Mutual relationships between SARS-CoV-2 test numbers, fatality and morbidity rates

Background The number of SARS-CoV-2 tests conversely to other factors, such as age of population or comorbidities, influencing SARS-CoV-2 morbidity and fatality rates, can be increased or decreased by decision makers depending on the development of the pandemic, operational capacity, and financial restraints. The key objective of this study is to identify and describe, within the probabilistic approach, the relationships between SARS-CoV-2 test numbers and the mortality and morbidity rates. Methods The study is based on a statistical analysis of 1058 monthly observations relating to 107 countries, from six different continents, in an 11-month period from March 2020 to January 2021. The variable utilised can be defined as the number of tests performed in a given country in 1 month, to the number of cases reported in a prior month and morbidities and mortalities per 1 million population. The probabilities of different mortality and morbidity rates for different test numbers were determined by moving percentiles and fitted by the power law and by the three-segment piecewise-linear approximation based on Theil Sen trend lines. Results We have identified that for a given probability the dependence of mortality and morbidity rates on SARS-CoV-2 test rates follows a power law and it is well approximated by the three Theil Sen trend lines in the three test rate ranges. In all these ranges Spearman rho and Kendall tau-b rank correlation coefficients of test numbers and morbidity with fatality rates have values between − 0.5 and − 0.12 with p-values below 0.002. Conclusions According to the ABC classification: the most important, moderately important, and relatively unimportant ranges of test numbers for managing and control have been indicated based on the value of the Theil Sen trend line slope in the three SARS-CoV-2 test rate ranges identified. Recommendations for SARS-CoV-2 testing strategy are provided.

Associations between Mental Health and Oral Health among Korean Adolescents: Analysis of the National Surveys (2008–2017)

We aimed to analyze the trends and associations between the oral and mental health of Korean adolescents using the Korea Youth Risk Behavior Web-based Surveys. In total, 713,713 adolescents who participated in the surveys were included. To examine trends in oral and mental health, Pearson’s correlation coefficients were calculated between the weighted percentages and years, and the regression line slope was assessed to estimate annual changes. A complex sample logistic regression analysis was also performed. Experiencing oral symptoms and suicide-related factors both showed a gradually decreasing trend from 2008 and slight increases in 2017 and 2016, respectively. Compared with adolescents who had no oral symptoms, those with all six oral symptoms showed an increase in suicide attempts in the last 12 months, suicide ideation, and feelings of sadness and despair. In conclusion, experiencing more oral symptoms is associated with an increased risk of suicide-related factors.

Least-Squares Fitting of Multidimensional Spectra to Kubo Lineshape Models

We report a comprehensive study of the efficacy of least-squares fitting of multidimensional spectra to generalized Kubo lineshape models and introduce a novel least-squares fitting metric, termed the Scale Invariant Gradient Norm (SIGN), that enables a highly reliable and versatile algorithm. The precision of dephasing parameters is between 8× to 50× better for nonlinear model fitting compared to the CLS method, which effectively increases data acquisition efficiency by one to two orders of magnitude. Whereas the center-line-slope (CLS) method requires sequential fitting of both the nonlinear and linear spectra, our model fitting algorithm only requires nonlinear spectra, but accurately predicts the linear spectrum. We show an experimental example in which the CLS time constants differ by 60% for independent measurements of the same system, while the Kubo time constants differ by only 10% for model fitting. This suggests that model fitting is a far more robust method of measuring spectral diffusion than the CLS method, which is more susceptible to structured residual signals that are not removable by pure solvent subtraction. Statistical analysis of the CLS method reveals a fundamental oversight in accounting for the propagation of uncertainty by Kubo time constants in the process of fitting to the linear absorption spectrum. A standalone desktop app and source code for the least-squares fitting algorithm are freely available with example lineshape models and data. We have written the MATLAB source code in a generic framework where users may supply custom lineshape models. Using this application, a standard desktop fits a 12-parameter generalized Kubo model to a 106 data-point spectrum in a few minutes.

