Pair Of Metrics Research Articles

Revisiting equivalent optical properties for cerebrospinal fluid to improve diffusion-based modeling accuracy in the brain.

The diffusion approximation (DA) is used in functional near-infrared spectroscopy (fNIRS) studies despite its known limitations due to the presence of cerebrospinal fluid (CSF). Nearly all of these studies rely on a set of empirical CSF optical properties, recommended by a previous simulation study, that were not selected for the purpose of minimizing DA modeling errors. We aim to directly quantify the accuracy of DA solutions in brain models by comparing those with the gold-standard solutions produced by the mesh-based Monte Carlo (MMC), based on which we derive updated recommendations. For both a 5-layer head and Colin27 atlas models, we obtain DA solutions by independently sweeping the CSF absorption ( ) and reduced scattering ( ) coefficients. Using an MMC solution with literature CSF optical properties as reference, we compute the errors for surface fluence, total brain sensitivity and brain energy-deposition, and identify the optimized settings where the such error is minimized. Our results suggest that previously recommended CSF properties can cause significant errors (8.7% to 52%) in multiple tested metrics. By simultaneously sweeping and , we can identify infinite numbers of solutions that can exactly match DA with MMC solutions for any single tested metric. Furthermore, it is also possible to simultaneously minimize multiple metrics at multiple source/detector separations, leading to our new recommendation of setting = 0.15 mm-1 while maintaining physiological for CSF in DA simulations. Our new recommendation of CSF equivalent optical properties can greatly reduce the model mismatches between DA and MMC solutions at multiple metrics without sacrificing computational speed. We also show that it is possible to eliminate such a mismatch for a single or a pair of metrics of interest.

Association between passively collected walking and bicycling data and purposefully collected active commuting survey data-United States, 2019.

Commercially-available location-based services (LBS) data derived primarily from mobile devices may provide an alternative to surveys for monitoring physically-active transportation. Using Spearman correlation, we compared county-level metrics of walking and bicycling from StreetLight with metrics of physically-active commuting among U.S. workers from the American Community Survey. Our strongest pair of metrics ranked counties (n=298) similarly for walking (rho=0.53 [95% CI: 0.44-0.61]) and bicycling (rho=0.61 [0.53-0.67]). Correlations were higher for denser and more urban counties. LBS data may offer public health and transportation professionals timely information on walking and bicycling behavior at finer geographic scales than some existing surveys.

Virome comparison (VC): A novel approach to comparing viromes based on virus species specificity and virome specificity diversity.

The human virome, or the viral communities distributed on or in our body, is estimated to contain about 380 trillion of viruses (individuals), which has far reaching influences on our health and diseases. Obviously, the sheer numbers of viruses alone make the comparisons of two or multiple viromes extremely challenging. In fact, the theory of computation in computer science for so-termed NP-hard problems stipulates that the problem is unsolvable when the size of virome is sufficiently large even with fastest supercomputers. Practically, one has to develop heuristic and approximate algorithms to obtain practically satisfactory solutions for NP-hard problems. Here, we extend the species-specificity and specificity-diversity framework to develop a method for virome comparison (VC). The VC method consists of a pair of metrics: virus species specificity (VS) and virome specificity diversity (VSD) and corresponding pair of random search algorithms. Specifically, the VS and VS permutation (VSP) test can detect unique virus species (US) or enriched virus species (ES) in each virome (treatment), and the VSD and VSD permutation (VSDP) test can further determine holistic differences between two viromes or their subsets (assemblages of viruses). The test with four virome data sets demonstrated that the VC method is effective, efficient, and robust.

Compromised reactive but intact proactive inhibitory motor control in Tourette disorder

Tourette disorder (TD) is characterized by tics, which are sudden repetitive involuntary movements or vocalizations. Deficits in inhibitory control in TD patients remain inconclusive from the traditional method of estimating the ability to stop an impending action, which requires careful interpretation of a metric derived from race model. One possible explanation for these inconsistencies is that race model’s assumptions of independent and stochastic rise of GO and STOP process to a fixed threshold are often violated, making the classical metric to assess inhibitory control less robust. Here, we used a pair of metrics derived from a recent alternative model to address why stopping performance in TD is unaffected despite atypical neural circuitry. These new metrics distinguish between proactive and reactive inhibitory control and estimate them separately. When these metrics in adult TD group were contrasted with healthy controls (HC), we identified robust deficits in reactive control, but not in proactive control in TD. The TD group exhibited difficulty in slowing down the speed of movement preparation, which they rectified by their intact ability to postpone the movement.

