Results Of Manual Analysis Research Articles

Analyzing K-12 AI education: A large language model study of classroom instruction on learning theories, pedagogy, tools, and AI literacy

There is growing recognition among researchers and stakeholders about the significant impact of artificial intelligence (AI) technology on classroom instruction. As a crucial element in developing AI literacy, AI education in K-12 schools is increasingly gaining attention. However, most existing research on K-12 AI education relies on experiential methodologies and suffers from a lack of quantitative analysis based on extensive classroom data, hindering a comprehensive depiction of AI education's current state at these educational levels. To address this gap, this article employs the advanced semantic understanding capabilities of large language models (LLMs) to create an intelligent analysis framework that identifies learning theories, pedagogical approaches, learning tools, and levels of AI literacy in AI classroom instruction. Compared with the results of manual analysis, analysis based on LLMs can achieve more than 90% consistency. Our findings, based on the analysis of 98 classroom instruction videos in central Chinese cities, reveal that current AI classroom instruction insufficiently foster AI literacy, with only 35.71% addressing higher-level skills such as evaluating and creating AI. AI ethics are even less commonly addressed, featured in just 5.1% of classroom instruction. We classified AI classroom instruction into three categories: conceptual (50%), heuristic (18.37%), and experimental (31.63%). Correlation analysis suggests a significant relationship between the adoption of pedagogical approaches and the development of advanced AI literacy. Specifically, integrating Project-based/Problem-based learning (PBL) with Collaborative learning appears effective in cultivating the capacity to evaluate and create AI.

Development of a Machine Learning Algorithm for Drug Screening Analysis on High-Resolution UPLC-MSE/QTOF Mass Spectrometry.

Ultra-performance liquid chromatography (UPLC)-MSE/quadrupole time-of-flight (QTOF) high-resolution mass spectrometry employs untargeted, data-independent acquisition in a dual mode that simultaneously collects precursor ions and product ions at low and ramped collision energies, respectively. However, algorithmic analysis of large-scale multivariate data of comprehensive drug screening as well as the positivity criteria of drug identification have not been systematically investigated. It is also unclear whether ion ratio (IR), the intensity ratio of a defined product ion divided by the precursor ion, is a stable parameter that can be incorporated into the MSE/QTOF data analysis algorithm. IR of 91 drugs were experimentally determined and variation of IR was investigated across 5 concentrations measured on 3 different days. A data-driven machine learning approach was employed to develop multivariate linear regression (MLR) models incorporating mass error, retention time, number of detected fragment ions and IR, accuracy of isotope abundance, and peak response using drug-supplemented urine samples. Performance of the models was evaluated in an independent data set of unknown clinical urine samples in comparison with the results of manual analysis. IR of most compounds acquired by MSE/QTOF were low and concentration-dependent (i.e., IR increased at higher concentrations). We developed an MLR model with composite score outputs incorporating 7 parameters to predict positive drug identification. The model achieved a mean accuracy of 89.38% in the validation set and 87.92% agreement in the test set. The MLR model incorporating all contributing parameters can serve as a decision-support tool to facilitate objective drug identification using UPLC-MSE/QTOF.

Opportunities and Challenges in Repeated Revisions to Pull-Requests: An Empirical Study

Background: The Pull-Request (PR) model is a widespread approach adopted by open source software (OSS) projects to support collaborative software development. However, it is often challenging to continuously evaluate and revise PRs in several iterations of code reviewsinvolving technical and social aspects. Aim: Our objective is twofold: identifying best practices for effective collaboration in continuous PR improvement and uncovering problems that deserve special attention to improve collaboration efficiency and productivity. Method: We conducted a mixed-methods empirical study of repeatedly revised PRs (i.e. those that have undergone a high number of revisions). Historical trace data of five long-lived popular GitHub projects were used for manual investigation of practices for requesting changes to PRs and reasons for nonacceptance of repeatedly revised PRs. Surveys of OSS practitioners were conducted to evaluate the results of manual analysis and to provide additional insights into developers' willingness regarding PR revisions and factors causing avoidable revisions in practice. Results: The main results of our research were as follows: (1) We identified 15 code review practices for requesting changes to PRs, among which practices with respect to explaining the reasoning behind requested changes and tracking the progress of PR review and revision were undervalued by reviewers; (2) While submitters can in general undergo 1-5 rounds of revisions, they are willing to offer more revisions when they are in a friendly community and receive helpful feedback; (3) We revealed 11 factors causing avoidable revisions regarding to reviewers' feedback, code review policy, pre-submission issues, and implementation of new revisions; and (4) Nonacceptance of repeatedly revised PRs was due mainly to inactivity of submitters or reviewers and being superseded for better maintenance. Finally, based on these findings, we proposed recommendations and implications for OSS practitioners and tool designers to facilitate efficient collaboration in PR revisions.

