Measurements Of Different Variables Research Articles

Measuring Tree Diameter Using LiDAR Equipped iPad: An Evaluation of ForestScanner and Arboreal Forest Applications

Abstract Forest owners need simple and efficient tools to capture and understand forest metrics. Additionally, they could benefit from emerging technologies in forest analysis. Light detection and ranging (LiDAR) sensors allow for precise measurements of different variables and can be used more easily in forestry settings thanks to their introduction into smartphones and tablets. ForestScanner and Arboreal Forest are two applications (apps) that allow for the measurement of tree diameter at breast height (DBH) on LiDAR-equipped devices. Our study sought to analyze and compare (1) the timing of traditional and LiDAR-based forest inventory methods and (2) the accuracy of traditional and LiDAR-based forest measurements. We established a series of plots to record and compare tree DBH and measurement time between a traditional diameter tape, ForestScanner, and Arboreal Forest. We found that DBH measurements from the apps were in good agreement with diameter tape measurements; however, both apps tended to underestimate DBH. Additionally, measurement time for both apps was found to be significantly shorter than traditional tape measurements. Further improvements in LiDAR apps can present a simple and efficient way for future forest analysis by seasoned foresters and private landowners. Study Implications: LiDAR smartphone applications represent a cost-effective and time-efficient method for wide-spread forest management, especially among landowners who have little access to forestry-specific equipment. As these technologies continue to advance, the incorporation of functions for plot establishment, height measurements, biomass estimations, and ecosystem dynamics could become valuable assets in the forest industry. We encourage individuals to further test LiDAR measurement applications themselves, as further training on these applications will help developers to improve application accuracy.

A Convolutional Neural Network Classifies Beat-to-Beat Arterial Pressure Spectrograms and Wavelet Transforms according to Age, Sex, and Metabolic State: Novel Frequencies for Cardiovascular Risk Appraisal

Hemodynamic homeostasis is under the control of multiple systems. Continuous blood pressure (BP) time series carry information relevant to the pathophysiological status of the cardiovascular system. Beside average BP, different measures of variability provide prognostic value for distinguishing between cardiovascular risk states. The latter are derived from time- and frequency- domain analysis of BP recordings and are limited by their capacity to provide cumulative risk appraisal among different risk groups. The prediabetic state is associated with cardiovascular risk which is often described to be age- and sex-specific. In this study, we sought to determine distinctive features of continuous arterial pressure (AP) time-series for risk appraisal in a pre-established prediabetic rat model. To overcome the shortcomings associated with conventional BP variability parameters, we trained a convolutional neural network (CNN) using spectrograms and scalograms generated from short-term Fourier- and Morlet wavelet- transforms of AP time series, respectively, from male and female prediabetic rats fed a mild hypercaloric diet for 12- or 24- weeks and their corresponding controls. The CNN consisted of 5 convolutional layers, separated by batch normalization, ReLU activation, and max pooling. The outcome of the fifth convolutional layer had 40% of the data dropped out and delivered to a fully-connected dense layer and then to a softmax function. The data was divided into 80% training, 10% validation, and 10% test sets. The model classified spectrograms and scalograms with test accuracy of 90%+ for the different binary and multi-class classification tasks. On backward propagation of model scores, different salient frequencies were identified as critical features for classification of AP time-series. The identified frequencies were much higher than those typically used in conventional power spectral density (PSD) analysis. Using 3-way ANOVA or principal component analysis for comparison and clustering of the different cardiovascular risk groups of age, sex, and metabolic disease, respectively, according to PSD at the identified peaks does not yield suffcient risk appraisal. This indicates that the CNN possibly captures non-linear relations which are undetectable using inherently linear methods.The results indicate sex- and age-specific patterns of cardiovascular deterioration in prediabetes. Use of artificial intelligence models for the identification of abnormal BP fluctuation patterns can provide suffcient risk appraisal needed for early intervention, particularly in at-risk patients lacking clinical signs of overt cardiovascular disease. None. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Naturalistic assessment of reaction time variability in older adults at risk for Alzheimer's disease.

