PubMed), Cochrane Central Register of Controlled Trials (CENTRAL), Embase, Scopus, and Web of Science. Eligible studies were randomized controlled trials (RCT) with CP patients under the age of 18. Gross motor function and kinematic gait parameters of patients were the main outcomes. Two authors determined the risk of bias of the RCTs independently using the revised Risk of Bias 2 (ROB 2) tool. Mean Differences (MDs) along with their 95% Confidence Interval (CI) were calculated when at least three studies were present for an outcome, subgroup analysis was performed based on the treatment of the control group. Of the 7363 screened articles, 13 papers met our inclusion criteria and among them, 7 studies could be used in our meta-analyses. The results related to RAGT suggest nonsignificant improvement in standing and walking function (Gross Motor Function Measure D, E), moreover changes in gait speed, step length, and in cadence were also only comparable to controls. The results indicate that there is a trend in some gait parameters where the improvement was higher in the intervention group than in control group. The therapeutic effect of RAGT was probably not superior to physiotherapy combined with treadmill training. • Robotic-assisted gait training is a promising new treatment in cerebral palsy. • Effects and significance are not proven yet. • This review found a tendency for gait improvement after robotic training. • Straightforward evidence for effectiveness is still missing. [ABSTRACT FROM AUTHOR]

Strong relation between reliability studies and product quality. And reliability analysis deals with failure time of units and there are many well-known lifetime distributions. In this paper, we adopt the statistical inference of one more flexible one parameter distribution called Suja lifetime distribution. We primarily take into account four methods to estimate the distributional parameter other than the maximum likelihood estimation. The approximate confidence interval and two bootstrap confidence intervals have also been determined. The point and interval estimators of the Suja' parameter are assessed and compared throughout the Monte Carlo simulation study. Finally, the Suja distribution is used to modeled and analyzed three real data sets. [ABSTRACT FROM AUTHOR]

Sequential (or adaptive) designs are common in acceptance sampling and pharmaceutical trials. This is because they can achieve the same type 1 and type 2 error rate with fewer subjects on average than fixed sample trials. After the trial is completed and the test result decided, we need full inference on the main parameter Δ. In this paper, we are interested in exact one-sided lower and upper limits. Unlike standard trials, for sequential trials there need not be an explicit test statistic, nor even p -value. This motivates the more general approach of defining an ordering on the sample space and using the construction of Buehler (1957). This is guaranteed to produce exact limits, however, there is no guarantee that the limits will agree with the test. For instance, we might reject Δ ≤ Δ 0 at level α but have a lower 1 − α limit being less then Δ 0. This paper gives a very simple condition to ensure that this unfortunate feature does not occur. When the condition fails, the ordering is easily modified to ensure compatibility. • For sequential tests, it is unclear how to define a p-value which can be inverted to a confidence limit. • Consequently, confidence limits can conflict with the results of a sequential test. • For discrete endpoints, standard approximate limits have poor accuracy so we seek exact limits. • Exact limits also need not agree with the results of an exact sequential test. • We give a simple easily checked condition that ensures agreement. [ABSTRACT FROM AUTHOR]

Examine the relationship between nutrition knowledge, diet quality, and eating behavior among active-duty US Army Soldiers. Cross-sectional study with data collection in February 2018 via paper surveys during the validation of the Military Eating Behavior Survey. Among 440 US Army Soldiers, nutrition knowledge was positively and significantly associated with diet quality (b = 0.29, P < 0.001). For every 1-point increase in nutrition knowledge, the Healthy Eating Index-2015 score was expected to increase by 0.29 points. Nutrition knowledge was not significantly associated with skipping breakfast (odds ratio, 1.01; 95% confidence interval, 0.98–1.04) or dining out (odds ratio, 1.01; 95% confidence interval, 0.98–1.03). The outcomes of this study warrant further investigation to determine what interventions provide the strongest outcomes for improving nutrition knowledge and diet quality, as well as create and support an environment that enhances healthy behaviors regarding nutrition that lead to improved diet quality among active-duty Soldiers. [ABSTRACT FROM AUTHOR]

