Comparison Plots Research Articles

Designing a Cylindrical Capacitive Based Sensor for Monitoring the Table Salt’s Moisture Content during Iodization

Coaxial cylinder capacitive moisture sensor for determination of moisture content of table salts has been fabricated. The CMS method for determination of moisture content of table salts overcomes the effect of evaporation of iodine in table salt which results from heating in the oven drying method. The CMS overcomes the polarization effect result from the resistive methods of moisture content determination and it is non expensive to construct and it has high accuracy since measurements involves programming system in interpretation of the results. In this research, moisture content sensor based on capacitive principal created using two coaxial cylinders with height 5.207 cm, and different diameters of 4.303 cm and 1.198 cm embedded inside one another. The input signal of the CMS system was provided by the AC signal from the sensor capacitor, the capacitance of the sensor capacitor is directly proportional to the moisture content of the salt sample placed between the two coaxial cylinders of the sensor capacitor. The moisture content was obtained from the model m=6.6145×10-4c+4.54044 for calibration of the CMS by using the OVD as a reference method for determination of moisture content in the table salts. The model was then validated by constructing the comparison plot of OVD and CMS moisture contents. The comparison graph of OVD and CMS MC against test had conceding error bars between OVD and CMS MC. The coefficient of determination of 0.94 was obtained and the correlation plot was a linear relation expressed as y=0.971x+0.773. The model was then validated by solving for moisture content from measured values of capacitance.

Effect of interfacial surface roughness condition on damping of riveted cantilever beams

Purpose This paper aims to analyze deeply the effect of surface roughness conditions of the common interface of the two-layered riveted cantilever beams on their frictional damping during free lateral vibration at first mode. Here, the product, (µ × α), and damping ratio, ξ, are the parameters whose variations are analyzed in this investigation. For this, the influencing parameters considered are the natural frequency of vibration, f; the amplitude of initial excitation, y; and surface roughness value, Ra. Design/methodology/approach For experimentally evaluating logarithmic damping decrement, d, the frequency response function analyzer for the case of free lateral vibrations was used. Later, for evaluating the product, µ × α (where µ is the kinematic coefficient of friction and α is the dynamic slip ratio), and then, the damping ratio, ξ, the empirical relation suggested for logarithmic damping decrement, d, of riveted cantilever beams was used. After this, the full and reduced quadratic models of the product, µ × α, ξ, response surface methodology (RSM) with the help of Design Expert 11 software was used. Corresponding main effects plots, surface plots and prediction comparison plots were obtained to observe the variations of the product, µ × α, ξ for the variations of influencing parameters: f, y and Ra. Finally, a machine learning technique such as artificial neural networks (ANNs) using “nntool” present in MATLAB R13a software was used to predict the ξ for the different combinations of f, y and Ra. Findings The full and reduced quadratic regression models for the product, (µ × α) and the damping ratio, ξ of riveted cantilever beams for free lateral vibrations of the first mode in terms of the parameters: f, y and Ra were obtained. In addition, the main effects plots, surface plots and prediction comparison plots for the product, µ × α, ξ, with the corresponding experimental values of the product, µ × α, ξ, were obtained. Also, the execution of ANNs using MATLAB R13a software is proved to be the more accurate tool for the prediction of damping ratios in comparison to quadratic regression equations obtained from Design Expert 11 software. In the end, the assumption that the effect of surface roughness value on the product, (µ × α), and the damping ratio, ξ, is negligible is proved to be true using the main effects plots for the product, (µ × α) and ξ obtained from the Design Expert 11 software. Originality/value Obtaining the full and reduced quadratic regression equations for the product, (µ × α), and ξ of the two-layered riveted cantilever beams in terms of parameters: f, y and Ra was done. In addition, the conditions for the corresponding minimum and maximum values of the product, (µ × α), and ξ were obtained. Later, the main effects plots, surface plots and comparison plots of the predicted product, (µ × α), and ξ versus experimental product, (µ × α), and ξ were also obtained. Finally, the predicted values of the product, (µ × α), and ξ using the ANNs tool are observed to be the more accurate values in comparison to that obtained from RSM using the Design Expert 11 software.