The Relationship Among Glucose Metabolism, Cerebral Blood Flow, and Functional Activity: a Hybrid PET/fMRI Study.

18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) estimate brain activities from different aspects, including regional glucose uptake (rGU) by 18FDG-PET, regional cerebral blood flow (rCBF) by arterial spin labeling, and dynamic changes of deoxyhemoglobin by blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI). However, the relationships between them remain incompletely understood. In the current study, twenty-four subjects (14 males, 10 females) were recruited and investigated the correlation among rGU, rCBF, and BOLD fMRI-derived metrics reflecting the neural activity, including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) by hybrid PET/fMRI. Correlation analyses were performed across subject and across space at both voxel level and region level, considering partial volume effects by adjusting for gray matter volume. Each pair of metrics showed significant across-space correlations. rGU against ReHo showed the highest mean correlation coefficients. rGU had higher correlations with three resting-state (RS) fMRI metrics than did ASL-rCBF. However, the across-subject correlations were not significant among functional modalities (rGU, rCBF, and RS-fMRI BOLD data) at either voxel level or region level even with a liberal threshold, except for significant across-subject correlation between RS-fMRI metrics (ALFF, ReHo, and DC). These comprehensive findings from hybrid PET/MR might provide complementary information to reveal the underlying mechanisms of the brain activity and open new perspective to interpret pathologic conditions.

Robotic MLC-based plans: A study of plan complexity.

The utility of complexity metrics has been assessed for IMRT and VMAT treatment plans, but this analysis has never been performed for CyberKnife (CK) plans. The purpose of this study is to perform a complexity analysis of CK MLC plans, adapting and computing complexity indices previously defined for IMRT plans. Metrics were used to compare the complexity of plans created by two optimization systems and to study correlations between plan complexity and patient-specific quality assurance (PSQA) results. Relationships between pairs of metrics were also analyzed to get insight into possible interdependencies. Two independent in-house software platforms were developed to compute six complexity metrics: modulation complexity score (MCS), edge metric (EM), plan irregularity (PI), plan modulation (PM), leaf gap (LG), and small aperture score (SAS10). MCS and PM definitions were adapted to account for CK plans characteristics. The computed metrics were used to compare the existing optimization algorithms (sequential and VOLO) in terms of plan complexity over 24 selected cases. Metrics were then computed over a large number (103) of VOLO SBRT clinical plans from different treatment sites, mainly liver, prostate, pancreas, and spine. Pearson's r was used to study relationships between each pair of metrics. Correlation between complexity indices and PSQA results expressed as gamma index passing rates (GPR) at (3%, 1mm) and (2%, 1mm) was finally analyzed. Correlation was regarded as weak for absolute Pearson's r values in the range 0.2-0.39, moderate 0.4-0.59, strong 0.6-0.79, and very strong 0.8-1. When compared to VOLO, sequential plans exhibited a higher complexity degree, showing lower MCS and LG values and higher EM, PM and PI values. Differences were significant for 5/6 metrics (Wilcoxon P<0.05). The analysis of VOLO clinical plans highlighted different degrees of complexity among plans from different treatment sites, increasing from liver to prostate, pancreas, and finally, spine. Analysis of dependencies between pairs of metrics showed a very strong significant negative correlation (P<0.01), respectively, between MCS and PM (r=-0.97), and EM and LG (-0.82). Most of the remaining pairs showed moderate to strong correlations with the exception of PI, which showed weaker correlations with the other metrics. A moderate significant correlation was observed with GPR values both at (3%, 1mm) and (2%, 1mm) for all metrics except PI, which showed no correlation. Modulation complexity metrics were computed for CK MLC-based plans for the first time and some metrics' definitions were adapted to CK plans peculiarities. The computed metrics proved a useful tool for comparing optimization algorithms and for characterizing CK clinical plans. Strong and very strong correlations were found between some pairs of metrics. Some significant correlations were found with PSQA GPR, indicating that some indices are promising for rationalizing and reducing PSQA workload. Our results set the basis for evaluating new optimization algorithms and TPS versions in the future, as well as for comparing the complexity of CK MLC-based plans in multicenter and multiplatform comparisons.