Maintaining attention underlies many aspects of cognition and becomes compromised early in neurodegenerative diseases like Alzheimer's disease (AD). The consistency of maintaining attention can be measured with reaction time (RT) variability. Previous work has focused on measuring such fluctuations during in-clinic testing, but recent developments in remote, smartphone-based cognitive assessments can allow one to test if these fluctuations in attention are evident in naturalistic settings and if they are sensitive to traditional clinical and cognitive markers of AD. Three hundred and seventy older adults (aged 75.8 +/- 5.8 years) completed a week of remote daily testing on the Ambulatory Research in Cognition (ARC) smartphone platform and also completed clinical, genetic, and conventional in-clinic cognitive assessments. RT variability was assessed in a brief (20-40 seconds) processing speed task using two different measures of variability, the Coefficient of Variation (CoV) and the Root Mean Squared Successive Difference (RMSSD) of RTs on correct trials. Symptomatic participants showed greater variability compared to cognitively normal participants. When restricted to cognitively normal participants, APOE ε4 carriers exhibited greater variability than noncarriers. Both CoV and RMSSD showed significant, and similar, correlations with several in-clinic cognitive composites. Finally, both RT variability measures significantly mediated the relationship between APOE ε4 status and several in-clinic cognition composites. Attentional fluctuations over 20-40 seconds assessed in daily life, are sensitive to clinical status and genetic risk for AD. RT variability appears to be an important predictor of cognitive deficits during the preclinical disease stage.

Osteometric Dimension of Lower End of Femoral Bone among Bangladeshi Population

Introduction: The osteometric dimensions of the lower end of the femur have significant clinical implications, particularly in the context of total knee arthroplasty (TKA). Accurate measurements are crucial for the design of femoral components in TKA, which can influence surgical outcomes. This study aims to determine the measurements of different variables of the lower end of the femur, including femoral condylar width, intercondylar width and depth, and the depth of the medial and lateral condyles, in a Bangladeshi population. Methods: This cross-sectional study was conducted on 50 dried femurs collected from three medical colleges in Dhaka, Bangladesh. Measurements were obtained using digital sliding calipers and were rounded to two decimal places. Data analysis was performed using SPSS. Result: Statistical analysis revealed that 56% of the femurs were right-sided and 44% were left-sided. The mean femoral bicondylar width was 69.78 ± 5.38 mm, falling mostly in the "Above Average" range (30%). The mean intercondylar width was 23.77 ± 1.55 mm, with 50% falling in the "Medium" range. Other variables like femur medial condylar width had a mean of 31.05 ± 1.74 mm. Conclusion: Observationally, the study successfully delineates the osteometric dimensions of the lower end of the femur in a Bangladeshi cohort. The statistical results not only fulfill the study's initial aim but also provide a nuanced understanding of the osteometric variations. These findings are instrumental for clinicians in the design and customization of femoral components in TKA, thereby potentially enhancing surgical outcomes and patient satisfaction. The data also lay the groundwork for future research in this area.

Energy Efficiency Optimization in Onboard SWRO Desalination Plants Based on a Genetic Neuro-Fuzzy System

This work presents a novel intelligent control system based on a Genetic Neuro-Fuzzy tool to optimize and improve the performance of a seawater reverse osmosis desalination plant (SWRO) on board a marine vessel. This investigation pays special attention to minimizing energy consumption to improve the energy efficiency of this marine installation. The system analyzes measurements of different variables—seawater pH, seawater conductivity, permeate flow rate, permeate conductivity, and total energy consumed—in order to provide the most appropriate value of permeate flow rate control and operating pressure of the high-pressure pump (HPP). This intelligent method allows the plant to achieve output values nearer to the desired setpoints set by the plant operators.