A novel approach for numerical treatment of traveling wave solution of ion acoustic waves as a fractional nonlinear evolution equation on Shehu transform environment

Abstract In this paper, we develop and employ an efficient numerical technique for traveling wave solution of the Time Fractional Zakharov-Kuznetsov (TFZK) equation, also known as the nonlinear evolution equation, using the Modified Adomian Decomposition Approach (MADA) in collaboration with the cubic order convergence of the Newton-Raphson method (also known as the improvised Newton-Raphson method) on the Shehu Transform environment (STE). In the current study, the time fractional Caputo-Fabrizio Derivative (CFD) is used in singular and non-singular kernel derivatives to address the influence of fractional parameters. Some of the current numerical and analytical results are displayed utilizing 3D plots, while others are depicted in the form of a legend 2D plots for comparison. To validate the robustness of the current approach, the uniqueness, stability, and convergence analyses are described. The current result is compared to the analytical solution as well as previous solutions in order to demonstrate the efficiency of our suggested technique.

Applications to the dynamics of the suspension system of fast finite time stability in probability of p-norm stochastic nonlinear systems

This paper elucidates the finite-time stability in probability problem for a class of p-norm stochastic nonlinear systems. Among them, from the point of view of convergence speed, finite-time control does have optimal properties. Consequently, a fast finite-time criterion for deterministic systems is established. However, although there exist a significant amount of results on fast finite time stability, there is no article involves p-norm stochastic nonlinear systems case available so far. There are random disturbance terms that made the traditional fast finite-time control methods inapplicable. To overcome this problem, we establish a fast finite-time control criterion for stochastic systems by revamping the fast finite time method of deterministic systems. Then, with the aid of sign function and adding a power integrator technology, a non-Lipschitz continuous state feedback controller is established successfully. Next, the control strategy can effectively improve the control speed compared to the existing results in this paper. Finally, numerical and dynamic suspension simulations are offered to augment our theoretical analysis results, and comparison plots with conventional control strategies are shown.

IMPACT OF PARTICULATE MATTER 2.5 CONCENTRATION AND DENSITY TRICHOMES LEAF OF SHADE PLANTS ON PROTOCOL ROAD, SEBERANG ULU II DISTRICT, PALEMBANG CITY

An increase in the number of motorized vehicles has the potential to increase air pollution, es-pecially on protocol roads, one of which is Particulate matter (PM 2.5). The response of tri-chomes from shade plants to vehicle exhaust gases can be used as environmental biomonitor-ing. The main road in Seberang Ulu II District has a fairly dense mobility in terms of the Ve-hicle Volume Ratio to Road Capacity (VCR). The purpose of this study was to determine the relationship between particulate dust levels and the density of leaf trichomes of shade plants on the protocol road, Seberang Ulu II District, Palembang City. The method in this research is ex post facto with a laboratory approach. Determination of the plot of this study using purpos-ive sampling based on consideration of the circumstances surrounding the study. Plots 1 and 2 are on Jalan A. Yani, Plots 3 and 4 are on DI. Panjahitan Street and Plot 5 as a comparison plot are on Kapten Abdullah Street. The results in this study showed that the highest trichome density values were found in polluted areas.

Biomonitoring of atmospheric PAHs using fir and spruce needles in forests in the vicinity of mountain villages

The aim of the study was to use chemical analyses of spruce and fir needles to determine environmental exposure to polycyclic aromatic hydrocarbons (PAHs) in forests surrounding small mountain towns, including popular tourist destinations. The Beskid Mountains in Poland were chosen as the study area because they are very popular with tourists. The 6- and 12 month old needles were collected in two consecutive years from permanent study plots. Two vintages of needles were used to determine the differences between seasons in the profile of deposited pollutants. Some of plots were located away from roads and buildings, while others were located near tourist destinations. The comparison plots were located in the centre of a tourist resort, near a highway, and in a forest localised in the industrial city characterised by a high degree of urbanization. The analyses of 15 PAHs content showed that the amount and type of compounds retained by the needles were influenced not only by the proximity and amount of the surface emitters, but also by the location of the research sites above sea level. The results obtained can be explained, among other things, by the phenomenon of smog, which is not uncommon in the study region in autumn and winter.

