Search

BACKGROUND: An accurate, rapid estimate of glomerular filtration rate (GFR) in kidney transplant patients affords early detection of transplant deterioration and timely intervention. This study compared the performance of serum creatinine (Cr) and cystatin C (CysC)-based GFR equations to measured GFR (mGFR) using iohexol among pediatric kidney transplant recipients. METHODS: CysC, Cr, and mGFR were obtained from 45 kidney transplant patients, 1-18 years old. Cr- and CysC-estimated GFR (eGFR) was compared against mGFR using the Cr-based (Bedside Schwartz, U25-Cr), CysC-based (Gentian CysC, CAPA, U25-CysC), and Cr-CysC combination (CKiD Cr-CysC, U25 Cr-CysC) equations in terms of bias, precision, and accuracy. Bland-Altman plots assessed the agreement between eGFR and mGFR. Secondary analyses evaluated the formulas in patients with biopsy-proven histological changes, and K/DOQI CKD staging. RESULTS: Bias was small with Gentian CysC (0.1 ml/min/1.73 m2); 88.9% and 37.8% of U25-CysC estimations were within 30% and 10% of mGFR, respectively. In subjects with histological changes on biopsy, Gentian CysC had a small bias and U25-CysC were more accurate-both with 83.3% of and 41.7% of estimates within 30% and 10% mGFR, respectively. Precision was better with U25-CysC, CKiD Cr-CysC, and U25 Cr-CysC. Bland-Altman plots showed the Bedside Schwartz, Gentian CysC, CAPA, and U25-CysC tend to overestimate GFR when > 100 ml/min/1.72 m2. CAPA misclassified CKD stage the least (whole cohort 24.4%, histological changes on biopsy 33.3%). CONCLUSIONS: In this small cohort, CysC-based equations with or without Cr may have better bias, precision, and accuracy in predicting GFR.

A variety of scattering-based, microscopy-based, and mobility-based methods are frequently used to probe the size distributions of colloidal nanoparticles with transmission electron microscopy (TEM) often considered to be the "gold standard". Charge detection mass spectrometry (CDMS) is an alternative method for nanoparticle characterization that can rapidly measure the mass and charge of individual nanoparticle ions with high accuracy. Two low polydispersity, ∼100 nm diameter nanoparticle size standards with different compositions (polymethyl methacrylate/polystyrene copolymer and 100% polystyrene) were characterized using both TEM and CDMS to explore the merits and complementary aspects of both methods. Mass and diameter distributions are rapidly obtained from CDMS measurements of thousands of individual ions of known spherical shape, requiring less time than TEM sample preparation and image analysis. TEM image-to-image variations resulted in a ∼1-2 nm range in the determined mean diameters whereas the CDMS mass precision of ∼1% in these experiments leads to a diameter uncertainty of just 0.3 nm. For the 100% polystyrene nanoparticles with known density, the CDMS and TEM particle diameter distributions were in excellent agreement. For the copolymer nanoparticles with unknown density, the diameter from TEM measurements combined with the mass from CDMS measurements enabled an accurate measurement of nanoparticle density. Differing extents of charging for the two nanoparticle standards measured by CDMS show that charging is sensitive to nanoparticle surface properties. A mixture of the two samples was separated based on their different extents of charging despite having overlapping mass distributions centered at 341.5 and 331.0 MDa.

Purpose: To investigate the accuracy of ChatGPT (Chat generative pretrained transformer), a large language model, in calculating sample size for sport-sciences and sports-medicine research studies. Methods: We conducted an analysis on 4 published papers (ie, examples 1–4) encompassing various study designs and approaches for calculating sample size in 3 sport-science and -medicine journals, including 3 randomized controlled trials and 1 survey paper. We provided ChatGPT with all necessary data such as mean, percentage SD, normal deviates (Zα/2 and Z1−β), and study design. Prompting from 1 example has subsequently been reused to gain insights into the reproducibility of the ChatGPT response. Results: ChatGPT correctly calculated the sample size for 1 randomized controlled trial but failed in the remaining 3 examples, including the incorrect identification of the formula in one example of a survey paper. After interaction with ChatGPT, the correct sample size was obtained for the survey paper. Intriguingly, when the prompt from Example 3 was reused, ChatGPT provided a completely different sample size than its initial response. Conclusions: While the use of artificial-intelligence tools holds great promise, it should be noted that it might lead to errors and inconsistencies in sample-size calculations even when the tool is fed with the necessary correct information. As artificial-intelligence technology continues to advance and learn from human feedback, there is hope for improvement in sample-size calculation and other research tasks. However, it is important for scientists to exercise caution in utilizing these tools. Future studies should assess more advanced/powerful versions of this tool (ie, ChatGPT4). [ABSTRACT FROM AUTHOR]

The world is progressing at a rapid rate, and with continuous advancements in technology, the need for cooperative spectrum sensing has evolved. Cooperative spectrum sensing is an approach used to enhance detection performance, wherein secondary users collaborate with each other to sense the spectrum and identify spectrum holes. As technology improves over time, the spectrum becomes increasingly allocated to primary users. The role of cooperative spectrum sensing in cognitive radio fulfills the essential requirement of protecting primary users from harmful interference. The progressive evolution of technology has led to a reduction in available spectrum, prompting the emergence of the concepts of cognitive radio and cooperative spectrum sensing. To begin with, this paper introduces the fundamental application of cooperative spectrum sensing algorithms, encompassing primary and secondary users' models and an energy model. Subsequently, three machine learning algorithms, namely K-means, support vector machine, and logistic regression, are explained, and their schematics are presented in detail. The proposed model uses supervised and unsupervised learning techniques to develop a cooperative spectrum sensing framework. It compares the performance of three machine learning algorithms, K-means clustering, logistics regression and support vector machine. The comparison is based on accuracy, recall and precision metrics, and the results show that the K-means clustering algorithm has better performance than the other two algorithms. The findings highlight the superiority of the K-means clustering algorithm over logistic regression and support vector machine. [ABSTRACT FROM AUTHOR]

During the analysis of a commingled human remains assemblage, pair‐matching is often conducted as part of the inventory to inform the DNA sampling strategy and to calculate the minimum or most likely number of individuals. As commingled assemblages become larger, pair‐matching becomes more difficult, and it is unknown whether accuracy declines. Therefore, a study to determine the accuracy rates of visual pair‐matching for multiple observers was conducted on a large, commingled human assemblage. The sample consisted of 580 left and right humeri (n = 287 and n = 293, respectively) from the commingled remains of the USS Oklahoma, which were undergoing analysis at the Defense POW/MIA Accounting Agency. Five anthropologists completed this study, determining humeri pairs with varying degrees of confidence and non‐pairs. The overall precision was 81.0% and ranged from 74.1% to 95.9% for participants, including all confidence levels. When considering only confident matches, the overall precision for all participants increased to 91.4%. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Materials and Methods Results Conclusions This study aims to examine differences in trueness and precision between surgical guides with (S) and without sleeves (SL). A secondary aim was to assess the impact of the sleeve‐to‐bone distance.Mandible replicas (n = 120) were printed from an STL file obtained from a clinical CBCT. The mandibles were divided into sleeved (S, n = 60) and sleeveless (SL, n = 60) groups, each further divided into three categories (n = 20 each) with different heights from the guide to the implant platform: 2 mm (H2), 4 mm (H4), or 6 mm (H6). Digital planning and surgical guide design were done for a 4.1 × 10 mm implant for site #30. Post‐op positions were captured using a scan body and lab scanner. Angular deviation was the primary outcome, with 3D and 2D deviations as secondary parameters. Statistical analysis included two‐sample t‐tests, and one‐way and two‐way ANOVA.Group S (2.41 ± 1.41°) had significantly greater angular deviation than Group SL (1.65 ± 0.93°; p = 0.0001). Angular deviation increased with sleeve‐to‐bone distance. H2 deviations were 1.48 ± 0.80° (S) vs. 1.02 ± 0.45° (SL; p < 0.05), H4: 2.36 ± 1.04° (S) vs. 1.48 ± 0.79° (SL; p < 0.05), H6: 3.37 ± 0.67° (S) vs. 2.46 ± 0.89° (SL; p < 0.05). 3D deviation at the implant platform was 0.36 ± 0.17 mm (S) vs. 0.30 ± 0.15 mm (SL; p < 0.05) and at the apex 0.74 ± 0.34 mm (S) vs. 0.53 ± 0.31 mm (SL; p < 0.01). Group SL at H2 had the smallest inter‐implant distance (0.53 ± 0.37°), while Group S at H4 had the largest (1.20 ± 0.84°; p < 0.05).Sleeveless guides are more accurate than sleeved guides, and angular deviation is influenced by the distance from the guide to the implant platform. [ABSTRACT FROM AUTHOR]