Medición de la eficiencia de las Facultades de la Universidad Santo Tomás seccional Tunja a través de modelos de eficiencia

Efficiency models are techniques used to measure the use of resources and their products or results, commonly called data management unit (DMU), which transform inputs into outputs to measure the efficiency of each study unit. Efficiency models make it possible to compare the different units in terms of results, taking into account their resources. In the present work, INPUTS or input variables are taken for each faculty and the outputs are reviewed, which in this case are the products of the 10 faculties of the Universidad Santo Tomás sectional Tunja, through the application of efficiency frontier models. To meet this objective, information was collected for a specific period through the measurement of different variables framed in the missionary axes of Higher Education in Colombia, namely: Training, Research and Extension or social projection. Two different efficiency frontier model approaches were applied: a parametric approach in which it is assumed that there is a known functional relationship between the input variables (inputs) and the output variables (outputs) by fitting a stochastic frontier model (SFA) and a non-parametric approach in which the data envelope model (DEA) is applied. It was possible to identify which faculties achieve their greatest efficiency with lower inputs, as well as variables that can be improved to achieve greater efficiency in the faculties with lower results. With this work it is expected to provide a management tool that allows generating plans for improvement and optimization of its resources.

Black-Box Mathematical Model for Net Photosynthesis Estimation and Its Digital IoT Implementation Based on Non-Invasive Techniques: Capsicum annuum L. Study Case

Photosynthesis is a vital process for the planet. Its estimation involves the measurement of different variables and its processing through a mathematical model. This article presents a black-box mathematical model to estimate the net photosynthesis and its digital implementation. The model uses variables such as: leaf temperature, relative leaf humidity, and incident radiation. The model was elaborated with obtained data from Capsicum annuum L. plants and calibrated using genetic algorithms. The model was validated with Capsicum annuum L. and Capsicum chinense Jacq. plants, achieving average errors of 3% in Capsicum annuum L. and 18.4% in Capsicum chinense Jacq. The error in Capsicum chinense Jacq. was due to the different experimental conditions. According to evaluation, all correlation coefficients (Rho) are greater than 0.98, resulting from the comparison with the LI-COR Li-6800 equipment. The digital implementation consists of an FPGA for data acquisition and processing, as well as a Raspberry Pi for IoT and in situ interfaces; thus, generating a useful net photosynthesis device with non-invasive sensors. This proposal presents an innovative, portable, and low-scale way to estimate the photosynthetic process in vivo, in situ, and in vitro, using non-invasive techniques.

Deliberative architecture for smart sensors in the filtering operation of a water purification plant

The increase of applications for industrial smart sensors is booming, mainly due to the use of distributed automation architectures, industrial evolution and recent technological advances, which guide the industry to a greater degree of automation, integration and globalization. In this research work, an architecture for deliberative-type intelligent industrial sensors is proposed, based on the BDI (Belief Desire Intentions) model, adaptable to the measurement of different variables of the filtering process of a water purification plant. An intelligent sensor with functions of signal digitalization, self-calibration, alarm generation, communication with PLC, user interface for parameter adjustment, and analysis with data extrapolation have been arranged. For decision making, the use of fuzzy logic techniques has been considered, which allows imprecise parameters to be appropriately represented, simplifying decision problem solving in the industrial environment, generating stable and fast systems with low processing requirements. The proposed architecture has been modelled, simulated and validated using UML language in conjunction with Petri nets, which facilitate the representation of discrete system events, presenting them clearly and precisely. In the implementation and testing of the prototype, C/C ++ language has been used in an 8-bit microcontroller, experimentally corroborating the operation of the device, which allowed evaluating the behavior of a pseudo-intelligent agent based on the requirements of the water treatment plant, and also through comparisons with similar works developed by other researchers.

Analysis of the Association Between Lung Function and Brain Tissue Oxygen Tension in Severe Traumatic Brain Injury.

