Immersive Virtual Reality Teaching in Colleges and Universities Based on Vision Sensors

With the progress of society and the development of economy, people pay more and more attention to education, and traditional teaching methods are gradually unable to meet the modern teaching system. As a leader in modern information technology, virtual reality technology has developed rapidly in recent years, and virtual reality technology has also been introduced into many fields, such as teaching. Based on the immersive and extended characteristics of virtual reality, this paper proposes a virtual reality active visual interaction method based on the visual sensor. Based on virtual teaching, after 3 months of learning, the average, standard deviation, and average standard error of the experimental group’s performance are higher than those of the control group. Compared with the control group, the experimental group’s performance has increased by 8.25%. The difference is statistically significant. Learning significance ( P < 0.05 ), immersive virtual reality teaching has played a significant role in the effect, which can greatly improve the cognitive experience of students and achieve a good learning experience and effect.

Association between Positive Airway Pressure Adherence and Healthcare Costs

Background: The impact of positive airway pressure (PAP) therapy for obstructive sleep apnea (OSA) on healthcare costs is uncertain. Research Question: Are three-year healthcare costs associated with PAP adherence in participants from the Tele-OSA clinical trial? Study Design and Methods: Participants with OSA and prescribed PAP in the Tele-OSA study were stratified into three PAP adherence groups based on usage patterns over three years: (a) high (consistently ≥4 hours/night); (b) moderate (2-3.9 hours/night or inconsistently ≥4 hours/night); (c) low (<2 hours/night). Using data from three months of the Tele-OSA trial and 33 months of post-trial follow-up, average healthcare costs (2020 US dollars) in six-month intervals were derived from electronic health records and analyzed using multivariable generalized linear models. Results: Of 543 participants, 25% were categorized as having high adherence, 22% moderate adherence, and 52% low adherence to PAP therapy. Average (standard deviation) PAP use was 6.5 (1.0) hours, 3.7 (1.2) hours, and 0.5 (0.5) hours for the high, moderate, and low adherence groups, respectively. The high adherence group had the lowest average [standard error] covariate-adjusted six-month healthcare costs ($3,162 [$240]) compared with the moderate ($3,658 [$369]) and low ($4,016 [$315]) adherence groups. Significant cost savings were observed between the high and low adherence groups ($854 [95% CI $158, $1,551]); savings between moderate and low adherence were non-significant ($359 [95% CI -$459, $1,176]). Interpretation: In participants with OSA, better PAP adherence was associated with significantly lower healthcare costs over three years. Findings support the importance of strategies to enhance long-term PAP adherence.

A genetic algorithm for optimal assembly of pairwise forced-choice questionnaires

The use of multidimensional forced-choice questionnaires has been proposed as a means of improving validity in the assessment of non-cognitive attributes in high-stakes scenarios. However, the reduced precision of trait estimates in this questionnaire format is an important drawback. Accordingly, this article presents an optimization procedure for assembling pairwise forced-choice questionnaires while maximizing posterior marginal reliabilities. This procedure is performed through the adaptation of a known genetic algorithm (GA) for combinatorial problems. In a simulation study, the efficiency of the proposed procedure was compared with a quasi-brute-force (BF) search. For this purpose, five-dimensional item pools were simulated to emulate the real problem of generating a forced-choice personality questionnaire under the five-factor model. Three factors were manipulated: (1) the length of the questionnaire, (2) the relative item pool size with respect to the questionnaire’s length, and (3) the true correlations between traits. The recovery of the person parameters for each assembled questionnaire was evaluated through the squared correlation between estimated and true parameters, the root mean square error between the estimated and true parameters, the average difference between the estimated and true inter-trait correlations, and the average standard error for each trait level. The proposed GA offered more accurate trait estimates than the BF search within a reasonable computation time in every simulation condition. Such improvements were especially important when measuring correlated traits and when the relative item pool sizes were higher. A user-friendly online implementation of the algorithm was made available to the users.

