Accuracy Of Criteria Research Articles

Physico-chemical studies of non-aqueous binary liquid mixtures of N-methyl aniline with amino alcohols at various temperatures

ABSTRACT Densities (ρ), speeds of sound (u) and viscosities (η) for three binary mixtures of N-methyl aniline with amino alcohols (3-amino-propan-1-ol, 2-amino-2-methyl-propan-1-ol and 1-amino propan-2-ol) were measured at temperatures ranging from 303.15 to 313.15 K and at atmospheric pressure across the entire composition range. Excess molar volume, excess isentropic compressibility, deviation in viscosity, and excess Gibbs free energy of activation of viscous flow were calculated using experimental data. Partial molar properties and infinite dilution molar partial properties were also determined for each binary system. The Prigogine-Flory-Patterson theory is used to identify the most important interaction. The results of the Jouyban-Acree model are discussed in terms of the mean relative deviation and individual relative deviation between the calculated and experimental densities, speed of sound, and viscosities as an accuracy criterion. FTIR studies have also been added to confirm the experimental findings of the investigated mixtures.

Use of Natural Language Processing to Extract and Classify Papillary Thyroid Cancer Features From Surgical Pathology Reports

BackgroundWe aim to use Natural Language Processing to automate the extraction and classification of thyroid cancer risk factors from pathology reports. MethodsWe analyzed 1410 surgical pathology reports from adult papillary thyroid cancer patients from 2010 to 2019. Structured and nonstructured reports were used to create a consensus-based ground truth dictionary and categorized them into modified recurrence risk levels. Nonstructured reports were narrative, while structured reports followed standardized formats. We developed ThyroPath, a rule-based Natural Language Processing pipeline, to extract and classify thyroid cancer features into risk categories. Training involved 225 reports (150 structured, 75 unstructured), with testing on 170 reports (120 structured, 50 unstructured) for evaluation. The pipeline's performance was assessed using both strict and lenient criteria for accuracy, precision, recall, and F1-score; a metric that combines precision and recall evaluation. ResultsIn extraction tasks, ThyroPath achieved overall strict F-1 scores of 93% for structured reports and 90% for unstructured reports, covering 18 thyroid cancer pathology features. In classification tasks, ThyroPath-extracted information demonstrated an overall accuracy of 93% in categorizing reports based on their corresponding guideline-based risk of recurrence: 76.9% for high-risk, 86.8% for intermediate risk, and 100% for both low and very low-risk cases. However, ThyroPath achieved 100% accuracy across all risk categories with human extracted pathology information. ConclusionsThyroPath shows promise in automating the extraction and risk recurrence classification of thyroid pathology reports at large scale. It offers a solution to laborious manual reviews and advancing virtual registries. However, it requires further validation before implementation.

Robust laser phase noise measurement by integration heterodyne for coherent beam combining applications.

Phase noise characteristics are critical for coherent beam combination engineering. Heterodyne with integration method for phase noise measurement has been studied numerically and experimentally, which reveals that the method is not only simple to implement with the least equipment but also capable of phase retrieval using under-sampling data. The integration method is compared with the traditional low-pass filter (LPF) method from both numerical and experimental perspectives. By introducing an evaluation criterion of measurement accuracy, the errors of the integration method are 0.44% and 0.08% for white noise and pink noise cases, respectively, which are smaller than that achieved by LPF one (1.52% and 0.25%). The errors of the integration method are below 1.4% when under-sampling data has been employed, which means that large consumption of data processing can be avoided, and the method is robust. Phase noise measurements in quiet laboratory and disturbed conditions are implemented, and the error between the results of the sampling rate of 250 MHz and 31.25 MHz is less than 0.08%, which is consistent with the simulation and demonstrates the excellent performance of the integration method.

Comparing Container Closure Integrity Test Methods - Performance of Headspace Carbon Dioxide Analysis versus Helium Leakage Using Positive Controls.