Low brain tissue oxygen tension (PbtO2) has been shown to be an independent factor associated with unfavourable outcomes in traumatic brain injury (TBI). Although PbtO2 provides clinicians with an understanding of ischaemic and non-ischaemic derangements of brain physiology, the value alone can be the result of several factors, including partial arterial oxygenation pressure (PaO2), haemoglobin levels (Hb) and cerebral perfusion pressure (CPP). This chapter presents a single-centre, retrospective cohort study of 70 adult patients with severe TBI who were admitted to the Neurocritical Care Unit (NCCU) at Addenbrooke's Hospital (Cambridge, UK) between October 2014 and December 2017. A total of 303 simultaneous measurements of different variables that included (but were not limited to) intracranial pressure (ICP), PaO2, PbtO2, CPP and the fraction of inspired oxygen (FiO2) were considered in this work. We conducted a correlation analysis between all of the variables. We also implemented a longitudinal data analysis of the PbtO2 and PaO2/FiO2 ratio (PF ratio). There were strong and independent correlations between PbtO2 and the PF ratio, and between PbtO2 and PaO2, with adjusted p values of <0.001 for both correlations. After adjustment for ICP, age, sex and the Glasgow Coma Scale (GCS) score, a PF ≤ 330 was shown to be an independent risk factor for a compromised PbtO2 value of <20, with an adjusted odds ratio of 1.94 (95% confidence interval 1.12-3.34) and a p value of 0.02. Brain and lung interactions in patients with TBI patients have complex interrelationships. Our results confirm the importance of employing lung-protective strategies to prevent brain hypoxia in patients with TBI.

Analysis of the Impact of Changes in the Functional Distribution of Income on Aggregate Demand

Analysis of the Impact of Changes in the Functional Distribution of Income on Aggregate Demand

English

This study draws on the understanding that when the correlation between variables is not known yet the non-linear expectation in the correlation between the variables is present, non-linear measurement tools can be used. In education, possibility measurement tools can be used for non-linear measurement. Multiple-choice possibility measurement tools (MCPMT) can be prepared similarly to conventional multiple-choice measurement tools (CMCMT) utilized in quantitative measurements. In comparison with CMCMT, both more qualified measurements and more qualified evaluations can be carried out via possibility measurement tools; therefore, the preparation techniques of MCPMT, which is one possibility measurement tool, which can be used in information-centered and learner-centered measurements, are set forth in this study. MCPMT can resolve the problem of CMCMT in terms of the measurement of different variables with multiple options in one item. Additionally, the correlation between the variables can be determined by evaluating data obtained via MCPMT by means of two different new methods.&nbsp; &nbsp; Key word: Multiple-choice measurement tool (MCMT), multiple-choice possibility measurement tool (MCPMT), item techniques (IT), option technique (OT). &nbsp

The alveolar process following single-tooth extraction: a study of maxillary incisor and premolar sites in man.

The present investigation was performed to determine some dimensional alterations that occur in the alveolar process of the incisor and premolar sites of the maxilla following tooth removal. Computer-assisted cone-beam computed tomography (CBCT) scans were obtained from the maxilla using an iCAT unit, and involved edentulous and contralateral tooth sites. For each site included in the study, parasagittal and axial reconstructions, 1mm apart, were made and measurements of different variables (cross-sectional area, height, and width) performed. The study involved 69 subjects and disclosed that the cross-sectional area and the height and width of the alveolar process of the lateral incisor site were the smallest and those of the second premolar the largest. All parameters had been significantly reduced after the completion of the ≥1year of healing. Thus, the overall (i) cross-sectional area was reduced from 99.1 to 65.0mm(2) , (ii) the height from 11.5 to 9.5mm, and (iii) the width from 8.5 to 3.2mm (marginal 1/3(rd) ), 8.9 to 4.8mm (middle portion), and 9.0 to 5.7mm (apical portion). The removal of single tooth caused marked hard tissue diminution. The loss of hard tissue was most pronounced in the buccal and marginal portions of the edentulous ridge that in most sites had acquired a triangular shape.