Measurement Bias in the Financial Performance of Family Firms

Notwithstanding the impressive body of research focusing on the financial performance of family-led enterprises over their non-family counterparts, no aggregate conclusion can be extrapolated from the existing data. In this article, we show that performance inference is biased and depends exclusively on the combined choice of financial measurements and family taxonomy; any general conclusion drawn from a specific pair of metrics should be interpreted with caution. We analyze the cross-combinations of eighteen variants of family firms with twenty financial metrics to show that family attributes greatly influence hybrid performance measures, display a notable effect on accounting-based metrics but have almost no impact on market returns. These peculiar results are ascribed to the fact that family businesses tend to favor creditors and directors over investors.

A Multi-Criteria Analysis of Benchmark Results With Expert Support for Security Tools

The benchmarking of security tools is endeavored to determine which tools are more suitable to detect system vulnerabilities or intrusions. The analysis process is usually oversimplified by employing just a single metric out of the large set of those available. Accordingly, the decision may be biased by not considering relevant information provided by neglected metrics. This article proposes a novel approach to take into account several metrics, different scenarios, and the advice of multiple experts. The proposal relies on experts quantifying the relative importance of each pair of metrics towards the requirements of a given scenario. Their judgments are aggregated using group decision making techniques, and pondered according to the familiarity of experts with the metrics and scenario, to compute a set of weights accounting for the relative importance of each metric. Then, weight-based multi-criteria-decision-making techniques can be used to rank the benchmarked tools. The usefulness of this approach is showed by analyzing two different sets of vulnerability and intrusion detection tools from the perspective of multiple/single metrics and different scenarios.

Spacetime diffeomorphisms as matter fields

We work on a 4-manifold equipped with Lorentzian metric g and consider a volume-preserving diffeomorphism that is the unknown quantity of our mathematical model. The diffeomorphism defines a second Lorentzian metric h, the pullback of g. Motivated by elasticity theory, we introduce a Lagrangian expressed algebraically (without differentiations) via our pair of metrics. Analysis of the resulting nonlinear field equations produces three main results. First, we show that for Ricci-flat manifolds, our linearized field equations are Maxwell’s equations in the Lorenz gauge with exact current. Second, for Minkowski space, we construct explicit massless solutions of our nonlinear field equations; these come in two distinct types, right-handed and left-handed. Third, for Minkowski space, we construct explicit massive solutions of our nonlinear field equations; these contain a positive parameter that has the geometric meaning of quantum mechanical mass and a real parameter that may be interpreted as electric charge. In constructing explicit solutions of nonlinear field equations, we resort to group-theoretic ideas: we identify special four-dimensional subgroups of the Poincaré group and seek diffeomorphisms compatible with their action in a suitable sense.

Invariant Tensors under the Twin Interchange of the Pairs of the Associated Metrics on Almost Paracomplex Pseudo-Riemannian Manifolds

The object of study is almost paracomplex pseudo-Riemannian manifolds with a pair of metrics associated each other by the almost paracomplex structure. A torsion-free connection and tensors with geometric interpretation are found which are invariant under the twin interchange, i.e. the swap of the counterparts of the pair of associated metrics and the corresponding Levi-Civita connections. A Lie group depending on two real parameters is constructed as an example of a 4-dimensional manifold of the studied type and the mentioned invariant objects are found in an explicit form.

Multi-objective evolutionary optimization using the relationship between F1 and accuracy metrics in classification tasks

This work analyses the complementarity and contrast between two metrics commonly used for evaluating the quality of a binary classifier: the correct classification rate or accuracy, C, and the F1 metric, which is very popular when dealing with imbalanced datasets. Based on this analysis, a set of constraints relating C and F1 are defined as a function of the ratio of positive patterns in the dataset. We evaluate the possibility of using a multi-objective evolutionary algorithm guided by this pair of metrics to optimise binary classification models. To check the validity of the constraints, we perform an empirical analysis considering 26 benchmark datasets obtained from the UCI repository and an interesting liver transplant dataset. The results show that the relation is fulfilled and that the use of the algorithm for simultaneously optimising the pair (C,F1) leads to a generally balanced accuracy for both classes. The experiments also reveal that, in some cases, better results are obtained by using the majority class as the positive class instead of using the minority one, which is the most common approach with imbalanced datasets.