In this paper, we study fluctuations and precise deviations of cumulative INAR time series, both in a non-stationary and in a stationary regime. The theoretical results are based on the recent mod- ϕ convergence theory as presented in Féray et al., 2016. We apply our findings to the construction of approximate confidence intervals for model parameters and to quantile calculation in a risk management context. [ABSTRACT FROM AUTHOR]

OBJECTIVE: The purpose of this paper was to understand associations between low sleep duration (< 8 hours) and positive mental health screens among adolescents (ages 13-18) seen for preventive visits in primary care. METHODS: Data were from two randomized controlled trials testing the efficacy of an electronic health risk behavior screening and feedback tool for adolescent preventive visits. Participants (n = 601) completed screeners at baseline, 3 months, and 6 months which included sleep duration in hours and the Patient Health Questionnaire 9 and Generalized Anxiety Disorder 7 screeners for depression and anxiety, respectively. Main analyses included adjusted logistic regressions testing associations between low sleep duration and positive mental health screens. RESULTS: Adjusted models showed that low sleep duration was associated with significantly greater odds of a positive depression screen (OR = 1.58, 95% CI: 1.06-2.37) but not with a positive anxiety screen or co-occurring positive depression and anxiety screens. However, follow-up analyses indicated an interaction between sleep duration and anxiety in the association with a positive depression screen, such that the association between low sleep and a positive depression screen was driven by those who did not screen positive for anxiety. CONCLUSIONS: As pediatric primary care guidelines for sleep continue to evolve, further research, training, and support for sleep screening are warranted to ensure effective early intervention for sleep and mental health problems during adolescence. [ABSTRACT FROM AUTHOR]

Object detection is one of the most important tasks involved in intelligent agriculture systems, especially in pest detection. This paper focuses on a most devastated agricultural disaster: grasshopper plagues. Grasshopper detection and monitoring is of paramount importance in preventing grasshopper plagues. This paper proposes a probabilistic faster R-CNN algorithm with stochastic region proposing, where a probabilistic region proposal network, an image classification network, and an object detection network are integrated to detect and locate grasshoppers. More specifically, in the proposed framework, the probabilistic region proposal network considers attributes (e.g. size, shape) of region proposals and the image classification network identifies the existence of grasshoppers while the object detection network scores recognition confidence for a region proposal. By integrating these three networks, the uncertainty can be passed from end to end, and the final confidence is obtained for each region proposal can be explicitly quantified. To enhance algorithm robustness, a stochastic region proposing algorithm is developed to screen region proposals rather than using a predetermined threshold. The proposed algorithm is validated by recently collected grasshopper datasets. The experimental results demonstrate that the proposed algorithm not only outperforms competing algorithms in terms of average precision (0.91), average missed rate (0.36), and maximum F 1 -score (0.9263), but also reduces the false positive rate of recognising the existence of grasshoppers in an open field. [ABSTRACT FROM AUTHOR]

• Analytical developments support the understanding of ELM variability. • A special attention is paid to the impact of the input weight randomness. • Variance estimates for homoskedastic, heteroskedastic, regularized cases are given. • The possibility of constructing accurate confidence intervals is discussed. • A new Python library allows the computation of the proposed estimates. Uncertainty quantification is crucial to assess prediction quality of a machine learning model. In the case of Extreme Learning Machines (ELM), most methods proposed in the literature make strong assumptions on the data, ignore the randomness of input weights or neglect the bias contribution in confidence interval estimations. This paper presents novel estimations that overcome these constraints and improve the understanding of ELM variability. Analytical derivations are provided under general assumptions, supporting the identification and the interpretation of the contribution of different variability sources. Under both homoskedasticity and heteroskedasticity, several variance estimates are proposed, investigated, and numerically tested, showing their effectiveness in replicating the expected variance behaviours. Finally, the feasibility of confidence intervals estimation is discussed by adopting a critical approach, hence raising the awareness of ELM users concerning some of their pitfalls. The paper is accompanied with a scikit-learn compatible Python library enabling efficient computation of all estimates discussed herein. [ABSTRACT FROM AUTHOR]