The impact of the variability and periodicity of rainfall on surface water supply systems in Scotland

This paper analyses the impact of the variability and periodicity of rainfall on the reliability of water supply systems in Scotland. A conceptual rainfall-runoff model was used to simulate catchment runoff, and the reliability of 29 notional and six actual reservoirs was calculated using a simple storage model. The relationship between water supply reliability and the variability of rainfall was then investigated using different measures of variability. A strong correlation was found between reservoir reliability and measures representing the distribution of rainfall between the winter and summer seasons, as well as the cumulative sum (CUSUM) of annual precipitation, quantifying the variability of rainfall between years. In contrast, mainly the intra-annual CUSUM range and the variance of monthly precipitation influenced the reliability of river-intake schemes. The presence of periodic patterns in rainfall anomalies was found to be more prevalent in West Scotland, where reservoir reliability is on average lower than in the East. In addition, a sensitivity analysis revealed the small influence of evapotranspiration on reservoir reliability in comparison to rainfall variability. This study reveals the measures of variability most affecting the reliability of surface water supplies in Scotland, and could therefore help with their management in the context of future climate change.

Genetic variability and character association among quantitative traits in gerbera

Ten gerbera genotypes were evaluated for 13 quantitative traits during 2011–12 and 2012–13 in RBD with three replications and pooled data were analysed. Different measures of variability, heritability and correlation and path coefficient were worked out to identify promising traits based on which selection could be made. High heritability coupled with high genetic advance as per cent of mean was observed for number of leaves/plant, leaf breadth, number of suckers/plant, disc diameter, flower stalk length and number of flowers/plant, indicating presence of additive gene action and consequently a distinct possibility of improving these traits through selection. The number of flowers per plant was highly significant and positively correlated with leaf length, days to bud burst, days to first flower opening and flower stalk length.

Plug-in tests for nonequivalence of means of independent normal populations.

In this paper, we consider the problem of testing nonequivalence of several independent normal population means. It is a well-known problem to test the equality of several means using the analysis of variance (ANOVA). Instead of determining the equality, one may consider more flexible homogeneity, which allows a predetermined level of difference. This problem is known as testing nonequivalence of populations. We propose the plug-in statistics for two different measures of variability: the sum of the absolute deviations and the maximum of the absolute deviations. For each test, the least favorable configuration (LFC) to ensure the maximum rejection probability under the null hypothesis is investigated. Furthermore, we demonstrate the numerical studies based on both simulation and real data to evaluate the plug-in tests and compare these with the range test.

Does variability in cognitive performance correlate with frontal brain volume?

Little is known about the neural correlates of within-person variability in cognitive performance. We investigated associations between regional brain volumes and trial-to-trial, block-to-block, and day-to-day variability in choice-reaction time, and episodic and working memory accuracy. Healthy younger (n=25) and older (n=18) adults underwent 101 daily assessments of cognitive performance, and their regional brain volumes were measured manually on magnetic resonance images. Results showed that smaller prefrontal white matter volumes were associated with higher block-to-block variability in choice-reaction time performance, with a stronger association observed among older adults. Smaller volumes of the dorsolateral prefrontal cortex covaried with higher block-to-block variability in episodic memory (number-word pair) performance. This association was stronger for younger adults. The observed associations between variability and brain volume were not due to individual differences in mean performance. Trial-to-trial and day-to-day variability in cognitive performance were unrelated to regional brain volume. We thus report novel findings demonstrating that block-by-block variability in cognitive performance is associated with integrity of the prefrontal regions and that between-person differences in different measures of variability of cognitive performance reflect different age-related constellations of behavioral and neural antecedents.

Trends and variability in daily precipitation in Scotland

The objective of this research is to analyse temporal changes in historic rainfall variability across Scotland using different measures of variability. The CUSUM and sequential Mann-Kendall test applied to records from 28 weather stations with up to 80 years of daily precipitation data reveal the occurrence of abrupt changes in the rainfall trends. Most weather stations show a turning point between 1978 and 1985, although some stations situated in Eastern Scotland have more than one turning point. The temporal changes in rainfall variability across Scotland are presented using a number of measures of variability.

