Accurate Method For Assessment Research Articles

Accurate gingival recession quantification using 3D digital dental models

ObjectivesTo develop and validate a method for accurate quantitative assessment of gingival recessions based on superimposition of serial 3D digital models.Materials and methodsGingival recessions of mild (0.5–2 mm) and increased (3–7 mm) severity were simulated on stone casts and surface models were created. The outlines of the gingival margins of the mild (A) and severe recessions (B) were compared to the original gingival margins following 3D best fit superimposition through a gold standard technique (GS), which used intact adjacent structures, and the tested method (CC), which used single tooth crowns at the position of recessions, as superimposition reference. The primary outcome was the distance between the most apical point of each corresponding gingival margin along the respective tooth long axis.ResultsFor mild recessions, the median difference of the test methods (CC_A) from the reference method (GS_A) was 0.008 mm (IQR: 0.093; range: − 0.143, 0.147). For severe recessions, the median difference of the test method (CC_B) from the reference method (GS_B) was 0.009 mm (IQR: 0.091; range: − 0.170, 0.198). The proposed method (CC) showed very high intra- and inter-operator reproducibility (median: 0.025 and 0.033 mm, respectively).ConclusionsThe suggested method offers highly accurate monitoring of gingival margin changes and diagnosis of gingival recessions using 3D digital dental models. The method is applicable irrespective of changes in tooth position or form, allowing for assessments over any time span.Clinical relevanceThe accurate detection and visualization of gingival margin changes in 3D will enhance diagnosis and patient-doctor communication.

Assessing the lidar revolution in the Maya lowlands: A geographic approach to understanding feature classification accuracy

It has been well over a decade since lidar-based research began in earnest in the Maya Lowlands of southern Mexico, Guatemala, Belize, and Honduras. Most investigations have an archaeological focus, with a few integrating studies of the ancient Maya with analyses of local ecology and land-use. A review of frequently cited publications reveals a lack of consistency in assessing the accuracy of archaeological feature classifications in lidar data with variables such as sensor type, class definitions, and ground-truthing methods differentially affecting assessment results across the Lowlands. In general, area-based ground-truthing approaches to classifications of full waveform lidar data present the most comprehensive accuracy assessments. New assessment data from the Buenavista Valley of north-central Guatemala are presented to compare against existing studies and to demonstrate how a geographic approach (a comprehensive, landscape-scale study of features over space and time) to classification error assessment can enhance understanding of classification accuracy. Results show that meaningful comparisons of archaeological features across lidar datasets cannot be considered reliable without more uniform and detailed presentations of accuracy assessment methods, analyses, and results. The article concludes with recommendations for how such collaborations might proceed.

Abstract 15710: Point-of-Care Ultrasonography: Artificial Intelligence in the Assessment of Left Ventricular Function

Introduction: Point-of-care ultrasonography (PoCUS) has become routine for the bedside assessment of patients. Current evidence shows that image acquisition and interpretation of left ventricular function can be achieved reliably by trained users, but evidence is lacking for interpretation by artificial intelligence. We sought to evaluate the accuracy of PoCUS devices with integrated artificial intelligence in comparison to transthoracic echocardiograms for assessment of left ventricular ejection fraction (LVEF). Methods: This is a prospective, multicenter cohort study using the KOSMOS portable ultrasound device (EchoNous, Redmon, WA). PoCUS studies included an apical four and two chamber views and were obtained by either novice trainees or experienced ultrasonographers. A real-time, automated LVEF was calculated by the device using a modified Simpson’s method. These patients also underwent a formal transthoracic echocardiogram, with image acquisition and interpretation completed by blinded ultrasonographers and level-3 trained echocardiographers, respectively. Results: A total of 449 patients were enrolled in the study with 227 and 222 studies completed by novice and experienced scanners, respectively. Images of suitable quality were obtained in 208 of the novice cohort (91.6%) and 216 of the experienced cohort (97.3%). In comparison to formal echocardiography, linear regression shows a R 2 value of 0.82 for the total cohort, and 0.85 for the novice and 0.72 in experienced scanner subgroups. Incorporating an intra-observer variability of ± 5%, the sensitivity and specificity for an abnormal (≤50%) and severely reduced (≤30%) LVEF was 99.2% and 97.7%, and 86.8% and 99%, respectively. Conclusions: Our study is one first to assess the accuracy of PoCUS devices with integrated artificial intelligence. Based on our study, a real-time, automated LVEF can be acquired by PoCUS with strong correlation to formal echocardiography. This study also highlights that diagnostic quality studies can be acquired by novice scanners with comparable accuracy to experienced scanners. This provides evidence for an immediate and inexpensive method for accurate LVEF assessment in emergent and resource-limited environments.