BACKGROUND: The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) promotes and supports breastfeeding for low-income women and children. A prior review reported negative associations of WIC with breastfeeding outcomes. WIC food package changes in 2009 increased breastfeeding support. OBJECTIVE: The objectives of this systematic review were to 1) evaluate evidence on WIC participation and breastfeeding outcomes and 2) evaluate breastfeeding outcomes of WIC participants before versus after the 2009 food package. DATA SOURCES: PubMed, Embase®, CINAHL, ERIC, SCOPUS, PsycINFO, and the Cochrane Central Register of Controlled Trials for papers published January 2009 to April 2022. ELIGIBILITY CRITERIA: Included studies compared breastfeeding outcomes (initiation, duration, exclusivity, early introduction of solid foods) of WIC participants with WIC-eligible nonparticipants, or among WIC participants before versus after the 2009 package change. STUDY APPRAISAL METHODS: Two independent reviewers evaluated each study and assessed risk of bias using EHPHP assessment. RESULTS: From 13 observational studies we found: 1) moderate strength of evidence (SOE) of no difference in initiation associated with WIC participation; 2) insufficient evidence regarding WIC participation and breastfeeding duration or exclusivity; 3) low SOE that the 2009 food package change is associated with greater breastfeeding exclusivity; 4) low SOE that WIC breastfeeding support services are positively associated with initiation and duration. LIMITATIONS: Only observational studies, with substantial risk of bias and heterogeneity in outcomes and exposures. CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS: WIC participation is not associated with a difference in breastfeeding initiation compared to WIC-eligible nonparticipants, but the 2009 food package change may have improved breastfeeding exclusivity among WIC participants and receipt of breastfeeding support services may have improved breastfeeding initiation and duration. [ABSTRACT FROM AUTHOR]

The aim of this paper is to better define the clinical features and outcomes of young patients with non-rhabdomyosarcoma soft tissue sarcoma (NRSTS) with regional and distant lymph node (LN) metastases treated in a standardised fashion, we analysed LN involvement in COG study ARST0332, which evaluated a risk-based treatment strategy for young patients with all stages of NRSTS. Patients <30 years old with newly diagnosed NRSTS and LN metastases enrolled on ARST0332 were studied. Regional LN sampling was required for those with epithelioid sarcoma, clear cell sarcoma or clinically/radiographically enlarged LNs. Tumour features and extent of pre-enrolment resection determined treatment, including chemotherapy, radiotherapy, and delayed surgery. Recommendations for LN metastases included LN dissection at the time of primary tumour resection and dose-adapted radiotherapy based on extent of LN resection. Twenty of 529 eligible and evaluable ARST0332 patients with NRSTS had LN metastases; epithelioid sarcoma had the highest incidence (18%, 5 of 28). Pre-treatment imaging identified LN enlargement in 19 of 20 patients; 1 had no pre-treatment LN imaging. At 6.9 years median follow-up for surviving patients, 5-year overall survival was 85.7% (95% CI: 33.4%, 97.9%) for seven patients with isolated LN metastases and 15.4% (95% CI: 2.5%, 38.8%) for 13 patients with additional extranodal metastases. LN recurrence occurred in only one patient without LNs sampled at initial diagnosis. LN metastases occur in about 4% of paediatric/young adult NRSTS, are limited to a few histologic subtypes, and are rare in patients who did not have clinical or imaging evidence of lymphadenopathy, suggesting that biopsies of non-enlarged LNs are not necessary to identify occult involvement. Patients with isolated LN metastases have high 5-year overall survival (∼85%) and should be treated with curative intent. NCT00346164. • Large prospective study of NRSTS with lymph node (LN) involvement in young patients. • Occult lymph node involvement is exceedingly rare. • Isolated LN metastases have a favourable prognosis so should be treated aggressively. • Complete enlarged LN excision and nodal bed radiation correlate with better outcome. [ABSTRACT FROM AUTHOR]