As described in USP Chapter <1207>, the deterministic leak test methods using laser-based gas headspace analysis and helium leakage are those with the highest sensitivities. As stated in the chapter, ″no single package leak test or package seal quality test method is applicable to all product-package systems″; therefore, knowing the advantages and disadvantages of both of these techniques, and the extent to which they can be substituted for each other, is valuable. In an effort to begin addressing this issue, a systematic study using these two techniques has been performed. This study used the same well-defined positive controls prepared with microcapillaries for both measurement techniques. For the headspace gas analysis technique, the headspace carbon dioxide content was measured at multiple timepoints during three separate conditioning cycles using either a 0.5, 1.0, or 2.0 bar CO2 overpressure; the observed change in headspace carbon dioxide was then used to determine an ingress rate for each positive control. For the helium leakage technique, the positive controls were measured with a standard helium leak detector with 100% helium atmosphere on the atmospheric pressure side of the artificial defects. The resulting leakage rates from both techniques were compared for ingress into both ISO 2R and ISO 10R vials. The obtained correlation between helium and carbon dioxide leakage rates resulted in a minimum R2 coefficient of 0.98 across all 12 runs. Additionally, both setups met the acceptance criteria for accuracy with their respective calibrated standards.

Analytical performance of publicly dispensed glucometers in primary health care in a southern Brazilian city

AimsThis study aimed to assess the use of glucometers by patients and the analytical performance of glucometers provided by the primary care services. MethodsThe analytical performance of 48 glucometers Accu-Chek® Active, was assessed through quintuplicate analyses of one Roche and one PNCQ (National Quality Control Program) control sample at different concentrations; 31 were also evaluated by a single proficiency testing sample. The evaluation metrics included imprecision, bias, and total error and were measured according to quality specifications based on biological variation (QSBV). Glucometer users answered a questionnaire regarding their experience. ResultsAmong the 48 glucometers evaluated with internal control samples, 17 met precision criteria at both control levels according to QSBV, while 24 met the criteria at only one control level. Of the 31 glucometers further evaluated through proficiency test, 11 met accuracy criteria according to QSBV, and only one device showed an unacceptable result. Out of these 31, only 15 demonstrated a total error within the acceptable maximum limits based on QSBV. ConclusionsOverall, our findings showed that patients had a good understanding of glucometer usage and suggested that some glucometers should be replaced, as they sometimes failed to meet even the manufacturer’s acceptable variation limits, and/or did not meet QSBV.

Non-Ideal Push–Pull Converter Model: Trade-Off between Complexity and Practical Feasibility in Terms of Topology, Power and Operating Frequency

Power converters are the basic elements of any power electronics system in many areas and applications. Among them, the push–pull converter topology is one of the most widespread due to its high efficiency, versatility, galvanic isolation, reduced number of switching devices and the possibility of implementing high conversion ratios with respect to non-isolated topologies. Optimal design and control requires very accurate models that consider all the non-idealities associated with the actual converter. However, this leads to the use of high-order models, which are impractical for the design of model-based controllers in real-time applications. To obtain a trade-off model that combines the criteria of simplicity and accuracy, it is appropriate to assess whether it is necessary to consider all non-idealities to accurately model the dynamic response of the converter. For this purpose, this paper proposes a methodology based on a sensitivity analysis that allows quantifying the impact of each non-ideality on the converter behaviour response as a function of the converter topology, power and frequency. As a result of the study, practical models that combine the trade-off between precision and simplicity are obtained. The behaviour of the simplified models for each topology was evaluated and validated by simulation against the most complete and accurate non-ideal model found in the literature. The results have been excellent, with an error rate of less than 5% in all cases.

Accuracy of Automatic Processing of Speech-Language Pathologist and Child Talk During School-Based Therapy Sessions.