Genetic and Microenvironment Features Do Not Distinguish Follicular Lymphoma Patients Requiring Immediate or Deferred Treatment.

Genetic and Microenvironment Features Do Not Distinguish Follicular Lymphoma Patients Requiring Immediate or Deferred Treatment.

Growth and Agronomic Traits of Green Onion under the Agrovoltaic System with Red Supplemental LED Lighting

Background and objective: An agrovoltaic system is a power generation method applying photovoltaics (PV) to crops cultivated on a farm. Usually, the PV system covers less than 30% of the upper surface of crops on the ground. If the PV system covers the upper layer of the crops, the yield will decrease by 15-20% due to the shading of the PV module. This study was carried out to investigate the effects of red supplemental light-emitting diode (LED) lighting under the PV system on growth and agronomic traits of green onions.Methods: To resolve the issue about decreasing yield, we constructed a 50 kW agrovoltaic system with the red (660 nm peak) LED dimming facility on the farm with 3 different plots for comparison. The 1<sup>st</sup> was PV + LED (two parts of dimming area: 3 hours and 6 hours). The second was only PV, and the last was a reference for comparison of yield (control plot). We transplanted uniform seedlings of green onions on three areas of the farm on June 23, 2020. We used red LED lighting for 3 hours and 6 hours after sunset and harvested green onions on October 25, 2020. We used less than 1% of electricity of total power generated by the agrovoltaic system for supplemental LED lighting.Results: The result of harvesting under the agrovoltaic system with 3 hours of lighting showed that there was 38% more yield than the control plot. We also discovered the optimal amount of supplemental LED lighting because even 6 hours of lighting were not better than 3 hours.Conclusion: Applying supplemental LED lighting after sunset can compensate for the yield decrease. The LED supplemental lighting for 3 hours is optimal for crop harvest. We expect that this system can be helpful to farmers who want to construct an agrovoltaic system.

Progress in the validation of rotor aerodynamic codes using field data

Abstract. Within the framework of the fourth phase of the International Energy Agency (IEA) Wind Task 29, a large comparison exercise between measurements and aeroelastic simulations has been carried out featuring three simulation cases in axial, sheared and yawed inflow conditions. Results were obtained from more than 19 simulation tools originating from 12 institutes, ranging in fidelity from blade element momentum (BEM) to computational fluid dynamics (CFDs) and compared to state-of-the-art field measurements from the 2 MW DanAero turbine. More than 15 different variable types ranging from lifting-line variables to blade surface pressures, loads and velocities have been compared for the different conditions, resulting in over 250 comparison plots. The result is a unique insight into the current status and accuracy of rotor aerodynamic modeling. For axial flow conditions, a good agreement was found between the various code types, where a dedicated grid sensitivity study was necessary for the CFD simulations. However, compared to wind tunnel experiments on rotors featuring controlled conditions, it remains a challenge to achieve good agreement of absolute levels between simulations and measurements in the field. For sheared inflow conditions, uncertainties due to rotational and unsteady effects on airfoil data result in the CFD predictions standing out above the codes that need input of sectional airfoil data. However, it was demonstrated that using CFD-synthesized airfoil data is an effective means to bypass this shortcoming. For yawed flow conditions, it was observed that modeling of the skewed wake effect is still problematic for BEM codes where CFD and free vortex wake codes inherently model the underlying physics correctly. The next step is a comparison in turbulent inflow conditions, which is featured in IEA Wind Task 47. Doing this analysis in cooperation under the auspices of the IEA Wind Technology Collaboration Program (TCP) has led to many mutual benefits for the participants. The large size of the consortium brought ample manpower for the analysis where the learning process by combining several complementary experiences and modeling techniques gave valuable insights that could not be found when the analysis is carried out individually.

Provide Bitcoin's daily optimal trading strategy based on LSTM

The purpose of this report is to develop a model that gives the best daily trading strategy based only on the price data before the day. We want to provide traders with strategies that will enable them to maximize their returns.we first utilize the LSTM time series neural network model using the first 956 data sets are used for training , and the subsequent 300 test sets are used to evaluate the model accuracy, calculate the prediction error and word comparison plots, and assess the difference between the prediction performance of the model and the actual value,This method has a better credibility. Finally, based on this model, we construct the optimal trading strategy model with the maximum value of total assets held as the objective function, add constraints, and finally arrive at an investment value of $1000.