Thermal lens spectrometry is a high-sensitivity method for measuring the optical and thermal parameters of samples of different nature. To obtain both thermal diffusivity and absorbance-based signal measurements with high accuracy and precision, it is necessary to pay attention to the factors that influence the trueness of photothermal measurements. In this study, the features of liquid objects are studied, and the influence of optical and thermal effects accompanying photothermal phenomena are investigated. Thermal lens analysis of dispersed solutions and systems with photoinduced activity is associated with a large number of side effects, the impact of which on trueness is not always possible to determine. It is necessary to take into account the physicochemical properties and optical and morphological features of the nanophase and components exhibiting photoinduced activity. The results obtained make it possible to reduce systematic and random errors in determining the thermal-diffusivity-based and absorbance-based photothermal signals for liquid objects, and also contribute to a deeper understanding of the physicochemical processes in the sample. [ABSTRACT FROM AUTHOR]

Introduction: Since the introduction of nanorobotics, the discipline of medicinal chemistry has seen an exponential development in the uses of nanotechnology. One of the most potential uses of nanotechnology is in the creation of nanobots, which can be applied to a variety of industries such as medicine delivery, medical imaging, and even the benefits of nanobots include their small size, light weight, great flexibility, high sensitivity, and big thrust-to-weight ratio. Nanobots have several uses and are being investigated in many domains. This review’s objective is to provide an overview of the rapidly developing field of medicinal chemistry’s nanorobotics and its potential applications in disease detection, treatment, and prevention. Method: Several articles and newsletters are considered and used as a reference to collect information regarding nano and microbots and a brief information was written in accordance to use in medicine delivery. Results: Various review articles were taken into consideration to provide a deep knowledge on the utilization of nano and microbots in drug delivery and treatment therapy of several diseases. Conclusions: The main parts of the robots and the many kinds of nanobots are covered separately. The future perspective and initiatives that can help us realize our dreams of creating small robots that can move around inside our bodies, administering medication with previously unattainable precision, locating and eliminating infected cells, and most importantly making science fiction, a reality is finally covered. [ABSTRACT FROM AUTHOR]

SUMMARY: The accessory proteins Hyponastic‐like 1 (HYL1) and Serrated (SE) enhance the precise and efficient processing of miRNAs by Dicer‐like 1 (DCL1), which is important for proper miRNA function. However, other factors determining the precision and efficiency of miRNA biogenesis are not well‐known. Here, we found that an asymmetric bulge (AB) at the 3′ end of miR‐5p (produced from the 5′ arm of the pre‐miRNA) reduced the precision of the second cleavage, whereas an AB at other sites of miR‐5p mainly affected the accumulation level of miR‐5p in transient expression in Nicotiana benthamiana. In contrast, many ABs in miR‐3p (produced from the 3′ arm of the pre‐miRNA) impose strong negative impact on the processing precision and the accumulation level of miR‐5p in N. benthamiana. Arabidopsis DCL1/SE/HYL1 complex‐mediated miRNA processing was reconstituted in Saccharomyces cerevisiae to further investigate AB‐mediated interference with DCL1 processing. With this system, the positional effect of AB on miRNA processing was tested. The results showed that ABs on the middle of miR‐5p have less of an impact on DCL1 cleavage efficiency and precision, whereas those on miR‐3p or near the ends of miR‐5p strongly reduce DCL1 cleavage activity, precision or both. Studies using the yeast miRNA processing system and transgenic Arabidopsis also revealed the importance of the interaction between the 2‐nt 3′ overhang of pre‐miRNA and the 3′ overhang binding pocket (3′BP) on the precision of the second cleavage reaction for many endogenous miRNAs. These findings provide new insights into the mechanism of miRNA biogenesis. Significance Statement: Factors determining the precision and efficiency of miRNA biogenesis are not well‐known. This study found that an asymmetric bulge at different positions of miR‐5p and miR‐3p had different impacts on miRNA levels and processing precision and revealed the importance of the interaction between the 2‐nt 3′ overhang of pre‐miRNA and the 3′ overhang binding pocket (3'BP) on the precision of the second cleavage reaction for many endogenous miRNAs. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Well‐chosen biomarkers have the potential to increase the efficiency of clinical trials and drug discovery and should show good precision as well as clinical validity. METHODS: We suggest measures that operationalize these criteria and describe a general approach that can be used for inference‐based comparisons of biomarker performance. The methods are applied to measures obtained from structural magnetic resonance imaging (MRI) from individuals with mild dementia (n = 70) or mild cognitive impairment (MCI; n = 303) enrolled in the Alzheimer's Disease Neuroimaging Initiative. RESULTS: Ventricular volume and hippocampal volume showed the best precision in detecting change over time in both individuals with MCI and with dementia. Differences in clinical validity varied by group. DISCUSSION: The methodology presented provides a standardized framework for comparison of biomarkers across modalities and across different methods used to generate similar measures and will help in the search for the most promising biomarkers. Highlights: A framework for comparison of biomarkers on pre‐defined criteria is presented.Criteria for comparison include precision in capturing change and clinical validity.Ventricular volume has high precision in change for both dementia and mild cognitive impairment (MCI) trials.Imaging measures' performance in clinical validity varies more for dementia than for MCI. [ABSTRACT FROM AUTHOR]

Artificial Intelligence-based system for Tuberculosis (TB) detection has been proposed in this work. Manual diagnostic through radiologists can be misdiagnosis due to human error. Designing an artificial intelligence-based decision support system can help in the accurate prediction of TB through lung Chest X-ray (CXR) image. In the proposed work, data centric and model centric approaches are applied. In data centric approach, images play an important role in feature extraction. In this context, experimentation on six varied kinds of image enhancement applied to the publicly available TB image dataset along with data pre-processing and data augmentation. In model centric approach, three pre-trained Convolutional Neural Network (CNN) with modification with specialized layers are proposed. Comparative Study of six image enhancement techniques along with original dataset in behavior response with network architectures is evaluated for best performance. Evaluation of the networks is based on accuracy, precision, recall and AUC. Sharpening of images applied on Modified ResNet50 is the best performer with accuracy 99.05%, precision 98.87%, recall 100% and AUC of 99.29%. In comparability with original dataset, sharpened images performed 0.8% better in metric evaluation, which gives better classification approach and predictability. [ABSTRACT FROM AUTHOR]