This study examines the accuracy of Interaction Detection in Early Childhood Settings (IDEAS), a program that automatically transcribes audio files and estimates linguistic units relevant to speech-language therapy, including part-of-speech units that represent features of language complexity, such as adjectives and coordinating conjunctions. Forty-five video-recorded speech-language therapy sessions involving 27 speech-language pathologists (SLPs) and 56 children were used. The F measure determines the accuracy of IDEAS diarization (i.e., speech segmentation and speaker classification). Two additional evaluation metrics, namely, median absolute relative error and correlation, indicate the accuracy of IDEAS for the estimation of linguistic units as compared with two conditions, namely, Oracle (manual diarization) and Voice Type Classifier (existing diarizer with acceptable accuracy). The high F measure for SLP talk data suggests high accuracy of IDEAS diarization for SLP talk but less so for child talk. These differences are reflected in the accuracy of IDEAS linguistic unit estimates. IDEAS median absolute relative error and correlation values for nine of the 10 SLP linguistic unit estimates meet the accuracy criteria, but none of the child linguistic unit estimates meet these criteria. The type of linguistic units also affects IDEAS accuracy. IDEAS was tailored to educational settings to automatically convert audio recordings into text and to provide linguistic unit estimates in speech-language therapy sessions and classroom settings. Although not perfect, IDEAS is reliable in automatically capturing and returning linguistic units, especially in SLP talk, that are relevant in research and practice. The tool offers a way to automatically measure SLP talk in clinical settings, which will support research seeking to understand how SLP talk influences children's language growth.

Reliability-oriented design of PCM thermodimensionally stable space structures

The problem of ensuring the specified thermo-dimensional stability of structures from laminated polymer composite materials for the service life period is considered. A method of reliability-oriented design of a thermo-dimensionally stable composite structure is proposed, according to which its design parameters are set with regard to the possibility of obtaining thermal strain properties under specific processing and the changes of these properties for the operational conditions and duration of using the article as intended. Within the framework of the presented approach, the features of design upon the dimensional accuracy and stability criterion when meeting the requirements of strength and stiffness are discussed, an algorithm of a packaged solution of the design task is given.

An Intrusion Detection System on The Internet of Things Using Deep Learning and Multi-objective Enhanced Gorilla Troops Optimizer

In recent years, developed Intrusion Detection Systems (IDSs) perform a vital function in improving security and anomaly detection. The effectiveness of deep learning-based methods has been proven in extracting better features and more accurate classification than other methods. In this paper, a feature extraction with convolutional neural network on Internet of Things (IoT) called FECNNIoT is designed and implemented to better detect anomalies on the IoT. Also, a binary multi-objective enhance of the Gorilla troops optimizer called BMEGTO is developed for effective feature selection. Finally, the combination of FECNNIoT and BMEGTO and KNN algorithm-based classification technique has led to the presentation of a hybrid method called CNN-BMEGTO-KNN. In the next step, the proposed model is implemented on two benchmark data sets, NSL-KDD and TON-IoT and tested regarding the accuracy, precision, recall, and F1-score criteria. The proposed CNN-BMEGTO-KNN model has reached 99.99% and 99.86% accuracy on TON-IoT and NSL-KDD datasets, respectively. In addition, the proposed BMEGTO method can identify about 27% and 25% of the effective features of the NSL-KDD and TON-IoT datasets, respectively.

Familial cross-testicular ectopia: a clinical case report

Cross or transverse testicular ectopia is a rare congenital condition of the reproductive system that involves the migration of a testicle into the opposite inguinal canal, along with the presence of an inguinal hernia on the same side as the ectopic testicle. In the modern literature, there are discussions about diagnostic issues, particularly the use of ultrasound scanning and magnetic resonance imaging to diagnose this condition. However, it is the results of laparoscopic examination that determine the most accurate criteria for surgical treatment. Many publications discuss the choice of surgical tactics, including separate transabdominal orchiopexy, with or without laparoscopic assistance; transeptal orchiopexy on both sides of the scrotum; and rare cases of orchiopexy for both testicles on one side of the scrotum. Ultimately, the choice of surgery depends on the individual characteristics and needs of the patient, and the surgeon should make the decision based on these factors. The article describes, for the first time, a case of familial testicular ectopia with bilateral inguinal hernia in siblings who underwent surgery using laparoscopic assistance. The method used was single-trocar laparoscopic access with transscrotal transeptal orchiopexy and simultaneous bilateral puncture of the inguinal ring and suture. During the long-term follow-up period (50 and 20 months after surgery) in both siblings, there were no signs of malformation or atrophy of the gonads.