Effect of a sleepless night combined with 2 cups of instant coffee on heart rate variability in an elderly man

Insomnia is harmful and has negative effects on the human body. Coffee is the most commonly used beverage to invigorate. Measurement of heart rate variability is the most accurate method for quantitative assessment of the sympatho-vagal balance of the autonomic nervous system, which determines adaptive capacity to stress. In our Case Report, after 1 sleepless night, the stress index rises and the sympathetic over parasympathetic prevails.

Characteristics of gastroesophageal reflux disease in children with interstitial lung disease.

Childhood interstitial lung disease (chILD) is a rare group of respiratory tract disorders. One of the factors suggested to be associated with its etiopathogenesis is microaspiration related to gastroesophageal reflux disease (GERD). The aim of the present study was to determine the frequency and characteristics of GERD in children with chILD, with a particular focus on proximal GER episodes. This was a prospective cross-sectional study. Consecutive patients with chILD underwent 24-h multichannel intraluminal pH-impedance monitoring. Different types of gastroesophageal reflux episodes (GER) were recorded and compared with regard to the GERD diagnosis. Sixty-two children (median age of 1.22 years) were included. GERD was diagnosed in 20 (32.3%) of them. The GERD (+) and GERD (-) subgroups differed mainly in their esophageal exposure to acid content (2.9 vs. 1.0%, p = 0.02) and bolus exposure (3.0 vs. 1.4%, p < 0.0001), as well as total number of GER (72.5 vs. 42.0 p = 0.0004), acid GER (35.5 vs. 15.0 p = 0.004), and acid proximal GER (21.0 vs. 12.0 p = 0.02). There were no differences in the number of proximal GER comparing GERD (+) and GERD (-) subgroups. The frequency of GERD seems to be relatively high in the population of children with chILD used in this study. However, it has not demonstrated an association between proximal GER and GERD diagnosis in chILD, which casts uncertainty over the microaspiration theory proposed to link the two diseases. The latter conclusion, however, needs to be confirmed using more accurate aspiration assessment methods.

Precision Enhancement of Wireless Localization System Using Passive DOA Multiple Sensor Network for Moving Target.

Determining the direction-of-arrival (DOA) of any signal of interest has long been of great interest to the wireless localization research community for military and civilian applications. To efficiently facilitate the deployment of DOA systems, the accuracy of wireless localization is critical. Hence, this paper proposes a novel method to improve the prediction result of a wireless DOA localization system. By considering the signal variation existing in the complex environment, the actual location of the target can be determined including the maximum prediction error. Moreover, the scenario of the moving target is further investigated by incorporating the adaptive Kalman Filter algorithm to obtain the prediction route of the flying drone based on the accuracy assessment method. This proposed adaptive Kalman Filter is a high-efficiency algorithm that can filter out the noise in the multipath area and optimize the predicted data in real-time. The simulation result agrees well with the measured data and thus validates the proposed DOA system with the adaptive Kalman Filter algorithm. The measured DOA of the fixed radiation source obtained by a single base station and the moving route of a flying drone from a two-base station localization system are presented and compared with the calculated results. Results show that the prediction error in an outdoor region of is about 10–20 m, which demonstrate the usefulness of the proposed wireless DOA system deployment in practical applications.