Obesity is a global disease with at least 2.8 million people dying each year as a result of being overweight or obese according to the world health organization figures. This paper aims to explore the links between obesity and mortality in COVID-19. Electronic search was made for the papers studying obesity as a risk factor for mortality following COVID-19 infection. Three authors independently selected the papers and agreed for final inclusion. The outcomes were the age, gender, body mass index, severe comorbidities, respiratory support and the critical illness related mortality in COVID-19. 572 publications were identified and 42 studies were selected including one unpublished study data. Only 14 studies were selected for quantitative analysis. All the primary points but the gender are significantly associated with COVID-19 mortality. The age >70, [odd ratio (OR): 0.17, CI; 95%, P-value: <0.00001], gender [OR: 0.89; CI: 95%, P-value: 0.32], BMI > 25 kg/m2 [OR: 3.68, CI: 95%, P-value: <0.003], severe comorbidities [OR: 1.84, CI:95%, P-value: <0.00001], advanced respiratory support [OR: 6.98, CI: 95%, P-value: <0.00001], and critical illness [OR: 2.03, CI: 95%, P-value: <0.00001]. Patients with obesity are at high risk of mortality from COVID-19 infection. [ABSTRACT FROM AUTHOR]

Objective: Pre-eclampsia (PE) is a common multi-systemic disease, and the effect of cytokines on PE is not clear. The purpose of this meta-analysis was to evaluate the circulating levels of interferon gamma (IFN-γ), interleukin (IL)-1, IL-17 and IL-22 in patients with PE.Study Design: Relevant studies were identified after a preliminary investigation of studies published up to May 2019 using PubMed and Embase. In this study, all 27 included articles underwent quality rating, with a total of 495 patients with PE and 557 controls. Among them, eight papers and 932 subjects contributed to the meta-analysis of IFN-γ, and six papers and 343 subjects contributed to the meta-analysis of IL-17. Based on the inclusion and exclusion criteria, the retrieved papers were screened and evaluated independently. Relevant data for IFN-γ and IL-17 were extracted for meta-analysis and subgroup analysis, and the stability of the results was evaluated by sensitivity analysis. At the same time, a systematic evaluation was carried out for IL-1 and IL-22 with a small number of included papers.Results: Several papers included in the systematic review showed that the circulating levels of IL-22 were higher in patients with severe PE than in controls, while IL-1 levels did not differ significantly between the two groups. The meta-analysis showed that patients with PE had higher circulating levels of IFN-γ than controls [standardized mean difference (SMD) 1.45, 95 % confidence interval (CI) 0.56-2.34]. There was no evidence of a difference in the circulating levels of IL-17 between patients with PE and controls (SMD 0.53, 95 %CI -0.43 to 1.48).Conclusion: This meta-analysis suggested that changes in circulating levels of IFN-γ might be associated with PE. [ABSTRACT FROM AUTHOR]

This paper reconsiders the estimation of structural gravity models. It introduces a constrained, projection-based Poisson pseudo maximum likelihood estimation procedure (constrained PPML) that exploits the equilibrium conditions introduced by Anderson and Van Wincoop (2003) for estimation and inference. The constrained PPML estimator avoids the estimation of the large number of exporter and importer fixed effects, and provides more reliable inference than the unconstrained PPML estimator. Moreover, based on the delta method the paper drives confidence intervals of counterfactual changes. Monte Carlo simulations yield encouraging results on the performance of the constrained PPML estimator. [ABSTRACT FROM AUTHOR]

This paper outlines the common statistical methods used to analyze four types of observational study: ecological studies, cross-sectional studies, case–control studies and cohort studies. Three statistical methods are considered in detail: correlation coefficients, t-tests for the difference between two means from independent samples and odds ratios. For each method, the need for the same four key outputs is highlighted: the measure of effect, its precision (95% confidence interval), its statistical significance (p-value) and its clinical significance (comparison to the minimum important difference). Where possible, this paper explains the derivation of measures of effect and statistical significance to help readers understand where the numbers come from. The paper also highlights other important aspects of analyzing the quantitative data collected in an observational study, potential biases to consider, and good practice in reporting. Examples from relevant pediatric studies are used where appropriate. [ABSTRACT FROM AUTHOR]

