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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 Alzheimers 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.

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

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.

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.

This study addresses the problem of coordination in cooperative multi-robot systems performing complex tasks. An analysis of cooperative behavior in mobile multi-robot systems in terms of task execution accuracy by heterogeneous robots is carried out. In addition, we evaluate the capacity and compatibility of tasks assigned to robots to optimize task execution without using direct communication with the robots or a central decision-making unit. A model for task selection in heterogeneous distributed multi-robot systems is proposed. It is based on two processes: the first decomposes complex tasks into elementary tasks, and the second assigns elementary tasks to mobile robots for real-time execution. The distribution of elementary tasks is NP-hard, which leads us to recommend approximate solutions. A fuzzy system called Fuzzy Decision Making in Task Selection is proposed, which uses fuzzy logic to solve this problem. This system allows robots to choose to perform any task in the future. An approach is presented that uses two cascading fuzzy systems. The first calculates the utility of the robot and then activates the second fuzzy system to calculate the utility of the task. By using the output of the fuzzy decision system in our model, each robot will be able to decide for itself which tasks to perform. The results of a simulation of mobile robots transporting goods demonstrate the effectiveness of this fuzzy decision-maker. [ABSTRACT FROM AUTHOR]

ABSTRACT Over 60% of the world's fish stocks suffer from limited data, which hampers effective fisheries management. Researchers have developed stock assessment methods for data‐limited fisheries using length‐frequency data, but reliability was questionable and not well researched. We evaluated the precision of the widely used length‐based method ELEFAN using 24 months of length‐frequency data from 14,190 individual yellowfin tuna and sequential and interval data fractions. Using bootstrapping (1000 times) and data reduction, growth parameters and precision L∞$$ {L}_{\infty } $$, K$$ K $$, and Φ′ were estimated. The CVs of L∞$$ {L}_{\infty } $$, K$$ K $$, and Φ′ were 2.55%, 23.04%, and 2.35%, respectively. From the result of data reduction, at least once in 1 or 2 months and 12 times measurements with 500 data per measurement on average is recommended for achieving high precision with CV of Φ′ < 3%. [ABSTRACT FROM AUTHOR]

Background: Right ventricular (RV) stroke volume (SV) can be calculated via Doppler echocardiography at multiple sites in the right chambers. However, the agreement between the calculated SVs at these sites is unknown. We aimed to assess the repeatability, reliability, and precision of the distal right ventricular outflow tract diameter (RVOTD), the mid-pulmonary artery diameter (MPAD), the right ventricular outflow tract velocity time integral (VTI), and the mid-pulmonary artery velocity time integral (MPAVTI). Additionally, we evaluated the agreement between RVOTSV and MPASV. Methods: Four observers each evaluated approximately 100 patients (n = 406). Basic measurements were made over three cardiac cycles, and the repeatability, reliability, and precision of the measurements were calculated. The agreement between the two methods was presented as intraclass correlation coefficients. Results: The repeatability coefficient ranges for RVOTD, MPAD, RVOTVTI, and MPAVTI were 2–3 mm, 2–4 mm, 2.1–2.8 cm, and 2.4–4.1 cm, respectively. The minimal detectable change ranges for these variables were 2–4 mm, 2–5 mm, 2.2–3.0 cm, and 2.6–4.3 cm, respectively. The respective precision ranges for RVOTD, MPAD, RVOTVTI, and MPAVTI were 2.7–4.7%, 2.4–5.4%, 5.0–7.4%, and 5.4–9.2%. There were significant correlations and agreements between MPASV and RVOTSV, with the Pearson correlation coefficient ranging from 0.63 to 0.89 (P < 0.001). The intraclass correlation coefficient ranged from 0.56 to 0.89 (P < 0.001), although there was a significant bias of 1.9–11.3 mL (P < 0.001). Conclusions: The RVOTD, MPAD, RVOTVTI, and MPAVTI measurements were repeatable, reliable, and precise. The agreement between RVOTSV and MPASV ranged from fair to excellent, although significant bias, along with a wide limit of agreement, was observed. Consequently, these methods cannot be used interchangeably. [ABSTRACT FROM AUTHOR]