Tricuspid valve geometry alterations in different aetiologies of functional regurgitation: 3D echocardiography study

Abstract Introduction Evaluation of tricuspid annulus (TA) has many challenges due to its complex three-dimensional shape. The 3D-echocardiography is a gold standard method for accurate assessment of tricuspid valve (TV). Studies investigating TV geometry in different aetiologies of tricuspid regurgitation (TR) are still scarce. Aim The aim was to clarify the TV geometry characteristics in different aetiologies of functional TR (FTR). Methods Prospective observational cohort study enrolled 107 patients with functional moderate or severe TR and 10 healthy controls. FTR patients were divided into two groups according to the different aetiology of FTR: 1. TR caused by dominant left-sided valvular pathology (LSVP) – 68 patients (pts); 2. TR caused by precapillary pulmonary hypertension (PH) (invasively measured pulmonary capillary wedge pressure &amp;lt;15 mmHg) – 39 pts. Pts with ischemic heart disease (assessed by coronary angiography) were excluded from the analysis. The 3D-transthoracic echocardiography was performed and included the following parameters: the systolic and diastolic 4-chambers (septal–lateral), 2-chambers (anterior–posterior), major axis TA diameters, TA area, perimeter, leaflets tenting height and volume. All parameters have been indexed to body surface area. The 3D TV analysis was made using 4D Auto TVQ quantification software package (GE Healthcare, USA). The statistical analysis was performed using SPSS statistical software. Results Study cohort included 66% females; mean age was 65±11 years. TR severity, measured quantitatively, did not differ between FTR groups (ERA – 32±18 in LSVP vs 35±18 mm2 in PH group, p=0.219). The distribution of echocardiography parameters in study groups are shown in Table 1. All the 3D TV parameters were increased in both FTR groups when compared to controls. Precapillary PH was associated with larger leaflets tenting height, volume, and more increased indices of TA systolic and diastolic septal-lateral and major axis diameters. LVSP aetiology was associated with higher TA sphericity index. Conclusions Tricuspid valvular geometry differs between different aetiologies of functional TR. The implementation of 3D echocardiography is useful in the determination of TV geometry changes and might provide valuable tools in the evaluation of patients with functional TR. Funding Acknowledgement Type of funding sources: None.

Understanding Urban Heat Vulnerability Assessment Methods: A PRISMA Review

Increasingly people, especially those residing in urban areas with the urban heat island effect, are getting exposed to extreme heat due to ongoing global warming. A number of methods have been developed, so far, to assess urban heat vulnerability in different locations across the world concentrating on diverse aspects of these methods. While there is growing literature, thorough review studies that compare, contrast, and help understand the prospects and constraints of urban heat vulnerability assessment methods are scarce. This paper aims to bridge this gap in the literature. A systematic literature review with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach is utilized as the methodological approach. PRISMA is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. The results are analyzed in three aspects—i.e., indicators and data, modelling approaches, and validation approaches. The main findings disclose that: (a) Three types of indicators are commonly used—i.e., demographic properties and socioeconomic status, health conditions and medical resources, and natural and built environmental factors; (b) Heat vulnerability indexing models, equal weighting method, and principal component analysis are commonly used in modelling and weighting approaches; (c) Statistical regressions and correlation coefficients between heat vulnerability results and adverse health outcomes are commonly used in validation approaches, but the performance varies across studies. This study informs urban policy and generates directions for prospective research and more accurate vulnerability assessment method development.

The Causal Relationship Between Radiofrequency-Electromagnetic Radiation from Wireless Phones and Brain Tumor, Part 1: A Systematic Review for Possible Biases and Confounding

Introduction: The hypothesis of this study is that RF-EMR exposure from wireless phones causes brain tumors and that this causal relationship can be accurately validated only when accurate exposure assessment methods are applied. As a starting point of this series article, a systematic review of published literature for possible biases and confounding in previous studies will be conducted in the first part. Methods: The medical librarian searched MEDLINE: PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library (until 24 December 2020). Results and Discussion: Of the total of 13 studies included, 8 studies concluded that the risk estimates in original studies were underestimated. The other 2 studies concluded that the risk estimates in original studies were underestimated in most scenarios except for a limited number of low possibility scenarios. The other 2 studies concluded the risk estimates might be under- or over-estimated equivocally, and another 1 study concluded the risk estimates might be fair. One study insisted the accurate assessment of RF-EMR exposure should be based on (ⅰ) site-specific, (ⅱ) time integral of (ⅲ) specific absorption rate (SAR). As for the ‘site specific’ component, the fact that the widespread Bluetooth technology is making the distance between the head and wireless phones farther than before should be considered. As for the ‘time-integral’ component, almost all people in modern society are using their mobile phones every day, every minute, even when they are sleeping (as a morning-alarm device), for various purposes other than mere calling. As for the ‘SAR’ component, the fluctuating output power range according to various conditions should be considered in the exposure assessment. Conclusion: Overall, the risk estimates were underestimated in previous literature. However, a more important point is that accurate exposure assessment is required for valid epidemiologic studies.