Solar Panel Parameters Estimation Method Using Manufacturer Information

The article considers the method of evaluating the parameters of equivalent schemes of solar panels using data provided by their manufacturers. The technique involves the use of a digitized volt-ampere characteristic of the solar panel and standard test conditions parameters (STC) to estimate the numerical derivatives at the points of short and open circuit. Digitizing the volt-ampere characteristic introduces some error, which significantly affects the accuracy of determining numerical derivatives. To solve this problem, it is advisable to average the values of the derivatives. It was found that it is sufficient to take 20-25% of the first points and 8-15% of the last points of the digitized curve. In this case, to estimate the value of the derivative at the point of short circuit, it is advisable to use linear fit, and at the point of open circuit – quadratic fit. The peculiarities of using the obtained formulas and the block diagram of the algorithm that implements this technique were also given. A fixed point algorithm is used to solve the transcendental equation of the external characteristic of the solar panel. It was found that in some cases this numerical method may not convergences near the open circuit point. To solve this problem, in the proposed to use the relaxation method. This increases the required number of iterations, but guarantees the convergence of numerical method. The block diagram of the simple iteration algorithm using the relaxation method is given. Modeling the developed technique, one- and two-diode solar panel replacement schemes were used on the example of KC200GT and ST40 solar panels. A comparative analysis of these schemes showed that a single-diode circuit is more relevant, because its use simplifies calculations and eliminates the need for a number of assumptions. The accuracy of the approximation provided by the single-diode circuit is proportional to the accuracy of the two-diode circuit. A comparative analysis of the developed methodology with other works was performed. The results indicate that the proposed algorithm provides the best approximation accuracy among the considered works. For monocrystalline solar panels, the average standard error is 7 times less and the modulus of relative error - 4 times. For polycrystalline panels, the average standard error is 1.5 times less, and the modulus of relative error is 1.75 times. For polycrystalline panels, the approximation error increases due to a non-unit value of the ideality factor for this manufacturing technology of the solar panels.

Effect of Basil Seed and Xanthan Gums Coating on Colour and Surface Change Kinetics of Peach Slices During Infrared Drying

The article presented conducts the research of infrared radiation power effect on the colour and surface changes of peach slices coated with basil seeds gum (BSG) and xanthan gum during drying. The colour indices include redness (a*), yellowness (b*), lightness (L*), and total colour difference (∆E), which were used for the purposes of colour change calculation. As the IR radiation power increased from 150 W to 375 W, the average values of L*, a* and b* of uncoated and coated peach slices decreased from 67.45 to 65.41; 7.95 to 5.89; and 49.21 to 38.52, respectively. The lowest ∆E and surface change values were observed in peach samples coated with BSG. The modelling results showed that the MMF model was the best model to describe the total colour difference of uncoated and coated peach slices (the average correlation coefficient was equal to 0.991 and the average standard error was equal to 1.791). The surface area change (%) of uncoated and coated peach slices increased with the progression of drying time, but the rate of changes was lower for the coated peach slices with BSG. The current research indicated that BSG coating has the potential to improve surface colour and appearance quality of dried peach slices.

Kriging: An advanced Geostatistical Tool to Interpolate the Textural Variation Influences the Yield and Productivity of Tapioca (Manihot esculenta) in Namakkal District, Tamil Nadu, India

Soil texture is a vital variable that reflects a number of soil properties such as Bulk Density, Particle Density, Infiltration Rate, Hydraulic conductivity, Water holding capacity, nutrient storage and availability as well as transport and binding and stability of soil aggregates. For better tuber development in cassava soil texture plays vital role. The main objective of this study is to produce kriged maps (Ordinary kriging map and semivariogram) to interpolate the soil texture for Tapioca growing soils of Paramthy block, Namakkal District at unsampled locations. In this study, nearly 54 surface samples were collected covering 19,149 ha of agriculture land with dominant cultivation of Tapioca. This study helps spatial interpolation of unsampled location of soil texture i.e. sand, silt and clay content which rules the soil physical, chemical and hydrological properties. The average standard error for sand and clay are 0.2 and 0.19 respectively. The results such as provided maps and their associated variance can be used as data source for the development and implementation of further land management and soil water conservation plans in the study area.

Cultivation-based quantification and identification of bacteria at two hygienic key sides of domestic washing machines

Detergent drawer and door seal represent important sites for microbial life in domestic washing machines. Interestingly, quantitative data on microbial contamination of these sites is scarce. Here, 10 domestic washing machines were swap-sampled for subsequent bacterial cultivation at four different sampling sites, each: detergent drawer, detergent drawer chamber as well as top and bottom part of the rubber door seal. The average bacterial load over all washing machines and sites was 2.1 ± 1.0 × 104 CFU cm−2 (average ± standard error of the mean (SEM)). The top part of the door seal showed the lowest contamination (11.1 ± 9.2 × 101 CFU cm−2), probably due to less humidity.Out of 212 isolates, 178 (84%) were identified on genus level and 118 (56%) on species level using MALDI biotyping, resulting in 29 genera and 40 identified species across all machines. The predominant bacterial genera were Staphylococcus and Micrococcus, which were found at all sites. 21 out of 40 species were classified as opportunistic pathogens, emphasizing the need for regular cleaning of the investigated sites.