Revisiting the nexus between financialization and natural Resource efficiency through the lens of financial development and green industrial optimization

Responsible natural resource management has become critical for ensuring the effective use of resources jeopardizing future generations' needs. Financialization based on artificial intelligence, green finance, and lower economic risks are important in this respect. The objective of this study is to explore the impact of financialization and economic uncertainty on the natural resource market. The analysis covers the period from 1980 to 2021 and is performed for selected South Asian Association for Regional Cooperation (SAARC) countries. In addition, among economic financialization processes, artificial intelligence (AI) based financial management (FM) is more significant than domestic financialization strategies. For that purpose, Artificial Neural Network (ANN) method and pooled regression analysis are employed for the empirical analysis. According to the findings, economic uncertainty has a stronger influence than economic financialization. Therefore, risk mitigation plays a larger role in creating shocks in all macroeconomic indicators and, as a result, on the natural resource market. The accuracy measures to support the finding's robustness like the value of R2 is highly acceptable and errors are minimum (% MAPE is 5.06 which falls under the criteria of high accuracy) in both testing and training datasets approximately by 50%. In addition, the findings of Garson method reveal that economic uncertainty and AI based FM are significantly important for the natural resource market as their important values (0.27, 0.26, and 0.20) touch the maximum importance statistics (0.30). The study, therefore, suggests that authorities in South Asian countries should focus on AI-based financial advancement and integrate AI into the traditional financialization methods to upgrade the regional economic financial system, which will help in regulating and improving the efficiency of the resource market. The results also provide the graphical and tabulation formation of financialization and economic uncertainty in SAARC countries. Additionally, analysis on the chosen variable by suing PCA has also been made to transform the dataset. Along with it, the regional corporation is crucial for dwindling economic uncertainty and promoting a steady growth and sustainable environment through the maintenance of the natural resource market.

Histopathologic Evaluation of Atypical Fibroxanthoma or Pleomorphic Dermal Sarcoma Debulk Specimen from Mohs Surgery: A Requirement for Their Proper Distinction.

Pleomorphic dermal sarcomas can be clinically aggressive, with a higher tendency to cause local recurrence, metastasis, and death. Atypical fibroxanthoma and pleomorphic dermal sarcoma are histopathologically similar, and their distinction requires a systematic examination of the entire excised tumor. Since Mohs micrographic surgery is commonly utilized to treat atypical fibroxanthoma, a histopathologic evaluation of debulk specimens by permanent pathology is prudent to avoid underdiagnosing pleomorphic dermal sarcoma. This approach can improve risk assessment and treatment decisions, ultimately enhancing patient outcomes. Also, the proper distinction will facilitate the future development of accurate staging criteria and additional treatment modalities.

Investigation of Wellbore Instability in Southern Rumaila Oil Field

This study aims to address the issue by providing valuable insights into the factors contributing to the wellbore instability and proposing effective measures to mitigate the problem in the southern part of the Rumaila oil field. A comprehensive one-dimensional mechanical earth model (1D MEM) was developed by utilizing various logs data from 4 wells across the south part of this field, including gamma ray, bit size, caliper, bulk density, and sonic compression and shear logs. The model was validated with laboratory tests, including Brazilin and Triaxial tests, as well as repeated formation tests. To analyze the wellbore stability, three different failure criteria, namely Mohr-Coulomb, Mogi-Coulomb, and Modified lade, were employed. The results indicated that the Mogi-Coulomb criterion was the most accurate failure criterion in predicting rock failure. Wellbore instability problems had been observed across the shale sections throughout the Rumaila oil field, particularly through Tanuma, Khasib, top and bottom of Ahmadi, Nahr Umr, and Upper Shale members and Middle Shale members of Zubair formations. The 1D MEM results indicated that Shaly formations exhibited low stiffness rocks (low Young's Modulus (YME)), low rock strength, and high Poisson's ratio (PR), suggesting potential challenges related to wellbore instability in the Tanuma, top and bottom of Ahmadi, Nahr-Umr, and Zubair formations. A sensitivity analysis was performed to determine the safest mud weight and the optimum well trajectory for future drilling operations. According to the updated mud window of this field in 2023, the pressure in the Mishrif and Zubair formations was reinforced by injection wells, as it was noted that the pressure behavior shifted from depletion (2000 Psi). Based on the findings of this study, the good inclination of (0-25°) can be drilled with the mud weight of 1.24-1.26 sg, while the good inclination of (25-40°) can be drilled with the mud weight of 1.28-1.30 sg in all directions (i.e., all azimuths). The stress regime in most of the formations was found to be a strike-slip to a normal fault regime. The findings of this study can significantly benefit the oil industry and enhance overall productivity.