In edge computing (EC), when the edge server (ES) is processing tasks delivered by the mobile devices (MDs), the MDs move outside the coverage of the ES, where task migration is required to ensure service continuity. Most current research on task migration ignores inter-task dependencies and uncertain computing environments, and it focuses mainly on migration scenarios where MDs have a one-to-one or many-to-one relationship with ESs. Aiming at the problem of workflow migration with multi-MDs and multi-ESs in uncertain environments, this paper proposes an interval many-objective optimized workflow migration in uncertain environments (I-MaOWMUE) model that considers transforming uncertainty factors into interval parameters for processing, along with the migration delay, maximum completion time, energy consumption, and load balancing as an objective function, and at the same time, utilize real-time priority scheduling strategies to achieve the fast response of the tasks. Considering the dependency of tasks and the changing characteristics of ES load in a migration environment, this paper designs a migration-based interval many-objective evolutionary algorithm (MI-MaOEA), which adopts an interval confidence strategy to improve algorithm convergence and formulates an objective-value-dominated hierarchical sorting and dual-migration selection strategy based on the migration delay and the success rate of the migration to improve the diversity of the populations. Simulation results show that MI-MaOEA optimizes 27%, 35%, 14%, and 80% in solving the four objective values of I-MaOWMUE, and enables the solution to have faster converse speed and better distribution. [ABSTRACT FROM AUTHOR]

Wind power point and interval prediction plays an important role in dispatching. However, for obtaining both point estimations and prediction intervals (PIs), the existing models like constructing the probability density function are too complicated. This paper proposes a novel multi-objective upper and lower bound and point estimation (MOULPE) model. It constructs a neural network (NN) with double outputs to directly estimate the prediction intervals (PIs) and the median of PIs is calculated as point estimation. Considering wide decision-making space, the problem formulation of MOULPE is defined as three objectives which covers both evaluation indices of PIs and point prediction. Furthermore, based on elite opposition-based learning (EOBL), this paper improves non-dominated fast sort genetic algorithm-III (INSGA-III) to search the optimal front. Two criteria called prediction interval nominal confidence (PINC) and point prediction nominal error (PPNE) are adopted to pick out the best solution. According to the general requirements in literature, four examples of real wind power data are conducted. Compared with some state-of-the-art methods, the coverage probability of PIs constructed by the proposed model not only reaches the preset PINC, but the average width is also the lowest. Similarly, the point estimation error of the proposed method is less than PPNE. • MOULPE is proposed to obtain PIs and PP results through one RWNN. • Using the median of PI as the PP result in MOULPE to improve the optimization effect. • An improved NSGA-III is proposed for optimizing the weights of NN in MOULPE. • MOULPE can provide a set of decision schemes with different standards for operators. • The proposed MOULPE shows superiority on four real-world datasets. [ABSTRACT FROM AUTHOR]

Using progressive Type-II censoring data, this study deals with the estimation of parameters of the Unit-Weibull distribution using two classical methods and the Bayesian method. In the classical methods, maximum likelihood and the maximum product of spacing (MPS) methods are used to obtain the parameters of the model by utilizing the Newton–Raphson method. On the basis of observed Fisher information matrix, approximate confidence intervals for the unknown parameters are obtained. In addition, two bootstrap methods are used to obtain confidence intervals for the unknown parameters of the model. In the Bayesian estimation, we have considered both likelihood function as well as product of spacing function to estimate the model parameters. Bayes estimators are obtained under squared error loss function using independent gamma density priors for the unknown model parameters. Since closed-form of the Bayes estimators is not available, the Metropolis–Hastings algorithm is proposed to approximate the Bayes estimates. In addition, highest posterior density credible intervals are obtained. Further, using different optimally criteria, an optimal scheme has been proposed. A simulation study is conducted to assess the statistical performance of all the estimators. To demonstrate the proposed methodology a real data analysis is provided to illustrate all the statistical inferential procedures developed in the paper. [ABSTRACT FROM AUTHOR]

• Explored a novel finite mixture modelling approach to deal with dependent competing risks data. • Assumed a more realistic scenario of competing risks data with multiple causes of failure. • Considered a flexible progressive first failure censoring scheme. • Different cause-specific lifetime distributions are assumed to belong to proportional hazard family of distributions. • A Diabetic Retinopathy dataset is analysed in details assuming some important members of the proportional hazard family. This paper proposes a flexible mixture modeling approach to analyze competing risks data with multiple causes of failure under a progressive first-failure censoring scheme where the causes may not be independent. The failure time distributions corresponding to different causes of failure are assumed to belong to the flexible proportional hazard family of distributions, some important members of which are Weibull, Burr XII and Gompertz distributions. We address the problem here from a classical viewpoint. The point estimates of the parameters can be easily obtained by employing the maximum likelihood principle. For interval estimation purposes, we resort to using the asymptotic confidence intervals. An extensive simulation study is carried out to validate our proposed model. Finally, a diabetic retinopathy treatment dataset is used as an application to study the effectiveness of our proposed model assuming some important members of the proportional hazard family. [ABSTRACT FROM AUTHOR]