Determining Role of Air Temperature in Predicting and Controlling COVID-19 Risk Levels Anywhere Anytime Using Multiple Modelling Analyses

COVID-19 is a pandemic with no cure. There is an urgent need for low-cost interventions. Macroclimate work through microclimate. In many situations, man-made microclimate, such as air conditioning, may override the effect of natural macroclimate in determining the pathogenicity of SARS-CoV-2. This study aimed to determine if there is a &lsquo;safe&rsquo; temperature that is comfortable to human beings while significantly inhibitory for SARS-CoV-2 pathogenicity. Data on monthly new deaths or new cases per million population (MDPM or MCPM) and monthly cumulated days with more cases than the previous day (DI) from March 2 to June 15, 2020 were collected from all 118 countries with population over five million. Monthly average AT negatively correlated with the transmission parameters. A significant decrease in transmission was observed when AT reached above 20 &ordm;C. Monthly average (not average high) AT of countries with MDPM &lt;2, MCPM&lt;10, or DI&lt;=7 was found to be between 24.54 and 25.90 &ordm;C (25.00 &ordm;C on average) with average standard error of 4.97. Thus, average AT &lt;20, 20-25, &gt;25 &ordm;C were considered as high, medium, and low risk AT. Furthermore, MDPM in countries with AT &lt;20 &ordm;C were 80.93, 50.23, 13.52, and 7.72 times of those in countries with AT &gt;25 &ordm;C in March, April, May, and June 1-15, respectively. MDPM high-risk rates in countries with AT &gt;25 &ordm;C were 0, 6.25, 14.55, and 9.84%, and the low-risk rates were 100, 83.33, 52.73, and 81.97%, respectively. In countries with AT &lt;20 &ordm;C, the trends were opposite. Setting indoor temperature to 25 &ordm;C could decrease the need of social distancing for containing SARS-CoV-2 transmission. Cooling indoor temperature too low may be a reason of COVID-19 outbreak in some high AT countries. Authorities and the general population can evaluate COVID-19 risk level and manipulate microclimate to reduce the risk anywhere anytime based on local day average AT.

“Finola” Cannabis Cultivation for Cannabinoids Production in Thessaloniki-Greece

Cannabis has garnered a great deal of new attention in the past couple of years due to the increasing hopes of its legalization for recreational use and indications for medicinal benefit. The increasing consumption and cultivation has led to a multiplication of scientific studies. Focus was placed in this study foremost on yielding morphological data (length of the plant, inflorescence fresh and dry weight) for appropriate mechanical harvest and biochemical cannabinoids analysis of the industrial cannabis &ldquo;Finola&rdquo; that is newly grown in Greece. The average, standard error and the coefficient of variation were estimated in case of necessity and the correlation among all results was done using Microsoft Excel 2010 and Minitab 19 Software. Furthermore, three chemical analyses for TLC and NMR techniques were applied for analysis. The Cannabinoid quality or chemotype analysis was also calculated. After extraction and isolation of cannabinoids using ethanol and other separation compounds, cannabinoid acids, tetrahydrocannabinol (THC), cannabidiol (CBD) and some other cannabinoids were extracted, isolated, identified and isolated with no delays or limitations. Finola cannabis provided a scientific background that may be considered by the Lebanese growers to accelerate and improve the relative mentality and to provide a collection of relevant scientific information, upon which the field of cannabis analysis can continue to grow.

The EFFECT OF SCALE CATEGORY NUMBER ON ACCURACY OF PREDICTIVE VALIDITY OF MATHEMATICAL SELF-EFFICACY SCALE

The purpose of this study was to obtain empirical data about the effect of the number of scale categories on the accuracy of the predictive validity of the Mathematics Self-Efficacy Scale between those using a scale of three categories of answers and a scale of five categories of answers. This research uses a quantitative method of comparative study. The population in this study were all students of Madrasah Aliyah (Islamic High School) class XI IPA in North Jakarta in the academic year 2019/2020. Sampling was done by simple random sampling and there were 230 students from six public and private Madrasah Aliyah. The instruments used were tests and non-tests. The test instrument was in the form of a Mathematics learning achievement test and a non-test instrument in the form of a Mathematics Self-Efficacy Scale. The research hypothesis was tested using a t-test. The results showed that the average standard error of estimating the predictive validity of the Mathematics Self-Efficacy Scale using the five answer categories scale was lower than the scale of the three answer categories. The conclusion of the study is the predictive validity of the Mathematics Self-Efficacy Scale which uses a five-answer category scale that is more accurate in predicting mathematics learning outcomes.