Benenti Tensors: A useful tool in Projective Differential Geometry

Abstract Two metrics are said to be projectively equivalent if they share the same geodesics (viewed as unparametrized curves). The degree of mobility of a metric g is the dimension of the space of the metrics projectively equivalent to g. For any pair of metrics (g, ḡ) on the same manifold one can construct a (1, 1)- tensor L(g, ḡ) called the Benenti tensor. In this paper we discuss some geometrical properties of Benenti tensors when (g, ḡ) are projectively equivalent, particularly in the case of degree of mobility equal to 2.

An experimental search-based approach to cohesion metric evaluation

In spite of several decades of software metrics research and practice, there is little understanding of how software metrics relate to one another, nor is there any established methodology for comparing them. We propose a novel experimental technique, based on search-based refactoring, to ‘animate’ metrics and observe their behaviour in a practical setting. Our aim is to promote metrics to the level of active, opinionated objects that can be compared experimentally to uncover where they conflict, and to understand better the underlying cause of the conflict. Our experimental approaches include semi-random refactoring, refactoring for increased metric agreement/disagreement, refactoring to increase/decrease the gap between a pair of metrics, and targeted hypothesis testing. We apply our approach to five popular cohesion metrics using ten real-world Java systems, involving 330,000 lines of code and the application of over 78,000 refactorings. Our results demonstrate that cohesion metrics disagree with each other in a remarkable 55 % of cases, that Low-level Similarity-based Class Cohesion (LSCC) is the best representative of the set of metrics we investigate while Sensitive Class Cohesion (SCOM) is the least representative, and we discover several hitherto unknown differences between the examined metrics. We also use our approach to investigate the impact of including inheritance in a cohesion metric definition and find that doing so dramatically changes the metric.

Rigidity of almost-isometric universal covers

Almost-isometries are quasi-isometries with multiplica- tive constant one. Lifting a pair of metrics on a compact space gives quasi-isometricmetrics on the universal cover. Under someadditional hypotheses on the metrics, we show that there is no almost-isometry between the universal covers. We also show that Riemannian mani- folds that are almost-isometric have the same volume growth entropy. We then establish various rigidity results as applications.

A strongly ill-posed problem for a degenerate parabolic equation with unbounded coefficients in an unbounded domain of

In this paper, we deal with a strongly ill-posed second-order degenerate parabolic problem in the unbounded open set , related to a linear equation with unbounded coefficients, with no initial condition, but endowed with the usual Dirichlet condition on and an additional condition involving the x-normal derivative on , with Γ being an open subset of Ω. The purpose of this paper is twofold: to determine sufficient conditions on our data implying the uniqueness of the solution u to the boundary value problem and determine a pair of metrics with respect to which u depends continuously on the data. The results obtained for the parabolic problem are then applied to a similar problem for a convolution integrodifferential linear parabolic equation.

When is multimetric gravity ghost-free?

We study ghosts in multimetric gravity by combining the mini-superspace and the Hamiltonian constraint analysis. We first revisit bimetric gravity and explain why it is ghost-free. Then, we apply our method to trimetric gravity and clarify when the model contains a ghost. More precisely, we prove trimetric gravity generically contains a ghost. However, if we cut the interaction of a pair of metrics, trimetric gravity becomes ghost-free. We further extend the Hamiltonian analysis to general multimetric gravity and calculate the number of ghosts in various models. Thus, we find multimetric gravity with loop type interactions never becomes ghost-free.