It is a dream of researchers to be able to tailor the catalytic performances by adjusting heterogeneous catalysts at the atomic level. Atomically precise metal clusters provide us with the possibility to achieve this challenge. Here, we design a push‐and‐pull synthesis strategy coupled with TiOx coating to prepare the heterogeneous catalysts denoted as TiOx/Au8M@SBA via cultivating atomically precise Au8M(PPh3)8n+ (M=Pd, Pt or Au; n=2 for Pd/Pt and 3 for Au) clusters in mesoporous molecular sieve. The catalysts are made up of the three functional units, which include Au8M(PPh3)8n+ clusters that can act as the active sites, the pore environment of the SBA‐15 that can announce a catalysis show for the clusters with precise number of atoms maintained during the chemical reactions, and the TiOx coating that can further inhibit the migration of the clusters under reaction conditions. The selective hydrogenation of acetylene performed in the fixed‐bed reactor taken, for example, we learn how the atom‐by‐atom tailoring of a heterogeneous catalyst can switch on elusive heterogeneous mechanisms with cluster catalysis. This work sheds light on the fundamental insight into catalysis origin of heterogeneous catalysts and achieves a distinguished level of detail for cluster catalysis. [ABSTRACT FROM AUTHOR]

Understanding and correctly interpreting statistical results presented in scientific articles is a required skill for practicing evidence‐based veterinary medicine. A prerequisite for doing so is the adequate reporting of the results in scientific journals. However, most authors of veterinary publications determine the importance of their findings based on statistical significance (ie, P < .05), indicating that neither the limitations of using P values for inference nor the existence of more appropriate alternatives are widely appreciated in veterinary medicine. This deficiency in knowledge indicates a need to increase awareness in veterinary medicine regarding reporting statistical measures that quantify the magnitude of an effect along with its level of uncertainty, and then interpreting these results for clinical decision making. We utilize a hypothetical randomized controlled trial of dietary management in cats with chronic kidney disease to discuss some common misconceptions about P values and provide practical suggestions for alternatives. Reporting appropriate effect estimates along with their confidence intervals will allow veterinarians to easily and correctly determine whether the magnitude of the effect of interest meets clinical needs while acknowledging uncertainty in the results. We also describe confidence interval functions and show their utility as visual tools in aiding interpretation of confidence intervals. By providing practical guidance, we show that a change in reporting and interpreting statistical results is feasible and necessary. We hope this crucial step will promote clinical decision making based on effect estimates and confidence intervals. [ABSTRACT FROM AUTHOR]

The accuracy of intraoral scanners (IOSs) plays a crucial role in the success of final restorations in digital workflows. Previous studies have shown that numerous factors affect the accuracy of IOSs. Most studies have evaluated the accuracy of IOS under one restoration condition. Therefore, the aim of this study was to evaluate the accuracy of two IOSs with different data acquisition methods across multiple restorations. A partially edentulous model with preparations were created and scanned using the laboratory scanner E4 as the reference model. Two IOSs, Trios 3 and Virtuo Vivo, were used in this study. Each scan was performed in same scanning strategy. Trueness and precision of each scan was compared by surface-matching software, and the data were statistically analyzed. Trios 3 showed no significant difference in trueness of full arch, single crown, and edentulous area, except for 3-unit bridge area than Virtuo Vivo (P = 0.008). However, Virtuo Vivo showed better precision than Trios 3 (P = 0.003). There was no differ in linear dental measurements between two scanners. We found Trios 3 had better trueness in 3-unit bridge area compared to Virto Vivo, but there was no significant difference in the other preparation areas. While Virtuo Vivo showed better precision. Our results can provide insights for the selection of IOSs for various restorations in clinical practice. However, this is an in vitro study, the chairside challenges of IOSs should be considered. [ABSTRACT FROM AUTHOR]

Many designs of static computer-assisted implant surgery (sCAIS) are available for clinician to achieve proper implant position. However, there were not any studies that approached the design alone to evaluate whether sleeve-in-sleeve or sleeve-on-drill design provided most accuracy implant position. The purpose of this study was to investigate the precision of implant placement with sleeve-in-sleeve and sleeve-on-drill static computer assisted implant surgery (sCAIS) designs. Thirty-two models were fabricated simulating a patient with bilateral missing first premolar. Eight models (sixteen implants) were assigned in each group: Group A, B and C represented sleeve-in-sleeve design with 2, 4 and 6 mm sleeve height respectively. Group D represented integrated sleeve-on-drill design with 4 mm sleeve height. 3D deviation at implant platform, apex and angular deviation were measured. Data were analyzed using one way ANOVA (P < 0.05). The overall deviation at platform ranged from 0.40 ± 0.14 mm (group A) to 0.73 ± 1.54 mm (group C), at apex from 0.46 ± 0.16 mm (group A) to 1.07 ± 0.37 mm (group C) and the angular deviation ranged from 0.86 ± 0.89° (group A) to 3.40 ± 1.29° (group C). Group A and B showed significantly less deviation than groups C and D (P < 0.05). There was no statistically significant difference in all parameters measured between group A and B, as well as between group C and D (P > 0.05). Sleeve-in-sleeve sCAIS demonstrated higher precision than sleeve-on-drill sCAIS. [ABSTRACT FROM AUTHOR]