The Causal Relationship Between Radiofrequency-Electromagnetic Radiation From Wireless Phones and Brain Tumor, Part 2: A Meta-Analysis of Current Literature Using Crude Proxies for RF-EMR Exposure Assessment

Introduction: Considering the imprecise characteristic of the currently used exposure classification categories discussed in the first part of this series article, in this second part, the authors will conduct a series of meta-analyses and subgroup analyses using various exposure classification categories from crude ones to more precise ones. Methods: The medical librarian searched MEDLINE (PubMed), EMBASE, and the Cochrane Library until 16 December 2020. Results and Discussion: As for the separate analysis stratified by each tumor type, the odds ratio for meningioma for regular users was statistically significantly decreased, 0.86 (95% CI 0.77-0.95). For ipsilateral users, the pooled odds ratio for meningioma (1.20 (95% CI 1.04-1.39)), glioma (1.45 (95% CI 1.16-1.82)), and malignant tumors (1.93 (95% CI 1.55-2.39)) showed a statistically significant increased estimate. For years of use, the pooled odds ratio for glioma for &amp;#x3e; 10 years of use group showed a statistically significant increased estimate (1.32 (95% CI 1.01-1.71)). To sum up, these results stratified by each tumor type, glioma, and malignant tumors were strong candidate tumor types of the possible tumorigenic effect of RF-EMR from wireless phones. In the meta-analysis for the total cumulative hours of use &amp;#x3e; 867 hours, the pooled odds ratio was 1.56 (95% CI 1.27-1.91). This statistically significant increased pooled odds ratio indicates that a rather moderate amount of cumulative exposure to RF-EMR from wireless phones could induce brain tumors. Conclusion: The study hypothesis, ‘the causal relationship between RF-EMR exposure and brain tumor incidence can be clearly validated only when accurate exposure assessment methods are applied,’ was validated by the increasing pattern of estimated odds ratios from the use of rather crude exposure categories to more precise exposure categories.

Real-World Evidence Shows Clinicians Appropriately Use the Prognostic 40-Gene Expression Profile (40-GEP) Test for High-Risk Cutaneous Squamous Cell Carcinoma (cSCC) Patients

Treatment decisions for patients with cutaneous squamous cell carcinoma (cSCC) are traditionally based upon clinicopathologic risk factors and staging systems. Due to the accuracy limitations of these resources in predicting poor outcomes, there is a clinically significant need for more accurate methods of risk assessment. The 40-gene expression profile (40-GEP) test was developed to augment metastatic risk prediction of high-risk cSCC patients and has been validated in two independent, multi-center studies involving over 1,000 patients. This study substantiates that the 40-GEP is appropriately utilized by clinicians and that the personalized risk-stratification results are impactful in guiding risk-aligned patient management.

Spatio-temporal evolution and driving factors of eco-environmental quality based on RSEI in Chang-Zhu-Tan metropolitan circle, central China

Accurately analyzing the spatial and temporal evolution of regional eco-environmental quality and exploring the response of eco-environmental quality to natural environment and human factors are essential to protect the regional ecological environment. This study analyzed the ecological environmental quality of Chang-Zhu-Tan metropolitan circle, central China from 2000 to 2020 based on Google Earth Engine (GEE) and Remote Sensing Ecological Index (RSEI). Subsequently, we introduced the Partial Least Squares Structural Equation Model (PLS-SEM) to explore the response of RSEI to the direct and indirect effects of natural and anthropogenic factors, and assessed the spatial autocorrelation of regional ecological environmental quality. The results showed that the mean value of RSEI in the study area was showing an increasing trend, with the lowest mean value of RSEI in 2010 (0.6508) and the highest mean value of RSEI in 2020 (0.6948). The eco-environmental quality level was mainly good and excellent, and the average area accounted for more than 70% of the total area, and showed an upward trend during 2000–2020. Climate, soil, terrain, and urbanization had different effects on the ecological environment, with climate, soil, and terrain had positive effects on the ecological environment, while urbanization had negative effects on it. The positive effect of climate on ecological environment was gradually weakened, while the negative effect of urbanization on ecological environment was gradually strengthened. Climate and urbanization weakened the positive effect of soil and terrain in different degrees. This study provides a method for rapid and accurate assessment of regional eco-environmental quality and exploration of complex interaction pathways of influencing factors, which is essential for balancing the relationship between regional development and nature.