Investigation of improved metrics for the characterization of musicians' room acoustical conditions in concert halls

A number of metrics for assessing the acoustical conditions for performers on concert hall stages have been proposed, notably by Anders Gade but also others. However, the subjective relevance of existing stage acoustic metrics for musicians, appears mainly to be associated with the communication with the audience rather than with the communication between musicians. No acoustic metrics have been identified to assess the balance between the hearing of others vs. the hearing of one's own instrument, which appears paramount to orchestral musicians. Problems regarding presence of orchestra, directional characteristics of instruments, distances from instruments to ears of musicians, etc., also have been an issue for researchers, making the work difficult, expensive and imprecise. However, in this paper, due to the comparative approach used, some of these problems were removed, since they are basically the result of properties of orchestral arrangement rather than stage conditions and can be assumed similar from one stage to another. In this paper, a number of laboratory experiments as well as measurements on real stages have been studied and a pair of metrics, namely GSelf and GOthers are suggested to assess the balance between the hearing of self and that of hearing others.

Climatology of Tropical Cyclogenesis in the North Atlantic (1948–2004)

Abstract The threat posed to North America by Atlantic Ocean tropical cyclones (TCs) was highlighted by a series of intense landfalling storms that occurred during the record-setting 2005 hurricane season. However, the ability to understand—and therefore the ability to predict—tropical cyclogenesis remains limited, despite recent field studies and numerical experiments that have led to the development of conceptual models describing pathways for tropical vortex initiation. This study addresses the issue of TC spinup by developing a dynamically based classification scheme built on a diagnosis of North Atlantic hurricanes between 1948 and 2004. A pair of metrics is presented that describes TC development from the perspective of external forcings in the local environment. These discriminants are indicative of quasigeostrophic forcing for ascent and lower-level baroclinicity and are computed for the 36 h leading up to TC initiation. A latent trajectory model is used to classify the evolution of the metrics for 496 storms, and a physical synthesis of the results yields six identifiable categories of tropical cyclogenesis events. The nonbaroclinic category accounts for 40% of Atlantic TCs, while events displaying perturbations from this archetype make up the remaining 60% of storms. A geographical clustering of the groups suggests that the classification scheme is identifying fundamentally different categories of tropical cyclogenesis. Moreover, significant differences between the postinitiation attributes of the classes indicate that the evolution of TCs may be sensitive to the pathway taken during development.

Assessing Riparian Quality Using Two Complementary Sets of Bioindicators

Biological indicators are being increasingly used to rapidly monitor changing river quality. Among these bioindicators are macroinvertebrates. A short-coming of macroinvertebrate rapid assessments is that they use higher taxa, and therefore lack taxonomic resolution and species-specific responses. One subset of invertebrate taxa is the Odonata, which as adults, are sensitive indicators of both riparian and river conditions. Yet adult Odonata are not necessarily an umbrella taxon for all other taxa. Therefore, we investigated whether the two metrics of aquatic macroinvertebrate higher taxa and adult odonate species might complement each other, and whether together they provide better clarity on river health and integrity than one subset alone. Results indicated that both metrics provide a similar portrait of large-scale, overall river conditions. At the smaller spatial scale of parts of rivers, Odonata were highly sensitive to riparian vegetation, and much more so than macroinvertebrate higher taxa. Odonate species were more sensitive to vegetation structure than they were to vegetation composition. Landscape context is also important, with the odonate assemblages at point localities being affected by the neighbouring dominant habitat type. Overall, benthic macroinvertebrates and adult Odonata species provide a highly complementary pair of metrics which together provide large spatial scale (river system) and small spatial scale (point localities) information on the impact of stressors such as riparian invasive alien trees. As adult Odonata are easy to sample and are sensitive to disturbance at both small and large spatial scales, they are valuable indicators for rapid assessment of river condition and riparian quality.

METRIC PAIRS AND THE FUTAKI CHARACTER

The non-vanishing of the Futaki character gives an obstruction to the existence of Kähler metrics of constant scalar curvature, having a Kähler form belonging to a fixed Kähler class [4, 6]. It is shown that, in combination with the resolution of the Calabi conjecture [18], one has an analogous obstruction on pairs of metrics having Kähler forms belonging to a fixed pair of Kähler classes. If the difference of the Futaki characters on two classes of fixed total volume does not vanish identically, there cannot exist a pair of metrics, with Kähler forms in these classes, having the same Ricci form and the same harmonic Ricci form. When the obstruction vanishes, results in [8] are used to construct non-trivial examples of such pairs, which are also extremal in the sense of Calabi [3].