Objectives: This study investigated the effect of additive manufacturing (AM) methods on the slot height dimensions and accuracy of 3D‐printed orthodontic brackets. Methods: A 3D model of a standard Mclaughlin Bennett Trevisi bracket was used as a reference to print the ceramic bracket in a 90° orientation using two representative AM methods: digital light processing (DLP) and material jetting (MJ). The dimensional accuracy and slot heights were determined using a scanning electron microscope and an optical scanner. Also, all specimens were analysed using the Geomagic Control X 3D inspection software. The root mean square (RMS) values were used for trueness and precision assessment. Statistical analyses were performed using an independent sample t‐test. Results: Slot height dimensions, trueness RMS, and precision RMS were statistically affected by different AM methods (p <.01). There was a significant difference between the different printing methods, with DLP meeting the tolerance requirements (mean slot height = 0.557 ± 0.018 mm) and MJ being slightly below them (mean slot height = 0.544 ± 0.021 mm). However, MJ significantly outperformed DLP in terms of accuracy. Among the two printing methods, MJ was associated with higher trueness (RMS = 0.025 ± 0.004 mm) and precision (RMS = 0.038 ± 0.005 mm). Conclusions: Both tested AM methods yielded clinically acceptable outcomes, with the RMS range set to ±100 μm and the slot height tolerance established at 0.549–0.569 mm. The MJ technology achieved the highest accuracy. [ABSTRACT FROM AUTHOR]

To address the issue of the numerous and various improvement methods for the you only look once version 8 (YOLOv8) algorithm and the lack of object detection performance comparison on a common dataset, the publicly available visual object classes (VOC) (2007+2012) dataset was used as the benchmark. The YOLOv8 nano (YOLOv8n) algorithm, with smaller parameters, was selected as the baseline model. Improvements were compared across five aspects; attention mechanisms, backbone networks, neck networksdetection heads, and loss functions. The best individual improvement modules were identified based on mean average precision (mAP) and detection speed. Further combination experiments yielded two optimal combined models with the highest mAP and fastest detection speeds. The results showed that, compared to the benchmark model, the mAP values of the best backbone networksneck networks, and detection head modules increased by 2.50% (Repvit), 1.75% (CGDown), and 1.75% (DyHead), respectively; the detection speed increased by 12.85% (RGCSPELAN), 2.60% (WaveletPool) and 20.22% (LSCD) respectively; the best attention mechanism module improved the mAP value by 1.88% (CAFM); the loss function did not improve the mAP value and the detection speed. Compared to the benchmark model, the combined model with the highest mAP improved the mAP value by 3.13% (YOLOv8n + CAFM + CGDown+DyHead), the combined model with the fastest detection speeds improved 31.11% (YOLOv8n+RGCSPELAN + LSCD). The former combined model is suitable for high-precision object detection scenarios, the latter combined model is suitable for deployment in edge computing devices with high real-time requirements. This study provides a reference for the improvement of the YOLOv8 algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a novel thrust ripple suppression method for multi-secondary permanent magnet synchronous linear motor based on independent coil structure is proposed. Independent coil structure can realize independent power supply for each coil by changing the driving mode of the coils. Combined with the new power supply strategy, the detent and electromagnetic force fluctuation can be suppressed. Firstly, the cogging and end force of moving-magnet-type linear motor are separated by periodic and vector boundary conditions and harmonic analysis is carried out. An analytical model of air gap magnetic field based on virtual magnetic poles is established to solve the back EMF and electromagnetic force fluctuation of the motor. The generation mechanism and harmonic of electromagnetic force fluctuation are analyzed. A multi-secondary PMLSM based on independent coil is proposed, the principle of suppressing motor thrust ripple is expounded, and the coupling effect between modules is analyzed. Finally, a zero-crossing power supply strategy is proposed. The simulation and experimental results show that multi-secondary independent coil PMLSM can effectively suppress the detent and electromagnetic force fluctuation. • The separation model of motor thrust ripple is established, and the harmonic content of thrust fluctuation is analysed. • A multi-secondary motor topology is proposed, which can greatly reduce the no-load detent force of the motor. • An independent coil structure is proposed, which can suppress the thrust ripple of no-load and load at the same time. [ABSTRACT FROM AUTHOR]

Copyright of LHB: Hydroscience Journal is the property of Taylor & Francis Ltd 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.)