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Polycrystalline diamond (PCD) is widely used for micro tools due to its high hardness and wear resistance. However, micro PCD tools face challenges in machining with high accuracy and efficiency. Therefore, electrical discharge machining grinding (EDM-grinding) composite machining was proposed. The effects of pulse discharge parameters on surface quality and microhole drilling performance of PCD tool were investigated. The results show that the surface roughness of helix flute and flank face of the fabricated PCD tool were 0.125 µm and 0.158 µm, respectively, as well as the inner wall roughness achieved 0.331 µm after drilling of microhole. The average current displayed a greater effect on the machining quality of PCD tools, with tool breakage in excessive average current. The preferred pulse discharge parameters were determined as an open-circuit voltage of 95 V, an average current of 1400 mA, a pulse width of 400 ns, and a pulse interval of 2000 ns. [ABSTRACT FROM AUTHOR]

ABSTRACT Objective Materials and Methods Results Conclusion Clinical Significance This systematic review and meta‐analysis compared the accuracy of intraoral scanners and spectrophotometers in determining tooth shade.An electronic search of five databases (PubMed, Scopus, Embase, Web of Science, CENTRAL) was conducted on October 19, 2023. A total of 163 studies were identified from the databases, of which 23 articles were eligible for inclusion. In vivo and in vitro quasi‐experimental studies were included. After data extraction, a quantitative analysis was performed to determine the accuracy of the intraoral scanner in subgroups using four outcomes: trueness and precision with different measurement locations. A random‐effects model was used to pool effect sizes. The pooled proportion with a 95% confidence interval (CI) was used for the effect size measure.Eleven articles were included in the meta‐analysis. Trueness with the intraoral scanner was between 0.28 (CI: 0.09–0.60) and 0.38 (CI: 0.24–0.53). Repeatability was between 0.81 (CI: 0.64–0.91) and 0.85 (CI: 0.74–0.92). Trueness showed low, and precision had moderate certainty of evidence.The trueness of shade matching with intraoral scanners is low compared to spectrophotometers, although the precision is considered high and is similar to spectrophotometers.Shade determination with intraoral scanners is not recommended. [ABSTRACT FROM AUTHOR]

Introduction Vection is a stationary individual's illusory experience of self-motion. This illusory self-motion is operationally important for aviation, particularly military aviation, since vection is a dramatic example of spatial disorientation (SD), which is an individual's failure to correctly sense the aircraft's position, motion, and/or attitude with respect to the fixed coordinate system of the Earth's surface and its gravitational vertical. Notably, SD is a major cause of fatal aviation mishaps, and the visual system is particularly prone to provoking vection. This article describes the Virtual Reality Vection System (VRVS), which uses computer-controlled virtual reality technology to induce vection under controlled conditions for training, demonstration, testing, and research. Materials and Methods The VRVS enables the precise specification of the number and appearance of visual stimulus elements intended to generate vection, including photorealistic images. The VRVS can present visual stimuli on any OpenXR-capable virtual reality headset. The VRVS currently records 2 types of behavioral responses, button presses to indicate the presence and duration of vection and the voltage of a handheld linear potentiometer to indicate the presence, duration, and magnitude of vection. Results An approved test plan helped guide, organize, document, and validate the VRVS during its development. Under this plan, a pair of tests guided hardware and software development of the VRVS system. Although the first test verified the ability of the VRVS to generate and measure vection, it also demonstrated that the VRVS can quickly manipulate the visual stimuli from one trial to the next so that the VRVS can support complex experimental designs. The second test used these capabilities to verify that the VRVS can characterize vection in a more analytic fashion using a masking paradigm. Specifically, the test assessed whether random stimulus elements injected into the vection-inducing stimulus disrupted vection in a quantifiable fashion. This work opens the door to studies that characterize the necessary and sufficient visual elements for vection-based SD. Discussion The VRVS is currently used to research, develop, test, and evaluate mitigation strategies targeting vection-related SD in degraded visual environments. Similarly, the VRVS is supporting research to develop methods to predict individual differences in visually induced motion sickness susceptibilities. The VRVS is currently being integrated with a precision motor-controlled rotating Barany chair for multisensory studies. It should be noted that since the VRVS was developed to support United States Army Aeromedical Research Laboratory projects, it is an Army product representing government intellectual property and may be freely available to other government institutions. [ABSTRACT FROM AUTHOR]

Introduction Current standards for hemoglobin monitoring during air transports of U.S. combat wounded are invasive and intermittent. Fielded pulse co-oximeters can noninvasively measure total hemoglobin, but this parameter is not currently utilized. The primary objective of this study was to assess the percentage of vital sign measurements with successful capture of total noninvasive hemoglobin measurement using spectrophotometry-based technology for Hb (SpHb) measurements in healthy participants during training flights. Secondary objectives were to assess the feasibility of a novel electronic data capture mechanism from usual patient movement items and perform a pilot analysis of SpHb changes in healthy participants during transitions from ground to air transport. Methods We conducted a feasibility study enrolling healthy participants who had hemodynamic monitoring during usual U.S. Air Force Critical Care Air Transport (CCAT) flight training exercises from 2022 to 2023. Usual CCAT monitoring equipment and currently used Masimo Rainbow® pulse co-oximeters had the capability to measure SpHb. After each training exercise, the study team wirelessly downloaded case files from patient monitors utilizing the Battlefield Assisted Trauma Distributed Observation Kit (BATDOKTM) Case Downloader application. We then calculated point and precision estimates for the percentage of time for successful SpHb capture during the exercise and compared this to pulse oximetry (SpO2) capture. An a priori precision analysis for percentage of flight-time with successful SpHb data capture and descriptive statistics were performed. This study received Exempt Determination by the 59th Medical Wing IRB. Results We analyzed 26 records with mean monitoring durations of 94.5 [59.3-119.9] minutes during ground phases and 78.0 [59.9-106.5] minutes during flight phases. SpHb measures were successfully captured for 97.7% (n  = 4,620) of possible ground measurements and 97.2% (n  = 3,973) of possible in-flight measurements compared to 99.5% ground and 98.2% in-flight capture for SpO2. Mean intervals of missing SpHb data were 2 ± 5 minutes on the ground and 4 ± 6 minutes in-flight. Mean SpHb increased by 0.93 ± 0.96 g/dL during the ground phase, but had minimal changes during ascent, cruising altitude or descent. The BATDOKTM Case downloader completed transfer for all files. Conclusion Masimo Rainbow® SpHb pulse co-oximeters reliably captured continuous, noninvasive hemoglobin measurements using usual CCAT patient movement items in healthy participants during both ground and flight training. The BATDOKTM Case Downloader successfully imported case files from CCAT patient monitors. Mean SpHb measures had a small increase during the ground phase of monitoring followed by minimal changes when transitioning to flight altitude. [ABSTRACT FROM AUTHOR]