Development of a simulation model of energy-saving system based on CCGT-110 and ABСM for energy and thermodynamic analysis

Objectives.Simulation modeling is increasingly being used for the study of complex economic, technical, biological, etc. systems. Such systems are characterized by multifactorial relationships of their functioning, nonlinear dependencies between system elements and stochasticity of their parameters, etc. The purpose of this work is to develop a simulation model based on the C# programming language for the energy-saving CCGT-110 and ABCM system based on the results of manual analysis according to the data of a full-scale experiment.Method.Methods of linear and nonlinear approximation, methods of energy and thermodynamic analysis, as well as methods of mathematical simulation modeling are used to develop the simulation model.Result.The result of this work is the developed software SAESS 3.0, which allows you to analyze the operation of the CCGT-110 and ABCM systems together and separately in a wide range of parameters and in real time. Conclusion.To assess the adequacy of the developed program, a comparative analysis of software and manual calculation was carried out. Deviations do not exceed an average of 3 %, which confirms the reliability of the simulation model.

Bayesian approach to automatic mass-spectrum peak identification in atom probe tomography

Identification of mass-spectrum peaks is an indispensable step of an atom-probe tomography reconstruction process and can be a time-consuming procedure, vulnerable to errors, if performed manually. We propose a Bayesian approach to the peak identification problem, based on ranking of candidate ions according to their calculated posterior probabilities. The sample model is reconstructed by iteratively accepting top-ranked ions while taking into account prior information, models of experimental errors, and the already accepted ions. The designed approach has been applied to a number of time-of-flight mass spectra, measured for inorganic samples, and enabled a reliable construction of sample models, consistent with the results of manual analysis. Additionally, a “sliding window” approach for an accurate and efficient peak decomposition of a mass spectrum was established on the base of Fisher information.

Supersaturation-controlled microcrystallization and visualization analysis for serial femtosecond crystallography

Time-resolved serial femtosecond crystallography with X-ray free electron laser (XFEL) holds the potential to view fast reactions occurring at near-physiological temperature. However, production and characterization of homogeneous micron-sized protein crystals at high density remain a bottleneck, due to the lack of the necessary equipments in ordinary laboratories. We describe here supersaturation-controlled microcrystallization and visualization and analysis tools that can be easily used in any laboratory. The microcrystallization conditions of the influenza virus hemagglutinin were initially obtained with low reproducibility, which was improved by employing a rapid evaporation of hanging drops. Supersaturation-controlled microcrystallization was then developed in a vapor diffusion mode, where supersaturation was induced by evaporation in hanging drops sequentially for durations ranging from 30 sec to 3 min, depending on the protein. It was applied successfully to the microcrystal formation of lysozyme, ferritin and hemagglutinin with high density. Moreover, visualization and analysis tools were developed to characterize the microcrystals observed by light microscopy. The size and density distributions of microcrystals analyzed by the tools were found to be consistent with the results of manual analysis, further validated by high-resolution microscopic analyses. Our supersaturation-controlled microcrystallization and visualization and analysis tools will provide universal access to successful XFEL studies.

Objective Identification of Trough Lines Using Gridded Wind Field Data

An objective method was developed to analyze longwave and shortwave trough lines in wind field data using different methods, given that these trough lines were researched in different ways. Longwave trough lines were analyzed by locating the cyclonic center and filtering candidate trough points simultaneously; the candidate longwave trough points were then traced based on distance and angle conditions. Next, candidate shortwave trough points were determined based on angular deflection and vorticity data, which were clustered and fitted to a curve for extraction. This method was applied to wind field data from the National Center for Environmental Prediction (NCEP) to analyze trough lines in East Asia and South Asia. The experimental results show that our method can effectively identify trough lines by comparing them with manual analysis results. The statistical results indicate that the method more precisely identifies longwave trough lines than shortwave trough lines, and that trough lines during the fall and winter are more accurately and effectively identified than those during the spring and summer.

Automated width measurements of Martian dust devil tracks

Studying dust devils is important to better understand Mars climate and resurfacing phenomena. This paper presents an automated approach to calculate the width of tracks in orbital images. The method is based on Mathematical Morphology and was applied to a set of 200 HiRISE and MOC images of five Mars quadrangles, which were Aeolis, Argyre, Noachis, Hellas and Eridania. Information obtained by our method was compared with results of manual analysis performed by other authors. In addition, we show that track widths do not follow a normal distribution.

Classification of creep crack and cavitation sites in tempered martensite ferritic steel microstructures using MTEX toolbox for EBSD

Tempered martensite ferritic steels exhibit a complex, hierarchical microstructure. Previous work has demonstrated the utility of electron backscatter diffraction (EBSD) analysis methods to classify crack and cavitation sites in terms of the substructural units and their boundaries. However, manual, interactive application of such methods is time consuming. The open-source MTEX toolbox for MATLAB allows scripting and automation of EBSD data analysis procedures. Here we present a validation of MTEX-based methods for identification of prior austenite grains, blocks and packets against the results of manual analysis for two example datasets, one exhibiting cracking and the other, cavitation.