This study investigates the morphological impact of using three-dimensional (3D) printed custom implants in surgical hip reconstruction compared to the conventional bone graft and standard size implant methods. An amount of 16 patients at the Rizzoli Orthopaedic Institute who underwent hip reconstruction surgery for tumors involving the P2 pelvis region were selected using stratified sampling. Half of them were randomly selected to receive 3D-printed implants, and the other half were selected to receive standard implants with bone grafts. Six months post-surgery, computed tomography (CT) scans were used to identify the hip joint center of rotation and to measure greater the trochanter offset and acetabular inclination angle. These CT scans were also used to construct a 3D model of the pelvis for 3D measurements. The results show no significant differences in accuracy, using Student's t-test and Mann–Whitney U-test (p-value > 0.05), between the two methods for reconstructing the hip joint center of rotation or greater trochanter offset. However, 3D-printed implants showed statistically significant greater precision, using Student's t-test (p-value < 0.05), in reconstructing the acetabular inclination angle compared to the conventional bone graft and standard-sized off-the-shelf implants. This superior precision reduces the risk of impingement of the femur implant neck with the acetabulum implant cup, which directly relates to improved implant survivorship. These findings support the continued exploration of 3D printing technology for personalized orthopedic solutions. [ABSTRACT FROM AUTHOR]

This research investigates machine learning models for predicting mental health consequences using survey data. The study employs a two-phase approach first, it utilizes TensorFlow for initial Deep Neural Network (DNN) model building, and then it applies Random Forest (RF), Naive Bayes classifier, and decision tree methods for comparative analysis. The DNN model demonstrates strong performance, achieving high accuracy in mental health prediction. Metrics such as testing time, precision, mean absolute error, and accuracy are compared to provide insight into the advantages and disadvantages of each model. While the DNN model excels in accuracy and precision, other models offer trade-offs in computational efficiency. The results clarify the role of machine learning in mental wellness evaluation and intervention, providing guidance for further research and real-world applications. This research enhances the discourse on predictive modeling for mental health outcomes, facilitating advancements in leveraging machine learning to improve mental health assessment and intervention strategies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Planning Education & Research is the property of Sage Publications Inc. 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.)

The field of satellite navigation has seen significant advancements due to the fast development of multi-constellation Global Navigation Satellite Systems (GNSS). Around 150 satellites will be in service when all six systems – GPS, GLONASS, Galileo, BeiDou, QZSS, and NAVIC – are launched by 2030, offering both enormous potential and advantages for research and engineering applications. This study used an experiment on the accuracy, particularly for short, medium, long baselines (Wide Lane ambiguity solution) of the BeiDou, QZSS and QZSS/BeiDou combinations. It showed that with the integration of BeiDou/QZSS static measurements in the study region millimetre-centimetre accuracy for short, medium, and long baselines can be attained. Based on the results of this study, it can be concluded that the 1st (QZSS/BeiDou), 2nd (BeiDou), and 3rd (QZSS) strategies feature different horizontal accuracies for all categories. The obtained results with different satellite configurations for the Fixed-Wide-Lane integer ambiguity solution are compared with each other. Accuracy at the short baseline (BeiDou, QZSS, and BeiDou/QZSS satellites) was obtained in the range of 0.5–0.7 cm. For the medium baseline, it was computed around 1.8–82 cm. For the long baseline, the accuracy was 5.6–13.3 cm. [ABSTRACT FROM AUTHOR]

Predictive processing is an influential theoretical framework for understanding human and animal cognition. In the context of predictive processing, learning is often reduced to optimizing the parameters of a generative model with a predefined structure. This is known as Bayesian parameter learning. However, to provide a comprehensive account of learning, one must also explain how the brain learns the structure of its generative model. This second kind of learning is known as structure learning. Structure learning would involve true structural changes in generative models. The purpose of the current paper is to describe the processes involved upstream of these structural changes. To do this, we first highlight the remarkable compatibility between predictive processing and the processing fluency theory. More precisely, we argue that predictive processing is able to account for all the main theoretical constructs associated with the notion of processing fluency (i.e., the fluency heuristic, naïve theory, the discrepancy‐attribution hypothesis, absolute fluency, expected fluency, and relative fluency). We then use this predictive processing account of processing fluency to show how the brain could infer whether it needs a structural change for learning the causal regularities at play in the environment. Finally, we speculate on how this inference might indirectly trigger structural changes when necessary. [ABSTRACT FROM AUTHOR]