Background: The accuracy of intraoral scanning is critical for computer-aided design/computer-aided manufacturing workflows in dentistry. However, data regarding the scanning accuracy of various adjacent restorative materials and intraoral scanners are lacking. This in vitro study aimed to evaluate the effect of adjacent restorative material type and CEREC's intraoral scanners on the accuracy of intraoral digital impressions for inlay cavities. Methods: The artificial tooth was prepared with an occlusal cavity depth of 2 mm, a proximal box width at the gingival floor of 1.5 mm, and an equi-gingival margin extended disto-occlusally at the transition line angle on both the lingual and buccal sides for an inlay restoration. The adjacent teeth were veneered with crowns made of gold and zirconia, and an artificial tooth (resin) was utilized as the control group. The inlay cavity and adjacent teeth (Gold, Zirconia, and resin) were scanned 10 times using Chairside Economical Restoration of Esthetic Ceramics (CEREC) Primescan (PS), Omnicam (OC), and Bluecam (BC). A reference scan was obtained using a laboratory scanner (3-shape E3). Scanning was performed according to the manufacturer's instructions, including powder application for the BC group. Standard tesselation language files were analyzed using a three-dimensional analysis software program. Experimental data were analyzed using a two-way analysis of variance and the Tukey's post-hoc comparison test. Results: The restorative materials of the adjacent teeth significantly affected the accuracy of the intraoral digital impressions (p <.05). The zirconia group exhibited the highest trueness deviation, followed by the resin and gold groups, with each demonstrating a statistically significant difference (p <.05). The resin group demonstrated the highest maximum positive deviation and deviation in precision. Gold exhibited the lowest average deviation value for trueness compared with those of the other adjacent restorative materials. Intraoral scanner type significantly influenced the trueness and precision of the scan data (p <.05). The average deviation of trueness according to the intraoral scanner type increased in the following order: BC > PS > OC. The average deviation in precision increased in the following order: PS>OC>BC (p <.05). Conclusion: The restorative materials of the adjacent tooth and the type of intraoral scanner affect the accuracy of the intraoral digital impression. The trueness of the digital images of the BC group, obtained by spraying the powder, was comparable to that of the PS group. Among the adjacent restorative materials, zirconia exhibited the lowest trueness. In contrast, PS demonstrated the highest precision among the intraoral scanners, while resin displayed the lowest precision among the adjacent restorative materials. [ABSTRACT FROM AUTHOR]

Geographic data quality is a complex issue requiring continuous operational improvements. Considering this to be one of the most topical research and technical issues in official statistics and environmental monitoring, this study re-connects the operational dimension of 'geographic data quality' with the broader issue of monitoring the quality of official statistics. By estimating the accuracy of public (spatially explicit) data, this study illustrates an operational framework with an exploratory exercise in estimating the geographic data quality characteristic of a specific information source within the official statistical system (i.e., building registry) in a given European country, namely, Italy. The results of this exercise provide a paradigmatic example of profound innovation in the activities of statistical services in Europe and specifically the Italian National Statistical Institute (Istat), transitioning from independent (and poorly connected) field surveys to an integrated system of registries. Since several studies are based on spatially explicit survey units, it is essential to estimate the quality of geographical data, especially those derived from information sources where space is topical information, such as (local, regional, or national) building registers. Thanks to the results of an empirical exercise applied to Italian building registers, the present article will discuss the issue of data accuracy, considered the main issue related to monitoring geographic data quality, from an official statistics' perspective. Statistical indicators will be proposed for the assessment of systematic and random errors of spatially explicit measures, possibly enabling a quali-quantitative improvement in the semantic content of building registers that address the inherent requirements of official statistics. Such indicators have some positive implications for the entire system of official statistics in Italy and, for generalization, within the European Statistical System. [ABSTRACT FROM AUTHOR]

Active inference describes (Bayes-optimal) behaviour as being motivated by the minimisation of surprise of one's sensory observations, through the optimisation of a generative model (of the hidden causes of one's sensory data) in the brain. One of active inference's key appeals is its conceptualisation of precision as biasing neuronal communication and, thus, inference within generative models. The importance of precision in perceptual inference is evident—many studies have demonstrated the importance of ensuring precision estimates are correct for normal (healthy) sensation and perception. Here, we highlight the many roles precision plays in action, i.e., the key processes that rely on adequate estimates of precision, from decision making and action planning to the initiation and control of muscle movement itself. Thereby, we focus on the recent development of hierarchical, "mixed" models—generative models spanning multiple levels of discrete and continuous inference. These kinds of models open up new perspectives on the unified description of hierarchical computation, and its implementation, in action. Here, we highlight how these models reflect the many roles of precision in action—from planning to execution—and the associated pathologies if precision estimation goes wrong. We also discuss the potential biological implementation of the associated message passing, focusing on the role of neuromodulatory systems in mediating different kinds of precision. [ABSTRACT FROM AUTHOR]

Objective To recommend precision dosing and improve therapeutic efficacy against invasive fungal disease, a physiologically based pharmacokinetic model (PBPK) of oral isavuconazole (ISA) was established and used to explore its disposition across populations in different physiological and pathological states. Methods Twenty-five pharmacokinetic (PK) studies of oral ISA were identified through a systematic search of PubMed. Concentration–time data were extracted using WebPlotDigitizer. Physiochemical parameters were obtained from published literature and DrugBank. Model development and simulation used the Simcyp population-based simulator, and visual predictive check and predictive error were used for the model evaluation. Probability of target attainment and the cumulative fraction of response analyses were performed for dose optimization. Results The developed PBPK model was successfully validated in different populations. Most predicted concentration–time points aligned with the observed data, with acceptable predictive errors for the critical parameters. We predicted the PK profiles and parameters of ISA in a population with severe hepatic impairment (HI), a population with obesity and paediatric patients aged 1 to less than 6 years old. The probability of target attainment and cumulative fraction of response analyses indicated that the population with severe HI should have half the maintenance dose. The population with obesity and population with severe HI should have a loading dose of 300 mg every 8 h for 2 days. For paediatric patients aged 1 to less than 6 years old, a weight-based dosing regimen (5.38 mg/kg) of ISA was suggested. Conclusion The predicted value aligns with observations, suggesting ISA's potential predictability in PK profiles for other populations. The recommended dosing regimens increase our understanding of the use of ISA in special populations. [ABSTRACT FROM AUTHOR]

Introduction Variability in return-to-duty (RTD) decision-making following mild traumatic brain injury (mTBI) is a threat to troop readiness. Current RTD assessments lack military-specific tasks and quantitative outcomes to inform stakeholders of a service member's (SM) capacity to successfully perform military duties. Augmented reality (AR), which places digital assets in a user's physical environment, provides a technological vehicle to deliver military-relevant tasks to a SM to be used in the RTD decision-making process. In addition to delivering digital content, AR headsets provide biomechanical data that can be used to assess the integrity of the central nervous system in movement control following mTBI. The objective of this study was to quantify cognitive and motor performance on an AR rifle qualification test (RQT) in a group of neurologically healthy military SMs. Materials and Methods Data were collected from 111 healthy SMs who completed a basic (single-task) and complex (dual-task) RQT with a simulated M4 rifle. The complex scenario required the SM to perform the RQT while simultaneously answering arithmetic problems. Position data from the AR headset were used to capture postural sway, and the built-in microphone gathered responses to the arithmetic problems. Results There were no differences in the number of targets hit, trigger pull reaction time, and transition time from kneeling to standing between the basic and complex scenarios. A significant worsening in postural sway following kneel-to-stand transition was observed in the complex scenario. The average reaction time to answer the arithmetic problems was nearly 2 times slower than the average reaction time to pull the trigger to a displayed target in the complex scenario. Conclusion The complex scenario provoked dual-task interference in SMs as evidenced by worsening postural sway and reaction time differences between the cognitive and motor tasks. An AR RQT provides objective and quantitative outcomes during a military-specific task. Greater precision in evaluating cognitive and motor performance during a military-relevant task has the potential to aid in the detection and management of SMs and their RTD following MTBI. [ABSTRACT FROM AUTHOR]