Myocardial Perfusion: Near-automated Evaluation from Contrast-enhanced MR Images Obtained at Rest and during Vasodilator Stress

To develop and validate a technique for near-automated definition of myocardial regions of interest suitable for perfusion evaluation during vasodilator stress cardiac magnetic resonance (MR) imaging. The institutional review board approved the study protocol, and all patients provided informed consent. Image noise density distribution was used as a basis for endocardial and epicardial border detection combined with nonrigid registration. This method was tested in 42 patients undergoing contrast material-enhanced cardiac MR imaging (at 1.5 T) at rest and during vasodilator (adenosine or regadenoson) stress, including 15 subjects with normal myocardial perfusion and 27 patients referred for coronary angiography. Contrast enhancement-time curves were near-automatically generated and were used to calculate perfusion indexes. The results were compared with results of conventional manual analysis, using quantitative coronary angiography results as a reference for stenosis greater than 50%. Statistical analyses included the Student t test, linear regression, Bland-Altman analysis, and κ statistics. Analysis of one sequence required less than 1 minute and resulted in high-quality contrast enhancement curves both at rest and stress (mean signal-to-noise ratios, 17±7 [standard deviation] and 22±8, respectively), showing expected patterns of first-pass perfusion. Perfusion indexes accurately depicted stress-induced hyperemia (increased upslope, from 6.7 sec(-1)±2.3 to 15.6 sec(-1)±5.9; P<.0001). Measured segmental pixel intensities correlated highly with results of manual analysis (r=0.95). The derived perfusion indexes also correlated highly with (r up to 0.94) and showed the same diagnostic accuracy as manual analysis (area under the receiver operating characteristic curve, up to 0.72 vs 0.73). Despite the dynamic nature of contrast-enhanced image sequences and respiratory motion, fast near-automated detection of myocardial segments and accurate quantification of tissue contrast is feasible at rest and during vasodilator stress. This technique, shown to be as accurate as conventional manual analysis, allows detection of stress-induced perfusion abnormalities.

INVESTIGATION IN SELECTING THE OPTIMUM AIRPORT RUNWAY ORIENTATION WITH SPECIAL REFERENCE TO EGYPTIAN AIRPORTS

Determination of a runway orientation is a critical task in the planning and design of an airport. Runways usually oriented in the direction of the prevailing winds. The best direction can be decided through proper execution of wind analysis for designated area. In this study, wind analysis is conducted by manual analysis and computer analysis to check the accuracy of used software in computer analysis by comparing their results with the manual procedure. The manual analysis represented by windrose type II while the computer analysis represented by two software FAA Airport design and Windrose PRO. In order to analyze the available local wind observations with windrose II manual procedure and FAA Airport design software they must be converted to suitable windrose statistics so that a third software should be used . In this study WRPLOT View software is used to do this task. In this study three case studies Aswan international airport, Al Nozha international airport and Marsa Alam international airport were studied. These cases studies subject to wind analysis by use of manual analysis and computer analysis. For FAA Airport Design and WindRose PRO software there were small differences between its results and windrose II manual analysis results. In order to verify the optimization process in each case study, a comparison was made between existing runways orientation and estimated optimum runways orientation. For Aswan international airport the existing runway which has actual orientation of 170.88/350.88 which provides 98.07% wind coverage while the optimum runway orientation is 174/354 which provides 98.2% wind coverage. For Al Nozha there are two existing runways which have actual orientation of 45.06/225.07 and 179.99/359.99 which provides 84.11% and 93.27% wind coverage respectively while the optimum runway orientation is one runway with orientation of 146/326 which provides 96.04% wind coverage. For Marsa Alam international airport the existing runway which has actual orientation of 149.75/329.76 which provides 99.65% wind coverage while the optimum runway orientation is 156/336 which provides 99.72% wind coverage. Parametric analysis applied on each case study in order to studying the effect of each controlling parameter on wind coverage. This analysis is proceed by use of FAA Airport Design software because it allow the designer to keep the other parameters fixed while changing one of them. These parameters are number of runways, runway orientation, maximum allowable crosswind component and maximum allowable tailwind component.