CoVID-19 has been linked to long-term consequences on several human body organs, including lung ailments, kidney malfunctions, heart dysrhythmia, alterations in brain nutrient levels, psychological difficulties, abrupt changes in blood pressure, and more. Because of the considerable variety in the impacts on different body parts, researchers find it challenging to create models that can incorporate these effects for treatment recommendations and future disease prevention scenarios. Thus, this article examines some of the most recently proposed models for identifying the impacts of CoVID19 on various human organs. This review examines the underlying theories in terms of clinical nuances, functional advantages, contextual limits, and potential empirical applications. Based on this discussion, researchers will be able to find the best models for detecting particular diseases on specific body parts. It was discovered that hybrid bioinspired models, when paired with deep learning-based classification algorithms, can effectively detect these impacts. This text also parametrically analyses these models in terms of accuracy, precision, and recall, allowing readers to select the best models for their performance-specific use cases. To expand on this discussion, this book evaluates a unique CoVID19 Classification Rank Metric (CCRM) that integrates these factors for thorough model identification. Based on this criteria, researchers will be able to develop appropriate models for clinical scenarios that have high accuracy, low delay, and scalability while costing less. [ABSTRACT FROM AUTHOR]

Background: The fixed effects model is a useful alternative to the mixed effects model for analyzing stepped-wedge cluster randomized trials (SW-CRTs). It controls for all time-invariant cluster-level confounders and has proper control of type I error when the number of clusters is small. While all clusters in a SW-CRT are typically designed to crossover from the control to receive the intervention, some trials can end with unexposed clusters (clusters that never receive the intervention), such as when a trial is terminated early due to safety concerns. It was previously unclear whether unexposed clusters would contribute to the estimation of the intervention effect in a fixed effects analysis. However, recent work has demonstrated that including an unexposed cluster can improve the precision of the intervention effect estimator in a fixed effects analysis of SW-CRTs with continuous outcomes. Still, SW-CRTs are commonly designed with binary outcomes and it is unknown if those previous results extend to SW-CRTs with non-continuous outcomes. Methods: In this article, we mathematically prove that the inclusion of unexposed clusters improves the precision of the fixed effects intervention effect estimator for SW-CRTs with binary and count outcomes. We then explore the benefits of including an unexposed cluster in simulated datasets with binary or count outcomes and a real palliative care data example with binary outcomes. Results: The simulations show that including unexposed clusters leads to tangible improvements in the precision, power, and root mean square error of the intervention effect estimator. The inclusion of the unexposed cluster in the SW-CRT of a novel palliative care intervention with binary outcomes yielded smaller standard errors and narrower 95% Wald Confidence Intervals. Conclusions: In this article, we demonstrate that the inclusion of unexposed clusters in the fixed effects analysis can lead to the improvements in precision, power, and RMSE of the fixed effects intervention effect estimator for SW-CRTs with binary or count outcomes. [ABSTRACT FROM AUTHOR]

The use of UAVs (drones) and photogrammetry has gained attention in recent years in the construction industry, allowing information to be obtained from a given area without having direct contact with the area, and thus, being a more efficient alternative in terms of time and costs when compared to a traditional topographic survey. Due to the increase in the use of UAVs for photogrammetry, an investigation is proposed to determine the influence of a non-controllable component in photogrammetric flights: the weather. Factors such as brightness, temperature, wind, KP index, and solar radiation affect the precision and quality of the images to be used in photogrammetry. This research determines which factors are most influential in these results through a varied database obtained over a year. In this way, the moments with the most favorable conditions for a photogrammetric flight in climates such as that of the city of Lima or similar are established. A total of 448 flights carried out over a year were analyzed, collecting climatic data such as air temperature, speed and wind direction, solar radiation, and KP index. The flights, which were carried out with a Mavic 2 Pro UAV, were carried out at 100 m high and with a camera at 90° to obtain detailed information on the works. [ABSTRACT FROM AUTHOR]

Photogrammetry is a common tool for evaluating ecosystem-scale questions on coral reefs due to the ability to measure complex structures in situ. This technique is also increasingly being used at smaller scales to collect growth and morphometric data about individual coral fragments in manipulative experiments. However, there are substantial uncertainties in data quality and interpretation and limited reporting of the parameters useful for standardization across studies. There is a need to characterize the capabilities of photogrammetry as applied to coral fragments, to establish validation metrics for reporting, and to determine sources of variation in measurements to refine and improve methods. Here, we used fragments of two common reef-building corals (Montipora capitata and Porites compressa) and known size standards to evaluate accuracy and precision and present suggested validation metrics. We also used a tiered experimental design to evaluate sources of error in a photogrammetry workflow in a manipulative experiment using a purpose-built multi-camera workstation. We demonstrate extremely high accuracy (R2 > 0.999) in determining the surface area and volume of known objects, as well as very high precision (average CV < 0.01) in coral measurements during tests of reproducibility. These outcomes show the utility of fragment photogrammetry for experimental coral reef science and present suggested validation metrics and approaches that can help standardize data evaluation and interpretation in any application of photogrammetry to coral fragments. [ABSTRACT FROM AUTHOR]