In this paper, we adopted the competing risks model considering that, the failure time is distributed with the Chen lifetime distribution, causes of failure are partially observed and the individuals are tested under type-I censoring scheme. The model parameters are estimated by maximum likelihood and Bayes estimations. Also, the asymptotic confidence intervals as well as credible interval are constructed. The proposed model is used to analyze two sets of data, real and simulate lifetime data sets for illustrative purposes. [ABSTRACT FROM AUTHOR]

It is challenging to obtain maximum power output from a Solar Photovoltaic System (SPVS) under uncertain weather conditions due to rapid change in temperature and irradiance. It is achievable through an application of an appropriate Maximum Power Point Tracking (MPPT) technique. The precise tracking of Maximum Power Point (MPP) is crucial for randomly varying irradiance and temperature due to sudden occurrence of clouds and rain during uncertain variable weather conditions. In this paper, an approach based on Intersection Point Determination Method (IPDM) is proposed to effectively track the MPP under such uncertain climatic conditions. It is an iterative method which starts with formation of a rectangle by drawing straight lines parallel to voltage and current axes of I–V curve, subsequently identifies the point of intersection of its diagonals. This identified intersection point is used as the initial point for the next iteration until the convergence is achieved i.e. the new intersection point superimposes the previous point in two successive iterations. The computer simulations have been carried out on a stand-alone (MSX-60) solar PVS of 60W along with a boost converter designed in MATLAB/Simulink. The performance of proposed IPDM technique is tested and compared with other well established MPPT techniques in four distinct theoretical test cases comprises all possible variable weather conditions to ensure its vast applicability. Further, an experimental setup is established in laboratory environment to also validate its performance for the real-life input variables. In which, the maximum and average power outputs are achieved to 50.5598 W and 30.6338 W respectively, for the unfavourable real-life weather conditions i.e. mostly a cloudy day with rainfall and sunshine for short durations. All these simulation results as obtained by all five MPPT methods are statistically validated through t-Tests with 5% of confidence of interval. The statistical analysis proves the superiority of the proposed IPDM technique as compared to the other four competing MPPT techniques. The proposed method is promising in terms of better convergence, fast tracking speed, negligible oscillations, and maximum power output in all possible weather conditions. [ABSTRACT FROM AUTHOR]

This paper investigates the role of primary healthcare in mitigating the consequences of the COVID-19 pandemic, focusing on the Brazilian Family Health Strategy (ESF) as a case study. ESF is Brazil's major primary care initiative, with prior evidence indicating its effectiveness in improving various health outcomes. The COVID-19 pandemic submitted the Brazilian healthcare system to a rigorous and unprecedented stress test, whose repercussions are still under study. Using comprehensive administrative microdata from 2016 to 2022 encompassing dimensions related to mortality, healthcare service, supply of family health teams, and vaccination coverage, our empirical strategy accounts for heterogeneous effects based on program intensity and pandemic evolution of the 5570 Brazilian municipalities. Our findings reveal that municipalities with high-intensity of ESF coverage (i.e. stronger primary care) experienced 347.93 (95% CI: 289.04, 406.81) fewer COVID-19 and cardiorespiratory deaths per million inhabitants throughout the pandemic period, compared to those in low-intensity ESF areas, despite sharing similar profiles of deaths from respiratory and cardiovascular causes. Among the channels contributing to this relative performance, high-intensity ESF municipalities were found to engage in more home-based primary care visits and health promotion activities while maintaining a similar supply of community health workers. Additionally, they achieved higher vaccination coverage, and these effects were more pronounced in areas with greater ESF presence, emphasising the importance of primary care coverage. In conclusion, our findings underscore the relevance of strong primary care in mitigating the consequences of the pandemic and addressing post-pandemic health challenges. • Study examines the Brazilian Family Health Strategy's impact on COVID-19 outcomes. • High ESF coverage areas had lower mortality rates than low-coverage areas. • Stronger primary care areas had more home visits and actions for health promotion. • Primary care was vital for effective pandemic recovery in Brazil. [ABSTRACT FROM AUTHOR]