Addressing Parameter Uncertainty in a Health Policy Simulation Model Using Monte Carlo Sensitivity Methods

We present a practical guide and step-by-step flowchart for establishing uncertainty intervals for key model outcomes in a simulation model in the face of uncertain parameters. The process starts with Powell optimization to find a set of uncertain parameters (the optimum parameter set or OPS) that minimizes the model fitness error relative to historical data. Optimization also helps in refinement of parameter uncertainty ranges. Next, traditional Monte Carlo (TMC) randomization or Markov Chain Monte Carlo (MCMC) is used to create a sample of parameter sets that fit the reference behavior data nearly as well as the OPS. Under the TMC method, the entire parameter space is explored broadly with a large number of runs, and the results are sorted for selection of qualifying parameter sets (QPS) to ensure good fit and parameter distributions that are centrally located within the uncertainty ranges. In addition, the QPS outputs are graphed as sensitivity graphs or box-and-whisker plots for comparison with the historical data. Finally, alternative policies and scenarios are run against the OPS and all QPS, and uncertainty intervals are found for projected model outcomes. We illustrate the full parameter uncertainty approach with a (previously published) system dynamics model of the U.S. opioid epidemic, and demonstrate how it can enrich policy modeling results.

Efficacy of COVID-19 vaccines: a systematic review and network meta-analysis of phase 3 randomized controlled trials.

Several vaccines have been approved for the prevention of COVID-19. However, no head-to-head trials comparing their clinical efficacy have been performed. This network meta-analysis aims to identify those, among the competing existing vaccines, conferring the maximum protection against COVID-19. A literature search was done in Medline (via PubMed), Embase and Cochrane Library databases for phase 3 randomized controlled trials evaluating the efficacy of different COVID-19 vaccines. Search results were screened and eligible studies were included to perform a network meta-analysis in software 'R' version 4.1.2 using a random effect model. Cochrane's 'Risk of Bias tool (RoB2)' was used for quality assessment. Raw data from the included studies was used for network meta-analysis. Assessment of inconsistency was not possible as no study compared two or more vaccines directly. A forest plot for indirect comparison of various COVID-19 vaccines was obtained. Rankogram and 'P' scores were obtained to rank the vaccines based on the indirect evidence of their comparative efficacy. A total of 17 randomized controlled trials evaluating the efficacy of 16 COVID-19 vaccines, were included in the network meta-analysis. A total of 361,386 participants was included in this network meta-analysis. Overall risk of bias among included studies was of 'some concern'. All the COVID-19 vaccines had a statistically significant reduction of risk for contracting symptomatic SARS-CoV-2 in comparison to the placebo, however, the maximum protection (RR 0.05) was with BNT126b2. The indirect comparison also revealed BNT126b2 vaccine confers the highest protection against symptomatic SARS-CoV-2 infection in comparison to all others included, with a 'P' score of 0.9771 followed by mRNA-1273, rAD26 & rAD5 and NVX-CoV2373. The evidence generated from this network meta-analysis indicates the good efficacy of all the included vaccines in preventing symptomatic COVID-19 as compared to placebo. The BNT126b2 vaccine was found to provide the highest protection against symptomatic SARS-CoV-2 among all included followed by mRNA-1273, rAD26 & rAD5, NVX-CoV2373 and others.