The Effect of Core Vocabulary Extension Program for Children with Inconsistent SSD

Objectives: The purpose of this study was to determine the effect of the Core Vocabulary Extension Program for establishing speech sound consistency on speech inconsistency and accuracy of children with inconsistent SSD.Methods: Four children with inconsistent SSD aged 3-5 years who exhibited speech sound inconsistency, phonological error patterns, and articulation problems at the same time participated in this study. The program of this study used a core vocabulary approach and a multi-sensory approach, and parental support was provided at the same time. The experimental design used a multiple probe baseline design, with 3-5 baseline evaluations, 10 treatment evaluations, and 3 maintenance evaluations were performed. Data analysis of dependent variables, mean, trend line slope, standard deviation, immediate effect of treatment, and ratio of non-overlapping data (PND) were analyzed.Results: As a result of the study, inconsistency was reduced and articulation ability was improved. Speech inconsistency improvement was effective in all four participating children, but accuracy improvement was only effective in three children.Conclusion: This study is significant in that it confirmed the therapeutic effect of the Core Vocabulary Extension Program which integrated a multisensory approach and parent coaching based on a core vocabulary approach on speech sound inconsistency and accuracy of children with severe speech sound disorder accompanied by intellectual problems and language disorders. In the future, it is necessary to apply a phonological approach to remove the remaining phonological error patterns after speech consistency is established and to confirm the effectiveness of the phonological approach

Undergraduate basic sciences and engineering students’ understanding of the concept of derivative

Derivative is one of the most important topics in calculus that has many applications in various sciences. However, according to the research, students do not have a deep understanding of the concept of derivative and they often have misconceptions. The present study aimed to investigate undergraduate basic sciences and engineering students’ understanding of the concept of derivative at Tehran universities on based the framework of Zandieh. The method was descriptive-survey. The population included all undergraduate students of Tehran universities who passed Calculus I. The sample included 604 students being selected through multi-stage random cluster sampling. The measurement tool was a researcher-made test for which the reliability coefficient was obtained using Cronbach's alpha (r=.88). Inspired by Hähkiöniemi’s research, nine tasks on derivative learning were given to the students. The students’ responses were evaluated using a five-point Likert scale and analyzed using descriptive responses. The results indicated that students have no appropriate understanding of the basic concepts of derivatives in numerical, physical, verbal, and graphical contexts. Basic sciences students performed meaningfully were better in understanding the tangent line slope compared to engineering students, while engineering students performed meaningfully were better than basic sciences students in the rate of change.

Small Current Fault Line Selection Based on Improved Empirical Mode Decomposition and Fractal Dimension Method

In this paper, the fault steady state and transient characteristics of small current grounding system are analyzed, and the distribution of transient zero sequence current is introduced. A fault line selection based on EMD and fractal dimension method is proposed. After the parameter is determined, the problem is proposed and improved. Using the simulated annealing K-means algorithm to find the scale-free interval curve to get the line slope is the correlation dimension of the line. Finally, by comparing the size of the associated dimension, you can select the corresponding line of the faulty distribution network.

Anomalies of precipitation and drought in objectively derived climate regions of Iran

By regionalizing precipitation in 113 synoptic stations in Iran, the characteristics of precipitations and the occurrence of droughts in each region were investigated over a period of 30 years, 1988–2017. Elevation, latitude and distance from moisture source have caused strong East–West and South–North gradients of precipitation across the territory of Iran so that the average annual precipitation increases from 55 mm in the eastern and central regions to 1,730 mm in the south-west coast of the Caspian Sea. Hierarchical cluster analysis identified six precipitation regions in Iran, including the arid, semi-arid, moderate, semi-humid, humid, and high humid regions. An investigation of the standardized precipitation index (SPI) showed that the trend in about 19 per cent of stations was significantly decreasing. It was non-significantly decreasing in 65 per cent, significantly increasing in less than 1 per cent, and non-significantly increasing in 15 per cent of the stations. While the occurrence of drought has increased in most parts of Iran, it has decreased in some stations only in the northern strip of the country. The line slope in more than 84 per cent of the stations represent negative values in SPI, which confirms an increase in the occurrence of droughts in Iran.