Reproducibility of Measures of Visit-to-Visit Variability in Blood Pressure after Transient Ischaemic Attack or Minor Stroke

Background: In certain patients in routine practice, blood pressure (BP) measurements differ substantially from week to week or month to month. Although often assumed to be random, such variability could provide information on underlying pathology or prognosis. In order to be informative, however, visit-to-visit BP variability would have to be neither random (i.e. it should be reproducible over time within individuals) nor artefactual (i.e. it should not be an artefact of the method/timing of measurement, for example). Methods: We quantified visit-to-visit variability in BP and explored potential confounding factors by analysing repeat measurements obtained every few months during follow-up in two large trials in patients with a transient ischaemic attack (TIA) or minor ischaemic stroke: the UK-TIA Aspirin Trial (effect of aspirin, effect of season and day of the week of measurement) and the European Carotid Surgery Trial (ECST – effect of carotid endarterectomy). By comparing different periods of follow-up, we also determined the reproducibilities of mean and several different measures of variability for both systolic (SBP) and diastolic BP (DBP). Results: The mean absolute difference between adjacent SBP readings was 14.7 mm Hg in the UK-TIA Trial and 16.0 mm Hg in ECST. Visit-to-visit variability in both SBP and DBP were independent of the potentially confounding factors studied, but reproducibility of all the variability measures was statistically significantly greater than zero. Reproducibility (intraclass correlation) of standard deviation of SBP was 0.32 (p < 0.0001) in the UK-TIA Trial and 0.18 (p = 0.0007) in ECST. Consequently, classification of patients with high (top quintile) or low (bottom quintile) variability was consistent over time (observed/expected = 2.21, 95% confidence interval 1.71–2.85, p < 0.0001, and 1.65, 1.23–2.21, p = 0.0007, respectively). Reproducibility increased with the number of measurements used to calculate variability, and was independent of any correlation with mean BP. Conclusions: Visit-to-visit variability in BP in these populations was reproducible, independently of any correlation with mean BP, demonstrating that visit-to-visit intra-individual BP variability is not random.

A new paradigm for profiling testicular gene expression during normal and disturbed human spermatogenesis

The aim of this study was to identify gene expression patterns of the testis that correlate with the appearance of distinct stages of male germ cells. We avoided the pitfalls of mixed pathological phenotypes of the testis and circumvented the inapplicability of using the first spermatogenic wave as done previously on rodents. This was accomplished by using 28 samples showing defined and highly homogeneous pathologies selected from 578 testicular biopsies obtained from 289 men with azoospermia (two biopsies each). The molecular signature of the different developmental stages correlated with the morphological preclassification of the testicular biopsies, as shown by resampling-based hierarchical clustering using different measures of variability. By using analysis of variance (ANOVA) and extensive permutation analysis, we filtered 1181 genes that exhibit exceptional statistical significance in testicular expression and grouped subsets with transcriptional changes within the pre-meiotic (348 genes), post-meiotic (81 genes) and terminal differentiation (38 genes) phase. Several distinct molecular classes, metabolic pathways and transcription factor binding sites are involved, depending on the transcriptional profile of the gene clusters that were built using a novel clustering procedure based on not only similarity but also statistical significance.

Proper Estimation of Random Uncertainties in Steady-State Testing

The estimation of the random uncertainty of an experimental result (such as specific impulse or drag coefficient) that is determined from multiple measured variables in a steady-state test is considered. Often in the actual engineering testing of complex systems, all conditions cannot be tightly controlled, and the variations in successive measurements of the variables are caused both by unsteadiness and by measurement errors. In such cases, the distributions of the measurements of different variables might not be independent of one another, that is, the variables “drift” in unison. The results of two test programs are used to show that calculation of the random standard uncertainty (the standard deviation) of a result using the traditional propagation equation can produce an estimate many times too large or too small because the correlations among the variations in the measured variables are not taken into account. In contrast, when the random standard uncertainty is calculated directly from a sample of multiple results determined within a single test, the effects of the correlations are accounted for implicitly. The direct approach has not commonly been used in single test situations because unfortunately it has been presented in the past with nomenclature that caused a mindset that experimental results from multiple tests were necessary for its use, and that is not the case.