In classification problems, many models with superior performance fail to provide confidence estimates or intervals for each prediction. This lack of reliability poses risks in real-world applications, making these models difficult to trust. Conformal prediction, as distribution-free and model-free approaches with finite-sample coverage guarantee, have recently been widely used to construct prediction sets for classification models. However, traditional conformal prediction methods only produce set-valued results without specifying a definitive predicted class. Particularly in complex settings, these methods fail to assist models in effectively addressing challenges such as high dimensionality, resulting in ambiguous prediction sets with low statistical efficiency, i.e. the prediction sets contain many false classes. In this study, a novel Ensemble Conformal Prediction algorithm based on Random Projection and a designed voting strategy, RPECP, is developed to tackle these challenges. Initially, a procedure for selecting the approximately oracle random projections and classifiers is executed to best leverage the internal information and structure of the data. Subsequently, based on the approximately oracle random projections and underlying classifiers, conformal prediction is performed on new test samples in a lower-dimensional space, resulting in multiple independent prediction sets. Finally, an accurate predicted class and a precise prediction set with high coverage and statistical efficiency are produced through a designed voting strategy. Compared to several base classifiers, RPECP obtain higher classification accuracy; against other conformal prediction algorithms, it achieves less ambiguous prediction sets with fewer false classes while guaranteeing high coverage. For illustration, this paper demonstrates RPECP's superiority over other methods in four cases: two high-dimensional settings and two real-world datasets. • Using random projection, we propose a new ensemble conformal prediction method, RPECP, for high-dimensional classification. • We devise a voting strategy to yield an accurate prediction and a precise prediction set for ensemble conformal prediction. • The experimental results demonstrate that RPECP achieves superior accuracy , coverage and statistical efficiency. [ABSTRACT FROM AUTHOR]

To reduce smoking uptake in adolescents, the medical students' network Education Against Tobacco (EAT) has developed a school-based intervention involving a face-aging mobile app (Smokerface). A two-arm cluster-randomized controlled trial was conducted, evaluating the 2016 EAT intervention, which employed the mobile app Smokerface and which was delivered by medical students. Schools were randomized to intervention or control group. Surveys were conducted at baseline (pre-intervention) and at 9, 16, and 24 months post-intervention via paper & pencil questionnaires. The primary outcome was the difference in within-group changes in smoking prevalence between intervention and control group at 24 months. Overall, 144 German secondary schools comprising 11,286 pupils participated in the baseline survey, of which 100 schools participated in the baseline and at least one of the follow-up surveys, yielding 7437 pupils in the analysis sample. After 24 months, smoking prevalence was numerically lower in the intervention group compared to control group (12.9 % vs. 14.3 %); however, between-group differences in change in smoking prevalence between baseline and 24-months follow-up (OR=0.83, 95 %-CI: 0.64–1.09) were not statistically significant (p = 0.176). Intention to start smoking among baseline non-smokers declined non-significantly in the intervention group (p = 0.064), and remained essentially unchanged in the control group, but between-group differences in changes at the 24-months follow-up (OR=0.88, 0.64–1.21) were not statistically significant (p = 0.417). While a trend towards beneficial effects of the intervention regarding smoking prevalence as well as intention to start smoking among baseline non-smokers was observed, our smoking prevention trial demonstrated no significant effect of the intervention. • A face-aging app intervention aimed to reduce adolescent smoking uptake. • Two-arm cluster-randomized controlled trial with 144 German secondary schools. • No significant difference in smoking prevalence change at 24 months (p = 0.176). • Subgroup analyses showed a tendency towards benefits among boys and grammar school pupils. • Intention to start smoking declined non-significantly in the intervention group (p = 0.064). [ABSTRACT FROM AUTHOR]