Coronary CT angiography derived fractional flow reserve: the consideration and practice of functional evaluation for cerebral arterial diseases

Cerebrovascular disease is a significant global public health concern, despite the diagnosis and treatment of stroke has made great progress in recent years, however, its mainly guided by anatomical indicators, which still needs to be further improved, and there is an urgent need to explore a more accurate and comprehensive functional imaging assessment method. Rapid development of coronary CT angiography derived fractional flow reserve (CT-FFR) has become an important technique for noninvasive evaluation of coronary artery disease, and these successful application experiences inspiried neurologists to explore the functional evaluation technique of cerebral arteries and demonstrated broad application prospects. In this paper, by analyzing and comparing the coronary CT-FFR technology, the progress, existing problems and possible solutions of the functional evaluation for cerebral arterial stenosis are discussed from the aspects of coronary CT-FFR study, cerebral artery functional evaluation study, and the comparison and consideration of cerebral arterial and coronary CT-FFR.

Evaluation Of Wrist-based Accelerometer Intensity Classifications During Activities Of Daily Living In A Whole-room Calorimeter

Objective measurements of physical activity (PA) from wrist-worn accelerometers are important for understanding the relationship between PA and disease risk. While locating activity monitors on the wrist improves participant compliance relative to hip-worn protocols, valid methods for classifying PA intensity from the wrist are still in their infancy. PURPOSE Evaluate intensity classification algorithms for wrist-worn accelerometers against a criterion measure during activities of daily living (ADL) and a treadmill walk. METHODS Informed consent was obtained from 7 males (mean ± SD; age 28 ± 3 y; body mass 86.0 ± 15.2 kg; height 178.5 ± 9.6 cm) who completed 1-hr of ADLs consisting of four 10-min tasks separated by 5 min seated rest, and a 30 min treadmill walk at 1.3 m·s-1. For all activities, an ActiGraph GT9X (AG) was worn on the non-dominant wrist and oxygen consumption (VO2, ml/kg) was measured by a whole-room calorimeter (RC). The Hildebrand 2014 and Montoye 2020 wrist classification algorithms were applied to raw AG data. The number of minutes in each intensity category for AG data and RC data were calculated. Metabolic equivalent (MET) categories were defined as: sedentary (sed): < 1.5 METs; light (LPA): 1.5-2.9 METs; and moderate to vigorous (MVPA): > 3.0 METs). Bias (AG estimated - RC measured), mean absolute error (MAE), and their 95% confidence intervals were used to assess method accuracy and precision. RESULTS Across both methods and activity intensities, bias estimates ranged from -33.3 to 27.4 min for the period, and -4.1 to 3.9 min for the treadmill walk (Table 1). Mean absolute error was highest for LPA (33.3 and 21.1 min) and MVPA (27.4 and 12.0 min) during ADLs. Both algorithms overestimated time in MVPA and underestimated time in LPA during ADLs. CONCLUSION These bias and MAE estimates suggest that additional studies are needed to develop more accurate and precise wrist-based accelerometer algorithms focused on ADLs and free-living behaviors.

An integrated method for assessing passenger evacuation performance in ship fires

In order to assess effectively the passenger evacuation performance in ship fires, a quantitative method combining the computational fluid dynamics (CFD)-derived fire data and AnyLogic evacuation simulation is proposed in this paper. In this developed method, the speed reduction factor, instantaneous untenable conditions and fractional effective dose (FED) model are utilized to consider the effects of smoke visibility, heat and toxic gases in ship fires on the passenger walking speed, activity space and human health conditions. In order to demonstrate this proposed method, passenger evacuation analysis is performed in a hypothetical zone of the ship with obstacles for fast t-squared fires. The results indicate that the relationship between the required safe egress time (RSET) and fire heat release rate (HRR) is non-monotonic. However, the total FED increases with the increase of the fire HRR and the sequence of survivors. Compared with two existing methods, this proposed method is able to assess more rigorously the passenger evacuation performance in ship fires. The existing ASET/RSET method is more conservative, and the existing FED method with the Pathfinder underestimates the FED in ship fires. This work will provide a more accurate method for ship fire safety assessment and performance-based fire protection design.