Simple Summary: Ultra-wideband (UWB) positioning systems offer promising solutions for monitoring dairy cow behaviour, but their performance in complex barn environments needs a thorough evaluation. This study assessed the TrackLab 2.13 UWB system (Noldus) in a commercial dairy barn, focusing on its accuracy and reliability for tracking cow movements and detecting proximities. We tested the system using stationary and moving tags that simulated cow movement. Positioning reliability varied widely for stationary tags, with central barn locations performing best. Stationary and moving tags satisfactorily complied with the manufacturer's specified accuracy of 0.30 m. The system accurately detected 81.42% of cow proximities to fixed points, indicating its potential for studying social interactions and resource use. While challenges remain, particularly near barn perimeters, this UWB technology shows great promise for enhancing animal welfare monitoring and behaviour research in commercial dairy settings. These findings will help farmers and researchers utilise positioning systems more effectively, improving livestock management and welfare assessment. UWB positioning systems offer innovative solutions for precision monitoring dairy cow behaviour and social dynamics, yet their performance in complex commercial barn environments requires thorough validation. This study evaluated the TrackLab 2.13 (Noldus) UWB system in a dairy barn housing 44–49 cows. We assessed stationary tag positioning using ten fixed tags over seven days, proximity detection between eight cows and ten stationary tags, and moving tag positioning using three tags on a stick to simulate cow movement. System performance varied by tag location, with reliability ranging from 4.09% to 96.73% and an overall mean accuracy of 0.126 ± 0.278 m for stationary tags. After the provider updated the software, only 0.62% of measures exceeded the declared accuracy of 0.30 m. Proximity detection between moving cows and stationary tags showed 81.42% accuracy within a 2-m range. While generally meeting specifications, spatial variations in accuracy and reliability were observed, particularly near barn perimeters. These findings highlight UWB technology's potential for precision livestock farming, welfare assessment, and behaviour research, including social interactions and space use patterns. Results emphasise the need for careful system setup, regular updates, and context-aware data interpretation in commercial settings to maximise benefits in animal welfare monitoring. [ABSTRACT FROM AUTHOR]

Objectives: The objective of this study was to compare the trueness and precision of three intraoral scanners (IOSs) for the digitization of dentate and edentulous maxillectomy and mandibulectomy defects in artificial models. Methods: Four representative defect models—a dentate and an edentulous maxillectomy model and a dentate and an edentulous mandibulectomy model—were used for digital scanning. After a reference scan of each model, they were scanned with three IOSs: CEREC AC Omnicam, True Definition, and cara TRIOS 3. For comparison, five conventional impressions with a polysiloxane material were taken and digitized with a laboratory scanner. The obtained data were evaluated with three-dimensional (3D) inspection software and superimposed with the reference scan data by using a best-fit algorithm. The mean absolute 3D deviations of the IOS compared to the reference data (trueness) and when comparing the datasets within the IOS (precision) were analyzed. Linear mixed models and multiple pairwise comparisons were used for statistical analyses. Results: The overall comparison of the four evaluated procedures for data acquisition showed a significant difference in trueness (p < 0.0001) and precision (p < 0.0001). The average mean trueness of the IOSs ranged from 32.17 to 204.43 µm, compared to 32.07 to 64.85 µm for conventional impressions. Here, the conventional impression and cara TRIOS 3 performed the most precisely with no significant difference. CEREC AC Omnicam achieved the worst precision. Conclusions: Using a suitable intraoral scanner, defective jaws even without teeth could be captured in satisfying accuracy. This shows the possibility to use an intraoral scanner for maxillofacial defect patients and gives a vision of using digital technology in maxillofacial prosthetics. [ABSTRACT FROM AUTHOR]