In the eighteenth century, the sciences and their applications adopted a new attitude based on quantification and, increasingly, on a notion of precision. Within this process, instruments played a significant role. However, while new devices such as the micrometer, telescope, and pendulum clock embodied a formerly unknown potential of precision, this could only be realized by defining a set of practices regulating their application and control. The paper picks up the case of pendulum clocks used in eighteenth-century observatories in order to show the process of learning in the course of which the pendulum clock first became a precision instrument. By examining the results of an especially developed statistical analysis, conducted to compare the performance of eighteenth-century clocks, it highlights the diversity of conditions, attitudes, and manners of handling that are characteristic for the epoch. In this way, it underlines the necessity of standardization of timekeeping practices rather than exclusively focusing on the technological development of clocks. Ultimately, the paper discusses the role of makers and users in order to show the evolution of a "precision instrument." [ABSTRACT FROM AUTHOR]

Most commercially available eye-tracking devices rely on video cameras and image processing algorithms to track gaze. Despite this, emerging technologies are entering the field, making high-speed, cameraless eye-tracking more accessible. In this study, a series of tests were conducted to compare the data quality of MEMS-based eye-tracking glasses (AdHawk MindLink) with three widely used camera-based eye-tracking devices (EyeLink Portable Duo, Tobii Pro Glasses 2, and SMI Eye Tracking Glasses 2). The data quality measures assessed in these tests included accuracy, precision, data loss, and system latency. The results suggest that, overall, the data quality of the eye-tracking glasses was lower compared to that of a desktop EyeLink Portable Duo eye-tracker. Among the eye-tracking glasses, the accuracy and precision of the MindLink eye-tracking glasses were either higher or on par with those of Tobii Pro Glasses 2 and SMI Eye Tracking Glasses 2. The system latency of MindLink was approximately 9 ms, significantly lower than that of camera-based eye-tracking devices found in VR goggles. These results suggest that the MindLink eye-tracking glasses show promise for research applications where high sampling rates and low latency are preferred. [ABSTRACT FROM AUTHOR]

The work conducted in this study was designed to establish achievable testing tolerances for non-destructive pavement density measurements using Density Profiling Systems (DPSs). Nine and six sensors were used to determine the precision of repeatability and reproducibility in the laboratory and the field, respectively. A minimum of six sensors (considered in this study as independent laboratories) were needed to comply with the minimum number of participants required in the current ASTM standard practice (ASTM E691). The methodology included the development of laboratory precision evaluation with a total of nine sensors and two different mixtures (9.5 mm fine-graded mix, 19.0 mm coarse-graded mix) compacted at four density levels (97%, 94%, 91%, and 88% of Gmm). For the field portion of this study, pavement sections built at the National Center for Asphalt Technology (NCAT) Test Track in 2021 served as experimental variables. These sections were built with fine-graded asphalt mixtures and open-graded mixes as wearing courses. Additionally, the pavement sections included three underlying materials: new asphalt (binder layer), milled asphalt surface, and granular base, with thicknesses ranging from 3.8 to 13.9 cm. Density profile testing was conducted at two locations: within the mat (center of the lane) and along the joint. Computed precision statements regarding dielectric values within and between laboratories were about double for field results compared to laboratory results. However, when converted to density, the statements were significantly below the reported statements for Bulk Specific Gravity and Vacuum Sealing in the laboratory and Nuclear and Electromagnetic density gauges in the field. [ABSTRACT FROM AUTHOR]

Potato crop has become integral part of our diet due to its wide use in variety of dishes, making it an important food crop. Its importance also stems from the fact that it is one of the cheapest vegetables available throughout the year. This makes it crucial to keep potato prices affordable for developing countries where the majority of the population falls under the middle-income bracket. Consequently, there is a need to develop a robust, effective, and portable technique to detect diseases in potato plant leaves. In this work, an attention-based disease detection technique is proposed. This technique selectively focuses on specific parts of an image which reveal the disease. This technique leverages transfer learning combined with two attention modules: the channel attention module and spatial attention module. By focusing on specific parts of the images, the proposed technique is able to achieve almost similar accuracy with significantly fewer parameters. The proposed technique has been validated using four pre-trained models: DenseNet169, XceptionNet, MobileNet, and VGG16. All of these models are able to achieve almost the same level of training and validation accuracy, around 90–97%, even after reducing the number of parameters by 40–50%. It shows that the proposed technique effectively reduces model complexity without compromising performance. [ABSTRACT FROM AUTHOR]

Background: The utility of preoperative abdominal ultrasonography (US) in evaluating patients with obesity before metabolic bariatric surgery (MBS) remains ambiguously defined. Method: Retrospective analysis whereby patients were classified into four groups based on ultrasound results. Group 1 had normal findings. Group 2 had non-significant findings that did not affect the planned procedure. Group 3 required additional or follow-up surgeries without changing the surgical plan. Group 4, impacting the procedure, needed further investigations and was subdivided into 4A, delaying surgery for more assessments, and 4B, altering or canceling the procedure due to critical findings. Machine learning techniques were utilized to identify variables. Results: Four thousand four hundred eighteen patients' records were analyzed. Group 1 was 45.7%. Group 2, 35.7%; Group 3, 17.0%; Group 4, 1.5%, Group 4A, 0.8%; and Group 4B, 0.7%, where surgeries were either canceled (0.3%) or postponed (0.4%). The hyperparameter tuning process identified a Decision Tree classifier with a maximum tree depth of 7 as the most effective model. The model demonstrated high effectiveness in identifying patients who would benefit from preoperative ultrasound before MBS, with training and testing accuracies of 0.983 and 0.985. It also showed high precision (0.954), recall (0.962), F1 score (0.958), and an AUC of 0.976. Conclusion: Our study found that preoperative ultrasound demonstrated clinical utility for a subset of patients undergoing metabolic bariatric surgery. Specifically, 15.9% of the cohort benefited from the identification of chronic calculous cholecystitis, leading to concomitant cholecystectomy. Additionally, surgery was postponed in 1.4% of the cases due to other findings. While these findings indicate a potential benefit in certain cases, further research, including a cost–benefit analysis, is necessary to fully evaluate routine preoperative ultrasound's overall utility and economic impact in this patient population. [ABSTRACT FROM AUTHOR]

Background: While many denture base materials are currently available on the market, little data exists regarding their dimensional stability after exposure to the oral environment. This study aimed to evaluate the effect of thermocycling on the trueness and precision of milled, 3-dimensional (3D)-printed, and conventional digitally fabricated complete denture bases (CDBs). Methods: A completely edentulous maxillary stone model was scanned to generate a standard tessellation language (STL) file; this was imported into metal-milling-machine software (Redon Hybrid CAD-CAM metal milling machine, Redon, Turkey) to produce a metal model for fabricating 30 CDBs. These were divided into three groups (n = 10 in each) according to the construction technique: group 1, CAD-CAM milled CDBs; group 2, 3D-printed CDBs; and group 3, conventional compression molded CDBs. All CDBs were scanned after fabrication and evaluated before and after thermocycling using superimposition. The data were analyzed using a one-way ANOVA, Tukey's post hoc test, and a paired t-test. Results: The level of trueness between the CAD-CAM milled, 3D-printed, and compression molded CDBs showed significant differences before and after thermocycling (P < 0.05). Group 1 showed the highest degree of trueness before and after thermocycling, group 3 exhibited a higher degree of trueness than group 2 before thermocycling, and group 2 had a higher degree of trueness than group 3 after thermocycling. There was a significant difference in the precision for each CDB type before and after thermocycling (P < 0.05). Conclusion: The trueness of the CAD-CAM milling system in complete denture (CD) fabrication is superior to that of the 3D printing and conventional compression molding systems before and after thermocycling. Thermocycling had a significant effect on the precision of all CDB types. The compression molding system in CD construction is the most negatively affected via thermocycling with regard to the measures of trueness and precision. Clinical trial number: Not applicable, no human participants were involved. [ABSTRACT FROM AUTHOR]