Assessing Generative Pretrained Transformers (GPT) in Clinical Decision-Making: Comparative Analysis of GPT-3.5 and GPT-4.

Artificial intelligence, particularly chatbot systems, is becoming an instrumental tool in health care, aiding clinical decision-making and patient engagement. This study aims to analyze the performance of ChatGPT-3.5 and ChatGPT-4 in addressing complex clinical and ethical dilemmas, and to illustrate their potential role in health care decision-making while comparing seniors' and residents' ratings, and specific question types. A total of 4 specialized physicians formulated 176 real-world clinical questions. A total of 8 senior physicians and residents assessed responses from GPT-3.5 and GPT-4 on a 1-5 scale across 5 categories: accuracy, relevance, clarity, utility, and comprehensiveness. Evaluations were conducted within internal medicine, emergency medicine, and ethics. Comparisons were made globally, between seniors and residents, and across classifications. Both GPT models received high mean scores (4.4, SD 0.8 for GPT-4 and 4.1, SD 1.0 for GPT-3.5). GPT-4 outperformed GPT-3.5 across all rating dimensions, with seniors consistently rating responses higher than residents for both models. Specifically, seniors rated GPT-4 as more beneficial and complete (mean 4.6 vs 4.0 and 4.6 vs 4.1, respectively; P<.001), and GPT-3.5 similarly (mean 4.1 vs 3.7 and 3.9 vs 3.5, respectively; P<.001). Ethical queries received the highest ratings for both models, with mean scores reflecting consistency across accuracy and completeness criteria. Distinctions among question types were significant, particularly for the GPT-4 mean scores in completeness across emergency, internal, and ethical questions (4.2, SD 1.0; 4.3, SD 0.8; and 4.5, SD 0.7, respectively; P<.001), and for GPT-3.5's accuracy, beneficial, and completeness dimensions. ChatGPT's potential to assist physicians with medical issues is promising, with prospects to enhance diagnostics, treatments, and ethics. While integration into clinical workflows may be valuable, it must complement, not replace, human expertise. Continued research is essential to ensure safe and effective implementation in clinical environments.

Artificial Neural Network-Based Real-Time Power Management for a Hybrid Renewable Source Applied for a Water Desalination System

Water desalination systems integrated with stand-alone hybrid energy sources offer a remarkable solution to the water–energy challenge. Given the complexity of these systems, selecting an appropriate energy management system is crucial. In this regard, employing artificial intelligence techniques to develop and validate an energy management system can be an effective approach for handling such intricate systems. Therefore, this paper presents an ANN-based energy management system (ANNEMS) for a pumping and desalination system connected to an isolated hybrid renewable energy source. Thus, a parametric sensitivity algorithm was developed to identify the optimal neural network architecture. The water–energy management-based supervised multi-layer perceptron neural network demonstrated effective power sharing within a short time frame, achieving accuracy criteria of RMSE, R, and R² between the actual and estimated electrical power of the three motor pumps. The ANNEMS is defined to facilitate real-time power sharing distribution among the various system motor pumps on the test bench, considering the generated power profile and water tank levels. The proposed strategy employs power field oriented control to maintain DC bus voltage stability. Experimental results from the implementation of the proposed ANNEMS are provided. Therein, the power levels of the three motor pumps demonstrated consistent adherence to their reference values. In summary, this study highlights the significance of selecting appropriate energy management for real-time experimental validation.