Changes in EEG Brain Connectivity Caused by Short-Term BCI Neurofeedback-Rehabilitation Training: A Case Study

BackgroundIn combined with neurofeedback, Motor Imagery (MI) based Brain-Computer Interface (BCI) has been an effective long-term treatment therapy for motor dysfunction caused by neurological injury in the brain (e.g., post-stroke hemiplegia). However, individual neurological differences have led to variability in the single sessions of rehabilitation training. Research on the impact of short training sessions on brain functioning patterns can help evaluate and standardize the short duration of rehabilitation training. In this paper, we use the electroencephalogram (EEG) signals to explore the brain patterns’ changes after a short-term rehabilitation training.Materials and MethodsUsing an EEG-BCI system, we analyzed the changes in short-term (about 1-h) MI training data with and without visual feedback, respectively. We first examined the EEG signal’s Mu band power’s attenuation caused by Event-Related Desynchronization (ERD). Then we use the EEG’s Event-Related Potentials (ERP) features to construct brain networks and evaluate the training from multiple perspectives: small-scale based on single nodes, medium-scale based on hemispheres, and large-scale based on all-brain.ResultsResults showed no significant difference in the ERD power attenuation estimation in both groups. But the neurofeedback group’s ERP brain network parameters had substantial changes and trend properties compared to the group without feedback. The neurofeedback group’s Mu band power’s attenuation increased but not significantly (fitting line slope = 0.2, t-test value p > 0.05) after the short-term MI training, while the non-feedback group occurred an insignificant decrease (fitting line slope = −0.4, t-test value p > 0.05). In the ERP-based brain network analysis, the neurofeedback group’s network parameters were attenuated in all scales significantly (t-test value: p < 0.01); while the non-feedback group’s most network parameters didn’t change significantly (t-test value: p > 0.05).ConclusionThe MI-BCI training’s short-term effects does not show up in the ERD analysis significantly but can be detected by ERP-based network analysis significantly. Results inspire the efficient evaluation of short-term rehabilitation training and provide a useful reference for subsequent studies.

Artificial intelligence (AI)–powered pathologic response (PathR) assessment of resection specimens after neoadjuvant atezolizumab in patients with non-small cell lung cancer: Results from the LCMC3 study.

106 Background: PathR is an efficacy endpoint in Phase II and III neoadjuvant trials and is proposed as a surrogate for disease-free survival (DFS) and overall survival. Machine learning (ML)–based, automated approaches standardize quantification of areas of tumor bed and residual viable tumor. Here we show that automation may provide a scalable alternative to or complementary tool for manual assessment. Methods: We determined inter-reader variability for PathR among pathologists in the LCMC3 (NCT02927301) study and developed an AI-powered digital PathR assessment tool in line with manual consensus recommendations. Study cases were reviewed for PathR by a local site pathologist and 3 central expert pathologists (n = 127). When determined manually, major PathR (MPR) was defined as ≤10% viable tumor averaged per case. ML models were trained and validated by the PathAI research platform using digitized H&E-stained tumor sections. The digital PathR model predicted percent viable tumor for each case as the sum of the cancer epithelium area from each slide divided by the sum of tumor bed area for each slide. DFS (clinical cutoff: Oct 23, 2020) was reported for patients with manual and digital PathR assessment (n = 135). For digital MPR, we used a prevalence-matched cutoff that maintained the same proportion of patients as manual MPR. Results: Inter-reader agreement among 1 local and 3 central pathologists for manual PathR was good (n = 127; ICC = 0.87; 95% CI: 0.84-0.90). Agreement was 91% (κ = 0.82) on manual MPR and 98% (κ = 0.88) on pathologic complete response (pCR). 6 patients had unanimous pCR. Digital and manual PathR were strongly correlated (n = 135, Pearson r = 0.78) and digital PathR demonstrated an outstanding predictability for manual MPR (AUROC = 0.975). The range was 0%-60% for digital PathR and 0%-100% for manual PathR with a regression line slope < 1.0 (m = 0.303) indicating systematic differences between the methods, consistent with digital PathR using a high-resolution segmentation of cancer epithelium from stroma across each slide. Longer DFS was observed for MPR yes vs no with both digital and manual assessment (Table). Conclusions: This analysis showed good inter-reader agreement for manual and strong correlation of AI-powered digital and manual PathR. Comparable DFS rates for manual MPR and digital MPR are encouraging in the preliminary data. These data support further studies of digital PathR as a standardized and scalable tool to determine PathR. Clinical trial information: NCT02927301. [Table: see text]