An independent evaluation of methane emissions data from GHGSat, a private company that operates a constellation of small microsatellites flying Fabry‐Perot spectrometers operating at 1.6 µm, was performed. Data from multiple GHGSat commercial satellites, consisting of retrieved methane, diagnostics, and, where detected, plume and emissions information from roughly 250 scenes across Canada were analyzed. From these, 10 scenes contained methane plumes with a 2% detection rate for oil and gas scenes, and 10% for landfills. Methane precision was found to be 5%/2% on average for the C1/C2–C5 designs, with some variability due to scene albedo, terrain roughness, and airmass. Synthetic GHGSat plumes, generated using Lagrangian plume dispersion model and GHGSat characteristics, indicates typical detection limits of 240/180 kg/hr(C1/C2–C5), with a best case of roughly 100 kg/hr. Emissions and their uncertainties calculated using an alternative approach were in broad agreement with GHGSat‐reported emissions. Overall, the performance of the GHGSat C2 design (also used for C3 onward) for favorable‐viewing conditions was found to be largely consistent with company‐advertised performance. Plain Language Summary: We performed an independent evaluation of methane emissions data from GHGSat, a private company that owns and operates its own group of satellites, in order to evaluate the precision of their methane data products and compare these findings with that advertised. Roughly 250 GHGSat data scenes were acquired with 10 plumes detected, 2 for oil and gas and 8 for landfills. These, combined with advanced plume models, statistical analyses, and alternative data processing software, were used in the evaluation. It was found that the GHGSat‐reported detection limit—the quantity of methane release that was is the edge of detectability—of 100 kg/hr was possible, but only for ideal conditions. Ideal in this case means a surface that is quite reflective (at the wavelengths detected by the GHGSat sensors, roughly 1.6 μm) and flat near the source of the emissions. A detection limit of 180 kg/hr is more representative of average conditions. Key Points: GHGSat methane precision was found to be 1%–5%, varying with surface reflectance, terrain variability, and solar zenith angleGHGSat methane detection limit can be as low as 100 kg/hr under ideal conditions, but more typically is about 200 kg/hrGHGSat performance was found to be generally consistent with that reported by the company [ABSTRACT FROM AUTHOR]

To enhance management of aquatic systems, long‐term monitoring programs are crucial. However, managers often lack sufficient guidance in decision‐making. In this study, we analyzed nearshore electrofishing data from Lake Ontario spanning 18 years and over 100,000 caught fish to assess sampling designs for various coastal habitats. Using simulation, we evaluated precision of catch per unit effort (CPUE) for all species, piscivores, and specialist species, at different levels of electrofishing sampling effort. For overall CPUE in any habitat type, increased precision declined with additional electrofishing runs, particularly after reaching 30–40 runs. Adjustments in sampling effort, such as adding 10 runs per year for open‐coast sites, increased precision of overall CPUE by 10%. Adding 8 runs per year for wetlands increased precision of specialist‐species CPUE by 10%. However, additional runs in embayments did not increase precision for all species, piscivores, or specialist species. Our findings underscore the importance of considering community composition and abundance when evaluating CPUE precision and illustrates a flexible approach to optimize sampling effort in aquatic monitoring programs. [ABSTRACT FROM AUTHOR]

Background: Preclinical technical feasibility study of robot-assisted microinvasive glaucoma surgery using a novel ophthalmic robot-assisted surgery system. Methods: Feasibility was assessed in synthetic eye models in two stages: Stage I, nonimplantable robot-assisted goniotomy; and Stage II, robot-assisted stent implantation using a trabecular bypass stent. Robot-assisted interventions were subsequently compared to the manual approach. Results: Stage I: Two surgeons completed 10 trials each of ab-interno sectoral goniotomy with and without robotic assistance for at least 3 clock hours using a standard goniotomy knife and more than 10 clock hours of extended goniotomy using a flexible, guided goniotomy instrument. Stage II: Trabecular bypass stent deployment was successfully achieved in 100% of the attempts with and without robotic assistance. Surgical time was recorded and compared between the robotic-assisted and the manual approach. Conclusions: A system for robot-assisted microinvasive glaucoma surgery can successfully achieve implantable and nonimplantable interventions in the anterior segment. This is the first known demonstration of the feasibility of robot-assisted glaucoma surgery. [ABSTRACT FROM AUTHOR]

This article presents a generalized model of two-axis flexure hinges based on quadratic rational Bézier curve. The generalized closed-form compliance equations are derived based on the virtual work theory and the superposition relationship of the deformation. Then, how to determine the number of sensitive axes, the location of the primary and secondary sensitive axes, and the configuration of the notch profile are discussed. There are 20 types of notch profiles derived from single or mixed, symmetrical or asymmetrical curves. And, the correctness of the compliance equations is verified by finite-element analysis. The maximum relative error does not exceed 10%. Finally, the precision of rotation, the maximum stress, and the effect of structural parameters on the compliance are analyzed. The results show that for two-axis flexure hinges with a flush single curve notch profile, the proximity of the center of rotation to the load end does not significantly affect the axial compliance as well as the torsional compliance. For hybrid two-axis flexure hinges with symmetric structure, the ability to maintain the center of rotation under lateral forces is better than that under the same torque. The proposed generalized model provides a reference for the design of spatial compliant mechanisms. [ABSTRACT FROM AUTHOR]

In response to the problems of slow detection speed, cumbersome operation, and solvent pollution in the detection of petroleum ether extract in tobacco leaves using the current traditional Soxhlet extraction method, low field nuclear magnetic resonance technology was used to detect the petroleum ether extract content in tobacco leaves. The detection parameters such as drying time, sample quality, echo time, and number of repeated scans were optimized to verify the repeatability and accuracy of the method, and the detection results were compared with the traditional Soxhlet extraction method. The results showed that 3. 0 g of tobacco leaf powder passing through a 40 mesh sieve was dried at 80 °C for 4 hours. Under the conditions of echo time of 0. 25 ms and 8 repeated scans, the petroleum ether extract detection results were good. The standard curve R2 reached 0. 999 81, and the relative standard deviation of repeatability was 1. 45% to 2. 99%. The intra day and inter day precision were 2. 61% and 1. 10%, respectively. The correlation coefficient between the detection results of this method and the Soxhlet extraction method reaches 0. 998 55, with an absolute error within 0. 02% ~ 0. 35% and a relative error within 0. 26%~3. 69%. Compared with the traditional Soxhlet extraction method, this method is simple, fast, accurate, and solvent free, making it suitable for the accurate quantification of petroleum ether extracts from large quantities of flue-cered tobacco leaves. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to compare the accuracy of full‐arch conventional implant impressions using two different materials (A‐silicone and polyether) to full‐arch digital implant impressions produced from two intraoral scanning devices. Materials and Methods: A master model was fabricated representing an edentulous mandible with four implants with internal connection placed at the sites of canines and first molars. The anterior implants were parallel to the residual ridge, while the two posterior implants had an angulation of 15° to the distal and 15° to the lingual respectively. The conventional technique was performed with open‐tray of non‐splinted impression copings. Two different impression materials were used, A‐silicone and polyether at monophase medium body consistencies. The digital impressions were obtained with the use of two different intraoral scanners, after the connection of scan bodies. A total of 10 impressions were produced for each of the four experimental groups. The conventional models as well as the master model were digitized using a high‐resolution laboratory scanner. The STL files of the models and of the intraoral impressions were imported in a powerful superimposition software, for the conduction of measurements in pairs of files. The software calculated the 3D deviations, as well as the linear and angular displacements among scan bodies at the digital files. For "trueness" measurements every STL file of each experimental group was superimposed to the digital master model, while for "precision" measurements all STL files of each experimental group were superimposed to each other. Results and Conclusions: The accuracy of full arch mandibular implant impressions was influenced both by the impression technique used (conventional vs. digital) and the impression material used (A‐silicone vs. polyether) or the intraoral scanner used (Trios vs. Heron).In terms of "trueness," A‐silicone showed the highest impression accuracy with the lowest deviation values, followed by polyether and Trios, but the differences between the three groups were in the majority not statistically significant. Heron showed statistically lower accuracy results in all measurements compared to the other groups.In terms of "precision", conventional impressions with the use of A‐Silicone or polyether were statistically significantly superior to digital impressions with either scanner. A‐Silicone and polyether showed no statistically significant difference between them. [ABSTRACT FROM AUTHOR]