Assessing Multi-Temporal Global Urban Land-Cover Products Using Spatio-Temporal Stratified Sampling

In recent years, the availability of multi-temporal global land-cover datasets has meant that they have become a key data source for evaluating land cover in many applications. Due to the high data volume of the multi-temporal land-cover datasets, probability sampling is an efficient method for validating multi-temporal global urban land-cover maps. However, the current accuracy assessment methods often work for a single-epoch dataset, and they are not suitable for multi-temporal data products. Limitations such as repeated sampling and inappropriate sample allocation can lead to inaccurate evaluation results. In this study, we propose the use of spatio-temporal stratified sampling to assess thematic mappings with respect to the temporal changes and spatial clustering. The total number of samples in the two stages, i.e., map and pixel, was obtained by using a probability sampling model. Since the proportion of the area labeled as no change is large while that of the area labeled as change is small, an optimization algorithm for determining the sample sizes of the different strata is proposed by minimizing the sum of variance of the user’s accuracy, producer’s accuracy, and proportion of area for all strata. The experimental results show that the allocation of sample size by the proposed method results in the smallest bias in the estimated accuracy, compared with the conventional sample allocation, i.e., equal allocation and proportional allocation. The proposed method was applied to multi-temporal global urban land-cover maps from 2000 to 2010, with a time interval of 5 years. Due to the spatial aggregation characteristics, the local pivotal method (LPM) is adopted to realize spatially balanced sampling, leading to more representative samples for each stratum in the spatial domain. The main contribution of our research is the proposed spatio-temporal sampling approach and the accuracy assessment conducted for the multi-temporal global urban land-cover product.

Evaluating the efficiency of coarser to finer resolution multispectral satellites in mapping paddy rice fields using GEE implementation

Timely and accurate estimation of rice-growing areas and forecasting of production can provide crucial information for governments, planners, and decision-makers in formulating policies. While there exists studies focusing on paddy rice mapping, only few have compared multi-scale datasets performance in rice classification. Furthermore, rice mapping of large geographical areas with sufficient accuracy for planning purposes has been a challenge in Pakistan, but recent advancements in Google Earth Engine make it possible to analyze spatial and temporal variations within these areas. The study was carried out over southern Punjab (Pakistan)-a region with 380,400 hectares devoted to rice production in year 2020. Previous studies support the individual capabilities of Sentinel-2, Landsat-8, and Moderate Resolution Imaging Spectroradiometer (MODIS) for paddy rice classification. However, to our knowledge, no study has compared the efficiencies of these three datasets in rice crop classification. Thus, this study primarily focuses on comparing these satellites’ data by estimating their potential in rice crop classification using accuracy assessment methods and area estimation. The overall accuracies were found to be 96% for Sentinel-2, 91.7% for Landsat-8, and 82.6% for MODIS. The F1-Scores for derived rice class were 83.8%, 75.5%, and 65.5% for Sentinel-2, Landsat-8, and MODIS, respectively. The rice estimated area corresponded relatively well with the crop statistics report provided by the Department of Agriculture, Punjab, with a mean percentage difference of less than 20% for Sentinel-2 and MODIS and 33% for Landsat-8. The outcomes of this study highlight three points; (a) Rice mapping accuracy improves with increase in spatial resolution, (b) Sentinel-2 efficiently differentiated individual farm level paddy fields while Landsat-8 was not able to do so, and lastly (c) Increase in rice cultivated area was observed using satellite images compared to the government provided statistics.

Cleft Lip Repair Competence Can Be Evaluated with High-fidelity Simulation.