1H NMR-Based Metabolomic Analysis of Liver, Serum, and Brain Following Ethanol Administration in Rats

Ethanol is a widely used drug that is consumed in large amounts for pharmacologic effects. Elimination of ethanol alters metabolism in the liver and throughout an organism. Ethanol's effect on metabolites can influence the regulation of key pathways such as gluconeogenesis. We adopted a proton NMR-based metabolomic approach to study ethanol-induced metabolic changes in liver, blood, and brain tissue from rats exposed to either a single dose of ethanol or a chronic 4 day binge-ethanol protocol. Both acute and binge ethanol caused (i) decreased glucose, lactate, and alanine in liver and serum; (ii) increased acetate in liver and serum; and (iii) increased acetoacetate in serum. Binge-ethanol increased liver beta-hydroxybutyrate and decreased betaine. Pretreatment with the antioxidant butylated hydroxytoluene (BHT) increased betaine and reduced ethyl glucuronide (EtG) in livers of binge-ethanol animals, as compared to those not pretreated with BHT. We found no change in brain metabolites after a single dose of ethanol. Unsupervised principal component (PC) analysis of spectral data from liver and serum successfully discriminated treatment groups, based largely on the biochemical differences outlined above, confirming the results of manual analysis. To explain the observed lack of gluconeogenesis following ethanol treatment and to resolve apparently discordant results from previous studies, we propose a model in which decreased hepatic alanine removes inhibition on pyruvate kinase, thus permitting a futile cycle that diverts phosphoenolpyruvate away from gluconeogenesis. This is a new mechanism that biochemically elucidates the well-known, yet unexplained, "empty calorie" phenomenon of ethanol. Reduction of EtG by pretreatment with BHT suggests that BHT and perhaps other compounds may alter the pharmacokinetics of EtG so that EtG may not always be a sensitive marker for ethanol abuse.

Incorporating topic transition in topic detection and tracking algorithms

Topics often transit among documents in a document collection. To improve the accuracy of the topic detection and tracking (TDT) algorithms in discovering topics or classifying documents, it is necessary to make full use of this kind of topic transition information. However, TDT algorithms usually find topics based on topic models, such as LDA, pLSI, etc., which are a kind of mixture model and make the topic transition difficult to be denoted and implemented. A topic transition model representation based on hidden Markov model is present, and learning the topic transition from documents is discussed. Based on the model, two TDT algorithms incorporating topic transition, i.e. topic discovering and document classifying, are provided to show the application of the proposed model. Experiments on two real-world document collections are done with the two algorithms, and performance comparison with other similar algorithm shows that the accuracy can achieve 93% for topic discovering in Reuters-21578, and 97.3% in document classifying. Furthermore, topic transition discovered by the algorithm on a dataset which was collected from a BBS website is consistent with the manual analysis results.

High-throughput flow cytometry: validation in microvolume bioassays.

We recently reported an automated sample handling system, designated HyperCyt, by which samples are aspirated from microplate wells and delivered to the flow cytometer for analysis at rates approaching 100 samples per minute. In this approach, an autosampler and peristaltic pump introduce samples into a tubing line that directly connects to the flow cytometer. Air bubbles are inserted between samples to prevent sample dispersion. In the present work, we compare results of HyperCyt with those of conventional manual flow cytometric analysis in representative flow cytometric bioassays and describe a cell suspension method in which HyperCyt exploits the use of microvolume wells. Human eosinophils and neutrophils were treated with trypsin to generate a wide (>25-fold) range of membrane P-selectin glycoprotein ligand-1 (PSGL-1) expression and then stained with fluorescent anti-PSGL-1 antibodies. Human peripheral blood mononuclear cells were stained with fluorescein isothiocyanate- and phycoerythrin-conjugated monoclonal antibodies for multiparameter immunophenotype analysis. U937 cells labeled with PKH62GL were used to assess cell settling in microplate wells. Differences in PSGL-1 expression levels were detected by HyperCyt autosampling of leukocytes from 96-well plates at an analysis rate of approximately 1.5 s/well. HyperCyt measurements linearly correlated with parallel manual measurements (r(2) = 0.98). Lymphocyte subpopulations were accurately distinguished and reproducibly quantified in multiparameter immunophenotyping assays performed over a range of HyperCyt analysis rates (1.4-5.5 s/sample). When assay volumes were reduced to 10 microl/well in 60-well Terasaki plates, cells could be maintained in uniform suspension for up to 30 min by periodically inverting plates on a rotating carousel before HyperCyt analysis. HyperCyt analysis of five fluorescence-level Cyto-Plex beads sampled from Terasaki plate microwells at 2.5 s/well produced highly reproducible results over a wide range of input bead concentrations (from 7 x 10(5) to 20 x 10(6) beads/ml) that linearly correlated with manual analysis results. The HyperCyt autosampling system enabled a 10-fold or greater increase in sample throughput compared with conventional manual flow cytometric sample analysis, with comparable analysis results. Assays were performed efficiently in 10-microl volumes to enable significant reagent cost savings, use of quantity-limited reagents at otherwise prohibitive concentrations, and maintenance of uniform suspensions of cells for prolonged periods.