The phenomenon of aesthetic chills—shivers and goosebumps associated with either rewarding or threatening stimuli—offers a unique window into the brain basis of conscious reward because of their universal nature and simultaneous subjective and physical counterparts. Elucidating the neural mechanisms underlying aesthetic chills can reveal fundamental insights about emotion, consciousness, and the embodied mind. What is the precise timing and mechanism of bodily feedback in emotional experience? How are conscious feelings and motivations generated from interoceptive predictions? What is the role of uncertainty and precision signaling in shaping emotions? How does the brain distinguish and balance processing of rewards versus threats? We review neuroimaging evidence and highlight key questions for understanding how bodily sensations shape conscious feelings. This research stands to advance models of brain-body interactions shaping affect and may lead to novel nonpharmacological interventions for disorders of motivation and pleasure. [ABSTRACT FROM AUTHOR]

An Intrinsic Gaussian Markov Random Field (IGMRF) can be used to induce conditional dependence in Bayesian hierarchical models. IGMRFs have both a precision matrix, which defines the neighborhood structure of the model, and a precision, or scaling, parameter. Previous studies have shown the importance of selecting the prior for this scaling parameter appropriately for different types of IGMRF, as it can have a substantial impact on posterior estimates. Here, we focus on cases in one and two dimensions, where tuning of the prior is achieved by mapping it to the marginal SD of an IGMRF of corresponding dimensionality. We compare the effects of scaling various IGMRFs, including an application to real two‐dimensional blood pressure data using MCMC methods. [ABSTRACT FROM AUTHOR]

Intrusion Detection Model (IDM) is an essential device for network defence in current trend. Malicious users analyse the vulnerabilities of IDSs to capture unauthorized access. Furthermore, intrusion detection encompasses numerous numerical attributes and models, resulting in elevated detection errors and triggering false alarms. Hence, optimal computational intelligence shall be incorporated in IDM to achieve high detection rate and less number of false alarms. Considering the same, a new hybrid IDM framework is developed as the combination of Fuzzy Genetic Algorithm with Multi-Objective Particle Swarm Optimization that maximizes the detection accuracy, minimizes the false alarms and takes less computational complexity which will be explained first phase. The existing IDSs are constraint to the information trained incur into false positives based on user continuity for normal activity. The objective of this proposal is to extract optimal classification rules automatically from training data that helps to identify types of attacks correctly including the unknown attack types. For achieving this goal, Multi-Objective Particle Swarm Optimization (MOPSO) is used as classifier to enhance the identification of the rare attack classes within the IDM. The effectiveness of this method lies in its capacity to leverage information within an unfamiliar search space, guiding subsequent searches towards valuable subspaces. It provides better separability of various classes' i.e. normal behaviour and false alarms. In this FGA-MOPSO model, Principal Component Analysis (PCA) serves as the feature selection technique employed to identify pertinent features within the dataset, thereby enhancing the classifier's performance and Fuzzy Genetic Algorithm (FGA) is used to create new population for training the classifier with the help of three operations namely selection, crossover and mutation that helps to practice more patterns in training phase and to obtain better understanding of the proposed classifier. The simulation will illustrate that the system is competent to speed-up the training and testing process of intrusions detection is important for network applications.Please confirm if the author names are presented accurately and in the correct sequence (given name, middle name/initial, family name). Author 1 Given name: [Arun Kumar] Last name [Ramamoorthy]. Also, kindly confirm the details in the metadata are correct.Checked and Verified for Author 1. In Author 2 name, Given Name was [K.] and last name was[Karuppasamy], But its is just the opposite. Given Name is [Karuppasamy] and Last Name is [K.]. I have edited it. [ABSTRACT FROM AUTHOR]

Background: Timely detection and treatment of serious diseases, including cancer, are crucial for saving lives and improving longevity. The Internet of Medical Things (IoMT) holds promise for enhancing healthcare by enabling real-time disease identification through automated image analysis. However, integrating large deep learning models with IoMT devices poses challenges. Objective: This study aims to develop an efficient deep learning model, "EffiPathNet," specifically designed for analyzing histopathological images with a focus on achieving both accuracy and speed. Method: EffiPathNet was developed to address the challenges associated with large models and to ensure compatibility with IoMT imaging devices. The model was tested on a reputable histopathological image dataset, evaluating its accuracy, speed, and computational requirements. Result: EffiPathNet achieved an average accuracy of 97.79% and a 0.987 F1 score, demonstrating its exceptional ability to accurately classify histopathological images. The model's lightweight design, requiring only a few kilobytes in size, enhances its compatibility with IoMT imaging devices. Main Findings: The study highlights EffiPathNet's efficacy in accurately classifying histopathological images and its potential for integration with IoMT devices. The lightweight design further enhances its suitability for practical IoMT applications. Conclusion: EffiPathNet emerges as a promising solution for real-time disease identification in histopathological images, combining high accuracy with computational efficiency. Its compatibility with IoMT devices suggests its potential for practical implementation in healthcare settings, contributing to timely and effective medical interventions. [ABSTRACT FROM AUTHOR]

The study aimed to classify two classes of vehicles, Tuktuk and Motorcycle, using a modified RCNN model. The MAjN_IRAQ Dataset, created from a camera system in Baghdad city, was used for training, detection, and classification of some vehicles to allow them to enter some crowded streets of Baghdad and to prevent others from entering the same streets. New layers were added and the number and size of filters were changed, which led to improve the process of training, detection and classification of vehicles with high accuracy, which leads to improving the proposed model's performance. The results showed that the modified RCNN model performed better when trained for 80 epochs. It improved performance measures such as precision, recall, and F1 score measure. The model was compared to other transfer learning methods (Alex Net, VGG16, and VGG19) and showed superior results for the Tuktuk class. The training and testing time for the proposed RCNNmodified model was also lower compared to the other models. At 80 epochs, the precision for the Tuktuk class was approximately 0.94, while for the Motorcycle class, it was approximately 0.89. The TPR was higher for the Tuktuk class at approximately 0.93, while the lower value was approximately 0.84 for VGG16. When the VGG16 model was used, the F1 score was better in the Motorcycle category (about 0.95) but worse in the Tuktuk category (0.86%). Both the suggested RCNN-modified model and the Alex Net model worked well in a reasonable amount of time. [ABSTRACT FROM AUTHOR]