PERAMALAN GARIS KEMISKINAN PROVINSI DAERAH ISTIMEWA YOGYAKARTA MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING

Poverty is the inability to meet the minimum standard of living. This situation can be seen from the low income in meeting basic needs, both in the form of needs for food, clothing, and shelter. Based on Law No. 24 of 2004, poverty is a socioeconomic condition of a person or group of people for which the non-fulfillment of its basic rights to maintain and develop a dignified life. The issuance of this policy from the government is due to differences in social, economic, and natural characteristics and conditions in each region, with the aim of maximizing the potential in each region, so that it is expected to be able to improve welfare and reduce poverty. Yogyakarta Special Region (D.I.Y) is a province-level Special Region in Indonesia located in the southern part of Java Island, and bordering Central Java Province. According to the BPS report, the number of diy poor people until September 2021 was 474.49 thousand people. This study used Double Exponential Smoothing as the analysis method. The results of the analysis obtained are data on the poverty line of the Yogyakarta Special Region from 2004 to 2022 patterned on upward trand. the MAPE value of the model is 1.8% which indicates that the forecasting model uses the DES method accurately. 4. After looking at the comparison plot of the actual data and forecasting. From 2023 to 2027, the poverty line in the Special Region of Yogyakarta will continue to increase compared to the previous year

91. Reoperation rates following minimally invasive lumbar fusion compared to open fusion: a survivorship analysis with a minimum of five-year follow up

<h3>BACKGROUND CONTEXT</h3> Both traditional open and less-invasive techniques such as minimally invasive (MIS) lumbar fusion have been shown to be effective for degenerative lumbar pathology. One of the critical measures of success following surgery is the reoperation rate, as well as the duration of reoperation from the index procedure. It is known that fusion of one or more segments alters the biomechanics of the adjacent level(s) and may cause accelerated degeneration of the adjacent segment(s). The clinical significance of muscle and musculotendinous preservation offered by MIS fusion and whether it offsets some of the altered biomechanics of fusion, and thus the reoperation rates for adjacent segment degeneration, are unclear. Current studies suggest that MIS fusion may demonstrate a lower long-term reoperation rate. However, evidence in this regard is very limited and conflicting. <h3>PURPOSE</h3> The primary objective of this study is to assess the long-term reoperation rate of 1- to 2-level MIS vs open lumbar instrumented fusion with a minimum of 5-year follow-up. <h3>STUDY DESIGN/SETTING</h3> Obervational study. <h3>PATIENT SAMPLE</h3> Adults with degenerative lumbar disease who underwent 1- to 2-level open and MIS fusion at our institution from January 2006 to December 2016. <h3>OUTCOME MEASURES</h3> Rate of reoperation for MIS vs open lumbar fusion. <h3>METHODS</h3> Retrospective study of all consecutive cases of operatively managed patients with lumbar degenerative disease who underwent 1- to 2-level lumbar fusion between January 2006 to December 2016 performed by two experienced surgeons from a single academic center. One surgeon exclusively uses an MIS tubular retractor fusion technique for all scheduled 1- to 2-level fusions, and the other surgeon only utilizes a midline open posterior approach. The patients were divided into an MIS fusion group and an open surgery group based on the surgical technique performed. The two groups were compared for baseline demographic features, surgical variables and diagnosis at index surgery. Reoperation rates defined as any operation on the same or adjacent levels were assessed. Levels of reoperation were assessed as (1) cranial, (2) caudal, (3) same level of index surgery and (4) both levels. Descriptive and comparative statistics were utilized for between-group comparison and Kaplan-Meier survivorship plots were generated. <h3>RESULTS</h3> A total of 370 patients were included, with range of follow-up (5-14 years). Fusion involved 1 level in 67.5 % of cases and 2 levels in 32.4 %. There was no significant difference between the two groups in age, sex (p = 0.34) or number of levels of fusion (p= 0.214). The overall rate of reoperation was 25.9 %, with incidence of 21.8 % in the MIS fusion group (n=42/192) and 30.3 % (n=54/178) in the open fusion group (p = 0.149). The mean time to reoperation was 4.45 years in the MIS group while in the open group it is 4.24 years. Adjacent segment degenerative pathology was the main reason for reoperation in both groups (69% [n=29/42] for MIS fusion and 76% [n=41/55] for open fusion [p=0.161]). Additionally, for MIS vs open fusions, instrumentation-related reoperations were 19% vs 3.7% (p=0.344); 9.5% vs 14.5% (p=0.376) for pseudoarthrosis; 2.4% vs 3.6% (p=0.468) for infection and 1 revision case for LIV fracture in open group. <h3>CONCLUSIONS</h3> While there seems to be a trend for a higher adjacent segment degeneration reoperation rate in open vs MIS fusion, this effect is offset by a higher rate of instrumentation-related re-operation in the MIS group. The overall reoperation rate did not statistically differ between MIS and open 1- to 2-level lumbar fusion at minimum of 5-year follow-up. <h3>FDA DEVICE/DRUG STATUS</h3> This abstract does not discuss or include any applicable devices or drugs.