Evaluation and Refractive Results Comparison of MIOL-­SOFT-­2­-13 IOL Implantation with Foreign Models

Purpose. Evaluation and refractive results comparison of MIOL-­SOFT-­2­-13 (Reper­NN, Russia) IOL implantation with foreign models. Material and methods. The study included 816 patients (816 eyes) who underwent phacoemulsification (PE) with IOL implantation, divided into four groups depending on IOL model: MIOL­-SOFT-2-­13 (Reper­-NN, Russia) (n = 199); SA60AT (Alcon, USA) (n = 237); Adapt AO (Bausch&amp;Lomb, USA) (n = 179); Acryfold 601 (Appasamy Associates, India) (n = 201). All patients underwent optical biometry using IOL­-Master 500 (Carl Zeiss, Germany). A month after PE spherical equivalent of refraction was assessed by Topcon­8800 (Japan). Mean calculation error (ME) and mean absolute error (MAE) were used as a IOL calculation accuracy criterion. Results. Zeroing of ME allowed to determine real a­constant of MIOL-­SOFT­-2-­13 (119.83 instead of 118.4 declared by the manufacturer). MAE in the groups was: 0.39 ± 0.27, 0.33 ± 0.35, 0.38 ± 0.31 and 0.38 ± 0.30 D, respectively (p = 0.068). All IOLs demonstrated hitting the target refraction within ±1.00 D in more than 95 % of cases. Conclusion. MIOL­-SOFT­-2­-13 has comparable refractive results with other monofocal IOLs used in national medical insurance system. MIOL­-SOFT-­2­-13 achieves target refraction within ±1.00 D in 98 % of cases.To obtain optimal refractive results, an optimized a­constant of 118.83 is required.

Deterministic Localization for Fully Automatic Operation: A Survey and Experiments.

With the rapid development of fully automatic operation (FAO) and location-based services, the evaluation criteria of average localization accuracy can no longer meet our demands, in favor of deterministic localization. However, most localization researches modeled localization performance function and enhanced it by minimizing average localization root mean square error (RMSE). The performance degradation in a small region was not considered. In this paper, we present a survey of deterministic localization and analyze the relationship between accuracy and certainty. In this paper, two common solutions of localization enhancement are presented and their localization certainties are discussed. Furthermore, we carry out related localization enhancement experiments in rail transit line and analyze their improvement on deterministic localization. The experimental results show that the overall localization performance is improved, while the deterministic localization requires the stricter solution to promote.

An Alternative Microbiological Validation for an Online Water Bioburden Analyzer.

The Mettler-Toledo 7000RMS analyzer is a bio-fluorescent particle counter (BFPC) used to monitor real-time bioburden results from purified water (PW). Validation of the analyzer using 13 microorganisms and a low-intensity, fluorescent, polystyrene bead. During the execution of the validation, a laboratory water system that met PW quality standards was connected to the 7000RMS, and a syringe pump was used to introduce various concentrations of microorganisms and fluorescent polystyrene beads to the analyzer. Samples were collected and tested via the traditional membrane filtration (MF) method and the colony-forming unit (CFU) plate count results were compared to the auto-fluorescent unit (AFU) of the 7000RMS analyzer. The validation study was designed to follow the guidance in United States Pharmacopeia (USP) Chapter <1223>, European Pharmacopeia (EP) Chapter 5.1.6, and parenteral drug association (PDA) Technical Report 33. Concepts and strategies were adapted from EP Chapter 2.6.12 Microbiological Examination of Non-Sterile Products: Microbial Enumeration Tests, EP Chapter 10.2, EP Chapter 2.6.1 Sterility, USP Chapter <61> Microbiological Examination of Non-Sterile Products: Microbial Enumeration Tests, USP Chapter <71> Sterility Tests, and Japanese Pharmacopoeia (JP) General Information Chapter G8 Water: Quality Control of Water for Pharmaceutical Use. All pre-determined validation acceptance criteria for accuracy, specificity, precision, LOD, LOQ, linearity, and range were met. The 7000RMS demonstrated performance equivalence to the MF method per USP <1223> but characteristically lacked correlation to the CFU. This validation approach highlights the superior capabilities of the 7000RMS when compared against the traditional compendial MF testing method for PW.