Background: Methods for matching in longitudinal cohort studies, such as sequential stratification and time-varying propensity scores, facilitate causal inferences in the context of time-dependent treatments that are not randomized where patient eligibility or treatment status changes over time. The tradeoffs in available approaches have not been compared previously, so we compare two methods using simulations based on a retrospective cohort of patients eligible for weight loss surgery, some of whom received it. Methods: This study compares matching completeness, bias, coverage, and precision among three approaches to longitudinal matching: (1) time-varying propensity scores (tvPS), (2) sequential stratification that matches exactly on all covariates used in tvPS (SS-Full) and (3) sequential stratification that exact matches on a subset of covariates (SS-Selected). These comparisons are made in the context of a deep sampling frame (50:1) and a shallow sampling frame (5:1) of eligible comparators. A simulation study was employed to estimate the relative performance of these approaches. Results: In 1,000 simulations each, tvPS retained more than 99.9% of treated patients in both the deep and shallow sampling frames, while a smaller proportion of treated patients were retained for SS-Full (91.6%) and SS-Selected (98.2%) in the deep sampling frame. In the shallow sampling frame, sequential stratification retained many fewer treated patients (73.9% SS-Full, 92.0% SS-Selected) than tvPS yet coverage, precision and bias were comparable for tvPS, SS-Full and SS-Selected in the deep and shallow sampling frames. Conclusion: Time-varying propensity scores have comparable performance to sequential stratification in terms of coverage, bias, and precision, with superior match completeness. While performance was generally comparable across methods, greater match completeness makes tvPS an attractive option for longitudinal matching studies where external validity is highly valued. [ABSTRACT FROM AUTHOR]

In investigations of domains under post-stratified random sampling, it is difficult to get an acceptable precision for domain-specific estimates due to low sample sizes. Small area estimate, a popular technique that has been widely used over the past few decades, involves indirect estimating using the auxiliary data from the entire population. In this article, we utilize a ranked set sampling (RSS) technique to achieve a greater level of precision in area-specific estimations under the assumption that ranking the smaller sets is simple, inexpensive, and flawless. RSS optimizes sample size for a fixed degree of precision or increases precision for a fixed sample size. We create direct estimators for population total under homogeneous, ratio, and regression models that are area specific. To evaluate the effectiveness and application of the suggested RSS technique, data from the Pakistan Demographic Health Survey (PDHS 2017–18) and Iris flower data are used. The effectiveness of the RSS mechanism is supported by both theoretical characteristics and Bootstrapped tests. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Materials and Methods Results Conclusions Clinical Significance This systematic review aimed to assess the impact of printing orientation on the accuracy and properties of additively manufactured provisional restorations.A systematic literature search databases (PubMed, Scopus, Web of Science, and Cochrane) were conducted in July 2024 without language restrictions. The included studies were evaluated using the modified CONSORT checklist, and the effect measures and synthetic methods were employed to assess the accuracy of resin provisional restorations printed at various orientations.The web search resulted in 8228 records, and 15 records were ultimately included in the analysis. The printing orientation of provisional restorations has an impact on various factors such as the internal and marginal gap, trueness, precision, and accuracy. To achieve optimal results, it is recommended to utilize printing orientations of 180°, 150°, and 210°, as they showed lower marginal and internal gaps and higher accuracy. Caution should be exercised during the virtual positioning of supporting pillars, as this may also influence the overall accuracy.Horizontally and slightly tilted orientations have demonstrated superior accuracy. To achieve optimal results, factors such as printing layer thickness, printing technology, materials, and supportive pillars should be taken into consideration, besides the printing orientations.The selection of the optimum printing parameters overall printing orientations, layer thickness, and supportive pillar position can generate prosthetic and restorative dental parts with a long survival rate, saving time and effort by avoiding fracture, loss of retention, and consequent clinical complications. [ABSTRACT FROM AUTHOR]

The unravelling of the human genome created new perceptions of the origin and evolution of diseases, and for cancer in particular, it established the notion that neoplasia has been a companion of life since its appearance on Earth. It is not surprising that neoplasms, in various forms, develop in numerous species of animals and even in plants. Unmistakable accounts of cancer with clinical features as are understood today begin in the 5th c. B.C. The principles and practice of the Hippocratic and Galenic tradition dominated cancer care virtually into the 20th century. Advanced sequencing technologies at the dawn of the 21st century generated new therapeutic opportunities with immunotherapy, oncolytic virotherapy, and gene transfer, with the latter especially being used in cases of hereditary cancer. [ABSTRACT FROM AUTHOR]