Introduction: Mobile health diagnostics have demonstrated effectiveness in detecting and managing chronic diseases. This method comparison study aims to assess the accuracy and precision of the previously evaluated OptiBP™ technology over a four-week study period. This device uses optical signals recorded by placing a patients fingertip on a smartphones camera to estimate blood pressure (BP). Methods: In adult participants without cardiac arrhythmias and minimal interarm blood pressure difference (systolic arterial pressure (SAP) < 15 mmHg or diastolic arterial pressure (DAP) < 10 mmHg), three pairs of 30 s BP measurements with the OptiBP™ (test method) were simultaneously compared using three pairs of measurements with the non-invasive oscillometric brachial cuff (reference method) on the opposite arm over a period of four consecutive weeks at a rate of two measurements per week (one in the morning and one in the afternoon). The agreement of BP values between the two technologies was analyzed using Bland-Altman and error grid analyses. The performance of the smartphone application was investigated using the International Organization for Standardization (ISO) definitions, which require the bias ± standard deviation (SD) between two technologies to be lower than 5 ± 8 mmHg. Results: Among the 65 eligible volunteers, 53 participants had adequate OptiBP™ BP values. In 12 patients, no OptiBP™ BP could be measured due to inadequate signals. Only nine participants had known chronic arterial hypertension and 76% of those patients were treated. The mean bias ± SD between both technologies was -1.4 mmHg ± 10.1 mmHg for systolic arterial pressure (SAP), 0.2 mmHg ± 6.5 mmHg for diastolic arterial pressure (DAP) and -0.5 mmHg ± 6.9 mmHg for mean arterial pressure (MAP). Error grid analyses indicated that 100% of the pairs of BP measurements were located in zones A (no risk) and B (low risk). Conclusions: In a cohort of volunteers, we observed an acceptable agreement between BP values obtained with the OptiBPTM and those obtained with the reference method over a four-week period. The OptiBPTM fulfills the ISO standards for MAP and DAP (but not SAP). The error grid analyses showed that 100% measurements were located in risk zones A and B. Despite the need for some technological improvements, this application may become an important tool to measure BP in the future.

Abstract Objective was to assess the precision and reproducibility of spatial penalty-based intravoxel incoherent motion (IVIM) methods in comparison to the conventional bi-exponential (BE) model-based IVIM methods. IVIM-MRI (11 b-values; 0–800 s/mm2) of forty patients (N = 40; Age = 17.7 ± 5.9 years; Male:Female = 30:10) with biopsy-proven osteosarcoma were acquired on a 1.5 Tesla scanner at 3 time-points: (i) baseline, (ii) after 1-cycle and (iii) after 3-cycles of neoadjuvant chemotherapy. Diffusion coefficient (D), Perfusion coefficient (D*) and Perfusion fraction (f) were estimated at three time-points in whole tumor and healthy muscle tissue using five methodologies (1) BE with three-parameter-fitting (BE), (2) Segmented-BE with two-parameter-fitting (BESeg-2), (3) Segmented-BE with one-parameter-fitting (BESeg-1), (4) BE with adaptive Total-Variation-penalty (BE + TV) and (5) BE with adaptive Huber-penalty (BE + HPF). Within-subject coefficient-of-variation (wCV) and between-subject coefficient-of-variation (bCV) of IVIM parameters were measured in healthy and tumor tissue. For precision and reproducibility, intra-scan comparison of wCV and bCV among five IVIM methods were performed using Friedman test followed by Wilcoxon-signed-ranks (WSR) post-hoc test. Experimental results demonstrated that BE + TV and BE + HPF showed significantly (p

Weed infestation poses a critical challenge to sustainable agriculture, leading to significant crop yield losses and escalating the use of chemical herbicides, which contribute to environmental degradation and health risks. One of the most pressing issues in weed management is the declining effectiveness of traditional weed control methods, which struggle to keep pace with the growing global food demands and the challenges posed by an anticipated population of 10 billion by 2050. The focus is on Precision Weed Management (PWM), emphasizing cutting-edge technologies such as computer vision, Unmanned Aerial Vehicles (UAVs), GPS-controlled patch spraying, laser treatments, and autonomous weeding robots. Computer vision, employing image processing and deep learning, emerges as a key player in automated weed detection, challenging traditional herbicide methods. UAVs equipped with advanced sensors facilitate high-resolution weed mapping, allowing for timely interventions. Laser and thermal treatments showcase targeted and efficient weed control, while autonomous weeding robots exemplify a hands-free, precise approach. The integration of these technologies not only promises enhanced productivity but also signifies a sustainable and environmentally conscious shift in global agriculture. The article highlights the limitations of traditional weed control methods and underscores the potential of emerging technologies to revolutionize weed management, offering precise, cost-effective, and environmentally friendly solutions.

Geographic data quality is a complex issue requiring continuous operational improvements. Considering this to be one of the most topical research and technical issues in official statistics and environmental monitoring, this study re-connects the operational dimension of ‘geographic data quality’ with the broader issue of monitoring the quality of official statistics. By estimating the accuracy of public (spatially explicit) data, this study illustrates an operational framework with an exploratory exercise in estimating the geographic data quality characteristic of a specific information source within the official statistical system (i.e., building registry) in a given European country, namely, Italy. The results of this exercise provide a paradigmatic example of profound innovation in the activities of statistical services in Europe and specifically the Italian National Statistical Institute (Istat), transitioning from independent (and poorly connected) field surveys to an integrated system of registries. Since several studies are based on spatially explicit survey units, it is essential to estimate the quality of geographical data, especially those derived from information sources where space is topical information, such as (local, regional, or national) building registers. Thanks to the results of an empirical exercise applied to Italian building registers, the present article will discuss the issue of data accuracy, considered the main issue related to monitoring geographic data quality, from an official statistics’ perspective. Statistical indicators will be proposed for the assessment of systematic and random errors of spatially explicit measures, possibly enabling a quali-quantitative improvement in the semantic content of building registers that address the inherent requirements of official statistics. Such indicators have some positive implications for the entire system of official statistics in Italy and, for generalization, within the European Statistical System.

Abstract Background The accuracy of intraoral scanning is critical for computer-aided design/computer-aided manufacturing workflows in dentistry. However, data regarding the scanning accuracy of various adjacent restorative materials and intraoral scanners are lacking. This in vitro study aimed to evaluate the effect of adjacent restorative material type and CEREC's intraoral scanners on the accuracy of intraoral digital impressions for inlay cavities. Methods The artificial tooth was prepared with an occlusal cavity depth of 2 mm, a proximal box width at the gingival floor of 1.5 mm, and an equi-gingival margin extended disto-occlusally at the transition line angle on both the lingual and buccal sides for an inlay restoration. The adjacent teeth were veneered with crowns made of gold and zirconia, and an artificial tooth (resin) was utilized as the control group. The inlay cavity and adjacent teeth (Gold, Zirconia, and resin) were scanned 10 times using Chairside Economical Restoration of Esthetic Ceramics (CEREC) Primescan (PS), Omnicam (OC), and Bluecam (BC). A reference scan was obtained using a laboratory scanner (3-shape E3). Scanning was performed according to the manufacturer's instructions, including powder application for the BC group. Standard tesselation language files were analyzed using a three-dimensional analysis software program. Experimental data were analyzed using a two-way analysis of variance and the Tukey’s post-hoc comparison test. Results The restorative materials of the adjacent teeth significantly affected the accuracy of the intraoral digital impressions (p PS > OC. The average deviation in precision increased in the following order: PS>OC>BC (p