Biological Variation in Peripheral Inflammation and Oxidative Stress Biomarkers in Individuals with Gaucher Disease.

The lack of reliable biomarkers is a significant challenge impeding progress in orphan drug development. For appropriate interpretation of intervention-based results or for evaluating candidate biomarkers, other things being equal, lower variability in biomarker measurement would be helpful. However, variability in rare disease biomarkers is often poorly understood. Type 1 Gaucher disease (GD1) is one such rare lysosomal storage disorder. Oxidative stress and inflammation have been linked to the pathophysiology of GD1 and validated measures of these processes can provide predictive value for treatment success or disease progression. This study was undertaken to investigate and compare the extent of longitudinal biological variation over a three-month period for various blood-based oxidative stress and inflammation markers in participants with GD1 on stable standard-of-care therapy (N = 13), treatment-naïve participants with GD1 (N = 5), and in age- and gender-matched healthy volunteers (N = 18). We utilized Bland–Altman plots for visual comparison of the biological variability among the three measurements. We also report group-wise means and the percentage of coefficient of variation (%CV) for 15 biomarkers. Qualitatively, we show specific markers (IL-1Ra, IL-8, and MIP-1b) to be consistently altered in GD1, irrespective of therapy status, highlighting the need for adjunctive therapies that can target and modulate these biomarkers. This information can help guide the selection of candidate biomarkers for future intervention-based studies in GD1 patients.

Visualization of balanced interlacement for digital jacquard based on interlacement frequency statistics and data

The balanced interlacement of woven structures directly affects the surface effect and production efficiency of woven fabric. If it fails to meet the requirement of balanced interlacement, the manufacturing of woven fabric could be unable to proceed. Under layered-combination design mode, the structure of full-color compound digital jacquard fabric designed in this study is a type of compound structure expressing the effect of single-layer structure. The warp and weft interlacement frequency of compound structure is the key to the balanced interlacement. The fabric expresses balanced interlacement if interlacement frequency in the warp/weft remains relatively constant, if not, then it is unbalanced. Apart from the analysis of the covering effect of adjacent threads, an interlacement frequency statistical program was compiled, the statistical data of warp/weft interlacement frequency were acquired, and then they were visualized in form of tables, figures, or scatter plots for balanced interlacement status comparison and optimal selection of balanced interlacement for full-color compound weaves. The results proved that the visualization of interlacement frequency was not only able to quantify the warp/weft balanced interlacement for basic/joint weaves, full-color compound weaves and compound structures, but also offered potential assistance to predict balanced interlacement status and prevent unbalanced interlacement before weaving. This study outlines how the visualization of balanced interlacement can be applied to the soft proofing of digital jacquard fabrics.

The role of indoor positioning analytics in assessment of simulation‐based learning