Objectives Myeloid neoplasms require comprehensive characterization of genetic abnormalities, including single-nucleotide variants, small insertions and deletions, and fusions and translocations for management. The Oncomine Myeloid Assay GX v2 (Thermo Fisher Scientific) analyzes 17 full genes, 28 hotspot genes, 30 fusion driver genes, and 5 expression genes. Methods The validation set included 192 DNA samples, 28 RNA samples, and 9 cell lines and contrived controls. The DNA and RNA were extracted from both peripheral blood and bone marrow. Library preparation, templating, and sequencing was performed on the fully automated Genexus Integrated Sequencer (Thermo Fisher Scientific). The sequencing data were analyzed by manual curation, default Oncomine filters and the Oncomine Reporter (Thermo Fisher Scientific). Results Of the 600 reference pathogenic DNA variants targeted by the assay, concordance was seen in 98.3% of unfiltered variant call format files. Precision and reproducibility were 100%, and the lower limit of detection was 2% variant allele frequency for DNA. Inability to detect variants in long homopolymer regions intrinsic to the Ion Torrent chemistry led to 7 missed variants; 100% concordance was seen with reference RNA samples. Conclusions This extensive clinical validation of the Oncomine Myeloid Assay GX v2 on the Genexus Integrated Sequencer with its built-in bioinformatics pipeline and Ion Torrent Oncomine Reporter shows robust performance in terms of variant calling accuracy, precision, and reproducibility, with the advantage of a rapid turnaround time of 2 days. The greatest limitation is the inability to detect variants in long homopolymer regions. [ABSTRACT FROM AUTHOR]

Background: Advances in digital technology and intraoral scanners (IOSs) have the potential to enable accurate digital impressions for patients with maxillary defects. This study aimed to compare the accuracy of IOSs in completely and partially edentulous models with maxillary defects. Methods: Three polyurethane models—one completely edentulous (CE) and two partially edentulous, following Aramany classifications I (ACI) and II (ACII)—were created using stereolithography. These models were scanned with a desktop scanner to create reference models. Ten scans were performed using three different intraoral scanners (TRIOS 3, Primescan, and Virtuo Vivo). The IOS datasets were analyzed to assess trueness and precision using a two-way ANOVA and multiple-comparison tests with Bonferroni corrections (α = 0.05). Results: Both the model type and the IOS significantly influenced trueness and precision. The interaction between the model type and the IOS was found to be statistically significant (trueness: p = 0.001; precision: p = 0.005). The highest trueness was observed in the ACII model scanned with TRIOS 3 and Primescan. TRIOS 3 and Primescan also exhibited the highest precision in the ACII model. For Virtuo Vivo, there were no significant differences among the models (p = 0.48). Conclusions: Although intraoral scanners (IOSs) demonstrated significant differences in trueness when used in completely and partially edentulous models with maxillary defects, these differences may be considered clinically insignificant. [ABSTRACT FROM AUTHOR]

To determine the accuracy and precision of oral thermometry in pediatric patients, along with its sensitivity and specificity for detecting fever and hypothermia, with rectal thermometry as reference standard. This method-comparison study enrolled patients aged between 6 and 17 years, admitted to the surgical ward during a 21-month period. KD-2150 and IVAC Temp Plus II were used for oral and rectal temperature measurements respectively. Fever and hypothermia were defined as core temperature ≥38.0 °C and ≤ 35.9 °C respectively. Accuracy and precision of oral thermometry were determined by the Bland-Altman method. Sensitivity, specificity, positive and negative predictive value, and correct classification of oral temperature cutoffs for detecting fever and hypothermia were calculated. Based on power analysis, 100 pediatric patients were enrolled. The mean difference between oral and rectal temperatures was −0.34 °C, with 95 % limits of agreement ranging between −0.52 and −0.16. Sensitivity and specificity of oral thermometry for detecting fever were 0.50 and 1.0 respectively; its sensitivity and specificity for detecting hypothermia were 1.0 and 0.88 respectively. The oral temperature value of 37.6 °C provided excellent sensitivity for detecting fever, while the value of 35.7 °C provided optimal sensitivity and specificity for detecting hypothermia. Oral thermometry had low sensitivity for detecting fever and suboptimal specificity for detecting hypothermia; thus, temperature values <38.0 °C and <36.0 °C cannot exclude fever and confirm hypothermia respectively with high certainty. Diagnostic accuracy of oral thermometry can be improved by the use of oral temperature thresholds <38.0 °C for detecting fever and <35.9 °C for detecting hypothermia. • Oral thermometry underestimated systematically rectal temperatures. • Mean difference ± SD of oral vs. rectal temperatures was −0.34 ± 0.09 °C. • Oral thermometry had low sensitivity for detecting fever. • Oral thermometry had excellent sensitivity for detecting hypothermia. [ABSTRACT FROM AUTHOR]