A Validation of the Equivalence of the Cell-Based Potency Assay Method with a Mouse LD50 Bioassay for the Potency Testing of OnabotulinumtoxinA.

(1) Background: At present, the only potency assay approved in China for the in-country testing of botulinum toxin type A for injection products is the mouse bioassay (MBA). The Chinese market for neurotoxin products is rapidly expanding, but MBAs are subject to high variability due to individual variations in mice, as well as variations in injection sites, in addition to the limited number of batches tested for one MBA. Compared with the mLD50 method, the cell-based potency assay (CBPA) developed for the potency testing of onabotulinumtoxinA (BOTOX) by AbbVie not only does not use any experimental animals but also allows for significant time and cost savings. Due to the significant benefits conferred by the replacement of the mLD50 assay with CBPA in China, the CBPA method has been transferred, validated, and cross-validated to demonstrate the equivalence of the two potency methods. (2) Methods: The differentiated SiMa cells were treated with both BOTOX samples and the reference standard, and the cleaved SNAP25197 in the cell lysates was quantified using Chemi-ECL ELISA. A 4-PL model was used for the data fit and sample relative potency calculation. The method accuracy, linearity, repeatability, and intermediate precision were determined within the range of 50% to 200% of the labeled claim. A statistical equivalence of the two potency methods (CBPA and mLD50) was initially demonstrated by comparing the AbbVie CBPA data with NIFDC mLD50 data on a total of 167 commercial BOTOX lots (85 50U lots and 82 100U lots). In addition, six lots of onabotulinumtoxinA (three 50U and three 100U) were re-tested as cross-validation by these two methods for equivalence. (3) Results: The overall assay's accuracy and intermediate precision were determined as 104% and 9.2%, and the slope, R-square, and Y-intercept for linearity were determined as 1.071, 0.998, and 0.036, respectively. The repeatability was determined as 6.9%. The range with the acceptable criteria of accuracy, linearity, and precision was demonstrated as 50% to 200% of the labeled claim. The 95% equivalence statistic test using margins [80%, 125%] indicates that CBPA and mLD50 methods are equivalent for both BOTOX strengths (i.e., 50U and 100U). The relative potency data from cross-validation were within the range of ≥80% to ≤120%. (4) Conclusions: The CBPA meets all acceptance criteria and is equivalent to mLD50. The replacement of mLD50 with CBPA is well justified in terms of ensuring safety and efficacy, as well as for animal benefits.

Novel multi-spatial receptive field (MSRF) XGBoost method for predicting geological cross-section based on sparse borehole data

Due to the complex spatial features of geological formation, it remains a significant challenge to accurately predict geological cross-sections from limited borehole data. This study develops an innovative multi-spatial receptive field (MSRF) XGBoost approach, which encompasses classification and identification modules to forecast geological cross-sections using sparse borehole data. The classification module exclusively employs sparse borehole data to train a series of MSRF XGBoost models for soil classification. The identification module leverages all the trained models to generate potential predictions of unknown soil strata, automatically pinpointing the optimal one via Gaussian filtering and boundary similarity algorithms. A new boundary accuracy criterion is proposed to assess the prediction capacity of different models. Following this, the developed MSRF XGBoost method is compared with an existing conventional XGBoost method using both linear and nonlinear cases. The findings illustrate that our proposed method enhances the prediction accuracy for both linear and nonlinear geological cross-sections. Furthermore, the developed method is employed to determine a geological cross-section in the Netherlands using open-source borehole data. The accuracy of the method in predicting soil layers in all in situ boreholes reaches an impressive 90%, validating its effectiveness in practical geotechnical engineering.