AbstractSimulation‐based learning provides students with unique opportunities to develop key procedural and teamwork skills in close‐to‐authentic physical learning and training environments. Yet, assessing students' performance in such situations can be challenging and mentally exhausting for teachers. Multimodal learning analytics can support the assessment of simulation‐based learning by making salient aspects of students' activities visible for evaluation. Although descriptive analytics have been used to study students' motor behaviours in simulation‐based learning, their validity and utility for assessing performance remain unclear. This study aims at addressing this knowledge gap by investigating how indoor positioning analytics can be used to generate meaningful insights about students' tasks and collaboration performance in simulation‐based learning. We collected and analysed the positioning data of 304 healthcare students, organised in 76 teams, through correlation, predictive and epistemic network analyses. The primary findings were (1) large correlations between students' spatial‐procedural behaviours and their group performances; (2) predictive learning analytics that achieved an acceptable level (0.74 AUC) in distinguishing between low‐performing and high‐performing teams regarding collaboration performance; and (3) epistemic networks that can be used for assessing the behavioural differences across multiple teams. We also present the teachers' qualitative evaluation of the utility of these analytics and implications for supporting formative assessment in simulation‐based learning. Practitioner notesWhat is currently known about this topic Assessing students' performance in simulation‐based learning is often challenging and mentally exhausting. The combination of learning analytics and sensing technologies has the potential to uncover meaningful behavioural insights in physical learning spaces. Observational studies have suggested the potential value of analytics extracted from positioning data as indicators of highly‐effective behaviour in simulation‐based learning. What this paper adds Indoor positioning analytics for supporting teachers' formative assessment and timely feedback on students' group/team‐level performance in simulation‐based learning. Empirical evidence supported the potential use of epistemic networks for assessing the behavioural differences between low‐performing and high‐performing teams. Teachers' positively validated the utility of indoor positioning analytics in supporting reflective practices and formative assessment in simulation‐based learning. Implications for practitioners Indoor positioning tracking and spatial analysis can be used to investigate students' teamwork and task performance in simulation‐based learning. Predictive learning analytics should be developed based on features that have direct relevance to teachers' learning design. Epistemic networks analysis and comparison plots can be useful in identifying and assessing behavioural differences across multiple teams.

Effect of Magnetic Interactions on Magnetic Remanence in a Fine Particle System

The magnetic field-dependent remanent magnetization and demagnetization of magnetite nanoparticles dispersed in a frozen isoparaffin oil have been measured as a function of magnetite concentration. Frozen ferrofluid samples with magnetite volume fractions between 7.1% and 0.03% were demagnetized using either thermal or dc demagnetization and were kept frozen at 77 or 4 K during measurement to restrict mechanical rotation and translation of the particles. The magnetization and demagnetization remanences of the frozen ferrofluid were measured and plotted parametrically in the magnetic field magnitude to produce Henkel and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta M$ </tex-math></inline-formula> plots for comparison with the Wohlfarth model. The Henkel and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathrm {\Delta }M$ </tex-math></inline-formula> plots of the ferrofluid samples with higher concentrations of magnetite deviated from the predictions of the Wohlfarth non-interacting model, consistent with demagnetizing interactions in the system. The magnitude of this deviation decreased with decreasing magnetite concentration. A simple model is presented that quantitatively explains the deviations from the expected relations and can be used in other systems to characterize magnetic interactions.

Analysis of Non-Invasive Fingerprint Thickness Based Authentication Method Utilizing Near Infrared Spectroscopy

Fingerprints are a popular method of biometric based authentication. However, methods currently in use are susceptible to being bypass through the use of forgeries of the fingerprint pattern. Measuring the epidermal thickness of the fingerprint is a solution to the issue, as there are no current ways for a third-party to precisely replicate the thickness measurements. Near-Infrared Diffused Reflectance (NIR-DR) spectroscopy is the proposed method of measuring fingerprint thickness. Reflectance reading is taken at 5 specific wavelength points to generate a simplified plot for comparison. Thickness measurement is gauged by calculationg change in reflectance percentage between the 800-900nm range. Data gathered showed variation in the reflectance spectra that was unique to each subject. Application for a fingerprint thickness-based authentication method is plausible but require additional research with a larger population sample and looking into the effects of age and skin colour for their effect on epidermal thickness.

MD DaVis: interactive data visualization of protein molecular dynamics.

Molecular dynamics (MD) simulations have become an integral part of biomolecular study. Most MD software suites do not include analysis tools and those which do create very basic visualizations. Molecular Dynamics Data Visualizer (MD DaVis) is a python package developed to facilitate quick comparative analysis of MD trajectories of similar proteins or the same protein under different conditions. MD DaVis can quickly generate interactive visualization from molecular dynamics trajectories with a few simple steps. Interactive plots eliminate the need to make multiple plots for comparison, improving productivity and saving time. MD DaVis is an open-source Python 3 package (https://pypi.org/project/md-davis/) distributed under MIT license. The source code is available at https://github.com/djmaity/md-davis or https://doi.org/10.5281/zenodo.6227047. Supplementary data are available at Bioinformatics online.