Background:Demonstrating competency before independent practice is increasingly important in surgery. This study tests the hypothesis that a high-fidelity cleft lip simulator can be used to discriminate performance between training levels, demonstrating its utility for assessing procedural competence.Methods:During this prospective cohort study, participants performed a unilateral cleft lip repair on a high-fidelity simulator. Videos were blindly rated using the Objective Structured Assessment of Technical Skills (OSATS) and the Unilateral Cleft Lip Repair Competency Assessment Tool (UCLR). Digital measurement of symmetry was estimated. Influence of training level and cumulative prior experience on each score was estimated using Pearson r.Results:Participants (n = 26) ranged from postgraduate year 3 to craniofacial fellow. Training level correlated best with UCLR (R = 0.4842, P = 0.0122*) and more weakly with OSATS (R = 0.3645, P = 0.0671), whereas cumulative prior experience only weakly correlated with UCLR (R = 0.3450, P = 0.0843) and not with OSATS (R = 0.1609, P = 0.4323). UCLR subscores indicated marking the repair had little correlation with training level (R = 0.2802, P = 0.1656), whereas performance and result did (R = 0.5152, P = 0.0071*, R = 0.4226, P = 0.0315*, respectively). Correlation between symmetry measures and training level was weak.Conclusions:High-fidelity simulation paired with an appropriate procedure-specific assessment tool has the construct validity to evaluate performance for cleft lip repair. Simply being able to mark a cleft lip repair is not an accurate independent assessment method nor is symmetry of the final result.

Integrated analytical approaches for the characterization of Spirulina and Chlorella microalgae

Microalgae are well-known for their content of bioactive molecules such as pigments, proteins, fatty acids, polysaccharides, vitamins and antioxidants, all of which are of great interest in the preparation of a wide range of products such as food, cosmetics and nutraceuticals. The purpose of this project was the analytical characterization of commercial dry microalgal biomass: four samples of Chlorella and five of Spirulina were analysed in order to highlight their content in terms of micro/macro nutrients. The research was oriented towards the development and validation of accurate, fast and reproducible methods for the nutritional assessment of algal biomasses, aiming to provide a guiding methodology. The lipid profiles of algal matrixes were analysed for the content of saturated, unsaturated and polyunsaturated fatty acids. The process was divided into two phases: firstly, the extraction and determination of the total lipids and pigment content; secondly, the trans-esterification of the extracted lipid-pigment portion in order to analyse fatty acid methyl esters (FAMEs) with a GC-MS method. A fingerprinting of MUFAs and PUFAs was obtained regarding microalgae species. The determination of total carotenoids and chlorophylls content in the lipid extracts was evaluated through a fast UV-Vis spectrophotometric analysis, which was validated by a new HPLC-DAD analysis. Furthermore, the total antioxidant activity of each lipid extract was determined along with the determination of the microalgae protein content. Then, with the aid of the principal component analysis (PCA) plots, the two microalgae were clustered in terms of their micro/macro nutrients, for differentiating their properties. Spirulina, resulting to have a greater antioxidant activity, supposedly due to a higher content in pigments and higher protein concentration, could be suggested for an appropriate diet for sporting people. Chlorella, instead, showed a more balanced profile of PUFAs and MUFAs and its use could be suggested for cosmetics and vegan diets. This paper puts forward an overall analytical approach, sustained by a multivariate analysis, for emphasising content differences and activity of two different microalgae strains, in order to underline specific claims for each class, addressed to defined final users.

High accuracy monitoring of honey bee colony development by a quantitative method

Honey bees are key insect pollinators, providing important economic and ecological value for human beings and ecosystems. This has triggered the development of several monitoring methods for assessing the temporal development of colony size, food storage, brood and pathogens. Nonetheless, most of these methods are based on visual assessments that are observer-dependent and prone to bias. Furthermore, the impact on colony development (invasiveness), as well as accuracy, were rarely considered when implementing new methods. In this study, we present and test a novel accurate and observer-independent method for honey bee colony assessment, capable of being fully standardized. Honey bee colony size is quantified by assessing the weight of adult bees, while brood and provision are assessed by taking photos and conducting image analysis of the combs with the image analysis software Deepbee®. The invasiveness and accuracy of the method were investigated using field data from two experimental apiaries in Portugal, comparing results from test and control colonies. At the end of each field experiment, most of the tested colonies had the same colony size, brood levels and honey production as the control colonies. Nonetheless, continuous weight data indicated some disturbance in tested colonies in the first year of monitoring. The overall accuracy of the image analysis software was improved by training, indicating that it is possible to adapt the software to local conditions. We conclude that the use of this fully quantitative method offers a more accurate alternative to classic visual colony assessments, with negligible impact on colony development.